There are provided a medical image processing apparatus, an endoscope system, a diagnosis assistance method, and a program capable of coping with an erroneous determination while utilizing an observation completion determination in which image processing is used and of suppressing oversight of an observation target part by a doctor. The medical image processing apparatus includes at least one processor. The at least one processor acquires a medical image; makes, on the basis of the medical image, an observation completion determination as to whether observation is completed for a target part; performs display control for causing a determined result of the observation completion determination to be displayed on a display device, receives a user input including an instruction for correcting display content indicating the determined result of the observation completion determination, and causes corrected content based on the user input to be reflected in the display.

A processor for an endoscope includes an image processing unit that obtains a severity of a lesion in which a degree of progression is represented by one value, wherein the image processing unit includes a feature amount calculation unit configured to calculate a first pixel evaluation value indicating a degree of a first feature of appearance appearing in a lesion part, a representative value calculation unit configured to calculate a first representative evaluation value by integrating the first pixel evaluation values, and an integration unit configured to adjust an influence degree of the first representative evaluation value indicating a change in the severity with respect to a change in the first representative evaluation value based on information on a color component of an image, and calculate the severity of the lesion based on at least the first representative evaluation value by using the adjusted influence degree.

A gastroscopic image diagnosis supporting system is configured to analyze a video frame of the gastroscopic image using a first medical image analysis model of the medical image analysis models; classify a gastrointestinal anatomical position of the video frame by identifying a part corresponding to a preset gastrointestinal anatomical position class in the video frame; and store information about the gastrointestinal anatomical position of the video frame as index information of the finding information together with finding information when a user captures and stores the video frame as the finding information about a gastrointestinal lesion.

An image processing device 1X includes a three-dimensional reconstruction means 31X, a matching means 32X, and an output control means 33X. The three-dimensional reconstruction means 31X generates reconstruction data Mr acquired by three-dimensionally reconstructing an inspection target on a basis of captured images Ic which a photographing unit provided in an endoscope generates by photographing the inspection target. The matching means 32X performs matching between a standard model “Ms”, which is a standard three-dimensional model of the inspection target, and the reconstruction data Mr. The output control means 33X displays on a display device 2X a photographed area indication image indicating a photographed area of the inspection target on the standard model based on a result of the matching.

A physical abdominal surgical simulation system including an abdominal model mimicking the biomechanical properties and response of a patient specific abdomen and an image acquisition and analysis system. The abdominal model includes an abdominal wall model insert forming a frame of the abdominal model, an abdominal wall member secured to the abdominal wall model insert, a back member secured to the abdominal wall model insert in opposed relation with respect to the abdominal wall member, and an abdominal model cavity defined within abdominal wall model insert, the abdominal wall member, and the back member. The image acquisition and analysis system includes a plurality of cameras configured to capture images of the abdominal model cavity.

Methods of generating a metric to quantitatively represent an effect of a treatment are disclosed. In one arrangement, first and second sample data units are received, each representing a segmented image of a biological sample taken from a subject. The segmentation divides the image into plural segmentation sets of regions. Each of the first and second sample data units is analysed to determine information about a spatial distribution of biomarkers relative to the segmentation sets. A metric is generated using a combination of the determined information about the spatial distribution of biomarkers relative to the segmentation sets for the first and second sample data units.

A parasite analysis system includes a pressure vessel configured to store a biological sample, an imaging cell connected to the pressure vessel, and a waste depository connected to the imaging cell. An input valve controls whether biological sample can flow from the pressure vessel into the imaging cell and an output valve controls whether biological sample can flow from the imaging cell into the waste depository. The parasite analysis system also includes a camera that captures a chronological set of images of a portion of the biological sample in the imaging cell and an image analysis system that analyzes the chronological set of images to generate an estimate of a number of parasites in the portion of the biological sample. Estimates for multiple portions of the biological sample may be generated and sampling techniques used to estimate the number of parasites in the entire biological sample.

Example embodiments of the present invention relate to an image processing apparatus. The apparatus may include a processor and memory storing instructions that when executed on the processor cause the processor to perform the operations of detecting a deep region of a duct in an image and extracting a plurality of contour edges of an inner wall of the duct in the image. The apparatus then may identify a plurality of convex regions among the plurality of contour edges, analyze a respective curvature of each of the plurality of convex regions to identify a convex direction for each of the plurality of convex regions, and detect, as an abnormal region, a convex region having a convex direction directed toward the deep region.

First RGB image signals are inputted. A first B/G ratio and a first G/R ratio are calculated. The first B/G ratio and the first G/R ratio are converted into a second B/G ratio and a second G/R ratio, respectively, through a color information conversion process. Owing to the color information conversion process, a difference between first and second observation areas in a second signal ratio space formed by the second B/G ratio and the second G/R ratio is greater than a difference between the first and second observation areas in a first signal ratio space formed by the first B/G ratio and the first G/R ratio, and a difference between the first and third observation areas in the second signal ratio space is greater than a difference between the first and third observation areas in the first signal ratio space.

An embodiment in accordance with the present invention provides concurrent measurement of motion during T2-weighted magnetic resonance imaging. The present invention combines T2 preparation, a module used to impart T2 contrast, and motion measurement, tracking, and/or correction. The present invention provides for the expedition of more efficient motion compensation during T2-weighted imaging. The proposed invention can be used to provide a variety of measurements of motion, with no overhead in imaging time. The proposed invention also enables T2 contrast imaging to be executed while a subject is breathing freely, without the additional time cost associated with the standard motion tracking methodologies.