Automatic classification method and system for pathological diagrams of cell and region levels

Abstract

The invention belongs to the field of image analysis, and discloses an automatic classification method and system for pathological diagrams of cell and regional hierarchies, and the method comprises the following steps: (1) cutting an initial pathological diagram into small diagrams, and drawing a cell mask diagram; (2) carrying out image segmentation on the small image to obtain cell coordinates; (3) cutting the initial pathological map into single cell small maps, and judging cell types; (4) cutting the initial pathological diagram into small diagrams, and judging whether the small diagrams belong to a cancerous region and a para-cancerous region or not; (5) cutting the initial pathological diagram into small diagrams, and respectively judging whether the small diagrams belong to a tumor tissue parenchyma region, a mesenchymal region, a protein keratinization region and a vessel region or not; (6) integrating the scores, and determining the cell type and the belonging region thereof. According to the method, the overall process processing of the method is improved, so that the defect that the analysis of the pathological diagram stays in block type analysis in the prior art can be overcome, the information of the pathological diagram is deeply mined, and therefore, the automatic classification of the pathological diagram is realized.

Description

technical field [0001] The invention belongs to the field of image analysis, and more specifically relates to a method and system for automatically classifying pathological maps at cell and region levels. Background technique [0002] Pathological maps often contain a lot of information. The macroscopic situation of cancer development can be identified through clinical index detection, X-ray and other methods, but it is difficult to determine more detailed information, so it is impossible to refine and individualize the classification and treatment of patients. The current pathological image analysis and classification methods are mainly concentrated at the block level, lacking analysis and classification at the cell level and physiological regions. Contents of the invention [0003] In view of the above defects or improvement needs of the prior art, the purpose of the present invention is to provide a method and system for automatic classification of pathological maps at...

AI Technical Summary

Problems solved by technology

The macroscopic situation of cancer development can be identified through clinical index detection, X-ray and other methods, but it is difficult to determine more detailed information, so it is impossible to refine and individualize the classification and treatment of patients

The current pathological image analysis and classification methods are mainly concentrated at the block level, lacking analysis and classification at the cell level and physiological regions

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