Patent Publication Number: US-8989459-B2

Title: Image processing apparatus, image processing program product, and image processing method

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of PCT international application Ser. No. PCT/JP2008/059997 filed on May 30, 2008 which designates the United States, incorporated herein by reference, and which claims the benefit of priority from Japanese Patent Application No. 2007-158027, filed on Jun. 14, 2007, incorporated herein by reference. 
    
    
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to an image processing apparatus, an image processing program, and an image processing method that process an in-vivo image that is obtained by taking an image of inside of body cavity. 
     2. Description of the Related Art 
     In recent years, swallow-type capsule endoscopes have been proposed in the field of endoscopy. The capsule endoscope has various functions, such as imaging, wireless communication, and illuminating sites to be imaged. The capsule endoscope is swallowed by a patient through the mouth and then introduced inside the body. Then, while moving inside the body cavity along, for example, the gullet, the stomach, and the small intestine by peristaltic action, the capsule endoscope sequentially takes in-vivo images and wirelessly sends the taken in-vivo images to a receiving device, which is arranged outside the body, until the capsule endoscope is naturally excreted outside the body. 
     The capsule endoscope takes a large number of in-vivo images during the period from when it is swallowed by the patient through the mouth to when it is naturally excreted. Therefore, image processing apparatuses that detect a lesion from the taken in-vivo images by image processing are used. A typical image processing apparatus that detects a lesion using the in-vivo images splits an image of inside of the alimentary truck into blocks, calculates color data for each block, and compares the color data of a region well-known for lesions, such as a bleeding region, with a reference value representing color data of healthy tissues (see Japanese Patent Application Laid-open No. 2004-521693). 
     SUMMARY OF THE INVENTION 
     An image processing apparatus according to an aspect of the present invention includes a suspected-lesion-region extracting unit that extracts a suspected lesion region from an in-vivo image that is obtained by taking an image of inside of body; a groove determining unit that determines whether the suspected lesion region is a region corresponding to a shadow of a groove that is formed between in-vivo organ walls; and a lesion-region extracting unit that extracts a lesion region using the suspected lesion region and a result of determination by the groove determining unit. 
     An image processing program product according to another aspect of the present invention has a computer readable medium including programmed instructions that, when executed by a computer, causes the computer to perform a suspected-lesion-region extracting that extracts a suspected lesion region from an in-vivo image that is obtained by taking an image of inside of body; a groove determining that determines whether the suspected lesion region is a region corresponding to a shadow of a groove that is formed between in-vivo organ walls; and a lesion-region extracting that extracts a lesion region using the suspected lesion region and a result of determination by the groove determining. 
     An image processing method according to still another aspect of the invention includes a suspected-lesion-region extracting that extracts a suspected lesion region from an in-vivo image that is obtained by taking an image of inside of body; a groove determining that determines whether the suspected lesion region is a region corresponding to a shadow of a groove that is formed between in-vivo organ walls; and a lesion-region extracting that extracts a lesion region using the suspected lesion region and a result of determination by the groove determining. 
     The above and other features, advantages and technical and industrial significance of this invention will be better understood by reading the following detailed description of presently preferred embodiments of the invention, when considered in connection with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic diagram showing a whole configuration of an image processing system that includes an image processing apparatus; 
         FIG. 2  is a whole flowchart showing a process performed by the image processing apparatus; 
         FIG. 3  is a flowchart showing a suspected-lesion-region extracting process in detail; 
         FIG. 4  is a schematic diagram that explains a pixel-value-variation-amount calculating method; 
         FIG. 5  is a schematic diagram that explains how to determine an outline pixel; 
         FIG. 6  is a schematic diagram that explains how to calculate a Feret&#39;s diameter Fere —     m   (θ 1 ); 
         FIG. 7-1  is a schematic diagram showing a horizontal sobel filter; 
         FIG. 7-2  is a schematic diagram showing a vertical sobel filter; 
         FIG. 8  is a flowchart showing a groove determining process in detail; 
         FIG. 9-1  is a schematic diagram that explains how to define a surrounding pixel area; 
         FIG. 9-2  is a schematic diagram that explains how to define the surrounding pixel area; 
         FIG. 10  is a display example of an in-vivo image; 
         FIG. 11  is an example of an extracted concavity image that represents a suspected concavity region that is extracted from the in-vivo image shown in  FIG. 10 ; 
         FIG. 12  is an example of a groove-direction extended region that is created from the suspected concavity lesion region shown in the extracted concavity image of  FIG. 11 ; and 
         FIG. 13  is a display example of the extracted lesion region. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Exemplary embodiments of image processing apparatuses, image processing programs, and image processing methods according to the present invention are described in detail below with reference to the accompanying drawings. 
       FIG. 1  is a schematic diagram showing a whole configuration of an image processing system that includes an image processing apparatus according to an embodiment of the present invention. As shown in  FIG. 1 , the image processing system includes a capsule endoscope  2  that takes in-vivo images of inside of body cavity of a subject  1 ; a receiving device  3  that receives the in-vivo images wirelessly from the capsule endoscope  2 ; and an image processing apparatus  5  that processes the in-vivo images that are taken by the capsule endoscope  2  using the in-vivo images that are received by the receiving device  3 . For example, a recording medium that can be carried (portable recording medium)  4  is used for input/output of data on the in-vivo images between the receiving device  3  and the image processing apparatus  5 . 
     The receiving device  3  includes a wireless unit  3   a  that receives wireless signals from the capsule endoscope  2  via a group of receiving antennas A 1  to An that is attached to an outer surface of the subject  1 ; and a receiving main unit  3   b  that processes the wireless signals received from the wireless unit  3   a . The wireless unit  3   a  and the receiving main unit  3   b  are connected to each other via a connector or the like in a detachable manner. The receiving device  3  is designed such that the portable recording medium  4  is attached to and detached from it. The receiving device  3  receives image data on the in-vivo images of inside of the subject  1  that are taken by the capsule endoscope  2  and sequentially stores the data in the portable recording medium  4 . 
     The image processing apparatus  5  includes a control unit  10  that controls the whole image processing apparatus  5 ; a storage unit  11 ; an image obtaining unit  12 , to which the portable recording medium  4  is detachably attached and which obtains the in-vivo images from the portable recording medium  4 ; a processing unit  13  that performs predetermined image processing on the in-vivo images that are obtained by the image obtaining unit  12 ; an input unit  14  that inputs various instruction data; and a display unit  15  that displays a result of the image processing performed by the processing unit  13 , etc. 
     The storage unit  11  includes, for example, a data recording medium and a reading device that reads data therefrom. The data recording medium is, for example, various IC memories, such as a rewritable flash memory including ROM and RAM, a built-in hard disk, a hard disk that is connected via a data communications terminal, and a CD-ROM. Programs related to operation of the image processing apparatus  5 , programs that implement various functions of the image processing apparatus  5 , and data that is used to run these programs, etc., are stored in the storage unit  11 . Moreover, an image processing program  11   a  with which the processing unit  13  processes the in-vivo images and extracts a lesion region is stored in the storage unit  11 . 
     The processing unit  13  includes a suspected-lesion-region extracting unit  16  that extracts a suspected convexity lesion region and a suspected concavity lesion region using a pixel having a pixel value that is different from those of the surrounding pixels; a groove determining unit  17  that determines whether the suspected concavity lesion region is a region corresponding to a shadow of a groove that is formed between organ walls in the body cavity (hereinafter, “groove region”); and a lesion-region extracting unit  18  that excludes the suspected concavity lesion region that is determined to be the groove region, thereby extracting a lesion region. 
     The suspected-lesion-region extracting unit  16  includes a different-pixel extracting unit  16   a  that extracts a pixel having a pixel value different from those of the surrounding pixels; a region-data obtaining unit  16   b  that extracts a region that is possibly a suspected lesion region using the extracted pixel and calculates feature data of the extracted region; and a regional-feature-data determining unit  16   c  that extracts the suspected lesion region, i.e., the suspected convexity lesion region and the suspected concavity lesion region from the regions that are possibly the suspected lesion regions using the calculated feature data. 
     The groove determining unit  17  includes a surrounding-similar-pixel extracting unit  17   a  that extracts a pixel having a pixel value close to those of pixels that form the suspected concavity lesion region from an area surrounding the suspected convexity lesion region; and an extended-groove-region creating unit  17   b  that creates an extended groove region surrounding the suspected concavity lesion region using the pixels of the suspected concavity lesion region and the pixel extracted from the area surrounding the suspected concavity lesion region and determines, using a shape feature-data variation amount between the suspected concavity lesion region and the extended groove region that is created from the suspected concavity lesion region, whether the suspected concavity lesion region is the groove region. 
     A lesion-region extracting process performed by the image processing apparatus  5  according to the present embodiment is described below.  FIG. 2  is a whole flowchart showing the process performed by the image processing apparatus  5 . The process described below is implemented when the units of the image processing apparatus  5  operate in accordance with the image processing program  11   a  that is stored in the storage unit  11 . 
     As shown in  FIG. 2 , the image obtaining unit  12  first reads image data on an in-vivo image from the attached portable recording medium  4  and obtains the in-vivo image that is taken by the capsule endoscope  2  (Step S 1 ). Then, the suspected-lesion-region extracting unit  16  of the processing unit  13  performs a suspected-lesion-region extracting process, i.e., extracts a suspected concavity lesion region and a suspected convexity lesion region from the in-vivo image that is obtained at Step S 1  as suspected lesion regions (Step S 2 ). The groove determining unit  17  performs a groove determining process, i.e., determines whether the suspected concavity lesion region is the groove region (Step S 3 ). The lesion-region extracting unit  18  performs a lesion-region extracting process, i.e., extracts the lesion region from the suspected concavity lesion regions and the suspected convexity lesion regions using a result of the determination by the groove determining process (Step S 4 ). The processing unit  13  then displays the lesion region that is extracted at Step S 4  on the display unit  15  via the control unit  10  (Step S 5 ), and the process performed by the image processing apparatus  5  ends. 
     The suspected-lesion-region extracting process at Step S 2  of  FIG. 2  is described below.  FIG. 3  is a flowchart showing the suspected-lesion-region extracting process in detail. The suspected lesion region is considered to be a section having a pixel value different from those of the surrounding pixels that form healthy tissues. In the suspected-lesion-region extracting process, the different-pixel extracting unit  16   a  sets the pixels that form the in-vivo image to a focus pixel sequentially and calculates a pixel-value variation amount using the focus pixel and surrounding pixels that are away from the focus pixel by a predetermine number of pixels λ or a distance equivalent to the number of pixels λ (Step S 201 ). The color component corresponding to a blood absorbing band is used to calculate the pixel-value variation amount. If the in-vivo image is an RGB image, a change of the pixel value due to a lesion tends to appear in the G component corresponding to the blood absorbing band. Therefore, in the present embodiment, the RGB image is used and the G component image out of the RGB image is used to calculate the pixel-value variation amount. 
       FIG. 4  is a schematic diagram that explains a pixel-value-variation-amount calculating method. In the calculation of the pixel-value variation amount, for example, four directions with respect to a focus pixel IP are used including the horizontal direction, the vertical direction, the lower-left-and-upper-right direction, and the upper-left-and-lower-right direction. As shown in  FIG. 4 , pixels away from the focus pixel IP in the horizontal direction by the predetermined number of pixels λ or the distance equivalent to the number of pixels λ are assumed to be surrounding pixels IA hor  and IB hor ; pixels away from the focus pixel IP in the vertical direction are assumed to be surrounding pixels IA ver  and IB ver ; pixels away from the focus pixel IP in the lower-left-and-upper-right direction are assumed to be surrounding pixels IA sla  and IB sla ; pixels away from the focus pixel IP in the upper-left-and-lower-right direction are assumed to be surrounding pixels IA bac  and IB bac . The pixel-value variation amount is calculated using the focus pixel and these pixels. 
     A pixel-value variation amount V hor  in the horizontal direction with respect to the focus pixel IP is calculated in accordance with the following equation (1) using the focus pixel IP, the surrounding pixels IA hor  and IB hor : 
     
