Nec Corporation

Keio University

Tomoharu Kiyuna

Yoshiko Yoshihara

Akira Saito

Kenichi Kamijo

Maki Sano

Kenji Okajima

Toshimasa Yamazaki

Tomofumi Hiratsuka

Tetsuji Tanigawa

Keiichi Yoshida

Kimiyasu Takoh

Atsushi Marugame

Ikuma Takahashi

Masahiko Kuroda

Michiie Sakamoto

Akinori Hashiguchi

Akira Saitou

Tokiya Abe

Hiroaki Torii

Ken Yamazaki

Kenichi Kamijyo

Yoshikazu Kitamura

Ken' Ichi Kamijo

Kiyoshi Mukai

Maki Ogura

Kamjio Ken'Ichi

The acquisition unitB acquires a target image indicating a target object of inspection. The detection unitB detects, on the basis of a group of images each of which indicates the target object in a normal state, the target image that indicates the target object that is not in the normal state among the target images that the acquisition unitB acquires.

Inspection device, inspection method and storage medium

The present invention provides an information processing apparatus capable of accurately separating parenchymal cells and stromal cells from each other regardless of the staining intensity of the cells. The information processing apparatus is an information processing apparatusincluding: an image processing unitfor smoothing a tissue sample imageobtained by staining and then imaging a biological tissue containing parenchymal cellsand stromal cellsso that luminance values of cell components of each of the parenchymal cellsbecome less than those of each of the stromal cells; and a mask generation unitfor generating, through generating a binary image by binarizing the tissue sample imagesmoothed by the image processing unit, a maskfor removing a region of the stromal cells from the tissue sample image

Information processing apparatus, information processing system, information processing method, program, and recording medium

An image acquisition unit () acquires an analysis image. The analysis image is an image in which a plurality of cell nuclei in a lesion of a target person are captured. A feature-value calculation unit () calculates the feature-value relating to the cell nuclei from the analysis image. An evaluation function acquisition unit () acquires an evaluation function from an evaluation function storage unit (). The evaluation function is a function with which prediction information is calculated based on the feature-value. The prediction information generation unit () generates prediction information relating to a target person based on a feature-value, which has been calculated from an analysis image, and an evaluation function which has been acquired by the evaluation function acquisition unit (). The prediction information is information indicating a prediction of a prognosis of a disease of the target person or a prediction of malignancy of a disease of the target person.

Disease analysis apparatus, control method, and program

The present invention provides an information processing apparatus capable of selecting a region of cancer cells in any tissue sample image and easily and accurately counting the number of the cancer cells. The information processing apparatus is an information processing apparatusincluding: an acquisition unitfor acquiring image data obtained by reading a tissue sample imageobtained by putting a markspecifying a selected areaon an image obtained by immunostaining and then imaging a biological tissue; and a counting unitfor counting the number of cancer cells in the selected areaspecified by the markbased on the image data of the tissue sample imageacquired by the acquisition unit, wherein a diagnosis based on the tissue sample imageis supported.

A image input meansinputs a lifeform image which is a captured image of a lifeform sample. A structure standard color storage meansstores a standard color of a structure included in the lifeform image. A structure extraction meansextracts a target structure from the lifeform image. A structure color computation meanscomputes, from an image of the structure extracted by the structure extraction means, a color of the structure. A color distribution conversion meansconverts a color distribution of the input lifeform image so that a difference between the color of the structure computed by the structure color computation meansand the standard color of the corresponding structure stored in the structure standard color storage meansis reduced.

Lifeform image analysis system, lifeform image analysis method, and lifeform image analysis program

The invention is directed to a reduction in the influence on a pathological diagnosis when an image reading apparatus is exchanged. In order to solve the above-mentioned problem, there is provided an image processing apparatus that processes a biological image generated by capturing an image of a biological specimen in an image reading apparatus, including: an acquisition unit that acquires identification information of the image reading apparatus; a determination unit that determines a type of biological tissue included in the biological image; and a correction unit that adds a correction process to the biological image in correspondence with the identification information of the image reading apparatus and the type of biological tissue.

