Patent Publication Number: US-2021169305-A1

Title: Image processing apparatus, image processing method, and image processing system

Description:
FIELD 
     The present disclosure relates to an image processing apparatus, an image processing method, and an image processing system. 
     BACKGROUND 
     In recent years, an endoscope is sometimes used in medical practice. When an image is captured by the endoscope, normal observation to observe a normal image that is obtained by applying white light may be performed in some cases. Alternatively, in some other cases, fluorescence observation to obtain an image (fluorescence image) by fluorescence that is generated by applying excitation light may be performed. Further, a technique for displaying, on a monitor, a composite image in which the normal image and the fluorescence image are superimposed on each other has been disclosed (for example, see Patent Literature 1). 
     CITATION LIST 
     Patent Literature 
     Patent Literature 1: Japanese Laid-open Patent Publication No. 2011-5002 
     SUMMARY 
     Technical Problem 
     The fluorescence image obtained as described above is subjected to an enhancement process and thereafter displayed on a monitor. In this case, if a degree of the enhancement process on the fluorescence image input from a camera head is uniform, in some regions, the degree of the enhancement process may be too intense and visibility is not improved. As one example, it is acceptable to increase the degree of the enhancement process to be subjected to a region with large scattering and a thin blood vessel, but if the same degree of the enhancement process is performed on other regions, the degree of the enhancement process may be too intense. 
     Therefore, it is desired to provide a technology capable of improving visibility of a fluorescence image. 
     Solution to Problem 
     According to the present disclosure, an image processing apparatus is provided that includes: a feature detecting unit configured to detect a feature of first image data that is obtained by capturing an image of a blood vessel by ICG fluorescence imaging; and an enhancement processing unit configured to control a degree of an enhancement process performed on the first image data, on the basis of the feature. 
     According to the present disclosure, an image processing method is provided that includes: detecting a feature of first image data that is obtained by capturing an image of a blood vessel by ICG fluorescence imaging; and controlling, by a processor, a degree of an enhancement process performed on the first image data, on the basis of the feature. 
     According to the present disclosure, an image processing system is provided that includes: an imaging unit configured to capture an image of a blood vessel by ICG fluorescence imaging and obtain first image data; a feature detecting unit configured to detect a feature of the first image data; and an enhancement processing unit configured to control a degree of the enhancement process performed on the first image data on the basis of the feature. 
     Advantageous Effects of Invention 
     As described above, according to the present disclosure, a technology capable of improving visibility of a fluorescence image is provided. Meanwhile, the effects described above are not limitative, and, with or in the place of the above effects, any of the effects described in this specification or other effects that can be recognized from this specification may be achieved. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a diagram illustrating an example of a schematic configuration of an endoscopic surgery system. 
         FIG. 2  is a block diagram illustrating an example of a functional configuration of a camera head and a CCU illustrated in  FIG. 1 . 
         FIG. 3  is a block diagram illustrating a functional configuration example of the CCU according to a first embodiment of the present disclosure. 
         FIG. 4  is a diagram illustrating a detailed configuration example of an object feature detecting unit. 
         FIG. 5  is a diagram illustrating a detailed configuration example of a degree-of-scattering detecting unit. 
         FIG. 6  is a diagram illustrating an example of a correspondence relationship between a correlation value and a degree of scattering. 
         FIG. 7  is a diagram illustrating a detailed configuration example of a vascular diameter detecting unit. 
         FIG. 8  is a diagram for explaining a case in which image processing is performed on ICG images at different intensities. 
         FIG. 9  is a diagram illustrating an example of a correspondence relationship between a difference value and a vascular diameter. 
         FIG. 10  is a diagram illustrating an example of an ICG image. 
         FIG. 11  is a diagram illustrating an example of an ICG image at a scale “0.5”. 
         FIG. 12  is a diagram illustrating an example of an ICG image at a scale “5”. 
         FIG. 13  is a diagram illustrating an example of an ICG image at a scale “10”. 
         FIG. 14  is a diagram illustrating an example of an ICG image at a scale “15”. 
         FIG. 15  is a diagram illustrating an example of an ICG image at a scale “20”. 
         FIG. 16  is a diagram illustrating a detailed configuration example of a vascular density detecting unit. 
         FIG. 17  is a diagram for explaining a vascular density. 
         FIG. 18  is a diagram illustrating an example of a correspondence relationship between a combination of a ratio of blood vessels and a vascular diameter that most frequently appears and a vascular density. 
         FIG. 19  is a diagram illustrating a detailed configuration example of a vascular depth detecting unit. 
         FIG. 20  is a diagram illustrating an example of a correspondence relationship between a combination of blood vessel information and a correlation value and a vascular depth. 
         FIG. 21  is a diagram for explaining a case in which a degree of an enhancement process is uniform over the entire ICG image. 
         FIG. 22  is a diagram illustrating an example of an ICG image on which enhancement processes are performed at different degrees in accordance with vascular diameters. 
         FIG. 23  is a diagram illustrating an example of an ICG image on which enhancement processes are performed at different intensities in accordance with vascular diameters. 
         FIG. 24  is a diagram illustrating a case (first example) in which a coefficient corresponding to an object feature is registered in a coefficient DB. 
         FIG. 25  is a diagram illustrating a case (second example) in which a coefficient corresponding to a part of the object feature is registered in the coefficient DB but a coefficient corresponding to the rest of the object feature is not registered in the coefficient DB. 
         FIG. 26  is a diagram illustrating a case (third example) in which only a single coefficient is registered in the coefficient DB. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In this specification and the drawings, structural elements that have substantially the same functions and configurations will be denoted by the same reference symbols, and repeated explanation of the structural elements will be omitted. 
     Further, in this specification and the drawings, a plurality of structural elements that have substantially the same or similar functions and configurations may be distinguished from one another by appending different numbers after the same reference symbols. However, if the structural elements that have substantially the same or similar functions and configurations need not be specifically distinguished from one another, the structural elements will be denoted by only the same reference symbols. Furthermore, similar structural elements in different embodiments may be distinguished from one another by appending different alphabets after the same reference symbols. However, if the similar structural elements need not be specifically distinguished from one another, the structural elements will be denoted by only the same reference symbols. 
     In addition, hereinafter, explanation will be given in the following order. 
     1. System configuration example 
     2. Overview 
     3. First Embodiment 
     4. Second Embodiment 
     5. Conclusion 
     1. System Configuration Example 
     First, a configuration example as one example of a medical system (image processing system) according to an embodiment of the present disclosure will be described with reference to the drawings. Examples of the medical system according to the embodiment of the present disclosure include various systems. Here, as one example of the medical system according to the embodiment of the present disclosure, a configuration example of an endoscopic surgery system will be mainly described. 
       FIG. 1  is a diagram illustrating an example of a schematic configuration of an endoscopic surgery system  5000  to which a technology according to the present disclosure is adopted. In  FIG. 1 , a state is illustrated in which a surgeon (doctor)  5067  performs surgery on a patient  5071  on a patient bed  5069  by using the endoscopic surgery system  5000 . As illustrated in the figure, the endoscopic surgery system  5000  includes an endoscope  5001 , other surgery tools  5017 , a support arm apparatus  5027  that supports the endoscope  5001 , and a cart  5037  on which various apparatuses for endoscopic surgery are mounted. 
     In the endoscopic surgery, cylindrical drilling tools called trocars  5025   a  to  5025   d  are introduced to make a plurality of punctures into an abdominal wall, instead of opening an abdominal cavity by cutting the abdominal wall. Then, a lens barrel  5003  of the endoscope  5001  and the other surgery tools  5017  are inserted into a body cavity of the patient  5071  through the trocars  5025   a  to  5025   d . In the example illustrated in the figure, an insufflation tube  5019 , an energy treatment tool  5021 , and a forceps  5023  are inserted, as the other surgery tools  5017 , into the body cavity of the patient  5071 . Further, the energy treatment tool  5021  is a treatment tool for cutting and loosening tissue, sealing a blood vessel, and the like with high-frequency current or ultrasonic vibration. However, the surgery tools  5017  illustrated in the drawing are mere examples, and, as the surgery tools  5017 , for example, various surgery tools, such as a tweezer and a retractor, which are generally used in the endoscopic surgery, may be used. 
     An image of a surgical site inside the body cavity of the patient  5071  captured by the endoscope  5001  is displayed on a display apparatus  5041 . The surgeon  5067  views the image of the surgical site displayed on the display apparatus  5041  in real time and performs treatment, such as removal of an affected area, using the energy treatment tool  5021  or the forceps  5023 . While not illustrated in the figure, the insufflation tube  5019 , the energy treatment tool  5021 , and the forceps  5023  are supported by the surgeon  5067 , an assistant, or the like during the surgery. 
     (Support Arm Apparatus) 
     The support arm apparatus  5027  includes an arm section  5031  that extends from a base section  5029 . In the example illustrated in the drawing, the arm section  5031  includes joint sections  5033   a ,  5033   b , and  5033   c , and links  5035   a  and  5035   b , and is driven by being controlled by an arm control apparatus  5045 . The arm section  5031  supports the endoscope  5001  and controls a position and posture of the endoscope  5001 . With this configuration, it is possible to stably fix the position of the endoscope  5001 . 
     (Endoscope) 
     The endoscope  5001  includes the lens barrel  5003 , a certain region of which with a predetermined length from a distal end is to be inserted into the body cavity of the patient  5071 , and a camera head  5005 , which is connected to a proximal end of the lens barrel  5003 . In the example illustrated in the drawing, the endoscope  5001  that is configured as what is called a rigid scope having the rigid lens barrel  5003  is illustrated; however, the endoscope  5001  may be configured as what is called a flexible scope having the flexible lens barrel  5003 . 
