Method for training an artificial intelligence system, method for recognizing and classifying cells for pathological cell and tissue examination, classifying system, computer-readable medium

A method for training an artificial intelligence system and for recognizing and classifying cells for histopathological tissue examination, under use of the artificial intelligence system, wherein in a learning stage, the method comprises the steps of:

• a) manual marking of cells to be detected by the artificial intelligence system in digital images of histological tissue sections,
• b) each marking is assigned to either one of at least one tumor cell class or one of at least one non-tumor cell class,
• c) a number of marked digital images according to steps a) and b) are entered into the artificial intelligence system for deep learning purposes,
• d) the artificial intelligence system learns characteristics of the at least one tumor cell class and the at least one non-tumor cell class from the marked digital images, to establish a model for cell detection and classification,
• in an analysis stage, the following steps are performed:
• e) obtaining digital images of histological tissue sections,
• f) according to the model, the artificial intelligence system detects the cells and classifies them into the at least one tumor cell class and/or the at least one non-tumor cell class.

A method for recognizing and classifying cells for histopathological tissue examination, the method comprising steps of:

• obtaining digital images of histological tissue sections,
• according to a model, an artificial intelligence system detects the cells and classifies them into at least one tumor cell class and/or at least one non-tumor cell class, the model established by the following steps:
• manual marking of cells to be detected by the artificial intelligence system in digital images of histological tissue sections, each marking is assigned to either one of the at least one tumor cell class or one of the at least one non-tumor cell class,
• a number of the marked digital images entered into the artificial intelligence system for deep learning purposes,
• the artificial intelligence system learning characteristics of the at least one tumor cell class and the at least one non-tumor cell class from the marked digital images to establish a model for cell detection and classification.