Source: http://www.google.com/patents/US5557687?dq=6,757,682
Timestamp: 2016-05-30 18:45:07
Document Index: 101670014

Matched Legal Cases: ['art 17', 'art 16', 'art 18', 'art 16', 'art 56', 'art 56']

Patent US5557687 - Abnormal pattern detecting apparatus - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inPatentsAn abnormal pattern detecting apparatus comprises an image operating device which generates at least an original image signal representing an original image and a soft tissue image signal representing a soft tissue image from several image signals representing radiation images of an object, which radiation...http://www.google.com/patents/US5557687?utm_source=gb-gplus-sharePatent US5557687 - Abnormal pattern detecting apparatusAdvanced Patent SearchPublication numberUS5557687 APublication typeGrantApplication numberUS 08/389,744Publication dateSep 17, 1996Filing dateFeb 15, 1995Priority dateOct 19, 1989Fee statusPaidPublication number08389744, 389744, US 5557687 A, US 5557687A, US-A-5557687, US5557687 A, US5557687AInventorsShoji HaraOriginal AssigneeFuji Photo Film Co., Ltd.Export CitationBiBTeX, EndNote, RefManPatent Citations (15), Non-Patent Citations (6), Referenced by (20), Classifications (24), Legal Events (4) External Links: USPTO, USPTO Assignment, EspacenetAbnormal pattern detecting apparatus
US 5557687 AAbstract
An abnormal pattern detecting apparatus comprises an image operating device which generates at least an original image signal representing an original image and a soft tissue image signal representing a soft tissue image from several image signals representing radiation images of an object, which radiation images have been recorded by exposing the object to at least two kinds of radiation having different energy distributions. A region discriminating device discriminates anatomical regions in the radiation image from at least one of the image signals. An abnormal pattern finding device finds an abnormal pattern, which appears in the original image or the soft tissue image, by processing the original image signal or the soft tissue image signal with an abnormal pattern finding filter in accordance with the anatomical regions.
1. Apparatus for detecting an abnormal pattern from a plurality of image signals representing a radiation image of an object which is constituted of soft tissues and bones, comprising:an image operating circuit for generating from the plurality of image signals at least:a) an original image signal corresponding to an original image representing the soft tissues and the bones of said object, and b) a soft tissue image signal corresponding to a soft tissue image primarily representing soft tissues of said object, wherein said original image signal and said soft tissue image signal are generated from the plurality of image signals representing a radiation image which has been recorded by exposing said object to at least two kinds of radiation having different energy distributions, wherein the different energy distributions exhibit different transmittances with respect to soft tissues and bones; a region discriminating circuit which discriminates anatomical regions in the radiation image from at least one of said original image and soft tissue image signals, and provides an output indicative of different anatomical regions of said object; and an abnormal pattern finding circuit including an abnormal pattern finding filter, responsive to said original image and soft tissue image signals and to the output of said region discriminating circuit, said abnormal pattern finding circuit uniquely processing at least one of said original image signal and said soft tissue image signal and detecting an abnormal pattern, wherein, based on the output of said region discriminating circuit, said abnormal pattern finding circuit adaptively processes said original image signal to detect an abnormal pattern in the different anatomical regions of said object which include primarily soft tissues and processes said soft tissue image signal to detect an abnormal pattern in the different anatomical regions of said object which include primarily bones. 2. An apparatus as defined in claim 1 wherein said image operating circuit also generates a bone image signal corresponding to a bone image primarily representing the bones of said object, and wherein said region discriminating circuit finds the positions of bone patterns from said bone image signal.
3. An apparatus as defined in claim 2 wherein said abnormal pattern finding circuit processes one of said original image signal and said soft tissue image signal with an abnormal pattern finding filter in accordance with said anatomical regions and the positions of the bone patterns.
4. An apparatus as defined in claim 1 wherein said image operating circuit carries out superposition processing on the plurality of said image signals representing the plurality of said radiation images of said object and utilizes an image signal, which is obtained from the superposition processing, as said original image signal.
5. An apparatus as defined in claim 4 wherein said region discriminating circuit discriminates anatomical regions in the radiation image from said original image signal, which has been obtained from the superposition processing.
6. An apparatus as defined in claim 1 wherein said abnormal pattern finding filter is a spatial-domain filter.
7. An apparatus as defined in claim 1 wherein each of said radiation images of said object has been stored on a stimulable phosphor sheet.
8. An apparatus as defined in claim 7 wherein the image signals of said radiation images are obtained from a read-out operation wherein said stimulable phosphor sheet is exposed to stimulating rays, which cause said stimulable phosphor sheet to emit light in proportion to the amount of energy stored thereon during its exposure to radiation, and the emitted light is detected photoelectrically.
9. An apparatus as defined in claim 8 wherein said stimulating rays are a laser beam.
10. An apparatus as defined in claim 1 wherein each of said radiation images of said object has been recorded on photographic film.
This is a continuation of application Ser. No. 08/026,099 filed Mar. 4, 1993, which is a continuation of application Ser. No. 07/599,933 filed Oct. 19, 1990 both now abandoned.