Image processing apparatus, image reading apparatus, image processing method and information storage medium

This invention relates to an information processing apparatus which assists diagnosis based on a tissue sample image obtained by staining and capturing a tissue. The information processing apparatus receives and analyzes lower magnification image data among a plurality of image data obtained at different magnifications for an area image selected in the tissue sample image. Based on the analysis result, the information processing apparatus determines whether analysis based on higher magnification image data is necessary. When analysis based on the higher magnification image data is necessary, the information processing apparatus notifies a request of transmitting the higher magnification image data for the area image, receives and analyzes the higher magnification image data transmitted in response to the transmission request, and transmits the analysis result. This arrangement can quickly provide high-accuracy diagnosis assistance for a tissue sample image from a pathologist regardless of the restriction of the transmission capacity.

Information processing system, information processing method, information processing apparatus, control method therefor, and storage medium storing control program therefor

Information processing apparatus, method, and storage medium for assisting with a diagnosis based on a tissue sample

Information processing apparatus, information processing system, information processing method, program and recording medium

A spot quantification apparatus includes an image input unit, a filtering unit, and a spot quantification unit. The image input unit receives an image including a spot. The filtering unit filters the image input through the image input unit a plurality of times while changing a parameter of a kernel within a predetermined range. The spot quantification unit quantifies a feature of the spot based on the luminance distribution in each image which has been filtered a plurality of times by the filtering unit.

Spot quantification apparatus, spot quantification method, and recording medium

A cell feature amount calculating apparatus is provided that is capable of capturing the state of nuclear DNA. This cell feature amount calculating apparatus includes an image input unit that inputs an image of a cell, a cell nucleus region extracting unit that extracts a cell nucleus region of the cell from the image, a standard contour length calculating unit that calculates a standard contour length of the cell nucleus region, a contour length sequence calculating unit that extracts, for each threshold value of a plurality of different threshold values, a specific region which is a region having a pixel value larger than or equal to the threshold value from the cell nucleus region and calculating a contour length sequence by calculating a contour length of the specific region, and a contour complexity calculating unit that calculates a feature amount of the cell based on the standard contour length and the contour length sequence.

Cell feature amount calculating apparatus and cell feature amount calculating method

A pathological tissue image capturing system includes a pathological image acquirerfor capturing a pathological tissue image and an output devicefor outputting the pathological tissue image. The pathological tissue image capturing system also includes a weighting devicefor detecting a ROI from the pathological tissue image and adding a weight to pixels positioned in the ROI, and a range selectorfor selecting an enlarged image capturing range in which to capture the pathological tissue image at an enlarged scale based on the weight added by the weighting device. The pathological image acquirercaptures an enlarged pathological tissue image in the enlarged image capturing range selected by the range selector. The output deviceoutputs the captured enlarged pathological tissue image in the enlarged image capturing range.

Pathological tissue image capturing system, method, and program

A method of evaluating a cell state based on information of an image taken of a cell containing a chromosome territory is provided. This method includes extracting the chromosome territory from the image (S), standardizing a positioning state of the chromosome territory and then quantifying the positioning state (S), and evaluating the cell state based on the quantified positioning state of the chromosome territory (S).

Method of evaluating chromosome state and evaluation system

A pathological diagnosis support device, a pathological diagnosis support program, a pathological diagnosis support method, and a pathological diagnosis support system extract a pathological tissue for diagnosis from a pathological image and diagnose the pathological tissue. A tissue collected in a pathological inspection is stained using, for example, hematoxylin and eosin. In consideration of the state of the tissue in which a cell nucleus and its peripheral constituent items are stained in respective colors unique thereto, subimages such as a cell nucleus, a pore, cytoplasm, interstitium are extracted from the pathological image, and color information of the cell nucleus is also extracted. The subimages and the color information are stored as feature candidates so that presence or absence of a tumor and benignity or malignity of the tumor are determined.

Pathological diagnosis support device, program, method, and system

The picture region extraction method coarse-grains this picture data space, calculates a coarse-grained empirical probability distribution, initializes parameters, calculates a coarse-grained conditional probability distribution and a class membership probability, updates the parameters, and calculates an evaluation function, each process being repeated until there is no change in the evaluation function, at which point, a picture region is extracted based on the class membership probability.

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Tokyo, Japan

Tomoharu Kiyuna