A method and system for identifying and organizing foreground segmentation of IHC digital preview images

Abstract

The invention discloses a method and system for IHC digital preview image recognition and tissue foreground segmentation. The invention includes extracting a binary mask image M1 including tissue parts and impurity parts from an input IHC digital preview image; All connected domains in Figure M1 are divided into large-area connected domain contour sets q b and the set of small-area connected domain contours q s ;For large-area connected domain contour collection q b For each connected domain outline in , it is corresponding to the corresponding area in the original IHC digital preview image, the features of the corresponding area are extracted and the features are classified by the machine learning model to remove the connected domain outline of impurities and leave the connected domain outline of the organization . The invention can segment the foreground of the tissue from the IHC digital preview image with very light staining and the color of the foreground tissue is almost close to the background of the glass slide, and has the advantages of high recognition accuracy and good recognition effect.

Description

technical field [0001] The invention relates to the field of digital image processing, the field of biomedical engineering technology and the field of micropathological imaging, in particular to an IHC digital preview image recognition and tissue foreground segmentation method and system. Background technique [0002] In order to automatically scan the entire process of digital slides, minimize the travel of the scanner’s stage, and shorten the entire scanning time, the primary task of the scanner is to complete the preview and range confirmation of the tissue on the slide, and reduce the number of blank areas added to the slide. During the scanning process; this requires that the real tissue area should be identified as completely as possible, and the interference of artifacts caused by other impurities should be removed; therefore, the primary task of a digital slide scanner is to accurately preview and identify digital slides. Very important; for HE-stained digital slides...

AI Technical Summary

Problems solved by technology

[0003] The tissue presented by immunohistochemically stained digital slides is inconsistent with other digital slides; immunohistochemical staining is very light, and in many cases the color of the foreground tissue is almost close to the background of the slide, and many impurities are presented. All aspects of the color are basically consistent with the scene tissue, which makes it difficult to extract satisfactory results with general image processing methods. The conventional recognition process is either easy to process other impurities into the scene tissue, or it is the real tissue The foreground recognition is incomplete, and it is difficult to obtain effective recognition results

This shows that the traditional simple image processing is ineffective for the processing of immunohistochemical digital slides, and a more breakthrough thinking method is needed

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