       
         
           
             
               
                 
                   
                     
                       V 
                       hor 
                     
                     = 
                     
                       IP 
                       - 
                       
                         IM 
                         hor 
                       
                     
                   
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   where 
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   
                     
                       IM 
                       hor 
                     
                     = 
                     
                       
                         
                           IA 
                           hor 
                         
                         + 
                         
                           IB 
                           hor 
                         
                       
                       2 
                     
                   
                 
               
               
                 
                   ( 
                   1 
                   ) 
                 
               
             
           
         
       
     
     A pixel-value variation amount V ver  in the vertical direction with respect to the focus pixel IP is calculated in accordance with the following equation (2) using the focus pixel IP, the surrounding pixels IA ver  and IB ver : 
     
       
         
           
             
               
                 
                   
                     
                       V 
                       ver 
                     
                     = 
                     
                       IP 
                       - 
                       
                         IM 
                         ver 
                       
                     
                   
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   where 
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   
                     
                       IM 
                       ver 
                     
                     = 
                     
                       
                         
                           IA 
                           ver 
                         
                         + 
                         
                           IB 
                           ver 
                         
                       
                       2 
                     
                   
                 
               
               
                 
                   ( 
                   2 
                   ) 
                 
               
             
           
         
       
     
     A pixel-value variation amount V sla  in the lower-left-and-upper-right direction with respect to the focus pixel IP is calculated in accordance with the following equation (3) using the focus pixel IP, the surrounding pixels IA sla  and IB sla : 
     