     An opening in which an objective lens is fitted is arranged on the distal end of the lens barrel  5003 . A light source apparatus  5043  is connected to the endoscope  5001 , and light generated by the light source apparatus  5043  is guided to the distal end of the lens barrel by a light guide that is extended inside the lens barrel  5003 , and applied to an observation target inside the body cavity of the patient  5071  via the objective lens. The endoscope  5001  may be a forward-viewing endoscope, a forward-oblique viewing endoscope, or a side-viewing endoscope. 
     An optical system and an imaging element are arranged inside the camera head  5005 , and the optical system condenses reflected light (observation light) from the observation target toward the imaging element. The imaging element performs photoelectric conversion on the observation light, and an electrical signal corresponding to the observation light, that is, an image signal corresponding to an observation image, is generated. The image signal is transmitted, as RAW data, to a camera control unit (CCU)  5039 . The camera head  5005  has a function to adjust a magnification and a focal length by appropriately driving the optical system. 
     To cope with a stereoscopic view (3D-display) or the like for example, it may be possible to arrange a plurality of imaging elements on the camera head  5005 . In this case, a plurality of relay optical systems are arranged inside the lens barrel  5003  in order to guide the observation light to the respective imaging elements. 
     (Various Apparatuses Mounted on Cart) 
     The CCU  5039  is constructed by a central processing unit (CPU), a graphics processing unit (GPU), or the like, and integrally controls operation of the endoscope  5001  and the display apparatus  5041 . Specifically, the CCU  5039  performs various kinds of image processing, such as a developing process (demosaicing process), on the image signal received from the camera head  5005 , in order to display an image based on the image signal. The CCU  5039  provides the image signal subjected to the image processing to the display apparatus  5041 . Further, the CCU  5039  transmits a control signal to the camera head  5005  and controls drive of the camera head  5005 . The control signal may include information on imaging conditions, such as the magnification and the focal length. 
     The display apparatus  5041  displays the image based on the image signal subjected to the image processing by the CCU  5039 , under the control of the CCU  5039 . If the endoscope  5001  is compatible with high-resolution imaging, such as 4K (3840 horizontal pixels×2160 vertical pixels) or 8K (7680 horizontal pixels×4320 vertical pixels), and/or if the endoscope  5001  is compatible with 3D-display, an apparatus that can perform high-resolution display and/or 3D-display is used as the display apparatus  5041  in accordance with the respective compatibilities. If the apparatus is compatible with high-resolution imaging, such as 4K or 8K, it is possible to achieve increased immersion by adopting an apparatus with a size of 55 inch or larger as the display apparatus  5041 . Further, it may be possible to arrange the plurality of display apparatuses  5041  with different resolution and sizes for different uses. 
     The light source apparatus  5043  is constructed by a light source, such as a light emitting diode (LED), and supplies illumination light for capturing an image of a surgical site to the endoscope  5001 . 
     The arm control apparatus  5045  is constructed by a processor, such as a CPU, operates in accordance with a predetermined program, and controls drive of the arm section  5031  of the support arm apparatus  5027  in accordance with a predetermined control method. 
     An input apparatus  5047  is an input interface for the endoscopic surgery system  5000 . A user is able to input various kinds of information and instructions to the endoscopic surgery system  5000  via the input apparatus  5047 . For example, the user inputs, via the input apparatus  5047 , various kinds of information on surgery, such as body information on a patient or information on procedures of the surgery. Further, for example, the user inputs, via the input apparatus  5047 , an instruction to drive the arm section  5031 , an instruction to change imaging conditions (a type of illumination light, the magnification, the focal length, and the like) of the endoscope  5001 , an instruction to drive the energy treatment tool  5021 , and the like. 
     Types of the input apparatus  5047  are not specifically limited, and various known input apparatuses may be adopted as the input apparatus  5047 . As the input apparatus  5047 , for example, a mouse, a keyboard, a touch panel, a switch, a foot switch  5057 , and/or a lever may be adopted. If the touch panel is used as the input apparatus  5047 , the touch panel may be arranged on a display surface of the display apparatus  5041 . 
     Alternatively, the input apparatus  5047  may be, for example, a device that can be worn by the user, such as a glasses wearable device or a head mounted display (HMD), and various kinds of input are performed in accordance with gestures and lines of sight of the user detected by the device. Further, the input apparatus  5047  includes a camera that can detect motions of the user, and performs various kinds of input in accordance with gestures and lines of sight of the user detected from videos captured by the camera. Furthermore, the input apparatus  5047  includes a microphone that can collect voice of the user, and performs various kinds of input based on voice via the microphone. In this manner, the input apparatus  5047  is configured to be able to input various kinds of information in a non-contact manner, so that it is possible to allow, in particular, a user (for example, the surgeon  5067 ) who is in a clean zone to operate apparatuses located in a dirty zone in a non-contact manner. Moreover, the user is able to operate devices without releasing his/her hand from a carrying surgery tool, so that it is possible to improve the convenience of the user. 
     A treatment tool control apparatus  5049  controls drive of the energy treatment tool  5021  for tissue ablation, incision, sealing of a blood vessel, or the like. A pneumoperitoneum apparatus  5051  feeds gas into the body cavity via the insufflation tube  5019  to inflate the body cavity of the patient  5071 , to thereby ensure a visual field of the endoscope  5001  and ensure an operating space for the surgeon. A recorder  5053  is an apparatus that can record various kinds of information on surgery. A printer  5055  is an apparatus that can print various kinds of information on surgery in various formats, such as a text, an image, or a graph. 
     A particularly characteristic configuration of the endoscopic surgery system  5000  will be described in detail below. 
     (Support Arm Apparatus) 
     The support arm apparatus  5027  includes the base section  5029  as a base board, and the arm section  5031  extending from the base section  5029 . In the example illustrated in the drawing, the arm section  5031  includes the plurality of joint sections  5033   a ,  5033   b , and  5033   c  and the plurality of links  5035   a  and  5035   b  that are connected by the joint section  5033   b ; however, in  FIG. 1 , the configuration of the arm section  5031  is simplified for the sake of simplicity. In reality, shapes, numbers, and arrangement of the joint sections  5033   a  to  5033   c , directions of rotation axes of the links  5035   a  and  5035   b  and the like may be appropriately set to achieve desired flexibility of the arm section  5031 . For example, the arm section  5031  may be preferably configured to have flexibility of 6 levels or higher. With this configuration, it becomes possible to freely move the endoscope  5001  in a movable range of the arm section  5031 , so that it is possible to insert the lens barrel  5003  of the endoscope  5001  from a desired direction into the body cavity of the patient  5071 . 
     Actuators are arranged in the joint sections  5033   a  to  5033   c , and the joint sections  5033   a  to  5033   c  are configured to be able to rotate around predetermined rotation axes in accordance with the drive of the actuators. The drive of the actuators is controlled by the arm control apparatus  5045 , so that a rotation angle of each of the joint sections  5033   a  to  5033   c  is controlled and the drive of the arm section  5031  is controlled. Accordingly, it becomes possible to control the position and the posture of the endoscope  5001 . In this case, the arm control apparatus  5045  is able to control the drive of the arm section  5031  using various well-known control method, such as force control or position control. 
     For example, when the surgeon  5067  appropriately inputs operation via the input apparatus  5047  (including the foot switch  5057 ), the arm control apparatus  5045  may appropriately control the drive of the arm section  5031  in accordance with the input operation, and the position and the posture of the endoscope  5001  may be controlled. With this control, it is possible to first move the endoscope  5001  arranged on a distal end of the arm section  5031  from an arbitrary position to another arbitrary position, and thereafter fixedly support the endoscope  5001  at the moved position. The arm section  5031  may be operated by what is called a master-slave system. In this case, the arm section  5031  may be remotely operated by the user via the input apparatus  5047  that is installed at a place away from the surgery room. 
     Further, if the force control is adopted, the arm control apparatus  5045  may perform what is called power assist control to receive an external force from the user and drive the actuator of each of the joint sections  5033   a  to  5033   c  such that the arm section  5031  smoothly moves in accordance with the external force. With this configuration, when the user moves the arm section  5031  while directly touching the arm section  5031 , it is possible to move the arm section  5031  with a relatively small force. Therefore, it becomes possible to more intuitively move the endoscope  5001  with easier operation, so that it is possible to improve the convenience of the user. 
     Here, in general, in endoscopic surgery, the endoscope  5001  is supported by a doctor called a scopist. In contrast, with use of the support arm apparatus  5027 , it becomes possible to more reliably fix the position of the endoscope  5001  without manual intervention, so that it becomes possible to stably obtain an image of a surgical site and perform surgery smoothly. 
     Meanwhile, the arm control apparatus  5045  need not always be mounted on the cart  5037 . Further, the arm control apparatus  5045  need not always be a single apparatus. For example, the arm control apparatus  5045  may be mounted on each of the joint sections  5033   a  to  5033   c  of the arm section  5031  of the support arm apparatus  5027 , and the plurality of arm control apparatuses  5045  may operate in cooperation with one another and control drive of the arm section  5031 . 
     (Light Source Apparatus) 
     The light source apparatus  5043  supplies illumination light to the endoscope  5001  when an image of a surgical site is to be captured. The light source apparatus  5043  includes, for example, an LED, a laser light source, or a white light source that is constructed by a combination of an LED and a laser light source. In this case, if the white light source is constructed by a combination of RGB laser light sources, it is possible to control output intensity and an output timing of each of colors (each of wavelengths) with high accuracy, and therefore, in the light source apparatus  5043 , it is possible to adjust a white balance of a captured image. Further, in this case, by illuminating an observation target with laser light from each of the RGB laser light sources in a time-sharing manner and controlling the drive of the imaging element of the camera head  5005  in synchronization with illumination timings, it is possible to capture respective images corresponding to RGB in a time-sharing manner. With this method, it is possible to obtain a color image without arranging a color filter on the imaging element. 