Recently, in the radiation image recording and reproducing systems which use X-ray film or stimulable phosphor sheets, particularly in such radiation image recording and reproducing systems designed to facilitate medical diagnosis, not only have image signals been processed in ways which ensure that the visible images produced from them will be of high quality, but image signals have also been processed in ways which allow certain image patterns to be extracted from radiation images. One type of processing which results in extraction of an image pattern is disclosed in, for example, U.S. Pat. No. 4,769,850.
FIG. 1 is a block diagram showing the configuration of an abnormal pattern detecting apparatus in accordance with the present invention.
With reference to FIG. 1, a plurality of image signals SO1, SO2, . . . , SOn are fed from, for example, a radiation image read-out apparatus or a radiation image signal storage device, into an image operating means 1. The plurality of the image signals SO1, SO2, . . . , SOn represent radiation images of an object, which were recorded during an image recording operation wherein the object constituted of soft tissues and bones was exposed to at least two kinds of radiation having different energy distributions. The image operating means 1 carries out operations on the plurality of the image signals SO1, SO2, . . . , SOn in order to generate an original image signal S1, which represents an original image composed of both the patterns of soft tissues and the patterns of bones of the object, and a soft tissue image signal S2, which represents a soft tissue image primarily composed of the patterns of soft tissues of the object. In the image operating means 1, a bone image signal S3 may also be generated which represents a bone image primarily composed of the patterns of bones of the object.
The original image signal S1 and the soft tissue image signal S2 generated by the image operating means 1 are fed from the image operating means 1 into an abnormal pattern finding means 3. In cases where the bone image signal S3 is also generated by the image operating means 1, it is fed into the abnormal pattern finding means 3 (or into a region discriminating means 2 which will be described later).
Also, an image signal, from which information about anatomical regions in the radiation image of the object can be found, is fed from the image operating means 1 into the region discriminating means 2. By way of example, as such an image signal, one of the image signals SO1, SO2, . . . , SOn, or an original image signal S1, which has been obtained from the processing carried out on the image signals SO1, SO2, . . . , SOn, may be employed.
From the received image signal, the region discriminating means 2 discriminates anatomical regions D1, D2, . . . , Dn in the radiation image of the object from one another, and generates information about the positions of the anatomical regions D1, D2, . . . , Dn.
The term "anatomical regions" as used herein means the regions corresponding to the patterns of the structures of the object, which patterns appear in the radiation image. Specifically, the term "anatomical regions" as used herein means the regions corresponding to the patterns of the lung fields, a rib, the heart, the diaphragm, and the like, in an X-ray image of the chest. Of course, the region discriminating means 2 need not necessarily discriminate all of the regions corresponding to the patterns of the structures of the object from one another, which patterns appear in the radiation image, but may find only the necessary anatomical regions in accordance with the type of the abnormal patterns which are to be found. For example, in cases where an abnormal pattern in the lung region is to be detected, the region discriminating means 2 may discriminate only two regions, i.e. a region corresponding to the diaphragm and the heart and the other region, from each other.
The information about the positions of the anatomical regions D1, D2, . . . , Dn, which have been found by the region discriminating means 2, is fed into the abnormal pattern finding means 3.
The abnormal pattern finding means 3 processes the original image signal S1 or the soft tissue image signal S2 with an abnormal pattern finding filter in accordance with the anatomical regions D1, D2, . . . , Dn, which have been discriminated by the region discriminating means 2. In this manner, the abnormal pattern finding means 3 finds an abnormal pattern which appears in the original image or the soft tissue image. No limitation is imposed on the abnormal pattern finding filter. By way of example, one of various filters which will be described later, or a combination of two or more of the filters may be employed. Alternatively, any of known filters may be employed. By way of example, the abnormal pattern finding filter used to process the original image signal S1 may be selected from those which are suitable for finding an abnormal pattern in the original image. Also, the abnormal pattern finding filter used to process the soft tissue image signal S2 may be selected from those which are suitable for finding an abnormal pattern in the soft tissue image. In this manner, different filters may be employed during the processing of the original image signal S1 and during the processing of the soft tissue image signal S2. Additionally, in cases where the image signal components corresponding to a plurality of anatomical regions in the original image are to be processed, different filters may be employed for the image signal components corresponding to different anatomical regions. In this manner, different filters may be employed for different anatomical regions in the original image or the soft tissue image. (Such a technique is proposed in U.S. patent application Ser. No. 543,530.)
The term "abnormal pattern" as used herein means a pattern, which does not occur in standard patterns, for example, a pattern corresponding to a tumor, a calcified part, a fattened and thickened pleura, or a pneumothorax in an X-ray image of the chest. The abnormal pattern finding means 3 need not necessarily find all types of abnormal patterns, but may find only the patterns of, for example, tumors as the abnormal patterns.