       
         
           
             
               
                 
                   
                     
                       V 
                       sla 
                     
                     = 
                     
                       IP 
                       - 
                       
                         IM 
                         sla 
                       
                     
                   
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   where 
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   
                     
                       IM 
                       sla 
                     
                     = 
                     
                       
                         
                           IA 
                           sla 
                         
                         + 
                         
                           IB 
                           sla 
                         
                       
                       2 
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
     
     A pixel-value variation amount V bac  in the upper-left-and-lower-right direction with respect to the focus pixel IP is calculated in accordance with the following equation (4) using the focus pixel IP, the surrounding pixels IA bac  and IB bac : 
     
       
         
           
             
               
                 
                   
                     
                       V 
                       bac 
                     
                     = 
                     
                       IP 
                       - 
                       
                         IM 
                         bac 
                       
                     
                   
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   where 
                   ⁢ 
                   
                     
 
                   
                   ⁢ 
                   
                     
                       IM 
                       bac 
                     
                     = 
                     
                       
                         
                           IA 
                           bac 
                         
                         + 
                         
                           IB 
                           bac 
                         
                       
                       2 
                     
                   
                 
               
               
                 
                   ( 
                   4 
                   ) 
                 
               
             
           
         
       
     
     The pixel-value variation amounts V hor , V ver , V sla , and V bac  that are calculated in accordance with equations (1) to (4) are collectively referred to as pixel-value variation amount V dir . The suffix dir indicates any of the predetermined directions with respect to the focus pixel IP (any of the vertical direction, the horizontal direction, the lower-left-and-upper-right direction, and the upper-left-and-lower-right direction in the present embodiment). 
     If a region of the focus pixel IP is protruding more than the surroundings, the pixel-value variation amount V dir  is a positive value. In contrast, if a region of the focus pixel IP is depressing more than the surroundings, the pixel-value variation amount V dir  is a negative value. This is because, in general, a region protruding more than the surroundings is brighter than the surroundings and has a higher brightness value, while a region depressing more than the surroundings is darker than the surroundings and has a lower brightness value. 
     Subsequently, as shown in  FIG. 3 , the different-pixel extracting unit  16   a  extracts a pixel having a pixel value meaningfully different from those of the surrounding pixels as a pixel associated with a suspected lesion using the calculated pixel-value variation amount V dir  (Step S 202 ). At that step, the different-pixel extracting unit  16   a  determines convexity and concavity in an area of each of the pixels that form the in-vivo image and extracts a pixel that is determined as the suspected convexity lesion region or a pixel that is determined as the suspected concavity lesion region. Specifically, if it is determined using the calculated pixel-value variation amount of each direction that a pixel has the pixel-value variation amount in every direction larger than a predetermined convexity threshold (ConvexityTh), i.e., the pixel satisfies V hor &gt;ConvexityTh, V ver &gt;ConvexityTh, V sla &gt;ConvexityTh, and V bac &gt;ConvexityTh, the different-pixel extracting unit  16   a  determines that the pixel is protruding more than the surroundings and extracts the pixel. In contrast, if it is determined using the calculated pixel-value variation amount of each direction that a pixel has the pixel-value variation amount in every direction smaller than a predetermined concavity threshold (ConcaveTh), i.e., the pixel satisfies V hor &gt;ConcaveTh, V ver &gt;ConcaveTh, V sla &gt;ConcaveTh, and V bac &gt;ConcaveTh, the different-pixel extracting unit  16   a  determines that the pixel is depressing more than the surroundings and extracts the pixel. 
     Subsequently, the region-data obtaining unit  16   b  defines a region of the suspected convexity or concavity lesion that is extracted at Step S 202  and extracts a region that is possibly the suspected lesion region (Step S 203 ). Specifically, the region-data obtaining unit  16   b  first creates a convexity binary image, in which the pixel that is protruding more than the surroundings is “1” and the pixel that is no protruding more than the surroundings is “0”, and a concavity binary image, in which the pixel that is depressing more than the surroundings is “1” and the pixel that is no depressing more than the surroundings is “0”. The region-data obtaining unit  16   b  then performs the well-known labeling process on each of the convexity binary image and the concavity binary image and assigns a unique value (label) to connection components (a group of pixels connected to each other) of the binary images, thereby defining the region. By this definition, a convexity image containing labeled convexities that are obtained by defining the convexities in the convexity binary image and a concavity image containing labeled concavities that are obtained by defining the concavities in the concavity binary image are obtained. The region-data obtaining unit  16   b  then determines the convexity to be the convexity that is possibly the suspected lesion region and the concavity to be the concavity that is possibly the suspected lesion region and determines both the convexity and the concavity to be the regions that is possibly the suspected lesion regions. 
     Subsequently, the region-data obtaining unit  16   b  calculates feature data on each of the regions that are possibly the suspected lesion regions that are extracted at Step S 203  (Step S 204 ). The feature data is expressed by, for example, the average of pixel values within the region (R abs     —     m , G abs     —     m , B abs     —     m ), the average of pixel-value variation amounts within the region (R var     —     m , G var     —     m , B var     —     m ), the area of the region S —     m   , the perimeter of the region L —     m   , the Feret&#39;s diameter of the region Fere —     m   (θ), the longer diameter of the region L l     —     m , the shorter diameter of the region L s     —     m , the ratio between the longer diameter and the shorter diameter L r     —     m , the edge strength of the outline of the region E —     m   , and the degree of circularity of the region C —     m   . These values are calculated from each of the regions that are possibly the suspected lesion regions. The suffix m indicates an identification number of the suspected lesion region. 
     The average of pixel values within the region (R abs     —     m , G abs     —     m , B abs     —     m ) is obtained by calculating a sum of R values, a sum of G values, and a sum of B values of the pixels that are in the same suspected lesion region and then dividing the sums by the area of the region. 
     To calculate the average of pixel-value variation amounts within the region (R var     —     m , G var     —     m ), it is necessary to calculate the pixel-value variation amount of each of R, G, and B components of each of the pixels that form the in-vivo image. The pixel-value variation amount V dir  that is calculated at Step S 201  can be used as the pixel-value variation amount of the G component. 
     When it is focused on the G component, as for the pixels that is other than the background of the convexity image or the concavity image (labeled pixels), an average of the directional pixel-value variation amounts V r  is calculated using the following equation (5). As for the pixels that are the background of the convexity image or the concavity image (unlabeled pixels, i.e., pixels that are neither the convexity nor the concavity), V r =0. 
     