     Furthermore, it may be possible to control the drive of the light source apparatus  5043  such that the intensity of output light is changed at predetermined time intervals. By controlling the drive of the imaging element of the camera head  5005  in synchronization with a timing to change the intensity of light, obtaining images in a time-sharing manner, and combining the obtained images, it is possible to generate a high dynamic range image in which what is called blocked up shadows and blown out highlights do not occur. 
     Moreover, the light source apparatus  5043  may be configured to be able to supply light in a predetermined wavelength band corresponding to special light observation. In the special light observation, for example, what is called narrow band imaging is performed, in which light in a narrower band than that of illumination light (in other words, white light) used in normal observation is applied by using wavelength dependency of light absorption in body tissues and an image of a predetermined tissue, such as a blood vessel in a superficial portion of a mucous membrane, is captured with high contrast. Alternatively, in the special light observation, it may be possible to perform fluorescence observation to obtain an image by fluorescence that is generated by applying excitation light. In the fluorescence observation, it may be possible to perform observation (autofluorescence observation) in which a body tissue is illuminated with excitation light and fluorescence received from the body tissue is observed, or it may be possible to perform imaging by locally injecting reagent, such as indocyanine green (ICG), into a body tissue, illuminating the body tissue with excitation light corresponding to a fluorescence wavelength of the reagent, and acquiring a fluorescent image, for example. The light source apparatus  5043  may be configured to be able to supply the narrow band light and/or the excitation light corresponding to the special light observation as described above. 
     (Camera Head and CCU) 
     Functions of the camera head  5005  and the CCU  5039  of the endoscope  5001  will be described in detail below with reference to  FIG. 2 .  FIG. 2  is a block diagram illustrating an example of functional configurations of the camera head  5005  and the CCU  5039  illustrated in  FIG. 1 . 
     With reference to  FIG. 2 , the camera head  5005  includes, as the functions thereof, a lens unit  5007 , an imaging unit  5009 , a driving unit  5011 , a communication unit  5013 , and a camera head control unit  5015 . Further, the CCU  5039  includes, as the functions thereof, a communication unit  5059 , an image processing unit  5061 , and a control unit  5063 . The camera head  5005  and the CCU  5039  are connected to each other such that they can bi-directionally communicate with each other via a transmission cable  5065 . 
     First, the functional configuration of the camera head  5005  will be described. The lens unit  5007  is an optical system arranged in a connection part connected to the lens barrel  5003 . Observation light that has entered from the distal end of the lens barrel  5003  is guided to the camera head  5005  and enters the lens unit  5007 . The lens unit  5007  is constructed by a combination of a plurality of lenses including a zoom lens and a focus lens. Optical characteristics of the lens unit  5007  are adjusted such that observation light is condensed on a light-receiving surface of an imaging element of the imaging unit  5009 . Further, the zoom lens and the focus lens are configured such that positions thereof on an optical axis can be moved to adjust a magnification and a focal point of a captured image. 
     The imaging unit  5009  is constructed by the imaging element and is arranged on a subsequent stage of the lens unit  5007 . The observation light that has passed through the lens unit  5007  is condensed on the light-receiving surface of the imaging element, and an image signal corresponding to an observation image is generated through photoelectric conversion. The image signal generated by the imaging unit  5009  is provided to the communication unit  5013 . 
     As the imaging element included in the imaging unit  5009 , for example, a complementary metal oxide semiconductor (CMOS) type image sensor that has Bayer arrangement and that can capture color images may be used. Meanwhile, as the imaging element, for example, a device that is compatible with capturing of an image with high resolution of 4K or higher may be used. By obtaining an image of a surgical site at high resolution, the surgeon  5067  is able to more precisely recognize a condition of the surgical site, so that it is possible to perform the surgery more smoothly. 
     Further, the imaging element included in the imaging unit  5009  is configured to include a pair of imaging elements to obtain image signals for right and left eyes to cope with 3D-display. By performing 3D-display, the surgeon  5067  is able to accurately recognize a depth of a body tissue in the surgical site. If the imaging unit  5009  is configured as a multi-sensor system, the plurality of lens units  5007  are arranged in accordance with the respective imaging elements. 
     Furthermore, the imaging unit  5009  need not always be mounted on the camera head  5005 . For example, the imaging unit  5009  may be arranged immediately after the objective lens inside the lens barrel  5003 . 
     The driving unit  5011  is constructed by an actuator, and moves the zoom lens and the focus lens of the lens unit  5007  by a predetermined distance along the optical axis under the control of the camera head control unit  5015 . Accordingly, it is possible to appropriately adjust a magnification and a focal point of a captured image captured by the imaging unit  5009 . 
     The communication unit  5013  is constructed by a communication apparatus for transmitting and receiving various kinds of information to and from the CCU  5039 . The communication unit  5013  transmits the image signal obtained from the imaging unit  5009  as RAW data to the CCU  5039  via the transmission cable  5065 . In this case, to display the captured image of the surgical site with low latency, it is preferable to transmit the image signal through optical communication. The reason for this is as follows: when surgery is performed, the surgeon  5067  performs the surgery while observing a condition of an affected area using the captured image, and therefore, it is demanded to display a video of a surgical site in real time as best as possible to perform the surgery more safely and more reliably. When the optical communication is performed, a photoelectric conversion module that converts an electrical signal to an optical signal is arranged in the communication unit  5013 . The image signal is converted to an optical signal by the photoelectric conversion module, and thereafter transmitted to the CCU  5039  via the transmission cable  5065 . 
     Further, the communication unit  5013  receives, from the CCU  5039 , a control signal for controlling drive of the camera head  5005 . The control signal includes information on an imaging condition, such as information for designating a frame rate of a captured image, information for designating an exposure value at the time of imaging, and/or information for designating the magnification and the focal point of the captured image. The communication unit  5013  provides the received control signal to the camera head control unit  5015 . Meanwhile, the control signal from the CCU  5039  may be transmitted through optical communication. In this case, a photoelectric conversion module that converts an optical signal to an electrical signal is arranged in the communication unit  5013 , and the control signal is converted to an electrical signal by the photoelectric conversion module and thereafter provided to the camera head control unit  5015 . 
     The imaging conditions as described above, such as the frame rate, the exposure value, the magnification, and the focal point, are automatically set by the control unit  5063  of the CCU  5039  on the basis of the acquired image signal. In other words, the endoscope  5001  is equipped with what is called an automatic exposure (AE) function, an automatic focus (AF) function, and an automatic white balance (AWB) function. 
     The camera head control unit  5015  controls the drive of the camera head  5005  on the basis of the control signal that is received from the CCU  5039  via the communication unit  5013 . For example, the camera head control unit  5015  controls the drive of the imaging element of the imaging unit  5009  on the basis of the information for designating the frame rate of the captured image and/or the information for designating exposure at the time of imaging. Further, for example, the camera head control unit  5015  appropriately moves the zoom lens and the focus lens of the lens unit  5007  via the driving unit  5011  on the basis of the information for designating the magnification and the focal point of the captured image. The camera head control unit  5015  may further include a function to store information for identifying the lens barrel  5003  and the camera head  5005 . 
     By arranging the components, such as the lens unit  5007  and the imaging unit  5009 , inside a sealed structure with high air tightness and high waterproof property, it is possible to ensure resistance of the camera head  5005  to an autoclave sterilization process. 
     The functional configuration of the CCU  5039  will be described below. The communication unit  5059  is constructed by a communication apparatus for transmitting and receiving various kinds of information to and from the camera head  5005 . The communication unit  5059  receives an image signal that is transmitted from the camera head  5005  via the transmission cable  5065 . In this case, as described above, the image signal may be preferably transmitted through optical communication. In this case, to cope with the optical communication, a photoelectric conversion module that converts an optical signal to an electrical signal is arranged in the communication unit  5059 . The communication unit  5059  provides the image signal converted to the electrical signal to the image processing unit  5061 . 
     Further, the communication unit  5059  transmits a control signal for controlling the drive of the camera head  5005  to the camera head  5005 . The control signal may be transmitted through optical communication. 
     The image processing unit  5061  performs various kinds of image processing on the image signal that is RAW data transmitted from the camera head  5005 . Examples of the image processing include various kinds of well-known signal processing, such as a developing process, a high-quality image processing (band enhancement processing, super-resolution processing, noise reduction (NR) processing and/or shake correction processing), and/or enlargement processing (electronic zoom processing). Further, the image processing unit  5061  performs wave detection processing on the image signal to implement AE, AF, and AWB. 
     The image processing unit  5061  is constructed by a processor, such as a CPU or a GPU, and the processor operates in accordance with a predetermined program, so that the image processing and the wave detection processing as described above can be performed. If the image processing unit  5061  is constructed by a plurality of GPUs, the image processing unit  5061  appropriately divides information on the image signal, and performs image processing in parallel using the plurality of GPUs. 
     The control unit  5063  performs various kinds of control related to capturing of an image of a surgical site by the endoscope  5001  and display of the captured image. For example, the control unit  5063  generates a control signal for controlling the drive of the camera head  5005 . In this case, if the user has input an imaging condition, the control unit  5063  generates the control signal based on the input performed by the user. Alternatively, if the endoscope  5001  has the AE function, the AF function, and the AWB function, the control unit  5063  appropriately calculates an optimal exposure value, an optimal focal length, and an optimal white balance in accordance with a result of the wave detection processing performed by the image processing unit  5061 , and generates a control signal. 