As described above, the bone image signal S3 may also be fed into the abnormal pattern finding means 3. The bone image signal S3 may be utilized such that the mode of the processing with an abnormal pattern finding filter may be changed over between the processing of the original image signal S1 and the processing of the soft tissue image signal S2. By way of example, in cases where an anatomical region found by the region discriminating means 2 (e.g. the region corresponding to the lung field in an X-ray image of the chest) is composed of soft tissue patterns and bone patterns, the anatomical region may be divided into a region composed of the soft tissue patterns and a region composed of the bone patterns. When the image signal components corresponding to the region composed of the soft tissue patterns are processed with an abnormal pattern finding filter, the processing may be carried out on the corresponding region in the original image, which has better image quality than the soft tissue image. When the image signal components corresponding to the region composed of the bone patterns are processed with an abnormal pattern finding filter, the processing may be carried out on the corresponding region in the soft tissue image so that the detection of an abnormal pattern may not be adversely affected by the bone patterns.
Also, as described above, the bone image signal S3 may also be fed into the region discriminating means 2. Alternatively, the bone image signal S3 may be generated by the region discriminating means 2. When an anatomical region composed of soft tissue patterns and bone patterns is found, the region discriminating means 2 may utilize the bone image signal S3 in order to discriminate that the soft tissue patterns and the bone patterns constitute different anatomical regions.
Instead of the original image signal S1 and the soft tissue image signal S2 being processed independently in accordance with the anatomical regions, a new image signal representing a new image may be generated by combining the original image signal S1 and the soft tissue image signal S2 in the manner disclosed in, for example, U.S. Pat. No. 4,816,681. The new image signal thus generated may then be processed with an abnormal pattern finding filter. The term "processing an original image signal or a soft tissue image signal in accordance with anatomical regions" as used herein also embraces such cases.
With the abnormal pattern detecting apparatus in accordance with the present invention, at least the original image signal S1, which represents the original image, and the soft tissue image signal S2, which represents the soft tissue image, are generated from the plurality of the image signals SO1, SO2, . . . , SOn representing a plurality of radiation images of an object which were recorded with radiation having different energy distributions. Also, the anatomical regions in the radiation image are found. The original image signal or the soft tissue image signal is processed with an abnormal pattern finding filter in accordance with the anatomical regions, and an abnormal pattern is thereby found. Therefore, an abnormal pattern can be detected more accurately than with a conventional abnormal pattern detecting apparatus wherein an abnormal pattern is detected from the original image or from the soft tissue image.
FIG. 1 is a block diagram showing the abnormal pattern detecting apparatus in accordance with the present invention,
FIG. 3 is a perspective view showing an example of an X-ray image read-out apparatus and a computer system which is provided with an embodiment of the abnormal pattern detecting apparatus in accordance with the present invention,
FIGS. 4A, 4B, and 4C are schematic view showing examples of an original image, a soft tissue image, and a bone image,
FIG. 5 is a graph showing an example of a probability density function of an image signal,
FIG. 6 is an explanatory view showing how the positions of anatomical regions in the X-ray image of the chest are detected,
FIG. 7A is an enlarged view showing part of the bone image shown in FIG. 4C,
FIG. 7B is a graph showing the bone image signal S3 which corresponds to the part of the bone image shown in FIG. 7A,
FIG. 8 is a diagram having a predetermined picture element P0 from an X-ray image in the middle, which diagram serves as an aid in explaining how a spatial-domain filter works during the operations for finding a tumor pattern,
FIG. 9 is a graph showing an example of the profile of an X-ray image around a predetermined picture element P0 in the direction (x direction) along which the lines L1 and L5 shown in FIG. 8 extend,
FIG. 10 is a graph showing how a characteristic value is determined which is used during a judgment as to whether a predetermined picture element P0 falls or does not fall within the region corresponding to a tumor pattern,
FIG. 11 is an enlarged view showing part of rib patterns (not shown in FIG. 6) in the lung field regions 16a and 16b shown in FIG. 6, and
FIG. 12 is an explanatory view showing the vector of a gradient ∇fij of an image signal component fij.
In an embodiment described hereinbelow, X-ray images are stored on stimulable phosphor sheets, and a pattern of a tumor, which typically has an approximately spherical shape in the lungs of a human body, is detected as an abnormal pattern from the X-ray images. In a visible image reproduced from an image signal representing the X-ray image, the tumor pattern typically appears as an approximately circular pattern having a lower density than the areas of the image surrounding the tumor pattern.
FIG. 3 is a perspective view showing an example of an X-ray image read-out apparatus and a computer system which is provided with an embodiment of the abnormal pattern detecting apparatus in accordance with the present invention.
The computer system 40 is provided with an embodiment of the abnormal pattern detecting apparatus in accordance with the present invention. The computer system 40 comprises a main body 41 in which a CPU and an internal memory are incorporated, a disk drive unit 42 which operates a floppy disk serving as a subsidiary memory, a keyboard 43 from which necessary instructions, or the like, are fed into the computer system 40, and a CRT display device 44 which displays necessary information.
From the first image signal SO1 and the second image signal SO2 which have been fed into the computer system 40, an abnormal pattern in the X-ray image is detected. The computer system 40 carries out the operations corresponding to the blocks 1, 2, and 3 shown in FIG. 1. The blocks 1, 2, and 3 shown in FIG. 1 will hereinafter be referred to as the blocks representing the functions of the computer system 40.
