System and Methods for Fast Computation of Computed Tomography Based Fractional Flow Reserve
AssigneeSiemens Healthcare GmbH
InventorsLucian Mihai Itu, Saikiran Rapaka, Tiziano Passerini, Puneet Sharma
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Abstract
A method and system for fast non-invasive computer-based computation of a hemodynamic index, such as fractional flow reserve (FFR) from medical image data of a patient is disclosed. A patient-specific anatomical model of one or more arteries of a patient is automatically generated based on medical image data of the patient. Regions in the automatically generated patient-specific anatomical model for which user feedback is required for accurate computation of a hemodynamic index are predicted using one or more trained machine learning models.
Claims23
A method for providing fast non-invasive computer-based computation of a hemodynamic index from medical image data of a patient, comprising:
- automatically generating a patient-specific anatomical model of one or more arteries of a patient based on medical image data of the patient;
- and
- predicting regions in the automatically generated patient-specific anatomical model for which user feedback is required for accurate computation of a hemodynamic index using one or more trained machine learning models.
An apparatus for providing fast non-invasive computation of a hemodynamic index from medical image data of a patient, comprising:
- a processor;
- and
- a memory storing computer program instructions which when executed by the processor cause the processor to perform operations comprising:
- automatically generating a patient-specific anatomical model of one or more arteries of a patient based on medical image data of the patient;
- and
- predicting regions in the automatically generated patient-specific anatomical model for which user feedback is required for accurate computation of a hemodynamic index using one or more trained machine learning models.
A non-transitory computer readable medium storing computer program instructions for providing fast non-invasive computation of a hemodynamic index from medical image data of a patient, the computer program instructions when executed by a processor cause the processor to perform operations comprising:
- automatically generating a patient-specific anatomical model of one or more arteries of a patient based on medical image data of the patient;
- and
- predicting regions in the automatically generated patient-specific anatomical model for which user feedback is required for accurate computation of a hemodynamic index using one or more trained machine learning models.
Dependencies are inferred from the claim text.