     Further, the control unit  5063  causes the display apparatus  5041  to display an image of the surgical site on the basis of the image signal subjected to the image processing by the image processing unit  5061 . In this case, the control unit  5063  recognizes various objects in the image of the surgical site by using various image recognition techniques. For example, by detecting a shape, a color, or the like of an edge of an object included in the image of the surgical site, the control unit  5063  is able to recognize a surgery tool, such as a forceps, a specific site of a living body, bleeding, mist in the case of use of the energy treatment tool  5021 , and the like. The control unit  5063 , when causing the display apparatus  5041  to display the image of the surgical site, displays various kinds of surgery support information in a superimposed manner on the image of the surgical site by using a recognition result. By displaying and providing the surgery support information in a superimposed manner for the surgeon  5067 , it is possible to perform the surgery more safely and more reliably. 
     The transmission cable  5065  that connects the camera head  5005  and the CCU  5039  is an electrical signal cable corresponding to electrical signal communication, an optical fiber corresponding to optical communication, or a composite cable of the above-described cables. 
     In the example illustrated in the figure, communication is performed in a wired manner using the transmission cable  5065 , but communication between the camera head  5005  and the CCU  5039  may be performed in a wireless manner. If the communication between the camera head  5005  and the CCU  5039  is performed in a wireless manner, it is not necessary to arrange the transmission cable  5065  in the surgery room, so that it is possible to resolve a situation in which movement of a medical staff in the surgery room is disturbed by the transmission cable  5065 . 
     One example of the endoscopic surgery system  5000  to which the technology according to the present disclosure is applicable has been described above. In the description above, the endoscopic surgery system  5000  has been described as one example, but a system to which the technology according to the present disclosure can be adopted is not limited to this example. For example, the technology according to the present disclosure may be adopted to an examination flexible endoscope system or a microscopic surgery system. 
     Thus, the configuration example of the endoscopic surgery system  5000  to which the technology according to the present disclosure has been described above. 
     2. Overview 
     An overview of the technology according to the present disclosure will be described below. In medical practice, an endoscope is sometimes used. When an image is captured by the endoscope, normal observation to observe a normal image that is obtained by applying white light may be performed in some cases. Alternatively, in some other cases, fluorescence observation to obtain an image (fluorescence image) by fluorescence that is generated by applying excitation light may be performed. Further, a technique for displaying, on a monitor, a composite image in which the normal image and the fluorescence image are superimposed on each other has been disclosed. 
     The fluorescence image obtained as described above is displayed in some cases. In this case, if a degree of an enhancement process on the fluorescence image input from the camera head is uniform, in some regions, the degree of the enhancement process may be too intense and visibility is not improved. As one example, it is acceptable to increase the degree of the enhancement process to be subjected to a region with large scattering and a thin blood vessel, but if the same degree of the enhancement process is performed on other regions, the degree of the enhancement process may be too intense. 
     Therefore, in the embodiment of the present disclosure, a technology capable of of improving visibility of a fluorescence image is proposed. Further, it is expected that improvement of the visibility of the fluorescence image leads to assistance for diagnosis of an observation target. 
     Thus, the overview of the technology according to the present disclosure has been described above. 
     3. First Embodiment 
     A first embodiment of the present disclosure will be described below. 
     (Functional Configuration Example of CCU) 
     First, a functional configuration example of a CCU according to the first embodiment of the present disclosure will be described.  FIG. 3  is a block diagram illustrating the functional configuration example of the CCU according to the first embodiment of the present disclosure. As illustrated in  FIG. 3 , the CCU  5039  according to the first embodiment of the present disclosure includes an object feature detecting unit  110  and an enhancement processing unit  160 . The object feature detecting unit  110  and the enhancement processing unit  160  may be be included in the image processing unit  5061  described above. 
     As described above, in the special light observation, fluorescence observation to obtain an image (fluorescence image) by fluorescence that is generated by applying excitation light may be performed. In the fluorescence observation, imaging (what is called ICG fluorescence imaging) may be performed to obtain a fluorescent image by locally injecting reagent, such as indocyanine green (ICG), into a body tissue, and illuminating the body tissue with excitation light corresponding to a fluorescence wavelength of the reagent. In the following, as one example of the fluorescence image, it is mainly assumed that first image data (hereinafter, also referred to as an “ICG image”) that is obtained by capturing an image of a blood vessel by the ICG fluorescence imaging is input from the camera head  5005  to the CCU  5039 . 
     Furthermore, as described above, in the normal observation, a normal image that is obtained by applying white light is observed. In the following, as one example of the normal image, it is mainly assumed that second image data (hereinafter, also referred to as a “while light image (WLI) image”) that is obtained by capturing an image of a blood vessel by applying while light is input from the camera head  5005  to the CCU  5039 . 
     When both of the ICG image and the WLI image are input from the camera head  5005  to the CCU  5039 , an image sensor that captures the ICG image and an image sensor that captures the WLI image may be separated from each other. Alternatively, it may be possible to capture both of the ICG image and the WLI image by a common image sensor by switching between a timing to apply white light and a timing to apply excitation light by switching between types of light sources. Meanwhile, it is sufficient to input the ICG image to the CCU  5039 , and it is sufficient to input the WLI image to the CCU  5039  as needed basis. 
     As illustrated in  FIG. 3 , the object feature detecting unit  110  (feature detecting unit) detects a feature (hereinafter, also referred to as “object feature information”) of the ICG image. Then, the enhancement processing unit  160  controls a degree of an enhancement process to be performed on the ICG image, on the basis of the feature (object feature information) of the ICG image detected by the object feature detecting unit  110 . With this configuration, it is possible to improve visibility of the ICG image that is one example of the fluorescence image. 
     The ICG image that is subjected to the enhancement process by the enhancement processing unit  160  is output to the display apparatus  5041  (display unit) via the control unit  5063 . In this case, the control unit  5063  controls the display apparatus  5041  such that the ICG image subjected to the enhancement process is displayed on the display apparatus  5041 . With this configuration, the user is able to view the ICG image subjected to the enhancement process. 
     It may be possible to display the ICG image before being subjected to the enhancement process by the enhancement processing unit  160  on the display apparatus  5041  via the control unit  5063 , together with the ICG image after being subjected to the enhancement process by the enhancement processing unit  160 . In this case, the control unit  5063  may control the display apparatus  5041  such that both of the ICG images before and after being subjected to the enhancement process are displayed on the display apparatus  5041 . With this configuration, the user is able to visually compare the ICG images before and after being subjected to the enhancement process. 
     The degree of the enhancement process to be performed by the enhancement processing unit  160  may be changeable in accordance with operation performed by the user. In other words, the enhancement processing unit  160  may control the degree of the enhancement process on the basis of operation information input by the user. With this configuration, it is possible to adjust the degree of the enhancement process to be performed on the ICG image to a certain degree that is desired by the user. Meanwhile, the user may be able to input the operation information via the input apparatus  5047 . 
     It may be possible to display the WLI image on the display apparatus  5041  via the control unit  5063 , together with the ICG image subjected to the enhancement process by the enhancement processing unit  160 . In this case, the control unit  5063  may control the display apparatus  5041  such that both of the ICG image subjected to the enhancement process and the WLI image are displayed on the display apparatus  5041 . In this case, the ICG image subjected to the enhancement process and the WLI image may be displayed at separated positions, or the ICG image subjected to the enhancement process may be displayed in a superimposed manner on the WLI image. 
     Functions of the object feature detecting unit  110  and the enhancement processing unit  160  will be described in detail below. 
     (Object feature detecting unit  110 ) 
     First, the functions of the object feature detecting unit  110  will be described in detail below.  FIG. 4  is a diagram illustrating a detailed configuration example of the object feature detecting unit  110 . As illustrated in  FIG. 4 , the object feature detecting unit  110  includes a degree-of-scattering detecting unit  111 , a vascular diameter detecting unit  112 , a vascular density detecting unit  113 , a vascular depth detecting unit  114 , and an object feature vectorization processing unit  115 . 
     As will be described in detail later, the degree-of-scattering detecting unit  111  detects a degree of light scattering, the vascular diameter detecting unit  112  detects a vascular diameter, the vascular density detecting unit  113  detects a vascular density, and the vascular depth detecting unit  114  detects a vascular depth. 
     In the first embodiment of the present disclosure, it is mainly assumed that the object feature detecting unit  110  includes all of the degree-of-scattering detecting unit  111 , the vascular diameter detecting unit  112 , the vascular density detecting unit  113 , and the vascular depth detecting unit  114 . In this case, it is sufficient that the object feature vectorization processing unit  115  vectrorizes the degree of scattering, the vascular diameter, the vascular density, and the vascular depth as an object feature. In other words, the object feature may include the degree of scattering, the vascular diameter, the vascular density, and the vascular depth. 
     However, the object feature detecting unit  110  may include only a part of the degree-of-scattering detecting unit  111 , the vascular diameter detecting unit  112 , the vascular density detecting unit  113 , and the vascular depth detecting unit  114 . In this case, it is sufficient to vectorize the part as the object feature. In other words, the object feature may include a part of the degree of scattering, the vascular diameter, the vascular density, and the vascular depth. 