       
         
           
             
               
                 
                   
                     V 
                     r 
                   
                   = 
                   
                     
                       
                         V 
                         hor 
                       
                       ⁢ 
                       
                           
                       
                       + 
                       
                         V 
                         ver 
                       
                       + 
                       
                         V 
                         sla 
                       
                       + 
                       
                         V 
                         bac 
                       
                     
                     4 
                   
                 
               
               
                 
                   ( 
                   5 
                   ) 
                 
               
             
           
         
       
     
     The averages of the directional pixel-value variation amounts V r  in the G component of all the pixels in the same suspected lesion region are added, and the calculated sum is divided by the area of the region, whereby the average of the pixel-value variation amounts within the region G var     —     m  is calculated. Alternatively, the average of the pixel-value variation amounts within the region can be calculated using the maximum value or the minimum value of the pixel-value variation amounts V dir  instead of the average of the directional pixel-value variation amounts. 
     As for the R component and the B component, the pixel-value variation amount of each direction is calculated using equations (1) to (4) in the same manner as described with reference to  FIG. 4 . The average of the directional pixel-value variation amounts V r  is then calculated in the same manner as in the G component. The averages of the directional pixel-value variation amounts of all the pixels in the same suspected lesion region are added and the calculated sum is divided by the area of the region, whereby the averages of the pixel-value variation amounts within the region R var     —     m  and B var     —     m  are calculated. It is allowable to calculate the average of the direction pixel-value variation amounts V r  in the R component and the B component only if the pixel is extracted as the convexity or the concavity using the average of the direction pixel-value variation amounts V r  in the G component, i.e., the pixel has the pixel value “1” in the convexity binary image or the concavity binary image. This reduces the calculation load, which makes high-speed processing possible. 
     The area of the region S —     m    is calculated on each suspected lesion region by counting the number of pixels that are in the same suspected lesion region. 
     The perimeter of the region L —     m    is calculated on each suspected lesion region by counting the number of pixels that are positioned on the outline of the region from among the pixels that are in the same suspected lesion region. Specifically, a pixel from among the pixels that form the in-vivo image is assumed to be a focus pixel and whether the focus pixel is an outline pixel is determined. The pixels that form the in-vivo image are set to the focus pixel sequentially.  FIG. 5  is a schematic diagram that explains how to determine the outline pixel. As shown in  FIG. 5 , four pixels P 1  to P 4  that are adjacent to the focus pixel IP are assumed to be the surrounding pixels. It is then determined whether any of the surrounding pixels P 1  to P 4  is a background pixel or a pixel with a label number different from that of the focus pixel IP. If the determination is positive, the focus pixel IP is determined to be an outline pixel. The number of the outline pixels that are determined in this manner is counted on each suspected lesion region. 
     The Feret&#39;s diameter of the region Fere —     m   (θ 1 ), the longer diameter of the region L l     —     m , and the shorter diameter of the region L s     —     m  are calculated in the following procedure.  FIG. 6  is a schematic diagram that explains how to calculate the Feret&#39;s diameter Fere —     m   (θ 1 ) of a suspected lesion region  19 . As shown in  FIG. 6 , two lines  21   a  and  21   b  tangent to the suspected lesion region  19  are obtained in such a manner that an angle between the tangent line  21   a  and a horizontal line  20   a  and an angle between the tangent line  21   b  and a horizontal line  20   b  are set to θ 1  and the distance between the tangent lines  21   a  and  21   b  are set as long as possible. A distance  22  between the two tangent lines is the Feret&#39;s diameter Fere —     m   (θ 1 ) of the suspected lesion region  19  at the angle θ 1 . The Feret&#39;s diameter of the target suspected lesion region is calculated at each angle φ. The maximum Feret&#39;s diameter of the calculated Feret&#39;s diameters is the longer diameter of the region L l     —     m . The minimum Feret&#39;s diameter of the calculated Feret&#39;s diameters is the shorter diameter of the region L s     —     m . 
     The Feret&#39;s diameter Fere —     m   (0) where the angle θ 1  is 0 degree and the Feret&#39;s diameter Fere —     m   (90) where the angle θ 1  is 90 degrees are calculated using the following equations (6) and (7) using the start coordinate point (x S , y S ) and the end coordinate point (x E , y E ) of the bounding rectangle of the target suspected lesion region:
 
Fere —     m   (0)= x   E   −x   S   (6)
 
Fere —     m   (90)= y   E   −y   S   (7)
 
     To calculate the Feret&#39;s diameter Fere —     m   (φ 1 ) where the angle φ 1  is other than 0 degree or 90 degrees, a y coordinate of an intersection of a line having the angle φ 1  with the y axis (line of pixels with x=0), i.e., a value of an intercept b φ1 (j) is first calculated using the outline pixels of the target suspected lesion region. The value of the intercept b φ1 (j) is calculated using the following equation (8) where (x j , y j ) is the position of the j-th outline pixel of the target suspected lesion region. The pixel position (x j , y j ) of the outline pixel is used in equation (8). This is because every tangent line of the region is tangent to a pixel that is positioned on the outline of the region. Therefore, the Feret&#39;s diameter is calculated using only the outline pixels, i.e., part of the entire pixels in the region.
 
 b   φ1 ( j )=−tan φ 1   ·x   j   −y   j   (8)
 
     The minimum value Min_b φ1  and the maximum value Max_b φ1  of the value of the intercept, which is calculated using equation (8), of each outline pixel at the angle φ 1  are then calculated using the following equations (9) and (10):
 
Min —   b   φ1 =min( b   φ1 ( j ))  (9)
 
(j=0, 1, 2, . . . , n)
 
Max —   b   φ1 =max( b   φ1 ( j ))  (10)
 
(j=0, 1, 2, . . . , n)
 
where n is the number of the outline pixels.
 
     The Feret&#39;s diameter Fere —     m   (φ 1 ) at the angle φ 1  is then calculated using the following equation (11):
 
Fere —     m   (φ 1 )=(Max —   b   φ1 −Max —   b   φ1 )×|cos φ 1 |  (11)
 
     The Feret&#39;s diameter Fere —     m   (φ i ) at a different angle φ i  is calculated using equations (8) to (11) in the same manner. 
     Then, the longer diameter L l     —     m , which is the maximum Feret&#39;s diameter of the Feret&#39;s diameters Fere —     m   (φ i ) of the target suspected lesion region that are calculated by increment of the angle φ i , and the shorter diameter L s     —     m , which is the minimum Feret&#39;s diameter, are calculated using the following equations (12) and (13). The angle φ used in equations (12) and (13) is an arbitrary angle. In an actual calculation of the longer diameter L l     —     m  and the shorter diameter L s     —     m , the angle φ increases appropriately by an interval, for example, 22.5 degrees.
 
