System and method for automatic pulmonary embolism detection
AssigneeArizona Board of Regents on behalf of Arizona State University
InventorsJianming Liang, Nima Tajbakhsh
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Abstract
A system and method for detecting pulmonary embolisms in a subject's vasculature are provided. In some aspects, the method includes acquiring a set of images representing a vasculature of the subject, and analyzing the set of images to identify pulmonary embolism candidates associated with the vasculature. The method also includes generating, for identified pulmonary embolism candidates, image patches based on a vessel-aligned image representation, and applying a set of convolutional neural networks to the generated image patches to identify pulmonary embolisms. The method further includes generating a report indicating identified pulmonary embolisms.
Claims16
A system for detecting pulmonary embolisms in a subject's vasculature, the system comprising:
- an input configured to receive images acquired from a subject;
- a processor configured to process the images with steps comprising:
- i. receiving, using the input, a set of images representing a vasculature of the subject;
- ii. analyzing the set of images to identify pulmonary embolism candidates associated with the vasculature;
- iii. generating, for identified pulmonary embolism candidates, image patches based on a vessel-aligned image representation;
- iii. applying a set of convolutional neural networks to the generated image patches to identify pulmonary embolisms;
- vi. generating a report indicating identified pulmonary embolisms;
- and
- an output for displaying the report.
A method for detecting pulmonary embolisms in a subject's vasculature, the system comprising:
- acquiring a set of images representing a vasculature of the subject;
- analyzing the set of images to identify pulmonary embolism candidates associated with the vasculature;
- generating, for identified pulmonary embolism candidates, image patches based on a vessel-aligned image representation;
- applying a set of convolutional neural networks to the generated image patches to identify pulmonary embolisms;
- and
- generating a report indicating identified pulmonary embolisms.
Dependencies are inferred from the claim text.