     Meanwhile, if the object feature detecting unit  110  includes only one of the degree-of-scattering detecting unit  111 , the vascular diameter detecting unit  112 , the vascular density detecting unit  113 , and the vascular depth detecting unit  114 , the object feature vectorization processing unit  115  need not perform vectorization. In other words, the object feature may include one of the degree of scattering, the vascular diameter, the vascular density, and the vascular depth. 
     (Degree-of-Scattering Detecting Unit  111 ) 
     The functions of the degree-of-scattering detecting unit  111  will be described in detail below.  FIG. 5  is a diagram illustrating a detailed configuration example of the degree-of-scattering detecting unit  111 . As illustrated in  FIG. 5 , the degree-of-scattering detecting unit  111  includes a correlation value calculating unit  1111  and a degree-of-scattering assigning unit  1112 . 
     Here, the ICG image is obtained by capturing light that has transmitted through a living body. Accordingly, a degree of blurring of the ICG image due to light scattering is likely to increase as compared to the WLI image. Therefore, it is assumed that the degree of blurring of the ICG image due to light scattering increases with a decrease in a correlation value between the ICG image and the WLI image. In view of this, the degree-of-scattering detecting unit  111  causes the correlation value calculating unit  1111  to calculate the correlation value between the ICG image and the WLI image using, and causes the degree-of-scattering assigning unit  1112  to determine a degree of scattering on the basis of the correlation value (assign the degree of scattering to the correlation value). 
     More specifically, the correlation value calculating unit  1111  calculates the correlation value between the ICG image and the WLI image for each of regions (for example, for each of pixels or each of blocks). As a method of calculating the correlation value, any method may be adopted as long as it is possible to measure a degree of correlation between two data arrays. For example, it may be possible to use a normalized cross-correlation method as the method of calculating the correlation value. Examples of the normalized cross-correlation method include normalized cross-correlation (NCC) and zero-mean normalized cross-correlation (ZNCC). 
     Alternatively, the correlation value calculating unit  1111  may measure a frequency characteristic of each of the ICG image and the WLI image, and calculate a difference between the frequency characteristics of the ICG image and the WLI image as the correlation value. 
     The degree-of-scattering assigning unit  1112  determines the degree of scattering on the basis of the correlation value between the ICG image and the WLI image (assigns the degree of scattering to the correlation value). As described above, it is assumed that the degree of blurring of the ICG image due to light scattering increases with a decrease in the correlation value between the ICG image and the WLI image. Therefore, the degree-of-scattering assigning unit  1112  may determine a larger degree of scattering for a smaller absolute value of the correlation value (assign a large degree of scattering to the correlation value with a small absolute value). 
       FIG. 6  is a diagram illustrating an example of a correspondence relationship between the correlation value and the degree of scattering.  FIG. 6  illustrates a correspondence table  1113  that contains the absolute value of the correlation value and the degree of scattering. As for the degree of scattering, a larger value indicates a larger degree of scattering. As illustrated in  FIG. 6 , the degree-of-scattering assigning unit  1112  may determine a larger degree of scattering increases for a smaller absolute value of the correlation value (assign a large degree of scattering to the correlation value with a small absolute value). However, the correspondence relationship between the correlation value and the degree of scattering is not limited to the example as illustrated in  FIG. 6 . 
     Meanwhile, in the first embodiment of the present disclosure, it is mainly assumed that the object feature includes the degree of scattering. In other words, it is mainly assumed that the object feature detecting unit  110  detects the degree of scattering. However, the object feature may include the correlation value itself instead of the degree of scattering. In other words, the object feature detecting unit  110  need not detect the degree of scattering. In this case, the degree-of-scattering detecting unit  111  need not include the degree-of-scattering assigning unit  1112 . 
     Further, it may be possible to use a difference value between the ICG image and the WLI image instead of the correlation value between the ICG image and the WLI image. In this case, it is assumed that the degree of blurring of the ICG image due to light scattering increases with an increase in the difference value between the ICG image and the WLI image. Therefore, the degree-of-scattering assigning unit  1112  may determine a larger degree of scattering for a larger absolute value of the difference value (assign a large degree of scattering to the difference value with a large absolute value). 
     Thus, the details of the functions of the degree-of-scattering detecting unit  111  have been described above. 
     (Vascular Diameter Detecting Unit  112 ) 
     Functions of the vascular diameter detecting unit  112  will be described in detail below.  FIG. 7  is a diagram illustrating a detailed configuration example of the vascular diameter detecting unit  112 . As illustrated in  FIG. 7 , the vascular diameter detecting unit  112  includes a first image processing unit  1121 , a second image processing unit  1122 , a difference calculating unit  1123 , and a vascular diameter assigning unit  1124 . 
     Here, if image processing is performed on the ICG image at different intensities, a difference between blood vessels that appear in two processing results tends to increase with a decrease in the vascular diameter. This tendency will be described with reference to  FIG. 8 . Meanwhile, in the first embodiment of the present disclosure, it is mainly assumed that image processing is performed on the ICG image. However, it may be possible to perform image processing on the WLI image, instead of the ICG image or together with the ICG image. 
       FIG. 8  is a diagram for explaining a case in which image processing is performed on the ICG image at different intensities. In the example illustrated in  FIG. 8 , it is mainly assumed that the enhancement process (for example, an unsharp masking process or the like) is performed on the ICG image. However, the image processing performed on the ICG image is not limited to the enhancement process. For example, the image processing performed on the ICG image may be a smoothing process (for example, a Gaussian filtering process or the like). In other words, the image processing performed on the ICG image may be any image processing by which a difference between blood vessels that appear in two processing results increases with a decrease in the vascular diameter. 
       FIG. 8  illustrates an ICG image M 11  that is subjected to the enhancement process at a high intensity and an ICG image M 12  that is subjected to the enhancement process at a low intensity. A thin blood vessel K 11  and other blood vessels (a blood vessel with a medium thickness and a thick blood vessel) appear in the ICG image M 11  that is subjected to the enhancement process at the high intensity, and a blood vessel K 12  corresponding to the thin blood vessel K 11  and other blood vessels (a blood vessel with a medium thickness and a thick blood vessel) appear in the ICG image M 12  that is subjected to the enhancement process at the low intensity. 
     In this case, in a difference image M 13  of the ICG image M 11  that is subjected to the enhancement process at the high intensity and the ICG image M 12  that is subjected to the enhancement process at the low intensity, only the thin blood vessel K 11  appears and the other blood vessels (the blood vessel with a medium thickness and the thick blood vessel) do not appear. This phenomenon occurs due to the tendency to increase the difference between the blood vessels that appear in the two processing results with a decrease in the vascular diameter as described above. 
     Therefore, the first image processing unit  1121  performs image processing on the ICG image at a first intensity. Then, the second image processing unit  1122  performs image processing on the ICG image at a second intensity that is different from the first intensity. The difference calculating unit  1123  calculates a difference value between a processing result obtained by the first image processing unit  1121  and a processing result obtained by the second image processing unit  1122 . 
     The vascular diameter assigning unit  1124  determines the vascular diameter on the basis of the difference value between the processing results obtained by performing the image processing on the ICG image at two different intensities (assigns the vascular diameter to the difference value). As described above, it is assumed that the vascular diameter decreases with an increase in the difference value between the processing results of the two kinds of image processing. Therefore, the vascular diameter assigning unit  1124  may determine a smaller vascular diameter for a larger difference value between the processing results of the two kinds of image processing (assign a small blood vessel diameter to the difference value). 
       FIG. 9  is a diagram illustrating an example of a correspondence relationship between the difference value and the vascular diameter.  FIG. 9  illustrates a correspondence table  1125  that contains an absolute value of the difference value and the vascular diameter. As for the vascular diameter, a larger value indicates a smaller vascular diameter. As illustrated in  FIG. 9 , the vascular diameter assigning unit  1124  may determine a smaller vascular diameter decreases (a vascular diameter with a larger value) for a larger absolute value of the difference value. However, the correspondence relationship between the difference value and the vascular diameter is not limited to the example as illustrated in  FIG. 9 . 
     Meanwhile, in the first embodiment of the present disclosure, it is mainly assumed that the object feature includes the vascular diameter. In other words, it is mainly assumed that the object feature detecting unit  110  detects the vascular diameter. However, the object feature may include the difference value itself instead of the vascular diameter. In other words, the object feature detecting unit  110  need not detect the vascular diameter. In this case, the vascular diameter detecting unit  112  need not include the vascular diameter assigning unit  1124 . 
     (Modification of Vascular Diameter Detecting Unit  112 ) 
     A modification of the vascular diameter detecting unit  112  will be described below. The vascular diameter detecting unit  112  may determine the vascular diameter by a different method. Specifically, the vascular diameter detecting unit  112  may determine the vascular diameter on the basis of an eigenvalue of a Hessian matrix that is calculated from the ICG image. In the following, the modification will be described. For details of the method, it is possible to refer to a reference literature of “A. F. Frangi et. al., “Multiscale vessel enhancement filtering”, Proceedings of MICCAI, pp 130-137, 1998.”. 
       FIG. 10  is a diagram illustrating an example of the ICG image.  FIG. 10  illustrates an ICG image G 10  that is input to the vascular diameter detecting unit  112 . The vascular diameter detecting unit  112  calculates a Hessian matrix of the ICG image G 10  for each of pixels. Here, the Hessian matrix for each of the pixels is represented by Expression 1 below, where (x, y) represents a coordinate of a pixel, and I represents a pixel value. 
     
