Method And System For Purely Geometric Machine Learning Based Fractional Flow Reserve


Ontology type: sgo:Patent     


Patent Info

DATE

2017-08-31T00:00

AUTHORS

Lucian Mihai Itu , Puneet Sharma , Saikiran Rapaka , Tiziano Passerini , Max Schöbinger , Chris Schwemmer , Dorin Comaniciu , Thomas Redel

ABSTRACT

A method and system for determining hemodynamic indices, such as fractional flow reserve (FFR), for a location of interest in a coronary artery of a patient is disclosed. Medical image data of a patient is received. Patient-specific coronary arterial tree geometry of the patient is extracted from the medical image data. Geometric features are extracted from the patient-specific coronary arterial tree geometry of the patient. A hemodynamic index, such as FFR, is computed for a location of interest in the patient-specific coronary arterial tree based on the extracted geometric features using a trained machine-learning based surrogate model. The machine-learning based surrogate model is trained based on geometric features extracted from synthetically generated coronary arterial tree geometries. More... »

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