Patent US10650520 AI Biotech/Diagnostics: Cardio

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Patent US10650520

Issued 2020-05-12

Systems And Methods For Training A Statistical Model To Predict Tissue Characteristics For A Pathology Image

In some aspects, the described systems and methods provide for a method for training a statistical model to predict tissue characteristics for a pathology image. The method includes accessing annotated pathology images. Each of the images includes an annotation describing a tissue characteristic category for a portion of the image. A set of training patches and a corresponding set of annotations are defined using an annotated pathology image. Each of the training patches in the set includes values obtained from a respective subset of pixels in the annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels. The statistical model is trained based on the set of training patches and the corresponding set of patch annotations. The trained statistical model is stored on at least one storage device.

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2 Independent Claims

1. A method for training a statistical model to predict tissue characteristics for a pathology image, the method comprising: accessing a plurality of annotated pathology images, each of which includes at least one annotation describing one of a plurality of tissue characteristic categories for a portion of the image; defining a set of training patches and a corresponding set of annotations using the at least one annotated pathology image, wherein each of the training patches in the set includes values obtained from a respective subset of pixels in the at least one annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels; training the statistical model based on the set of training patches and the corresponding set of patch annotations; and storing the trained statistical model on at least one storage device.
17. A system for training a statistical model to predict tissue characteristics for a pathology image, the system comprising: at least one computer hardware processor; and at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform: accessing a plurality of annotated pathology images, each of which includes at least one annotation describing one of a plurality of tissue characteristic categories for a portion of the image; defining a set of training patches and a corresponding set of annotations using the at least one annotated pathology image, wherein each of the training patches in the set includes values obtained from a respective subset of pixels in the at least one annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels; training the statistical model based on the set of training patches and the corresponding set of patch annotations; and storing the trained statistical model on at least one storage device.