       
         
           
             
               
                 
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     Subsequently, the vascular diameter detecting unit  112  calculates an eigenvalue of the Hessian matrix for each of the pixels. The eigenvalue is represented by Expression 2 below. 
       EIGENVALUE (λ 1 ,λ 2 ) WHERE, λ 1 ≤λ 2   (2)
 
     The vascular diameter detecting unit  112  extracts blood vessels on the basis of a structure-based index RB and an intensity-based index S by using the eigenvalue. The structure-based index RB and the intensity-based index S are represented by Expression 3 below. 
     
       
         
           
             
               
                 
                   
                     
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     Specifically, the vascular diameter detecting unit  112  extracts blood vessels using an Expression for blood vessel extraction using the structure-based index RB and the intensity-based index S. The expression for blood vessel extraction is represented by Expression 4 below using the structure-based index RB and the intensity-based index S. 
     
       
         
           
             
               
                 
                   
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     Here, the structure-based index RB decreases and a value of V(s) increases with an increase in a difference between two eigenvalues, so that a correspondence pixel is likely to be determined as a blood vessel. In contrast, the intensity-based index S decreases and the value of V(s) decreases at a pixel for which a change of the pixel value is small (a pixel in a background portion or the like), so that the pixel is likely to be determined as not being a blood vessel. 
     A more detailed example will be described below. As described above, the vascular diameter detecting unit  112  calculates the Hessian matrix of the ICG image G 10  for each of the pixels. Here, a Hessian matrix H for each of the pixels is represented by Expression 5 below, where (x, y) represents a coordinate of a pixel. 
     
       
         
           
             
               
                 
                   
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                   ) 
                 
               
             
           
         
       
     
     The vascular diameter detecting unit  112  calculates the eigenvalue as described above by using the Hessian matrix H for each of the pixels represented as above, and extracts blood vessels by using the expression for blood vessel extraction. More specifically, at a scale at which a certain pixel has a maximum pixel value among all of scales (at a scale at which V(s) has a maximum value), the vascular diameter detecting unit  112  determines this pixel as a blood vessel portion, and extracts a blood vessel at each of the scales. With this configuration, it becomes possible to extract a blood vessel for each size of the vascular diameter (it becomes possible to extract a blood vessel by taking into account a magnitude of the vascular diameter). 
       FIG. 11  to  FIG. 15  are diagrams illustrating examples of ICG images at different scales.  FIG. 11  illustrates an ICG image G 11  at a scale of “0.5”.  FIG. 12  illustrates an ICG image G 12  at a scale of “5”.  FIG. 13  illustrates an ICG image G 13  at a scale of “10”.  FIG. 14  illustrates an ICG image G 14  at a scale of “15”.  FIG. 15  illustrates an ICG image G 15  at a scale of “20”. With reference to  FIG. 11  to  FIG. 15 , it is possible to recognize that a thicker blood vessel is extracted with an increase in the scale. 
     Thus, the details of the functions of the vascular diameter detecting unit  112  have been described above. 
     (Vascular Density Detecting Unit  113 ) 
     Functions of the vascular density detecting unit  113  will be described in detail below.  FIG. 16  is a diagram illustrating a detailed configuration example of the vascular density detecting unit  113 . As illustrated in  FIG. 16 , the vascular density detecting unit  113  includes a vascular density assigning unit  1131 . Meanwhile, as illustrated in  FIG. 16 , information on the vascular diameter detected by the vascular diameter detecting unit  112  may be input to the vascular density detecting unit  113 . 
     The vascular density assigning unit  1131  determines a vascular density based on the ICG image. In the following, it is mainly assumed that the vascular density is a combination of a ratio of an area of blood vessels in a certain area of the ICG image (hereinafter, also referred to as a “blood vessel ratio”) and a vascular diameter that most frequently appears in the area (hereinafter, also referred to as a “most-frequent vascular diameter”). However, the vascular density may be determined by any method. For example, the vascular density may be the number of blood vessels that are present in a certain area of the ICG image (hereinafter, also simply referred to as a “blood vessel number”) or a ratio of blood vessels. 
       FIG. 17  is a diagram for explaining the vascular density.  FIG. 17  illustrates a case in which thin blood vessels are present densely, a case in which a thick blood vessel is present sparsely, and a case in which a thin blood vessel is present sparsely. In the example illustrated in  FIG. 17 , the case in which the thick blood vessel is present sparsely has a higher vascular density than the case in which the thin blood vessel is present sparsely (the vascular density increases with an increase in the ratio of blood vessels). Further, a ratio (area) of blood vessels in a certain area of the ICG image is approximately the same between the case in which the thin blood vessels are present densely and the case in which the thin blood vessel is present sparsely, but the vascular density is higher in a case in which the most-frequent vascular diameter is thin than in the case in which the most-frequent vascular diameter is thick. 
     The vascular density assigning unit  1131  determines the vascular density on the basis of a combination of the ratio of blood vessels and the most-frequent vascular diameter (assigns the vascular density to the combination). As described above, it is assumed that the vascular density increases with an increase in the ratio of blood vessels. Further, it is assumed that the vascular density increases with a decrease in the most-frequent vascular diameter. Therefore, the vascular density assigning unit  1131  may determine a higher vascular density for a larger ratio of blood vessels or for a smaller most-frequent vascular diameter (assign a high vascular density to the combination of the ratio of blood vessels and the most-frequent vascular diameter). 
       FIG. 18  is a diagram illustrating an example of a correspondence relationship between the combination of the ratio of blood vessels and the most-frequent vascular diameter and the vascular density.  FIG. 18  illustrates a correspondence table  1132  that contains the combination of the ratio of blood vessels and the most-frequent vascular diameter and the vascular density. Here, as for the vascular density, a larger value indicates a higher vascular density. As illustrated in  FIG. 18 , the vascular density assigning unit  1131  may determine a higher vascular density for a larger ratio of blood vessels or for a smaller most-frequent vascular diameter (assign a high vascular density to a combination of the ratio of blood vessels and the most-frequent vascular diameter). However, the correspondence relationship between the combination of the ratio of blood vessels and the most-frequent vascular diameter is not limited to the example as illustrated in  FIG. 18 . 
     Meanwhile, as described above, the vascular density may be the number of blood vessels or the ratio of blood vessels. In this case, the vascular density assigning unit  1131  may determine a higher vascular density for a larger number of blood vessels (assign a high vascular density to the number of blood vessels). Alternatively, the vascular density assigning unit  1131  may determine a higher vascular density for a larger ratio of blood vessels (assign a high vascular density to the ratio of blood vessels). 
     (Vascular Depth Detecting Unit  114 ) 
     Functions of the vascular depth detecting unit  114  will be described in detail below.  FIG. 19  is a diagram illustrating a detailed configuration example of the vascular depth detecting unit  114 . As illustrated in  FIG. 19 , the vascular depth detecting unit  114  includes a blood vessel detecting unit  1141 , a correlation value calculating unit  1142 , and a vascular depth assigning unit  1143 . Meanwhile, the correlation value calculating unit  1142  may function similarly to the correlation value calculating unit  1111  of the degree-of-scattering detecting unit  111 . 
     Here, it is assumed that a blood vessel appears more clearly in the ICG image than the WLI image such that a blood vessel does not appear in the WLI image but a blood vessel appears in the ICG image. In this case, it is assumed that the blood vessel is present at a deep position in a living body. Therefore, it is assumed that a vascular depth increases with a decrease in the correlation value between the ICG image and the WLI image. Further, if a blood vessel is not detected, it is assumed that a vascular depth is larger as compared to a case in which a blood vessel is detected. 
     Therefore, the vascular depth detecting unit  114  causes the blood vessel detecting unit  1141  to detect whether a blood vessel is present in at least one of the ICG image and the WLI image, causes the correlation value calculating unit  1142  to calculate the correlation value between the ICG image and the WLI image, and causes the vascular depth assigning unit  1143  to determine a degree of scattering on the basis of information indicating whether a blood vessel is present (hereinafter, also referred to as “blood vessel information”) and the correlation value (assign the vascular depth to the blood vessel information and the correlation value). 
     More specifically, the blood vessel detecting unit  1141  detects whether a blood vessel is present in at least one of the ICG image and the WLI image (in the ICG image, in the WLI image, or in both of the ICG image and the WLI image) for each of regions (for example, for each of pixels or for each of blocks). In this case, it is sufficient that the blood vessel detecting unit  1141  calculates color information or a signal band, and detects whether a blood vessel is present on the basis of the color information or the signal band. 
     The vascular depth assigning unit  1143  determines the degree of scattering on the basis of the blood vessel information and the correlation value (assigns the vascular depth to the blood vessel information and the correlation value). As described above, it is assumed that the vascular depth increases with a decrease in the correlation value between the ICG image and the WLI image. Therefore, the degree-of-scattering assigning unit  1112  may determine a larger vascular depth for a smaller absolute value of the correlation value (assign a large vascular depth to the correlation value with a small absolute value). 
     Furthermore, as described above, if a blood vessel is not detected, it is assumed that the vascular depth is larger as compared to the case in which a blood vessel is detected. Therefore, if a blood vessel is not detected, the vascular depth assigning unit  1143  may determine a larger vascular depth as compared to the case in which a blood vessel is detected (if a blood vessel is not detected, a larger vascular depth is assigned as compared to the case in which a blood vessel is detected). 
       FIG. 20  is a diagram illustrating an example of a correspondence relationship between a combination of the blood vessel information and the correlation value and the vascular depth.  FIG. 20  illustrates a correspondence table  1144  that contains the combination of the blood vessel information and the correlation value and the vascular depth. As for the vascular depth, a larger value indicates a deeper position at which a blood vessel is present in a living body. As illustrated in  FIG. 20 , if a blood vessel is not detected, the vascular depth assigning unit  1143  may determine a larger vascular depth as compared to the case in which a blood vessel is detected, and may determine a larger vascular depth for a smaller absolute value of the correlation value. However, the correspondence relationship between the combination of the blood vessel information and the correlation value and the vascular depth is not limited to the example as illustrated in  FIG. 20 . 
     Further, it may be possible to use a difference value between the ICG image and the WLI image instead of the correlation value between the ICG image and the WLI image. In this case, it is assumed that the vascular depth increases with an increase in the difference value between the ICG image and the WLI image. Therefore, the vascular depth assigning unit  1143  may determine a larger vascular depth for a larger absolute value of the difference value (assign a large vascular depth to the difference value with a large absolute value). 
     Thus, the details of the functions of the vascular depth detecting unit  114  have been described above. 
     (Enhancement processing unit  160 ) 
     Functions of the enhancement processing unit  160  will be described in detail below. Here, a case will be described in which the degree of the enhancement process is uniform over the entire ICG image.  FIG. 21  is a diagram for explaining the case in which the degree of the enhancement process is uniform over the entire ICG image.  FIG. 21  illustrates an ICG image M 21  before being subjected to the enhancement process, an ICG image M 22  that is subjected to the enhancement process at a low intensity, and an ICG image M 23  that is subjected to the enhancement process at a high intensity. 
     Here, in the ICG image M 21  before being subjected to the enhancement process, a thin blood vessel K 21  remains thin and is not easily viewable. In contrast, in the ICG image M 22  that is subjected to the enhancement process at the low intensity, a thickness of a thin blood vessel K 22  is slightly increased, so that visibility of the thin blood vessel K 22  is slightly improved. Further, in the ICG image M 23  subjected to the enhancement process at the high intensity, a thickness of a thin blood vessel K 23  is further increased, so that visibility of the thin blood vessel K 23  is largely improved. However, it is recognized that noise in the entire image increases with an increase in the degree of the enhancement process. 
     Therefore, the enhancement processing unit  160  controls the degree of the enhancement process in accordance with the object feature detected by the object feature detecting unit  110 . Specifically, it is sufficient that the enhancement processing unit  160  increases the degree of the enhancement process with an increase in an object feature amount detected by the object feature detecting unit  110 . With this configuration, the enhancement process is performed at a high intensity on a region that needs to be largely enhanced, and the enhancement process is performed at a low intensity on a region in which excessive enhancement needs to be avoided to reduce noise; therefore, the visibility can be improved. 
     Specifically, if the degree-of-scattering detecting unit  111  detects the degree of scattering, the enhancement processing unit  160  may increase the degree of the enhancement process with an increase in the degree of scattering. Further, if the degree-of-scattering detecting unit  111  detects the correlation value, the enhancement processing unit  160  may increase the degree of the enhancement process with a decrease in the correlation value. With this configuration, the degree of the enhancement process performed on a region in which fluorescence scattering is large is increased, and the degree of the enhancement process performed on other regions is reduced, so that the visibility is improved. 
     Further, if the vascular diameter detecting unit  112  detects the vascular diameter, the enhancement processing unit  160  may increase the degree of the enhancement process with a decrease in the vascular diameter. Furthermore, if the vascular diameter detecting unit  112  detects the difference value between the ICG image and the WLI image, the enhancement processing unit  160  may increase the degree of the enhancement process with a decrease in the absolute value of the difference value. With this configuration, the degree of the enhancement process performed on a region in which the vascular diameter is small is increased, and the degree of the enhancement process performed on other regions is reduced, so that the visibility is improved. 
       FIG. 22  is a diagram illustrating an example of an ICG image on which enhancement processes are performed at different intensities in accordance with vascular diameters.  FIG. 22  illustrates an ICG image M 31  on which enhancement processes are performed at different intensities in accordance with vascular diameters. An enhancement process at a high intensity is performed on a region R 1  in which a blood vessel K 23  with a small diameter is present. In contrast, an enhancement process at a low intensity is performed on a region R 2  in which a blood vessel K 32  with a large diameter is present. Through the enhancement processes as described above, visibility of the blood vessel K 23  with the small diameter and the blood vessel K 32  with the large diameter is improved. 
     Explanation will be continued with reference to  FIG. 21 . If the vascular density detecting unit  113  detects the vascular density, the enhancement processing unit  160  may increase the degree of the enhancement process with an increase in the vascular density. With this configuration, the degree of the enhancement process performed on a region with a high vascular density is increased, and the degree of the enhancement process performed on other regions is reduced, so that the visibility is improved. 
     Further, if the vascular depth detecting unit  114  detects the vascular depth, the enhancement processing unit  160  may increase the degree of the enhancement process with an increase in the vascular depth. With this configuration, the degree of the enhancement process performed on a region with a large vascular depth is increased, and the degree of the enhancement process performed on other regions is reduced, so that the visibility is improved. 
     While it is assumed that, in the first embodiment of the present disclosure, the enhancement process is performed on the ICG image, it may be possible to perform a noise removal process instead of the enhancement process on the ICG image. 
     In this case, the enhancement processing unit  160  controls a degree of noise removal in accordance with the object feature detected by the object feature detecting unit  110 . Specifically, it is sufficient that the enhancement processing unit  160  increases the degree of the noise removal process with an increase in the object feature amount detected by the object feature detecting unit  110 . With this configuration, the noise removal process is performed at a high intensity on a region in which noise needs to be removed intensively (region that is not easily viewable), and the noise removal process is performed at a low intensity on other regions, so that the visibility is improved. 
     Specifically, if the degree-of-scattering detecting unit  111  detects the degree of scattering, the degree of the noise removal process may be increased with an increase in the degree of scattering. Further, if the degree-of-scattering detecting unit  111  detects the correlation value, the degree of the noise removal process may be increased with a decrease in the correlation value. Furthermore, if the vascular diameter detecting unit  112  detects the vascular diameter, the degree of the noise removal process may be increased with a decrease in the vascular diameter. Moreover, if the vascular diameter detecting unit  112  detects the difference value between the ICG image and the WLI image, the degree of the noise removal process may be increased with a decrease in the absolute value of the difference value. 
     Furthermore, if the vascular density detecting unit  113  detects the vascular density, the degree of the noise removal process may be increased with an increase in the vascular density. Moreover, if the vascular depth detecting unit  114  detects the vascular depth, the degree of the enhancement process may be increased with an increase in the vascular depth. 
     Meanwhile, a specific method for implementing the enhancement process by the enhancement processing unit  160  is not specifically limited. For example, if it is assumed that a pixel value obtained before the enhancement process is performed on the ICG image is denoted by x 0 , neighboring pixel values (including the pixel value x 0 ) used to the enhancement process on the pixel value x 0  are denoted by x 0  to x n , and the degree of enhancement is denoted by p, a pixel value y obtained after the enhancement process is performed on the ICG image is represented by Expression 6 below. 
     