A shift ΔX1 along the x direction between the marks 14' and 14" in the two X-ray images and a shift ΔY1 along the y direction between the marks 14' and 14" in the two X-ray images are expressed as
&#916;X1 =XB1 -{&#945;�(XA1 -CX)�cos&#952;-&#945;(YA1 -CY)�sin&#952;+CX }                   (2)
&#916;Y1 =YB1 -{&#945;�(XA1 -CX)�sin&#952;+&#945;(YA1 -CY)�cos&#952;+CY }                   (3)
Also, a shift ΔX2 along the x direction between the marks 15' and 15" in the two X-ray images and a shift ΔY2 along the y direction between the marks 15' and 15" in the two X-ray images are expressed as
&#916;X2 =XB2 -{&#945;�(XA2 -CX)�cos&#952;-&#945;(YA2 -CY)�sin&#952;+CX }                   (4)
&#916;Y2 =YB2 -{&#945;�(XA2 -CX)�sin&#952;+&#945;(YA2 -CY)�cos&#952;+CY }                   (5)
In Formulas (2) through (5), CX and CY respectively denote the X and Y coordinates of the center of rotation.
In ideal cases, ΔX1 and ΔX2 will be equal to each other. Also, ΔY1 and ΔY2 will be equal to each other. However, in some cases, they will not be equal to each other because of errors in sampling of the image signals SO1 and SO2. Therefore, position adjustment amounts ΔX and ΔY along the X and Y directions are calculated from the formulas
&#916;X=(&#916;X1 +&#916;X2)/2                (6)
&#916;Y=(&#916;Y1 +&#916;Y2)/2                (7)
The amounts thus calculated are used during the adjustment of the position of the first X-ray image along the X and Y directions.
In the manner described above, a first image signal SO1' and a second image signal SO2' are obtained, which respectively represent the first and second X-ray images whose positions have been adjusted. Thereafter, in the image operating means 1, superposition processing is carried out on the first image signal SO1' and the second image signal SO2'. Specifically, the image signal components of the first image signal SO1' and the second image signal SO2' which represent corresponding picture elements in the two X-ray images are added together. The superposition processing is expressed as
S1=Wa�SO1 '+Wb�SO2 '           (8)
where Wa and Wb denote weighting coefficients. In this manner, an original image signal S1 representing an original image, which is composed of both the soft tissue patterns and the bone patterns, is obtained from the superposition processing. Either one of the first and second X-ray images may be employed as the original image. However, in this embodiment, in order that noise occurring in the X-ray image due to, for example, sway of the X-rays during the image recording operation may be reduced, superposition processing is carried out with Formula (8), and the image obtained from the superposition processing is employed as the original image.
Also, a soft tissue image signal S2 representing a soft tissue image is generated by carrying out subtraction processing on the first image signal SO1' and the second image signal SO2' which respectively represent the first and second X-ray images whose positions have been adjusted. Specifically, the image signal components of the first image signal SO1' and the second image signal SO2' which represent corresponding picture elements in the two X-ray images are subtracted from each other. The subtraction processing is expressed as
where Wa' and Wb' denote weighting coefficients, and C' denotes the bias component.
In this embodiment, a bone image signal S3 representing a bone image may optionally be generated. For this purpose, the weighting coefficients and the bias component are changed from those in Formula (9), and the image signal components of the first image signal SO1' and the second image signal SO2' which represent corresponding picture elements in the two X-ray images are subtracted from each other. The subtraction processing is expressed as
S3=Wa"�SO1 '-Wb"�SO2 '+C"      (10)
where Wa" and Wb" denote weighting coefficients, and C" denotes the bias component.
In this embodiment, the image operating means 1 finds the original image, the soft tissue image, and the bone image from the image signals SO1 and SO2 representing the two X-ray images. Alternatively, the image operating means 1 may find the original image, the soft tissue image, and the bone image from a plurality of the image signals SO1, SO2, . . . , SOn. (Such a technique is disclosed in U.S. Pat. No. 4,855,598.)
FIGS. 4A, 4B, and 4C show examples of the original image, the soft tissue image, and the bone image.
In the original image shown in FIG. 4A, each of a right lung field region 16a and a left lung field region 16b in a lung region 16 is composed of a soft tissue pattern and bone (rib) patterns. Because the heart (soft tissue) is comparatively thick, a heart region 16c is predominantly composed of a soft tissue pattern. A right diaphragm region 16d and a left diaphragm region 16e are composed of soft tissues. A mediastinum region 16f is composed of bone patterns. In this manner, the original image is composed of both the soft tissue patterns and the bone patterns.
In the soft tissue image shown in FIG. 4B, the bone patterns have been eliminated from the lung region 16, and only the patterns of the soft tissues are formed.
Also, the bone image shown in FIG. 4C is composed of the patterns of the bones, such as the mediastinum and the ribs.
The original image signal S1 and the soft tissue image signal S2 generated by the image operating means 1 of the computer system 40 are fed into the abnormal pattern finding means 3 of the computer system 40.
