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DEEP IMAGE CLASSIFICATION OF MEDICAL IMAGES

  • US 20190318822A1
  • Filed: 04/13/2018
  • Published: 10/17/2019
  • Est. Priority Date: 04/13/2018
  • Status: Active Grant
First Claim
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1. A computer implemented method for improving classification of a medical image comprising:

  • extracting, by a processor, a plurality of samples from the medical image, wherein the plurality of samples includes;

    i) at least one image sample with a normal portion of organic matter and ii) at least one image sample with an abnormal portion of organic matter; and

    training a focus-learning function for an image analysis component with the plurality of samples by;

    comparing a first classification made by the image analysis component as to at least one of;

    i) the at least one normal image sample, and ii) the at least one abnormal image sample, to at least one annotation associated with at least one of;

    i) the at least one normal image sample, and ii) the at least one abnormal image sample;

    determining that the classification was erroneous based on the annotation; and

    updating the focus-learning function to reflect a correct classification of at least one of the i) the normal image sample and ii) the abnormal image sample based on the determination that the classification was erroneous.

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