 L   l     —     m =max(Fere —     m   (φ))  (12)
 
 L   s     —     m =min(Fere —     m   (φ))  (13)
 
     The ratio between the longer diameter and the shorter diameter L r     —     m  is calculated using the following equation (14): 
     
       
         
           
             
               
                 
                   
                     L 
                     
                       r 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       _ 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       m 
                     
                   
                   = 
                   
                     
                       L 
                       
                         l 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         _ 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         m 
                       
                     
                     
                       L 
                       
                         s 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         _ 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         m 
                       
                     
                   
                 
               
               
                 
                   ( 
                   14 
                   ) 
                 
               
             
           
         
       
     
     The edge strength of the outline of the region E —     m    is calculated by applying an edge detecting filter shown in  FIG. 7-1  or  FIG. 7-2  to a grayscale image that represents either any of the R component, the G component, and the B component of the in-vivo image or an average of the R, the G, and the B components. 
     An edge strength image E 1 (i) that is created using a sobel (Sobel) filter, which is the first deviation, is expressed by the following equation (15) using an output S 1 ( i ) that is a convolution of a sobel filter SF 1  in the horizontal direction (x direction) shown in  FIG. 7-1  and an output S 2 ( i ) that is a convolution of a sobel filter SF 2  in the vertical direction (y direction) shown in  FIG. 7-2  in which i indicates the pixel position in the image:
 
 E   1 ( i )=√{square root over ( S 1( i ) 2   +S 2( i ) 2 )}{square root over ( S 1( i ) 2   +S 2( i ) 2 )}  (15)
 
     Subsequently, values of the edge strength image at positions of the outline pixels are read on each suspected lesion region. All the edge strength values in the same suspected lesion region are added, and the calculated sum is divided by the perimeter L —     m    of the suspected lesion region using the following equation (16), whereby the edge strength of the outline of the region E —     m    is calculated. 
     
       
         
           
             
               
                 
                   
                     E 
                     
                       _ 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       m 
                     
                   
                   = 
                   
                     
                       
                         ∑ 
                         i 
                       
                       ⁢ 
                       
                         
                           E 
                           1 
                         
                         ⁡ 
                         
                           ( 
                           i 
                           ) 
                         
                       
                     
                     
                       L 
                       
                         _ 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         m 
                       
                     
                   
                 
               
               
                 
                   ( 
                   16 
                   ) 
                 
               
             
           
         
       
     
     The degree of circularity C —     m    is calculated using the following equation (17) using the area of the region S —     m    and the perimeter of the region L —     m   : 
     
       
         
           
             
               
                 
                   
                     C 
                     
                       _ 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       m 
                     
                   
                   = 
                   
                     
                       4 
                       ⁢ 
                       π 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       
                         S 
                         
                           _ 
                           ⁢ 
                           
                               
                           
                           ⁢ 
                           m 
                         
                       
                     
                     
                       L 
                       
                         
                             
                         
                         ⁢ 
                         
                           _ 
                           ⁢ 
                           
                               
                           
                           ⁢ 
                           m 
                         
                       
                       2 
                     
                   
                 
               
               
                 
                   ( 
                   17 
                   ) 
                 
               
             
           
         
       
     
     After the feature data of the suspected lesion region is calculated as described above, the regional-feature-data determining unit  16   c  refines suspected lesion regions by excluding concavities having feature data that indicates something other than lesions from the concavities that are possibly the suspected lesion regions (Step S 205 ) as shown in  FIG. 3 . Specifically, the regional-feature-data determining unit  16   c  determines whether each concavity that is possibly the suspected lesion region is a lesion or a non-lesion by comparing the feature data with a distribution of feature data on teacher data. If, for example, the average of pixel values within the region (R abs     —     m , G abs     —     m , B abs     —     m  is used as a feature-data parameter x to determine whether the target concavity is a lesion or a non-lesion, the following process is performed in advance. Sample regions that represent various medical conditions, such as bleeding, are collected as teacher data. The sample regions are categorized into some lesion groups on the medical-condition basis. A pixel-value average μ k  and a pixel-value covariance Σ k  of each of the lesion groups are calculated, in which k indicates the group number of the lesion group. Samples are collected even from the concavities that are not the suspected lesion regions. These samples are categorized into non-lesion groups in such a manner that some having the same factor because of which they are extracted as the concavities or some having the pixel-value averages closer to each other are categorized to the same non-lesion group. A pixel-value average μ i  and a pixel-value covariance Σ i  of each of the non-lesion groups are calculated, in which i indicates the group number of the non-lesion group. 
     A probability that the target concavity to be compared is generated from a distribution of a lesion group is calculated using the following equation (18) where the distribution of each of the lesion groups is assumed to be a normal distribution, and a probability that the target concavity is generated from a distribution of a non-lesion group is calculated using the following equation (19) where the distribution of each of the non-lesion groups is assumed to be a normal distribution: 
     
       
         
           
             
               
                 
                   
                     p 
                     ⁡ 
                     
                       ( 
                       
                         k 
                         | 
                         x 
                       
                       ) 
                     
                   
                   = 
                   
                     
                       1 
                       
                         
                           
                             ( 
                             
                               2 
                               ⁢ 
                               π 
                             
                             ) 
                           
                           
                             n 
                             / 
                             2 
                           
                         
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         
                           
                              
                             
                               Σ 
                               k 
                             
                              
                           
                           
                             1 
                             / 
                             2 
                           
                         
                       
                     
                     ⁢ 
                     exp 
                     ⁢ 
                     
                       { 
                       
                         
                           - 
                           
                             1 
                             2 
                           
                         
                         ⁢ 
                         
                           
                             ( 
                             
                               x 
                               - 
                               
                                 μ 
                                 k 
                               
                             
                             ) 
                           
                           t 
                         
                         ⁢ 
                         
                           
                             ( 
                             
                               Σ 
                               k 
                             
                             ) 
                           
                           
                             - 
                             1 
                           
                         
                         ⁢ 
                         
                           ( 
                           
                             x 
                             - 
                             
                               μ 
                               k 
                             
                           
                           ) 
                         
                       
                       } 
                     
                   
                 
               
               
                 
                   ( 
                   18 
                   ) 
                 
               
             
             
               
                 
                   
                     p 
                     ⁡ 
                     
                       ( 
                       
                         i 
                         | 
                         x 
                       
                       ) 
                     
                   
                   = 
                   
                     
                       1 
                       
                         
                           
                             ( 
                             
                               2 
                               ⁢ 
                               π 
                             
                             ) 
                           
                           
                             n 
                             / 
                             2 
                           
                         
                         ⁢ 
                         
                           
                              
                             
                               E 
                               i 
                             
                              
                           
                           
                             1 
                             / 
                             2 
                           
                         
                       
                     
                     ⁢ 
                     exp 
                     ⁢ 
                     
                       { 
                       
                         
                           - 
                           
                             1 
                             2 
                           
                         
                         ⁢ 
                         
                           
                             ( 
                             
                               x 
                               - 
                               
                                 μ 
                                 i 
                               
                             
                             ) 
                           
                           t 
                         
                         ⁢ 
                         
                           
                             ( 
                             
                               Σ 
                               i 
                             
                             ) 
                           