Also, in this embodiment, anatomical regions are discriminated from one another from the original image signal S1. For this purpose, the original image signal S1 is also fed into the region discriminating means 2 of the computer system 40. Additionally, in this embodiment, the bone image signal S3 is fed into the region discriminating means 2.
When necessary, the image operating means 1 carries out other image processing, such as frequency response enhancement processing, smoothing processing, or noise elimination processing on the first image signal SO1 and the second image signal SO2, or on the original image signal S1, the soft tissue image signal S2, and the bone image signal S3.
Region Discriminating Means
From the original image signal S1, the region discriminating means 2 of the computer system 40 discriminates anatomical regions 16a through 16f in the lung region 16 shown in FIG. 4A.
FIG. 5 is a graph showing an example of a probability density function of the original image signal S1. In FIG. 5, the horizontal axis indicates the value of the original image signal S1, and the vertical axis indicates the frequency of occurrence of the value of the original image signal S1.
FIG. 6 is an explanatory view showing how the positions of the regions 16a through 16f in the lung region 16 are detected.
With reference to FIG. 5, a projecting part 17, which is present on the right side, corresponds to a background region 17 shown in FIG. 4A, upon which the X-rays impinged directly without passing through the object 2 shown in FIG. 2 during the image recording operation. A projecting part 16 in the middle corresponds to the lung region 16 shown in FIG. 4A. Also, a projecting part 18 on the left side corresponds to a skin region 18 shown in FIG. 4A. As an aid in facilitating the explanation, in FIG. 5, the projecting parts corresponding to the regions shown in FIG. 4A are numbered with corresponding reference numerals.
In this embodiment, the right lung field region 16a and the left lung field region 16b are first found in the manner described below. The process used for this purpose is described "Automatic Threshold Value Selecting Process Based On Discrimination And Least Square Standards" by Nobuyuki Otsu, collected papers of The Institute of Electronics and Communication Engineers of Japan, 63-D-4, pp. 349-356, 1980.
A threshold value t is determined such that the value calculated with the formula ##EQU2## becomes the largest. In this formula, M1 and σ12 denote respectively the mean value and the variance of the values of the original image signal S1, which values are larger than the threshold value t. Also, M2 and σ22 denote respectively the mean value and the variance of the values of the original image signal S1, which values are smaller than the threshold value t. Thereafter, from the image signal components of the original image signal S1 corresponding to the projecting part 16, the image signal components having values larger than the threshold value t are extracted. Two regions, which are composed of the picture elements corresponding to the thus extracted image signal components and which have comparatively large areas, are found as corresponding to the right lung field region 16a and the left lung field region 16b as shown in FIG. 6.
Thereafter, as shown in FIG. 6, a line l1 is drawn which connects the bottom edges of the right lung field region 16a and the left lung field region 16b. The right edge of right lung field region 16a, which right edge is taken in the X-ray image shown in FIG. 6, is approximated by a straight line, and a line l2 is extended downwardly from the straight line. Also, the upper one-third part of the left edge of the left lung field region 16b, which left edge is taken in the X-ray image shown in FIG. 6, is approximated by a straight line, and a line l3 is extended downwardly from the straight line. In this manner, a region 16h is found which comprises the right diaphragm region 16d, the mediastinum region 16f, the heart region 16c, and the left diaphragm region 16e.
In cases where the heart region 16c and the left diaphragm region 16e are to be discriminated from each other, operations are carried out in the manner described below. Specifically, from the image signal components of the original image signal S1 representing the picture elements, which are considered to be located in the vicinity of the boundary between the heart region 16c and the left diaphragm region 16e in the region 16h, calculations are made to find differences between the values of the image signal components representing the picture elements which are adjacent to each other in the vertical direction, which vertical direction is taken in FIG. 6. The picture elements, for which the differences are larger than a predetermined value, are imaginarily plotted on the X-ray image. A line l4, which connects the thus plotted picture elements and which extends horizontally in FIG. 6, is found to be the boundary between the heart region 16c and the left diaphragm region 16e. In this manner, the positions of the regions 16a through 16f in the X-ray image are detected.
In this embodiment, the region discriminating means 2 also detects the positions of rib patterns (shown in FIG. 4A) in the right lung field region 16a and the left lung field region 16b.
In order for the rib patterns to be found, by way of example, the original image signal S1 may be processed with a method which is described in "Discrimination of Rib Patterns in X-ray Fluorographic Image of the Chest", The Institute of Electronics and Communication Engineers of Japan, Oct. 26, 1972, material No. IT72-24 (1972-10) of the society for the study of image engineering. With the method, a linear figure is extracted by processing an image signal representing an X-ray image of the chest with a filter, which is sensitive to lines. From the position of the linear figure in the X-ray image, the direction along which the linear figure extends, or the like, lines corresponding to a rib pattern are detected. Thereafter, boundary lines of the rib pattern are approximately represented by a function of second order. In this manner, a rib pattern is extracted.