       
         
           
             
               
                 
                   y 
                   = 
                   
                     
                       x 
                       0 
                     
                     + 
                     
                       p 
                        
                       
                         ( 
                         
                           
                             
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                                 i 
                                 = 
                                 0 
                               
                               n 
                             
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                              
                             
                               x 
                               i 
                             
                           
                           - 
                           
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                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   6 
                   ) 
                 
               
             
           
         
       
     
     Thus, the first embodiment of the present disclosure has been described above. 
     4. Second Embodiment 
     A second embodiment of the present disclosure will be described below. 
     (Functional Configuration Example of CCU) 
     First, a functional configuration example of a CCU according to the second embodiment of the present disclosure will be described.  FIG. 23  is a block diagram illustrating the functional configuration example of the CCU according to the second embodiment of the present disclosure. As illustrated in  FIG. 23 , the CCU  5039  according to the second embodiment of the present disclosure includes, similarly to the first embodiment of the present disclosure, the object feature detecting unit  110  and the enhancement processing unit  160 . The CCU  5039  according to the second embodiment of the present disclosure further includes a class classification unit  120 , a coefficient selecting unit  130 , and a coefficient database (DB)  140 . 
     In the coefficient DB  140 , a correspondence (hereinafter, also referred to as a “coefficient set”) between the object feature and a coefficient of the enhancement process (hereinafter, also simply referred to as a “coefficient”), which is generated by machine learning using a past ICG image, is registered. More specifically, the correspondence between the object feature and the coefficient is established through a learning process on a plurality of combinations of an object feature detected from a past ICG image and a coefficient. In this manner, the coefficient is prepared in advance for each of classes of the object feature. 
     The class classification unit  120  determines which of the coefficient sets includes a feature that matches a part or the whole of the object feature detected by the object feature detecting unit  110 , and determines a class to which the object feature belongs. The coefficient selecting unit  130  selects a coefficient corresponding to the class from the coefficient DB  140 . Meanwhile, as types of the feature included in the coefficient set, various types may be adopted. 
     Specifically, as a first example, it is assumed that a coefficient corresponding to the object feature detected by the object feature detecting unit  110  is registered in the coefficient DB  140 . As a second example, it is assumed that a coefficient corresponding to a part (a first feature) of the object feature detected by the object feature detecting unit  110  is registered in the coefficient DB  140 , but a coefficient corresponding to the rest (a second feature different from the first feature) of the object feature detected by the object feature detecting unit  110  is not registered in the coefficient DB  140 . As a third example, it is assumed that only a single coefficient is registered in the coefficient DB  140 . 
       FIG. 24  is a diagram illustrating a case in which the coefficient corresponding to the object feature is registered in the coefficient DB  140  (first example). As illustrated in  FIG. 24 , a coefficient set T 10  includes coefficient sets T 11  to T 14  in each of which the object feature (the degree of scattering, the vascular diameter, and the like) detected by the object feature detecting unit  110  and a coefficient are associated. 
     In this manner, if the coefficient corresponding to the object feature detected by the object feature detecting unit  110  is registered in the coefficient DB  140 , the coefficient corresponding to the whole object feature is acquired from the coefficient DB  140 . Therefore, it is sufficient that the enhancement processing unit  160  controls the enhancement process in accordance with the coefficient. In other words, the enhancement process performed by the enhancement processing unit  160  may be uniform independently of the object feature detected by the object feature detecting unit  110  (S 11 ). 
       FIG. 25  is a diagram illustrating a case (second example) in which the coefficient corresponding to the part (first feature) of the object feature is registered in the coefficient DB  140 , but the coefficient corresponding to the rest (second feature) of the object feature is not registered in the coefficient DB  140 . As illustrated in  FIG. 25 , a coefficient set T 20  includes coefficient sets T 21  to T 22  in each of which the part (degree of scattering) of the object feature detected by the object feature detecting unit  110  and a coefficient are associated. 
     In this manner, if the coefficient corresponding to the part (first feature) of the object feature detected by the object feature detecting unit  110  is registered in the coefficient DB  140  but the coefficient corresponding to the rest (second feature) of the object feature is not registered in the coefficient DB  140 , only the coefficient corresponding to the part of the object feature is acquired from the coefficient DB  140 . Therefore, it is sufficient that the enhancement processing unit  160  controls the enhancement process in accordance with the coefficient, and controls the degree of the enhancement process on the basis of the rest (second feature) of the object feature detected by the object feature detecting unit  110 . In other words, the degree of the enhancement process performed by the enhancement processing unit  160  may be controlled based on the other feature (feature other than the degree of scattering) (S 12 ). 
       FIG. 26  is a diagram illustrating a case (third example) in which only a single coefficient is registered in the coefficient DB  140 . As illustrated in  FIG. 26 , a coefficient set T 30  includes a coefficient set T 31  containing a single kind of coefficient. In this manner, if the single coefficient is registered in the coefficient DB  140 , the single coefficient is acquired from the coefficient DB  140 . Therefore, it is sufficient that the enhancement processing unit  160  controls the enhancement process in accordance with the single coefficient, and controls the degree of the enhancement process on the basis of the object feature detected by the object feature detecting unit  110 . In other words, the degree of the enhancement process performed by the enhancement processing unit  160  may be controlled based on the whole object feature (S 13 ). 
     Meanwhile, a specific method for implementing the enhancement process by the enhancement processing unit  160  according to the second embodiment of the present disclosure is not specifically limited. For example, similarly to the first embodiment of the present disclosure, if it is assumed that a pixel value obtained before the enhancement process is performed on the ICG image is denoted by x 0 , neighboring pixel values (including the pixel value x 0 ) used to the enhancement process on the pixel value x 0  are denoted by x 0  to x n , the degree of enhancement is denoted by p, and the coefficient of the second embodiment of the present disclosure is denoted by a i , a pixel value y obtained after the enhancement process is performed on the ICG image is represented by Expression 7 below. 
     
