Sysmex Corporation

Juntendo Educational Foundation

Yoko Tabe

Konobu Kimura

Koji Tsuchiya

Akimichi Ohsaka

Disclosed is a disease differentiation support method for supporting disease differentiation, the disease differentiation support method including: obtaining a first parameter obtained by analyzing an image including a cell contained in a sample collected from a subject; obtaining a second parameter regarding a number of cells contained in the sample; and generating, by using a computer algorithm, differentiation support information for supporting disease differentiation, on the basis of the first parameter and the second parameter.

Disease differentiation support method, disease differentiation support apparatus, and disease differentiation support computer program

Disclosed is an image analysis method including inputting analysis data, including information regarding an analysis target cell to a deep learning algorithm having a neural network structure, and analyzing an image by calculating, by use of the deep learning algorithm, a probability that the analysis target cell belongs to each of morphology classifications of a plurality of cells belonging to a predetermined cell group.

Image analysis method, apparatus, non-transitory computer readable medium, and deep learning algorithm generation method

Disclosed is a method for supporting disease analysis, the method including classifying, on the basis of images obtained from a plurality of analysis target cells contained in a specimen collected from a subject, a morphology of each analysis target cell, and obtaining cell morphology classification information corresponding to the specimen, on the basis of a result of the classification; and analyzing a disease of the subject by means of a computer algorithm, on the basis of the cell morphology classification information.

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Tokyo, Japan

Yoko Tabe