In this embodiment, because the bone image signal S3 representing the bone image has been generated by the image operating means 1, the bone image signal S3 is fed into the region discriminating means 2. In such cases, in the manner described below, the bone patterns can be found more easily than the aforesaid method.
As an aid in explaining how the information about the positions of the bone patterns in the bone image is found, FIG. 7A shows part of the bone image shown in FIG. 4C, and FIG. 7B shows the bone image signal S3 which corresponds to the part of the bone image shown in FIG. 7A.
The part of the bone image shown in FIG. 7A includes two rib patterns 56, 56. The two rib patterns 56, 56 overlap one upon the other at part 56a. The graph of FIG. 7B shows the levels of the image signal components of the bone image signal S3 representing the picture elements arrayed along the y axis in FIG. 7A. Because the bone image is composed only of the bone patterns, the regions corresponding to the bone patterns and the other region can be clearly discriminated from each other. Therefore, by investigating whether the levels of the image signal components of the bone image signal S3 are or are not lower than a threshold value Th1, it can be found whether a certain region corresponds or does not correspond to the bone patterns. In this manner, the information about the positions of the bone patterns can be obtained. In cases where the part 56a, at which the rib patterns 56, 56 overlap one upon the other, is to be detected, it can be detected by, for example, approximately representing the rib patterns 56, 56 with curves of secondary order and finding a region at which the approximate curves intersect with each other.
In cases where the information about the positions of the bone patterns is to be found from the bone image signal S3, the method employed for this purpose is not limited to the processing with the threshold value. For example, the information about the positions of the bone patterns may be found by carrying out differentiation processing on the image signal components of the bone image signal S3 and detecting the positions, which correspond to peaks of the values resulting from the differentiation processing.
The information about the positions of the regions 16a through 16f in the lung region 16 and the information about the positions of the rib patterns, or the like, which have been obtained in the manner described above, are fed into the abnormal pattern finding means 3.
No limitation is imposed on how the regions 16a through 16f and rib patterns in the X-ray image are detected.
Abnormal Pattern Finding Means
The abnormal pattern finding means 3, which is provided in the computer system 40, finds tumor patterns, which appear in the original image or the soft tissue image. For this purpose, the abnormal pattern finding means 3 processes the original image signal S1 or the soft tissue image signal S2 with a tumor pattern finding spatial-domain filter in accordance with the information about the anatomical regions (in this embodiment, the information about the regions 16a through 16f in the lung region 16 shown in FIG. 6) and the information about the rib patterns shown in FIG. 4A. The abnormal pattern finding means 3 works in the manner described below.
The diaphragm regions 16d and 16e in the lung region 16 shown in FIG. 6 correspond to the regions in the original image shown in FIG. 4A, which regions are composed of only the soft tissue patterns. Therefore, as for the diaphragm regions 16d and 16e, the processing with the abnormal pattern finding filter is carried out on the corresponding image signal components of the original image signal S1. The heart region 16c corresponds to the region in the original image, which region is predominantly composed of the soft tissue pattern. Therefore, as for the heart region 16c, the processing with the abnormal pattern finding filter is carried out on the corresponding image signal components of the original image signal S1. The lung field regions 16a and 16b are composed of soft tissue patterns and the bone (rib) patterns. Therefore, as for the areas of the lung field regions 16a and 16b other than the rib patterns, the processing with the abnormal pattern finding filter is carried out on the corresponding image signal components of the original image signal S1. Also, as for the areas of the rib patterns in the lung field regions 16a and 16b, the processing with the abnormal pattern finding filter is carried out on the corresponding image signal components of the soft tissue image signal S2. In cases where the information about the positions of the rib patterns is not used, the processing with the abnormal pattern finding filter is carried out on the image signal components of the soft tissue image signal S2, which correspond to the whole area of the lung field regions 16a and 16b. This is because, if the processing with the abnormal pattern finding filter is carried out on the image signal components of the original image signal S1, which correspond to the whole area of the lung field regions 16a and 16b, errors in finding tumor patterns will increase due to the adverse effects of the rib patterns.
FIG. 8 is a diagram having a predetermined picture element P0 from an X-ray image in the middle, which diagram serves as an aid in explaining how a spatial-domain filter works during the operations for finding a tumor pattern. A judgment is made as to whether a predetermined picture element P0 in the X-ray image falls or does not fall within the region corresponding to the tumor pattern in the X-ray image. The tumor pattern, which appears in the original image or the soft tissue image can be detected by processing the image signal components representing the picture elements of the original image or the soft tissue image with the filter illustrated in FIG. 8 in accordance with the anatomical regions. How the original image signal S3 is processed with the filter will mainly be described below. The filter described first is disclosed in U.S. patent application Ser. No. 542,487.
FIG. 9 is a graph showing an example of the profile of the original image around a predetermined picture element P0 in the direction (x direction) along which the lines L1 and L5 shown in FIG. 8 extend. In this example, the predetermined picture element P0 is located approximately at the middle of a tumor pattern 57, which is close to a rib pattern 56. Typically, the profile of a tumor pattern (i.e. the distribution of the values of the image signal components representing the tumor pattern) is approximately symmetric bilaterally. However, in cases where, for example, the tumor pattern 57 is close to a rib pattern 56 as in the illustrated example, it often occurs that the profile of the tumor pattern 57 is not symmetric bilaterally. It is important that the tumor pattern 57 can be detected even in such cases. In FIG. 9, the broken line 58 represents an example of the profile of the original image including no tumor pattern.
