Systems and methods for using image processing to generate inferences of biomarker for immunotherapy
AssigneeVerily Life Sciences LLC
InventorsCory Batenchuk, Huang-Wei Chang, Peter Cimermancic, Kimary Kulig, Graziella Solinas
Life of this patent
Estimating the term…
Abstract
Methods and systems are disclosed for image process biological samples to infer biomarker values. An image of a biological sample can be accessed. The image can be segmented into a set of patches. Edge detection performed on each patch can be used to identify one or more biological features represented by the patch. An indication of the one or more features of each patch may be used to generate one or more image level metrics. A value of a biomarker may be inferred using the one or more image level metrics. The value of the biomarker can then be output.
Claims18
A computer-implemented method comprising:
- accessing a microscopic image of at least part of a biological sample;
- detecting one or more portions of the microscopic image that correspond to the biological sample;
- identifying, for each portion of the one or more portions of the microscopic image, a biological feature of a set of possible biological features that is represented by the portion by:
- detecting one or more edges within the portion based on differences in pixel intensities between adjacent pixels;
- and
- identifying the biological feature based on the detected edges;
- generating one or more image level metrics based on the biological features from the one or more portions of the microscopic image;
- inferring a value of a biomarker represented in the biological sample based on the one or more image level metrics, wherein the value of the biomarker is associated with cancer;
- assigning, based on the biomarker, a weight to each identified biological feature, wherein inferring the value of the biomarker represented in the biological sample is further based on the weight assigned to each identified biological feature;
- and
- outputting the value of the biomarker.
A system comprising:
- one or more processors;
- and
- a non-transitory computer-readable medium including instructions, which when executed by the one or more processors, cause the one or more processors to:
- access a microscopic image of at least part of a biological sample;
- detect one or more portions of the microscopic image that correspond to the biological sample;
- identify for each portion of the one or more portions of the microscopic image, a biological feature of a set of possible biological features that is represented by the portion by:
- detect one or more edges within the portion based on differences in pixel intensities between adjacent pixels;
- and
- identify the biological feature based on the detected edges;
- generate one or more image level metrics based on the biological features from the one or more portions of the microscopic image;
- infer a value of a biomarker represented in the biological sample based on the one or more image level metrics, wherein the value of the biomarker is associated with cancer;
- assign, based on the biomarker, a weight to each identified biological feature, wherein inferring the value of the biomarker represented in the biological sample is further based on the weight assigned to each identified biological feature;
- and
- output the value of the biomarker.
A non-transitory computer-readable medium including instructions, which when executed by one or more processors, cause the one or more processors to perform operations including:
- accessing a microscopic image of at least part of a biological sample;
- detecting one or more portions of the microscopic image that correspond to the biological sample;
- identifying, for each portion of the one or more portions of the microscopic image, a biological feature of a set of possible biological features that is represented by the portion by:
- detecting one or more edges within the portion based on differences in pixel intensities between adjacent pixels;
- and
- identifying the biological feature based on the detected edges;
- generating one or more image level metrics based on the biological features from the one or more portions of the microscopic image;
- inferring a value of a biomarker represented in the biological sample based on the one or more image level metrics, wherein the value of the biomarker is associated with cancer;
- assigning, based on the biomarker, a weight to each identified biological feature, wherein inferring the value of the biomarker represented in the biological sample is further based on the weight assigned to each identified biological feature;
- and
- outputting the value of the biomarker.
Dependencies are inferred from the claim text.