Olympus Corporation

Oita University

Fukuoka Institute of Technology

Toshiya Kamiyama

Makoto Kitamura

Yamato Kanda

Takashi Kono

Masashi Hirota

Katsuyoshi Taniguchi

Hirokazu Godo

Mitsutaka Kimura

Makoto Ishikake

Yusuke Matsunobu

Tatsushi Tokuyasu

Makoto Nakashima

Yukio Iwashita

Tsuyoshi Etoh

Masafumi Inomata

An endoscope diagnosis support system includes a processor. The processor performs detection of an anomaly candidate area from an endoscope image obtained by performing image pickup of an inside of a subject to obtain a detection result, and generates a display image in which an indicator indicating detection of the anomaly candidate area is arranged in a periphery portion of the endoscope image in accordance with the detection result.

Endoscope diagnosis support system, storage medium, and endoscope diagnosis support method

An information processing system includes a storage device that stores therein a trained model, and a processor. The trained model is trained to output a position and shape of an object in a training image based on training data. The training data is data in which the training image is provided with an annotation indicating the position and shape of the object. The training image is an image captured with an angle of view including the object whose position and shape are not clearly displayed in an image. The processor executes detection processing on a detection image to output detected information indicating the position and shape of the object. The processor then causes a display device to display the detected information superimposed on the detection image.

Information processing system, endoscope system, information storage medium, and information processing method

An information processing system includes a storage device configured to store therein information of a trained model, and a processor. The processor performs a detection process based on the information of the trained model, and outputs position information detected in the detection process, the detection process being a process that detects the position information about an object from a detection image. The trained model is trained based on training data in which an object in a training image is added with multiple annotations, and is trained to output position information about the object in the training image based on an overlapping relationship of the multiple annotations.

A diagnosis support apparatus performs identification for a plurality of support items, which are identification classifications about diagnosis support, and the diagnosis support apparatus is provided with a processor. The processor performs analysis processing for acquiring analysis results including an analysis result about an observation mode by analyzing at least one of an input signal specifying the observation mode and an observation image obtained by observing an inside of a subject with an endoscope; performs support item setting processing for setting a support item corresponding to the analysis results obtained by the analysis processing, among the plurality of support items, which are the identification classifications; and generates diagnosis support information, which is information used for diagnosis of a legion candidate area included in the observation image, based on an identification index corresponding to the set support item and the observation image.

Diagnosis support apparatus, diagnosis support method and computer-readable non-transitory storage medium for storing program

An image processing device includes: an abnormality candidate region detection unit configured to detect, from an intraluminal image obtained by imaging a living body lumen, an abnormality candidate region in which a tissue characteristic of the living body or an in-vivo state satisfies a predetermined condition; a feature data calculation unit configured to calculate, from each of a plurality of regions inside the intraluminal image, a plurality of pieces of feature data including different kinds; an integrated feature data calculation unit configured to calculate integrated feature data by integrating the plurality of pieces of feature data based on information of the abnormality candidate region; and a detection unit configured to detect an abnormality from the intraluminal image by using the integrated feature data.

Image processing device, image processing method, and computer-readable recording medium for detecting abnormality from intraluminal image using integrated feature data

An image processing apparatus includes: a candidate region detection unit configured to detect, from an image acquired by imaging inside a lumen of a living body, a candidate region for a specific region that is a region where a specific part in the lumen has been captured; a candidate region information acquiring unit configured to acquire information related to the candidate region detected by the candidate region detection unit; an identification means determination unit configured to determine an identification means for identification of, based on the information related to the candidate region, whether or not the candidate region is the specific region; and an identification unit configured to identify whether or not the candidate region is the specific region by using the identification means determined by the identification means determination unit.

Image processing apparatus, image processing method, and computer-readable recording medium

A processing device includes a processor including hardware. The processor is configured to implement an image acquisition process of acquiring a tissue image obtained by capturing an image of a tissue and a process of determining a property of the tissue image acquired, and setting a plurality of identification criteria for identifying a state of the tissue as a normal state or an abnormal state, based on the tissue image and the property of the tissue image.

Processing device, processing method, and information storage device

An image processing device includes: a specific candidate area extracting unit configured to extract a specific candidate area that satisfies a predetermined condition from an intraluminal image captured inside a body lumen; a reference area setting unit configured to set a reference area that includes at least a part of the specific candidate area; a local area extracting unit configured to extract local areas based on the reference area; a local feature data calculator configured to calculate local feature data that is feature data of each of the local areas; a weight setting unit configured to set a weight depending on each of the local areas based on the specific candidate area; and a feature data integrating unit configured to integrate the local feature data.

Image processing device, image processing method, and computer-readable recording medium

An image processing apparatus includes: a detecting unit that detects regions of interest that are estimated as an object to be detected, from a group of a series of images acquired by sequentially imaging a lumen of a living body, and to extract images of interest including the regions of interest; a neighborhood range setting unit that sets, as a time-series neighborhood range, a neighborhood range of the images of interest in the group of the series of images arranged in time series so as to be wider than an interval between images that are continuous in time series in the group of the series of images; an image-of-interest group extracting unit that extracts an image-of-interest group including identical regions of interest from the extracted images of interest, based on the time-series neighborhood range; and a representative-image extracting unit that extracts a representative image from the image-of-interest group.

An image processing apparatus for processing an image acquired by imaging a living body includes: a blood vessel candidate region extraction unit configured to extract a plurality of blood vessel candidate regions from the image; an identical blood vessel candidate region extraction unit configured to extract, from among the plurality of blood vessel candidate regions, a blood vessel candidate region group estimated to form a line shape when integrated, as an identical blood vessel candidate region; an evaluation value calculation unit configured to calculate one or more kinds of evaluation values for evaluating a likelihood that the identical blood vessel candidate region corresponds to an identical blood vessel; and a blood vessel region discrimination unit configured to discriminate whether or not the identical blood vessel candidate region forms an identical blood vessel region, based on the evaluation values.

An image processing apparatus includes: an imaging distance estimating unit configured to estimate an imaging distance to a subject shown in an image; an examination region setting unit configured to set an examination region in the image such that an index indicating a spread of a distribution of imaging distances to the subject shown in the examination region is within a given range; and an abnormal structure identifying unit configured to identify whether or not a microstructure of the subject shown in the examination region is abnormal, by using texture feature data that enables identification of an abnormality in the microstructure of the subject shown in the examination region, the texture feature data being specified according the examination region.

Image processing apparatus for identifying whether or not microstructure in set examination region is abnormal, image processing method, and computer-readable recording device

An image processing apparatus includes: a region-of-interest setting unit configured to set a region of interest in an image; a linear convex region extracting unit configured to extract, from the region of interest, a linear region having a predetermined number or more of continuously-arranged pixels whose pixel values are higher than pixel values of neighboring pixels; an intra-region curvature feature data computing unit configured to compute curvature feature data based on curvatures of one or more arcs along the linear region; and an abnormality determining unit configured to determine whether there is an abnormal portion in the region of interest, based on a distribution of the curvature feature data.

An image processing apparatus processes an image obtained by capturing inside of a lumen of a living body. The image processing apparatus includes: a contour edge region extracting unit configured to extract a contour edge region of an examination target from the image; an examination region setting unit configured to set an examination region in the image so as not to include the contour edge region; and an abnormal structure identifying unit configured to identify whether a microstructure of a surface of the examination target is abnormal, based on texture information of the examination region.

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Hachioji, Japan

Toshiya Kamiyama