As shown in FIG. 8, a plurality of (in this case, eight) imaginary lines Li, where i=1, 2, . . . , 8, extend from the predetermined picture element P0 in the X-ray image to peripheral parts of the X-ray image. Also, imaginary circles Rj, where j=1, 2, 3, having radii r1, r2, and r3 extend around the predetermined picture element P0. The image signal component f0 representing the predetermined picture element P0 is found. Also, the image signal components fij, where i=1, 2, . . . , 8 and j=1, 2, 3, are found which represent the picture elements Pij located at the intersections of each of the lines Li and the circles Rj. (In FIG. 8, P11, P12, and P13 denote picture elements located at the intersections of a line L1 and circles R1, R2, and R3. Also, P51, P52, and P53 denote the picture elements located at the intersections of a line L5 and the circles R1, R2, and R3.)
Thereafter, differences Δij between the value of the image signal component f0 representing the predetermined picture element P0 and the values of the image signal components fij representing the picture elements Pij are calculated from Formula (11), which is expressed as
&#916;ij=fij-f0                                           (11)
(i=1,2, . . . ,8; j=1,2,3)
For each of the lines Li, the maximum value of the differences Δij, which have been calculated from Formula (11), is then found. Specifically, for the line L1, the maximum value of the differences between the value of the image signal component f0 representing the predetermined picture element P0 and the values of the image signal components f11, f12, and f13 representing the picture elements P11, P12, and P13 is found. The differences can be expressed as
In this example, as illustrated in FIG. 9, Δ13<Δ12<Δ11<0, and therefore the difference Δ11 is found to be the maximum value.
In this example, the difference Δ53 is found to be the maximum value.
Thereafter, calculations are made to find the mean-level value, for example, the mean value, of two maximum values, which have been found for each set of two lines extending from the predetermined picture element P0 in opposite directions. Specifically, mean values M15, M26, M37, and M48 are calculated respectively for the set of lines L1 and L5, the set of lines L2 and L6, the set of lines L3 and L7, and the set of lines L4 and L8. For the set of lines L1 and L5, the mean value M15 is given by the formula ##EQU3##
As described above, two lines extending from the predetermined picture element P0 in opposite directions are grouped into a single set. Therefore, a tumor pattern can be detected accurately even when, as shown in FIG. 9, it is present in the vicinity of, for example, a rib pattern and the distribution of the values of the image signal components representing the tumor pattern is asymmetric.
FIG. 10 is a graph showing how the characteristic value C1 is determined. In FIG. 10, the horizontal axis represents the mean values M15, M26, M37, and M48, which have been calculated in the manner described above. The vertical axis represents rating values C15, C26, C37, and C48, which correspond respectively to the mean values M15, M26, M37, and M48.
In the original image, the rib patterns are present in the lung field regions 16a and 16b. Therefore, in the manner described below, when the image signal components corresponding to the soft tissues in the lung field regions 16a and 16b in the original image are processed with the aforesaid filter, the filter is modified adaptively for the image signal components corresponding to the region in the vicinity of the rib patterns.
FIG. 11 is an enlarged view showing part of rib patterns (not shown in FIG. 6) in the lung field region 16a or the lung field region 16b shown in FIG. 6. In FIG. 11, the filter shown in FIG. 8 is also illustrated.
As illustrated in FIG. 11, part of the filter overlaps the rib patterns 56, 56. Therefore, when a characteristic value corresponding to a predetermined picture element P0 shown in FIG. 11 is calculated, the information about r1 and r2 is utilized for the lines L1, L3, L5, and L7. For the lines L2 and L6, the information about r1, r2 and r3 is utilized. Also, for the lines L4 and L8, only the information about r1 is utilized. In this manner, the spatial-domain filter is modified adaptively in accordance with the information about the positions of the rib patterns. Therefore, the calculation of the characteristic value C1 is not adversely affected by the rib patterns.
No limitation is imposed on the algorithms in the filter, which is employed to find the tumor patterns. Another example of the filter will be described hereinbelow. The filter described below is proposed in U.S. patent application Ser. No. 542,487.
Specifically, calculations are made to find the gradients ∇fij of the image signal components fij representing the picture elements Pij, where i=1, 2, . . . , 8 and j=1, 2, 3, which are shown in FIG. 8.
The term "gradient" as used herein means the vector expressed as
&#8711;f(m,n)=(f(m+1,n)-f(m,n), f(m,n+1)-f(m,n))        (14)
In Formula (14), (m,n) denotes the x and y coordinates of a certain picture element P in a radiation image, (m+1,n) denotes the coordinates of a picture element P', which is adjacent to the picture element P in the x direction, and (m,n+1) denotes the coordinates of a picture element P", which is adjacent to the picture element P in the y direction. Also, f(m,n), f(m+1,n), and f(m,n+1) respectively denote the values of the image signal components representing the picture elements P, P', and P".
