Machine learning-based automated abnormality detection in medical images and presentation thereof
AssigneeArterys Inc.
InventorsMatthew Joseph DiDonato, Daniel Irving Golden, John Axerio-Cilies, Taryn Nicole Heilman
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Abstract
The presently disclosed technology relates to medical image processing. An example method includes receiving medical image data which represents an anatomical structure and processing the received image data through convolutional neural network (CNN) to generate predictions. The predictions can include abnormality location proposals and abnormality class probabilities associated with each abnormality location proposals.
Claims23
A system for listing a set of radiological studies, comprising:
- at least one nontransitory processor-readable storage medium that stores at least one of processor-executable instructions or data;
- and
- at least one processor communicably coupled to the at least one nontransitory processor-readable storage medium, in operation the at least one processor:
- receives a list of radiological studies from a database, each of the radiological studies including image data associated therewith;
- receives the image data associated with the radiological studies;
- automatically processes the image data in order to determine which images are likely to contain abnormalities;
- and
- displays a list of one or more of the radiological studies or associated images.
2-11. (canceled)
The method of claim 90, wherein the processing of the image data is performed using one or more convolutional neural network models.
(canceled)
30-89. (canceled)
A computer-implemented method, comprising:
- receiving a list of radiological studies from a database, each of the radiological studies including image data associated therewith;
- receiving the image data associated with the radiological studies;
- automatically processing the image data in order to determine which images are likely to contain abnormalities;
- and
- displaying a list of one or more of the radiological studies or associated images.
A non-transitory computer-readable medium storing contents that, when executed by one or more processors, cause acts to be performed, the acts comprising:
- receiving a list of radiological studies from a database, each of the radiological studies including image data associated therewith;
- receiving the image data associated with the radiological studies;
- automatically processing the image data in order to determine which images are likely to contain abnormalities;
- and
- displaying a list of one or more of the radiological studies or associated images.
Dependencies are inferred from the claim text.