IHC digital preview recognition and organization foreground segmentation method and system

Abstract

The invention discloses an IHC digital preview image identification and organization foreground segmentation method and system, and the method comprises the steps: extracting a binary mask image M1 comprising an organization part and an impurity part for an inputted IHC digital preview image; dividing all connected domains in the binary mask map M1 into a large-area connected domain contour set qband a small-area connected domain contour set qs; and for each connected domain contour in the large-area connected domain contour set qb, corresponding the connected domain contour to a corresponding region in an original IHC digital preview, extracting features of the corresponding region, classifying the features through a machine learning model to remove impurity connected domain contours, and leaving connected domain contours of tissues. According to the method, the tissue foreground can be segmented for the IHC digital preview which is slightly dyed and has the foreground tissue color almost close to the slide background, and the method has the advantages of being high in recognition accuracy and good in 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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