FIG. 12 shows the gradient of an image signal component fij. How it is calculated is described below.
Thereafter, the projections of the normalized gradients ∇fij/|fij| onto the vectors directed from the picture elements Pij to the predetermined picture element P0 are calculated. The projections are expressed as ∇fij/|∇fij|*i, where i denotes the unit vectors directed from the picture elements Pij to the predetermined picture element P0, and * denotes the inner product.
Thereafter, the sum of the maximum values which were found for each of the respective lines Li is calculated. This sum is expressed as ##EQU4##
The sum expressed as ##EQU5## is taken as a characteristic value C2. The characteristic value C2 is then compared with a predetermined threshold value Th3. From whether C2≧Th3 or C2<Th3, a judgment is made as to whether the predetermined picture element P0 falls or does not fall within the region corresponding to the tumor pattern.
A further example of the filter utilizing different algorithms will be described hereinbelow. The filter described below is proposed in U.S. patent application Ser. No. 542,487.
As shown in FIG. 8, the area of a center region Q0 including the predetermined picture element P0 is selected. Also, the areas of peripheral regions Qij, where i=1, 2, . . . , 8 and j=1, 2, 3, are selected for each of the lines Li. Each of the peripheral regions Qij includes one of a plurality of picture elements Pij, where i=1, 2, . . . , 8 and j=1, 2, 3. (In FIG. 8, Q11, Q12, Q13, Q51, Q52, and Q53 denote the peripheral regions which respectively include the picture elements P11, P12, P13, P51, P52, and P53.)
U1=(&#916;1+&#916;2+&#916;5+&#916;6)/4                 (16)
U2=(&#916;2+&#916;3+&#916;6+&#916;7)/4                 (17)
U3=(&#916;3+&#916;4+&#916;7+&#916;8)/4                 (18)
U4=(&#916;4+&#916;5+&#916;8+&#916;1)/4                 (19)
V1=U1/U3                                                   (20)
V2=U2/U4                                                   (21)
V3=U3/U1                                                   (22)
V4=U4/U2                                                   (23)
By way of example, the process for calculating the characteristic value U1 from Formula (16) has the effects described below. Specifically, the addition of the maximum values corresponding to two adjacent groups of peripheral regions, which are located on the same side with respect to the predetermined picture element P0, (i.e. the addition of Δ1 and Δ2, or the addition of Δ5 and Δ6) corresponds to a smoothing process. Also, the maximum values corresponding to peripheral regions, which are located on opposite sides with respect to the predetermined picture element P0, are added together (in the case of Formula (16), the sum of Δ1 and Δ2 and the sum of Δ5 and Δ6 are added together). Such an addition is carried out in order that a tumor pattern can be detected even when, as shown in FIG. 9, the distribution of the values of the image signal components representing the tumor pattern is asymmetric.
As for the calculation of the characteristic value V1 from Formula (20), the characteristic values U1 and U3 represent characteristics of the image in directions which are perpendicular to each other. Therefore, in cases where the shape of the tumor pattern is circular in FIG. 9, V1 will be approximately equal to 1.0. In cases where the predetermined picture element P0 is present in a linear pattern, such as a rib pattern, V1 will not be equal to 1.0.
As the first characteristic value U, which is representative of the maximum values Δi, where i=1, 2, 8, of the aforesaid differences, the maximum value of the characteristic values U1, U2, U3, and U4, i.e.
U=MAX (U1,U2,U3,U4)                                        (24)
V=MAX (V1,V2,V3,V4)                                        (25)
is employed. After the first characteristic value U and the second characteristic value V have been found in the manner described above, a characteristic value C3 is calculated and then used during the judgment as to whether a predetermined picture element P0 falls or does not fall within the region corresponding to the tumor pattern. As the characteristic value C3, the ratio of the first characteristic value U to the second characteristic value V is employed, which is expressed as
C3=U/V                                                     (26)
The characteristic value C3 is then compared with a predetermined threshold value Th4. From whether C3≧Th4 or C3<Th4, the judgment is made as to whether the predetermined picture element P0 falls or does not fall within the region corresponding to the tumor pattern.
Also, the abnormal pattern finding means 3 may employ any of other filters. Additionally, different filters may be employed for the original image and the soft tissue image. Moreover, different filters may be employed for different regions in the original image or the soft tissue image.
In the aforesaid embodiment of the abnormal pattern detecting apparatus in accordance with the present invention, from X-ray images of the chest of a human body, which images have been stored on stimulable phosphor sheets, tumor patterns are detected which appear, typically, as circular patterns on the X-ray images. However, the abnormal pattern detecting apparatus in accordance with the present invention is not limited to the detection of circular tumor patterns nor to the processing of X-ray images of chests. Also, recording media other than stimulable phosphor sheets may be used. The abnormal pattern detecting apparatus in accordance with the present invention is applicable widely when, from image signals representing radiation images of an object, abnormal patterns in the radiation images are detected.
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