Tissue object-based machine learning system for automated scoring of digital whole slides

Tissue object-based machine learning system for automated scoring of digital whole slides

  • CN 105,027,165 A
  • Filed: 03/12/2014
  • Published: 11/04/2015
  • Est. Priority Date: 03/15/2013
  • Status: Active Application
First Claim
Patent Images

1. a method for the complete slide glass explanation of the digitized image for organising data performed by the computing system comprising processor, described method comprises:

  • Multiple digitized images of tissue receiving sample, each tissue samples corresponds to slide glass as true as a die;

    At least one association with digitized image for each reception in described multiple digitized image is classified;

    The digitized image received of using-system sample is to train organization object sorter;

    Receive the digitized image of data associated with the first slide glass, wherein the first slide glass is not slide glass as true as a die;

    Automatically identify the tissue in the digitized image of the data associated with the first slide glass;

    Identify or estimate all in-house leading dye color identified in complete first slide glass;

    Receive the instruction of the in-house multiple comment field identified in complete first slide glass;

    AndFor each in described multiple comment field,Detect the core Seed Points in comment field,Object is extracted from comment field at least in part based on the core Seed Points detected and the leading dye color estimated in complete first slide glass,For the object that each extracts,Local feature is calculated at least in part based on comment field and complete slide glass situation,Global characteristics is calculated at least in part based on annotating images region and complete slide glass situation,Based on the characteristic sum calculated housebroken organization object sorter, object is classified at least in part.

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