Sysmex Corporation

National Cancer Center

Kanako Masumoto

Kazumi Hakamada

Yuki Aihara

Yosuke Sekiguchi

Kohei Yamada

Krupali Jain

Hiroshi Yoshida

Shigeki Iwanaga

Masaya Okada

Takuya Kubo

The present invention provides an image analysis method for generating data indicating a region of a cell nucleus in an image of a tissue or a cell. The image analysis method is a method for analyzing an image of a tissue or a cell using a deep learning algorithm of a neural network structure, and generates data indicating a region of a cell nucleus in an analysis target image by the deep learning algorithm by generating analysis data from the analysis target image including an analysis target tissue or cell, and inputting the analysis data in the deep learning algorithm.

Image analysis method, apparatus, program, and learned deep learning algorithm

An image analysis method for generating data indicating a tumorigenic state of an image of a tissue or a cell. The image analysis method is an image analysis method for analyzing an image of a tissue or a cell using a deep learning algorithm of a neural network structure, analysis data are generated from the analysis target image including a tissue or cell to be analyzed, the analysis data are input to the deep learning algorithm, and data indicating the tumorigenic state of tissues or cells in the analysis target image are generated by the depth learning algorithm.

Image analysis method, image analysis apparatus, program, learned deep layer learning algorithm manufacturing method and learned deep layer learning algorithm

An image analysis method for analyzing an image of a tissue collected from a subject using a deep learning algorithm of a neural network structure. The image analysis method includes generating analysis data from the analysis target image that includes the tissue to be analyzed, inputting the analysis data to a deep learning algorithm, and generating data indicating a layer structure configuring a tissue in the analysis target image by the deep learning algorithm.

Image analysis method, image analysis apparatus and learned deep layer learning algorithm manufacturing method

Provided is a cell analyzer including: a light source unit configured to apply light to test cells each containing first substances which are bound to first fluorescent dyes and which serve as an index for therapeutic strategy judgement; an image capturing unit configured to capture an image of fluorescence caused by the light; a processing unit configured to process the image obtained by the image capturing unit; and a display unit configured to display a process result obtained by the processing unit, wherein the processing unit obtains a first image by performing an inactivation process of quenching the first fluorescent dyes, an activation process of activating a part of the first fluorescent dyes that have been quenched, and an image capturing process of capturing, by means of the image capturing unit, an image of the fluorescence by applying light from the light source unit to each test cell; extracts bright points based on the first fluorescent dyes on the basis of the first image; classifies the extracted bright points into groups each corresponding to one first substance, thereby to obtain the number of the first substances in the test cell on the basis of the number of the classified groups; obtains therapy index information serving as an index for therapeutic strategy judgement, on the basis of the obtained number of the first substances; and causes the display unit to display the obtained therapy index information.

Cell analyzer, cell analyzer controlling method, and program

Growing community of inventors

Kobe, Japan

Kanako Masumoto