Automated screening of histopathology tissue samples via analysis of a normal model
AssigneeDeciphex
InventorsMark Gregson, Donal O'Shea
Life of this patent
Estimating the term…
Abstract
Systems and methods are provided for screening histopathology tissue samples. An anomaly detection system is trained on a plurality of training images. Each of the plurality of training images represents a tissue sample that is substantially free of abnormalities. A test image, representing a tissue sample, is provided to the anomaly detection system. A deviation from normal score is generated for at least a portion of the test image. The deviation from normal score represents a degree of abnormality in the tissue sample represented by the test image.
Claims20
A system for screening histopathology tissue samples, comprising:
- a processor;
- and
- a non-transitory computer readable medium storing executable instructions comprising:
- an anomaly detection system trained on a plurality of training images, each of the plurality of training images representing a tissue sample that is substantially free of abnormalities, the anomaly detection system extracting a plurality of features from each of the plurality of training images that includes a set of features derived from a set of multi-scale histograms of color features;
- an image interface that receives a test image and provides the test image to the anomaly detection system, the anomaly detection system generating a deviation from normal score for at least a portion of the test image, the deviation from normal score representing a degree of abnormality in the tissue sample represented by the test image;
- and
- a user interface that provides the deviation score to a user at an associated output device.
A method for evaluating the effect of a therapeutic on an organ of a subject from histopathology tissue samples, the method comprising:
- administering the therapeutic to a subject;
- extracting a tissue sample to be tested from the organ of the subject;
- training an anomaly detection system on a plurality of training images, each of the plurality of training images representing a tissue sample that is substantially free of abnormalities;
- providing a test image, representing the tissue sample to be tested, to the anomaly detection system;
- and
- generating a deviation from normal score for at least a portion of the test image at the anomaly detection system, the deviation from normal score representing a degree of abnormality in the tissue sample represented by the test image.
A method for screening histopathology tissue samples, comprising:
- training an anomaly detection system on a plurality of training images, each of the plurality of training images representing a tissue sample that is substantially free of abnormalities;
- providing a first test image, representing a first tissue sample to be tested, to the anomaly detection system;
- generating a first deviation from normal score for at least a portion of the first test image at the anomaly detection system, the first deviation from normal score representing a degree of abnormality in the tissue sample represented by the first test image, administering a therapeutic to a subject associated with the first tissue sample;
- extracting a second tissue sample from the subject;
- providing a second test image, representing the second tissue sample to be tested, to the anomaly detection system;
- generating a second deviation from normal score for at least a portion of the second test image;
- and
- comparing the second deviation from normal score to the second deviation from normal score to the first deviation from normal score to determine an efficacy of the therapeutic.
Dependencies are inferred from the claim text.