       
         
           
             
               
                 
                   y 
                   = 
                   
                     
                       x 
                       0 
                     
                     + 
                     
                       p 
                        
                       
                         ( 
                         
                           
                             
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                                 i 
                                 = 
                                 0 
                               
                               n 
                             
                              
                             
                                 
                             
                              
                             
                               
                                 a 
                                 i 
                               
                                
                               
                                 x 
                                 i 
                               
                             
                           
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                         ) 
                       
                     
                   
                 
               
               
                 
                   ( 
                   7 
                   ) 
                 
               
             
           
         
       
     
     Thus, the second embodiment of the present disclosure has been described above. 
     5. Conclusion 
     As described above, according to the embodiments of the present disclosure, the CCU  5039  is provided as one example of the image processing apparatus, where the CCU  5039  includes the object feature detecting unit  110  that detects a feature of the ICG image that is one example of the first image data obtained by capturing an image of a blood vessel by the ICG fluorescence imaging, and the enhancement processing unit  160  that controls the degree of the enhancement process performed on the ICG image on the basis of the feature detected by the object feature detecting unit  110 . With this configuration, it is possible to improve visibility of a fluorescence image. Further, with the improvement of the visibility of the fluorescence image, it becomes possible to assist diagnosis of an observation target. 
     While the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the technical scope of the present disclosure is not limited to the examples as described above. It is obvious that a person skilled in the technical field of the present disclosure may conceive various alternations and modifications within the scope of the appended claims, and it should be understood that they will naturally come under the technical scope of the present disclosure. 
     For example, it may be possible to generate a program that causes hardware, such as a CPU, a ROM, and a RAM, incorporated in a computer to implement the same functions as the functions of the control unit  5063  as described above. Further, it may be possible to provide a computer-readable recording medium that stores therein the program. 
     Furthermore, the effects described in this specification are merely illustrative or exemplified effects, and are not limitative. That is, with or in the place of the above effects, the technology according to the present disclosure may achieve other effects that are clear to those skilled in the art from the description of this specification. 
     The following configurations are also within the technical scope of the present disclosure. 
     (1) 
     An image processing apparatus comprising: 
     a feature detecting unit configured to detect a feature of first image data that is obtained by capturing an image of a blood vessel by ICG fluorescence imaging; and 
     an enhancement processing unit configured to control a degree of an enhancement process performed on the first image data, on the basis of the feature. 
     (2) 
     The image processing apparatus according to (1), wherein the feature includes one of a correlation value between the first image data and second image data that is obtained by capturing an image of the blood vessel by applying white light and a degree of scattering that is determined based on the correlation value. 
     (3) 
     The image processing apparatus according to (2), wherein the enhancement processing unit increases a degree of the enhancement process with a decrease in the correlation value or with an increase in the degree of scattering. 
     (4) 
     The image processing apparatus according to any one of (1) to (3), wherein the feature includes one of a difference value between processing results of two kinds of image processing that are performed at different intensities on the first image data and a vascular diameter that is determined based on the difference value. 
     (5) 
     The image processing apparatus according to (4), wherein the enhancement processing unit increases the degree of the enhancement process with a decrease in an absolute value of the difference value or with a decrease in the vascular diameter. 
     (6) 
     The image processing apparatus according to any one of (1) to (3), wherein the feature includes a vascular diameter that is determined based on an eigenvalue of a Hessian matrix calculated from the first image data. 
     (7) 
     The image processing apparatus according to (6), wherein the enhancement processing unit increases the degree of the enhancement process with a decrease in the vascular diameter. 
     (8) 
     The image processing apparatus according to any one of (1) to (7), wherein the feature includes a vascular density that is determined based on the first image data. 
     (9) 
     The image processing apparatus according to (8), wherein the enhancement processing unit increases the degree of the enhancement process with an increase in the vascular density. 
     (10) 
     The image processing apparatus according to any one of (1) to (9), wherein the feature includes a correlation value between the first image data and second image data that is obtained by capturing an image of the blood vessel by applying white light and a vascular depth that is determined in accordance with information indicating whether a blood vessel is present in at least one of the first image data and the second image data. 
     (11) 
     The image processing apparatus according to (10), wherein the enhancement processing unit increases the degree of the enhancement process with an increase in the vascular depth. 
     (12) 
     The image processing apparatus according to any one of (1) to (11), wherein if a coefficient corresponding to the feature is registered, the enhancement processing unit controls the enhancement process in accordance with the coefficient. 
     (13) 
     The image processing apparatus according to any one of (1) to (11), wherein if a coefficient corresponding to a first feature is registered and a coefficient corresponding to a second feature that is different from the first feature is not registered, the enhancement processing unit controls the enhancement process in accordance with the coefficient and controls a degree of the enhancement process in accordance with the second feature. 
     (14) 
     The image processing apparatus according to any one of (1) to (11), wherein if a single coefficient is registered, the enhancement processing unit controls the enhancement process in accordance with the coefficient, and controls a degree of the enhancement process on the basis of the feature. 
     (15) 
     The image processing apparatus according to any one of (12) to (14), wherein the coefficient is generated in advance through machine learning. 
     (16) 
     The image processing apparatus according to any one of (1) to (15), wherein the image processing apparatus includes a control unit configured to cause a display unit to display the first image data subjected to the enhancement process. 
     (17) 
     The image processing apparatus according to (16), wherein the control unit causes the display unit to display both of the first image data before being subjected to the enhancement process and the first image data after being subjected to the enhancement process. 
     (18) 
     The image processing apparatus according to any one of (1) to (17), wherein the enhancement processing unit controls the degree of the enhancement process on the basis of operation information input from a user. 
     (19) 
     An image processing method comprising: 
     detecting a feature of first image data that is obtained by capturing an image of a blood vessel by ICG fluorescence imaging; and 
     controlling, by a processor, a degree of an enhancement process performed on the first image data, on the basis of the feature. 
     (20) 
     An image processing system comprising: 
     an imaging unit configured to capture an image of a blood vessel by ICG fluorescence imaging and obtain first image data; 
     a feature detecting unit configured to detect a feature of the first image data; and 
     an enhancement processing unit configured to control a degree of the enhancement process performed on the first image data on the basis of the feature. 
     REFERENCE SIGNS LIST 
     
         
         
           
               110  Object feature detecting unit 
               111  Degree-of-scattering detecting unit 
               112  Vascular diameter detecting unit 
               113  Vascular density detecting unit 
               114  Vascular depth detecting unit 
               115  Object feature vectorization processing unit 
               1111  Correlation value calculating unit 
               1112  Degree-of-scattering assigning unit 
               1121  First image processing unit 
               1122  Second image processing unit 
               1123  Difference calculating unit 
               1124  Vascular diameter assigning unit 
               1141  Blood vessel detecting unit 
               1142  Correlation value calculating unit 
               1143  Vascular depth assigning unit 
               120  Class classification unit 
               130  Coefficient selecting unit 
               140  Coefficient DB 
               160  Enhancement processing unit