                           
                             - 
                             1 
                           
                         
                         ⁢ 
                         
                           ( 
                           
                             x 
                             - 
                             
                               μ 
                               i 
                             
                           
                           ) 
                         
                       
                       } 
                     
                   
                 
               
               
                 
                   ( 
                   19 
                   ) 
                 
               
             
           
         
       
     
     where n in equations (18) and (19) is the dimension number of the feature data. If the average of pixel values within the region (R abs     —     m , G abs     —     m , B abs     —     m ) is used as the feature-data parameter x, n=3. 
     A probability p k=a  that the target concavity belongs to a certain medical condition a is then calculated using the following equation (20) using the probability p(k|x), which is calculated using equation (18) as the probability that the target concavity is generated from a distribution of a lesion group, and the probability p(i|x), which is calculated using equation (19) as the probability that the target concavity is generated from a distribution of a non-lesion group: 
     
       
         
           
             
               
                 
                   
                     p 
                     
                       k 
                       = 
                       a 
                     
                   
                   = 
                   
                     
                       p 
                       ⁡ 
                       
                         ( 
                         
                           k 
                           = 
                           
                             a 
                             | 
                             x 
                           
                         
                         ) 
                       
                     
                     
                       
                         ∑ 
                         
                           p 
                           ⁡ 
                           
                             ( 
                             
                               i 
                               | 
                               x 
                             
                             ) 
                           
                         
                       
                       - 
                       
                         ∑ 
                         
                           p 
                           ⁡ 
                           
                             ( 
                             
                               k 
                               | 
                               x 
                             
                             ) 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   20 
                   ) 
                 
               
             
           
         
       
     
     In equation (20), the probability that the target concavity having the feature-data parameter x is generated from the distribution of the lesion group that represents the medical condition a is expressed by p(k=a|x). The sum of the probabilities that the target concavity is generated from a distribution of a non-lesion group is expressed by Σp(i|x). The sum of the probabilities that the target concavity is generated from a distribution of a lesion group is expressed by Σp(k|x). In this manner, the probability p k=a  that the target concavity belongs to the certain medical condition a is calculated by normalizing the target concavity having the certain feature-data parameter x using the sum of the probabilities of all the groups that the target concavity is generated from a lesion group. 
     The probability that the target concavity belongs to a certain medical condition is calculated on each medical condition using equation (20). The value of the medical condition having the highest probability among the calculated probabilities is assumed to be p(k=a max |x). If this value is equal to or lower than a predetermined threshold LesionProbTh, i.e., p(k=a max |x)≦LesionProbTh, the target concavity is determined to be a concavity that is generated due to a factor other than a lesion and excluded from the concavities that are possibly the suspected lesion region. The remaining concavities are extracted as the suspected concavity lesion regions. 
     Subsequently, the regional-feature-data determining unit  16   c  performs the processing on the convexities that are possibly the suspected lesion regions in the same manner as it determines at Step S 205  whether the concavity is a lesion or a non-lesion and excludes the convexity having the feature data that indicates something other than lesions, thereby refining the suspected lesion regions (Step S 206 ). After that, the process control returns to Step S 2  of  FIG. 2 . That is, it calculates the probability, which is generated from a distribution of a group of the prepared teacher data, and determines whether the target region is a lesion or a non-lesion. Then, the convexities that are generated due to a factor other than a lesion are excluded from the convexities that are possibly the suspected lesion regions. The remaining convexities are extracted as the suspected convexity lesion regions. 
     The feature-data parameter that is used to determine whether the target region is the region that is possibly the suspected lesion region is not limited to the average of pixel values within the region (R abs     —     m , G abs     —     m , B abs     —     m ). Some other values, such as the area of the region S —     m   , the perimeter of the region L —     m   , the Feret&#39;s diameter of the region Fere —     m   (θ), the longer diameter of the region L l     —     m , the shorter diameter of the region L s     —     m , the ratio between the longer diameter and the shorter diameter L r     —     m , the edge strength of the outline of region E —     m   , and the degree of circularity of the region C —     m    can be used. Moreover, it is allowable to combine these values appropriately. The process at Step S 206  using the convexities can be performed prior to the process at Step S 205  using the concavities, or these processes can be performed in parallel. 
     The groove determining process at Step S 3  of  FIG. 2  is described below.  FIG. 8  is a flowchart showing the groove determining process in detail. In the groove determining process, each of the suspected concavity lesion regions is subjected to a set of processes indicated by a loop A (Steps S 301  to S 307 ). The reason why the suspected concavity lesion regions are in focus is that a part corresponding to a groove that is formed between in-vivo organ walls is included in regions that are depressing more than the surroundings. In the explanation about the processes of the loop A, the suspected concavity lesion region to be processed is referred to as a focus concavity. 
     In the loop A, the surrounding-similar-pixel extracting unit  17   a  first extracts a pixel having a pixel value that is close to those of the pixels that form the focus concavity from pixels surrounding the focus concavity (Step S 302 ). Specifically, the surrounding-similar-pixel extracting unit  17   a  first defines a surrounding pixel area that is a predetermined area surrounding the focus concavity. 
       FIGS. 9-1  and  9 - 2  are schematic diagrams that explain how to define the surrounding pixel area. The surrounding pixel area is defined by calculating, using a start coordinate point (x RS , y RS ) and an end coordinate point (x RE , y RE ) of a bounding rectangle Z 13  of a focus concavity Z 11 , a start coordinate point (x PS , y PS ) and an end coordinate point (x PE , y PE ) of a rectangular region Z 15  that is obtained by extending the bounding rectangle Z 13  using an extension value RegionLen. In the present embodiment, the extension value RegionLen depends on a size of the focus concavity as is clear from, for example, the following equation (21). As shown in  FIG. 9-2 , if a focus concavity Z 21  is positioned near a corner of the image, specifically, if an area Z 24  that is outside the image area as indicated by dot lines shown in  FIG. 9-2  is obtained when the surrounding pixel area is defined using the method that is described with reference to  FIG. 9-1 , the surrounding pixel area is defined in the following manner. The extension value RegionLen that is a value by which the region is extended in a direction opposite to a direction in which it is outside the image area is set, for example, double. In the example shown in  FIG. 9-2 , the area Z 24  indicated by the dotted lines is outside the side of the image area running toward right in  FIG. 9-2  along the x axis and the side of the image area running toward the bottom in  FIG. 9-2  along the y axis. The surrounding pixel area is defined by calculating the start coordinate point (x PS , y PS ) and the end coordinate point (x PE , y PE ) of the rectangular region Z 25  that is obtained by extending by RegionLen×2 in both the leftward direction in  FIG. 9-2  along the negative x axis and the upward direction in  FIG. 9-2  along the negative y axis. With this configuration, even if the focus concavity is present near an edge of the image, it is possible to define the large-enough surrounding pixel area. Therefore, a pixel having a pixel value close to those of the pixels that form the focus concavity can be extracted with a high accuracy in the later-described process. 
     Actually, the surrounding pixel area is calculated and defined using the following equations (21) to (25) using the start coordinate point (x RS , y RS ) and the end coordinate point (x RE , y RE ) of the bounding rectangle of the focus concavity. ImgSizeX is a size of the in-vivo image in the x coordinate. ImgSizeY is a size of the in-vivo image in the y coordinate. 
     
