Disease diagnostic apparatus, image processing method in the same apparatus, and medium storing program associated with the same method

Abstract

A diagnostic apparatus for diagnosing a disease using a captured image of an affected area includes an image-memorizing unit configured to memorize the captured image and a processing unit configured to process the captured image memorized in the image-memorizing unit. The processing unit includes a separating unit configured to separate the captured image into a brightness component and a color information component, an extracting unit configured to extract a region to be diagnosed based on the brightness component or the color information component of the captured image to highlight likeness of the region, and a highlighting unit configured to highlight the extracted region in accordance with the extracted likelihood V representing the likeness of the region.

1 . A diagnostic apparatus for diagnosing a disease using a captured image of an affected area, the diagnostic apparatus comprising:
 an image-memorizing unit configured to memorize the captured image; and   a processing unit configured to process the captured image memorized in the image-memorizing unit, the processing unit comprising:   a separating unit configured to separate the captured image into a brightness component and a color information component,   an extracting unit configured to extract a region to be diagnosed based on the brightness component or the color information component of the captured image to highlight likeness of the region, and   a highlighting unit configured to highlight the extracted region in accordance with the extracted likelihood V representing the likeness of the region.   
     
     
         2 . The diagnostic apparatus according to  claim 1 , wherein the highlighting unit comprises a generating unit configured to generate a highlighted image by adding a red color Red to the captured image in accordance with the likelihood V. 
     
     
         3 . The diagnostic apparatus according to  claim 1 , wherein when the likelihood V is 0, the likeliness of the vascular region is minimum, and wherein when the likelihood V is 1, the likeliness of the vascular region is maximum. 
     
     
         4 . The diagnostic apparatus according to  claim 1 , wherein the region is a vessel-corresponding region. 
     
     
         5 . The diagnostic apparatus according to  claim 1 , wherein the likelihood V indicates likeness of a vessel. 
     
     
         6 . The diagnostic apparatus according to  claim 1 , wherein the highlighting unit is further configured to combine the highlighted image with a background image. 
     
     
         7 . The diagnostic apparatus according to  claim 1 , wherein the highlighting unit is further configured to combine the highlighted image with the brightness component Gray. 
     
     
         8 . The diagnostic apparatus according to  claim 2 , wherein the highlighted image is generated in accordance with the following mathematical formula:
     E =IMG.*(1− V )+Red* V,  
   wherein “E” represents the highlighted image; “IMG” represents the captured image; “V” represents the likelihood V; “Red” represents the red color; “*” represents multiplication;   and “.*” represents multiplication per an element.   
     
     
         9 . The diagnostic apparatus according to  claim 7 , wherein the highlighted image is generated in accordance with the following mathematical formula:
     E =Gray(IMG).*(1− V )+Red* V,  
   wherein “E” represents the highlighted image; “Gray(IMG)” represents a grayscale image of the captured image; “V” represents the likelihood V; “Red” represents the red color;   “*” represents multiplication; and “.*” represents multiplication per an element.   
     
     
         10 . A method of processing an image in a diagnostic apparatus for diagnosing a disease using a captured image of an affected area, the method comprising:
 converting the captured image from a RGB color space to a Lab color space; and   extracting a region to be a vascular region as a likelihood V from the converted image using the brightness component as a L component and the color information component as a ab component in order to highlight likeness of the area.   
     
     
         11 . The method according to  claim 10 , wherein the region is a vessel-corresponding region. 
     
     
         12 . The method according to  claim 10 , wherein the likeness of the area indicates likeness of a vessel. 
     
     
         13 . The method according to  claim 10 , wherein the extracting comprises combining an extracted result for the region with a background image to generate a reconstructed image. 
     
     
         14 . The method according to  claim 13 , wherein the background image is at least one selected from a group consisting of the captured image, a grayscale image of the captured image, a contrast-highlighted image of the captured image, and a brightness component-highlighted image that is obtained by separating the brightness component of the captured image into a base component and a detail component and performing a highlighting process on the base component and the detail component in a different manner. 
     
     
         15 . The method according to  claim 10 , wherein the likelihood V indicates likeness of a vessel. 
     
     
         16 . The method according to  claim 13 , wherein in the extracting, if a vessel having a plurality of sizes is detected, the likelihood V is determined by an adjustment coefficient  6  corresponding to the size of the vessel, and a maximum V is selected per a pixel. 
     
     
         17 . A non-transitory computer readable medium storing a program for processing an image in a diagnostic apparatus for diagnosing a disease using a captured image of an affected area, the program being executable by a computer of the diagnostic apparatus to perform operations including:
 separating the captured image into a brightness component and a color information component; and   extracting a region to be diagnosed based on the brightness component or the color information component of the captured image to highlight likeness of the region;   wherein the separating comprises converting the captured image from a RGB color space to a Lab color space; and   wherein the extracting extracts a region to be a vascular region as a likelihood V from the converted image using the brightness component as a L component and the color information component as a ab component.