Medical image processing apparatus, luminal image processing apparatus, luminal image processing method, and programs for the same

Abstract

There is provided a medical image processing apparatus including an image-extracting section extracting a frame image from in vivo motion picture data picked up by an in vivo image pickup device or a plurality of consecutively picked-up still image data, and an image analysis section analyzing the frame image extracted by the image-extracting section to output an image analysis result. The image analysis section includes a first biological-feature detection section detecting a first biological feature, a second biological-feature detection section detecting, based on a detection result obtained by the first biological feature detection section, a second biological feature in a frame image picked up temporally before or after the image used for detection by the first biological feature detection section; and a condition determination section making a determination for a biological condition based on a detection result obtained by the second biological feature detection section to output the determination.

1 . A luminal image processing apparatus comprising:
 a feature value calculating section that calculates a predetermined feature value by executing image processing on one or a plurality of intraluminal images obtained by picking up an image of the gastrointestinal tract; and   a boundary detection section that detects a boundary of the gastrointestinal tract on the basis of the calculated feature value.   
     
     
         2 . The luminal image processing apparatus according to  claim 1 , further comprising a determination section that determines that the intraluminal image shows a part extending from the esophagus to the cardia, on the basis of a detection result obtained by the boundary detection portion. 
     
     
         3 . The luminal image processing apparatus according to  claim 1 , wherein the predetermined feature value is a color tone of the one or plurality of intraluminal images. 
     
     
         4 . The luminal image processing apparatus according to  claim 1 , wherein the predetermined feature value is a brightness of the one or plurality of intraluminal images. 
     
     
         5 . The luminal image processing apparatus according to  claim 1 , wherein the boundary is the EG junction. 
     
     
         6 . The luminal image processing apparatus according to  claim 1 , wherein the feature value calculation section calculates the feature value for pixels in the one or plurality of intraluminal images other than dark portion pixels and halation pixels. 
     
     
         7 . The luminal image processing apparatus according to  claim 1 , wherein if the predetermined feature value is calculated from the plurality of intraluminal images, the determination section determines that the image shows the boundary when a differential value of moving average of the calculated predetermined feature values is at least a predetermined threshold. 
     
     
         8 . The luminal image processing apparatus according to  claim 1 , wherein the feature value calculation section executes image processing on pixels in a predetermined region in each of the one or plurality of intraluminal images to calculate the predetermined feature value. 
     
     
         9 . The luminal image processing apparatus according to  claim 1 , wherein the predetermined feature value is an area of a dark portion region or a non-dark portion region in the one or plurality of intraluminal images. 
     
     
         10 . The luminal image processing apparatus according to  claim 9 , wherein
 the boundary is the open cardia, and   the boundary detection section detects the boundary by comparing the area with a predetermined threshold.   
     
     
         11 . The luminal image processing apparatus according to  claim 1 , wherein the predetermined feature value is a shape of the dark portion region in the one or plurality of intraluminal images. 
     
     
         12 . The luminal image processing apparatus according to  claim 11 , wherein the boundary detection section detects the boundary depending on whether or not the shape is a circle. 
     
     
         13 . The luminal image processing apparatus according to  claim 11 , wherein
 the shape of the dark portion region includes a shape of a boundary of the dark portion region and an edge portion, and   the boundary detection section detects the boundary by comparing a coincidence between the boundary and the edge portion with a predetermined threshold.   
     
     
         14 . The luminal image processing apparatus according to  claim 11 , wherein
 the shape of the dark portion region includes the edge portion of the dark portion region, and   the boundary detection section detects the boundary by comparing a rate at which the edge portion is present around a predetermined point in the dark portion region, with a predetermined threshold.   
     
     
         15 . The luminal image processing apparatus according to  claim 14 , wherein the boundary detection section determines the rate on the basis of whether or not the edge portion is present in a plurality of predetermined areas in each of the one or plurality of intraluminal images. 
     
     
         16 . The luminal image processing apparatus according to  claim 14 , wherein the boundary detection section determines the rate on the basis of an angular range in which the edge portion is present around a predetermined point in the dark potion region. 
     
     
         17 . The luminal image processing apparatus according to  claim 1 , wherein the predetermined feature value is an area of the dark portion region in the one or plurality of intraluminal images. 
     
     
         18 . The luminal image processing apparatus according to  claim 9 , wherein
 the boundary is the closed cardia, and   the boundary detection section detects the boundary by comparing the area with a predetermined threshold.   
     
     
         19 . The luminal image processing apparatus according to  claim 18 , wherein the boundary detection section detects the boundary by executing a labeling process to label a plurality of regions of a dark portion pixel in each of the one or plurality of intraluminal images and determining whether or not an area of one of the labeled plurality of regions which has the largest area is smaller than the predetermined threshold. 
     
     
         20 . The luminal image processing apparatus according to  claim 1 , wherein the boundary detection section detects the boundary by executing a thinning process on the dark portion pixel in each of the one or plurality of intraluminal images, calculating branching or intersecting points on each segment obtained by the thinning process, and executing the detection on the basis of a concentration level of the branching or intersecting points in each of the images. 
     
     
         21 . The luminal image processing apparatus according to  claim 20 , wherein
 the boundary is the closed cardia, and   the boundary detection section detects the boundary by comparing the concentration level with a predetermined threshold.   
     
     
         22 . A luminal image processing method comprising:
 a step of calculating a predetermined feature value by executing image processing on one or a plurality of intraluminal images obtained by picking up an image of the gastrointestinal tract; and   a step of detecting a boundary of the gastrointestinal tract on the basis of the calculated feature value.   
     
     
         23 . A program embodied on non-transitory computer-readable medium allowing a computer to execute:
 a function of calculating a predetermined feature value from one or a plurality of intraluminal images obtained by picking up an image of the gastrointestinal tract; and   a function of detecting a boundary of the gastrointestinal tract on the basis of the calculated feature value.