       
         
           
             
               
                 
                   RegionLen 
                   = 
                   
                     
                       
                         
                           ( 
                           
                             
                               x 
                               
                                 RE 
                                 ⁢ 
                                 
                                     
                                 
                               
                             
                             - 
                             
                               x 
                               RS 
                             
                           
                           ) 
                         
                         2 
                       
                       + 
                       
                         
                           ( 
                           
                             
                               y 
                               RE 
                             
                             - 
                             
                               y 
                               RS 
                             
                           
                           ) 
                         
                         2 
                       
                     
                   
                 
               
               
                 
                   ( 
                   21 
                   ) 
                 
               
             
             
               
                 
                   
                     x 
                     PS 
                   
                   = 
                   
                     { 
                     
                       
                         
                           
                             
                               x 
                               RS 
                             
                             - 
                             RegionLen 
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         x 
                                         PE 
                                       
                                     
                                     &lt; 
                                     
                                       ImgSizeX 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     calculated 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       24 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                       
                         
                           
                             
                               x 
                               RS 
                             
                             - 
                             
                               RegionLen 
                               × 
                               2 
                             
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         x 
                                         PE 
                                       
                                     
                                     ≥ 
                                     
                                       ImgSizeX 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     calculated 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       24 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   22 
                   ) 
                 
               
             
           
         
       
     
     If x PS &lt;0, x PS  is set to 0 after evaluated using Equation (24). 
     
       
         
           
             
               
                 
                   
                     y 
                     PS 
                   
                   = 
                   
                     { 
                     
                       
                         
                           
                             
                               y 
                               RS 
                             
                             - 
                             RegionLen 
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         y 
                                         PE 
                                       
                                     
                                     &lt; 
                                     
                                       ImgSizeY 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     calculated 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       25 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                       
                         
                           
                             
                               y 
                               RS 
                             
                             - 
                             
                               RegionLen 
                               × 
                               2 
                             
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         y 
                                         PE 
                                       
                                     
                                     ≥ 
                                     
                                       ImgSizeY 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     calculated 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       25 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   23 
                   ) 
                 
               
             
           
         
       
     
     If y PS &lt;0, y PS  is set to 0 after evaluated using Equation (25). 
     
       
         
           
             
               
                 
                   
                     x 
                     PE 
                   
                   = 
                   
                     { 
                     
                       
                         
                           
                             
                               x 
                               RE 
                             
                             + 
                             RegionLen 
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         x 
                                         PS 
                                       
                                     
                                     ≥ 
                                     
                                       0 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       calculated 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       22 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                       
                         
                           
                             
                               x 
                               RE 
                             
                             + 
                             
                               RegionLen 
                               × 
                               2 
                             
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         x 
                                         PS 
                                       
                                     
                                     &lt; 
                                     
                                       0 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       calculated 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       22 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   24 
                   ) 
                 
               
             
           
         
       
     
     If x PE ≧ImgSizeX,
         x PE  is set to ImgSizeX−1 after evaluated using Equation (22).       

     
       
         
           
             
               
                 
                   
                     y 
                     PE 
                   
                   = 
                   
                     { 
                     
                       
                         
                           
                             
                               y 
                               RE 
                             
                             + 
                             RegionLen 
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         y 
                                         PS 
                                       
                                     
                                     ≥ 
                                     
                                       0 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       calculated 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       23 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                       
                         
                           
                             
                               y 
                               RE 
                             
                             + 
                             
                               RegionLen 
                               × 
                               2 
                             
                           
                         
                       
                       
                         
                           
                             ( 
                             
                               
                                 
                                   
                                     
                                       IF 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       
                                         y 
                                         PS 
                                       
                                     
                                     &lt; 
                                     
                                       0 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       is 
                                       ⁢ 
                                       
                                           
                                       
                                       ⁢ 
                                       calculated 
                                     
                                   
                                 
                               
                               
                                 
                                   
                                     using 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     Equation 
                                     ⁢ 
                                     
                                         
                                     
                                     ⁢ 
                                     
                                       ( 
                                       23 
                                       ) 
                                     
                                   
                                 
                               
                             
                             ) 
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   25 
                   ) 
                 
               
             
           
         
       
     
     If Y PE ≧ImgSizeY,
         Y PE  is set to ImgSizeY−1 after evaluated using Equation (23).       

     The method of setting the surrounding pixel area is not limited to the setting method using the start point (x RS , y RS ) and the end coordinate point (x RE , y RE ) of the bounding rectangle of the focus concavity. Some other values, such as a length of the diagonal of the bounding rectangle of the focus concavity, the area, the Feret&#39;s diameter, the longer diameter, and the shorter diameter of the focus concavity, can be used. 
     The surrounding-similar-pixel extracting unit  17   a  then extracts a pixel having a pixel value close to those of the pixels that form the focus concavity from the pixels I p  (x, y, z) (x=x PS , . . . , x PE , y=y PS , . . . , y PE , z=R, G, B). Because the area from which pixels are extracted is limited to the surrounding pixel area, it is possible to reduce the calculation load and improve the processing speed. Specifically, if the pixel I P  satisfies the following inequalities (26) to (28), the pixel I P  is extracted as the pixel having the pixel value close to those of the pixels that form the focus concavity. This determination is made using at least one of the brightness, the chromaticity, and the color difference of the pixel containing the G component. In most true lesion regions where bleeding or discoloration of organ tissues is observed, an abnormality appears in the blood flowing through organ tissues. Therefore, the G component, which is corresponding to the blood bleeding band and is sensible enough to show a difference between the healthy region and the lesion region in the form of the pixel value, is used. SimilarGValTh, SimilarG_RValTh, and SimilarGBValTh are predetermined thresholds. R abs     —     m  is an average of the R components within the region of the focus concavity; G abs     —     m  is the G components within the region of the focus concavity; and B abs     —     m  is the B components within the region of the focus concavity. 
     
       
         
           
             
               
                 
                   
                      
                     
                       
                         
                           I 
                           p 
                         
                         ⁡ 
                         
                           ( 
                           
                             x 
                             , 
                             y 
                             , 
                             G 
                           
                           ) 
                         
                       
                       - 
                       
                         G 
                         
                           ab 
                           ⁢ 
                           
                               
                           
                           ⁢ 
                           s 
                           ⁢ 
                           
                               
                           
                           ⁢ 
                           _ 
                           ⁢ 
                           
                               
                           
                           ⁢ 
                           m 
                         
                       
                     
                      
                   
                   ≤ 
                   SimilarGValTH 
                 
               
               
                 
                   ( 
                   26 
                   ) 
                 
               
             
             
               
                 
                   
                      
                     
                       
                         
                           
                             I 
                             p 
                           
                           ⁡ 
                           
                             ( 
                             
                               x 
                               , 
                               y 
                               , 
                               G 
                             
                             ) 
                           
                         
                         
                           
                             I 
                             p 
                           
                           ⁡ 
                           
                             ( 
                             
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     Subsequently, the extended-groove-region creating unit  17   b  creates a groove-direction extended region (Step S 303 ) and calculates shape feature data of the created groove-direction extended region (Step S 304 ). Specifically, the extended-groove-region creating unit  17   b  performs well-know region definition process using particle analysis by using both the pixels that contribute the focus concavity and the pixels that are extracted from the surrounding pixel area at Step S 302  because they have pixel values close to those of the focus concavity and sets the obtained region to be the groove-direction extended region. The extended-groove-region creating unit  17   b  calculates the shape feature data of the groove-direction extended region using the particle analysis. The extended-groove-region creating unit  17   b  calculates, for example, an area ES —     m    of the obtained groove-direction extended region as the shape feature data. 
     After that, the extended-groove-region creating unit  17   b  calculates a ratio RS —     m    between the area S —     m    of the focus concavity and the area ES —     m    of the groove-direction extended region using the following equation (29) as a shape feature-data variation amount between the focus concavity and the groove-direction extended region that is created based on the focus concavity (Step S 305 ). 
     
       
         
           
             
               
                 
                   
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     The shape feature data that is calculated at Step S 304  is not limited to the area of the groove-direction extended region. Some other values, such as the perimeter of the region, the Feret&#39;s diameter, the longer diameter of the region, the shorter diameter of the region, the ratio between the longer diameter and the shorter diameter, can be calculated. The shape feature-data variation amount that is calculated at Step S 305  is not limited to the ratio between the area of the focus concavity and the area of the groove-direction extended region. Some other values, such as the difference in the perimeter of the region, the difference in the Feret&#39;s diameter of the region, the difference between the longer diameter and the shorter diameter of the region, and the difference in the ratio between the longer diameter and the shorter diameter of the region, can be calculated in accordance with the shape feature data. 
     If the ratio RS —     m    between the area S —     m    of the region and the area ES —     m    of the groove-direction extended region satisfies the following inequality (30), the extended-groove-region creating unit  17   b  determines that the focus concavity is the groove region (Step S 306 ):
 
 RS   —     m   &gt;SurroundAreaDifTh  (30)
 
where SurroundAreaDifTh is a predetermined threshold.
 
     After each of the suspected lesion regions has been subjected to the processes of the loop A as the focus concavity, the process control returns to Step S 3  of  FIG. 2 . 
     The lesion-region extracting process at Step S 4  of  FIG. 2  is described below. In the lesion-region extracting process, the lesion-region extracting unit  18  excludes the suspected concavity lesion region that is determined to be the groove region in the groove determining process from the suspected lesion regions and extracts the remaining suspected concavity regions and the suspected convexity regions that are extracted at Step S 206  as the lesion regions. 
     An example of the lesion region extracted in the present embodiment from an exemplary in-vivo image is described below.  FIG. 10  is a display example of an original in-vivo image. The in-vivo image shown in  FIG. 10  includes a bleeding section  23  and grooves  24  and  25  that are formed between organ walls.  FIG. 11  is an example of an extracted concavity image that represents the suspected concavity region that is extracted from the in-vivo image shown in  FIG. 10 . In the example shown in  FIG. 11 , a plurality of suspected concavity lesion regions  26  to  30  having the substantially same area that is extracted through the suspected-lesion-region extracting process is shown. 
       FIG. 12  is an example of the groove-direction extended region that is created from each of the suspected concavity lesion regions  26  to  30  shown in the extracted concavity image of  FIG. 11 . As shown in  FIG. 12 , the suspected concavity lesion regions  27  and  28  (see  FIG. 11 ), which are associated with the groove  24  that is formed between the organ walls (see  FIG. 10 ), are extended in the direction in which the pixels that form the groove  24  are arranged and converted to groove-direction extended regions  32  and  33 , respectively. The suspected concavity lesion regions  29  and  30  (see  FIG. 11 ), which are associated with the groove  25  that is formed between the organ walls (see  FIG. 10 ) are extended in the direction in which the pixels that form the groove  25  are arranged and converted to groove-direction extended regions  34  and  35 , respectively. In the suspected concavity lesion region that is associated with the groove, because the pixel value, such as brightness, changes gradually as it goes along the groove, pixels having pixels values close to each other are arranged along the groove direction. Therefore, the created groove-direction extended region is extended in the groove direction from the original extracted concavity image. 
     The suspected concavity lesion region  26  that is associated with the bleeding section  23  is converted to a groove-direction extended region  31  shown in  FIG. 12  as a result of creation of the groove-direction extended region. A change from the suspected concavity lesion region  26  to the groove-direction extended region  31  is not large. In most lesion regions, such as a bleeding section, the pixel value, such as the brightness, the color ratio, and the color difference, changes drastically when it comes from the surrounding area to the lesion region. The probability that a pixel having a close pixel value is present in the surrounding area is low. Therefore, a change from the original extracted concavity image to the created groove-direction extended region is small. 
     In this manner, the lesion-region extracting unit  18  determines, while assuming that the suspected concavity lesion regions  27 ,  28 ,  29 , and  30  shown in  FIG. 11  that are extended by the process performed by the groove determining unit  17  in the direction in which the pixels that form the groove to be the groove regions, the suspected concavity lesion region  26 , which is not extended largely, to be the lesion region and finally extracts the suspected concavity lesion region  26  as the lesion region. 
     After the lesion region is extracted, a lesion region  36  is displayed as an extracted lesion image in a recognizable manner on the display unit  15  at Step S 5  of  FIG. 2  as shown in  FIG. 13 , for example. The display manner is not limited to the manner shown in  FIG. 13  in which the extracted lesion region in a color different from a color of the background is displayed on a background image (in, for example, black color) having the same size as the original in-vivo image. For example, it is allowable to display this extracted lesion image overlapped with the in-vivo image. Alternatively, it is allowable to display the outline of the lesion region on the in-vivo image so that the lesion region within the in-vivo image can be identified. 
     According to the present embodiment, the accuracy in detecting a lesion region is maintained high, regardless of change of the pixel value due to, for example, how grooves and part other than the grooves are exposed to an illumination light. Therefore, an image processing apparatus that is stable against difference in an in-vivo image taking environment can detect the lesion region with a high accuracy. 
     Additional advantages and modifications will readily occur to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details and representative embodiments shown and described herein. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents.