ANATOMICALLY-INFORMED DEEP LEARNING ON CONTRAST-ENHANCED CARDIAC MRI FOR SCAR SEGMENTATION AND CLINICAL FEATURE EXTRACTION
Patent №
US 12,670,598
Granted
2026-06-30
Filed 2023
Owner
THE JOHNS HOPKINS UNIVERSITY
Lab
—
AI components
0
Assignment
None on record
Dataset
AIPD
Application
18249583
Fully automated computer-implemented deep learning techniques of contrast-enhanced cardiac MRI segmentation are provided. The techniques may include providing cardiac MRI data to a first computer-implemented deep learning network trained in order to identify a left ventricle region of interest to generate left ventricle region-of-interest-identified cardiac MRI data. The techniques may also include providing the left ventricle region-of-interest-identified cardiac MRI data to a second computer-implemented deep learning network trained in order to identify myocardium to generate myocardium-identified cardiac MRI data. The techniques may further include providing the myocardium-identified cardiac MRI data to at least one third computer-implemented deep learning network trained to conform data to geometrical anatomical constraints in order to generate anatomical-conforming myocardium-identified cardiac MRI data. The techniques may further include outputting the anatomical-conforming myocardium-identified cardiac MRI data.
Ownership
THE JOHNS HOPKINS UNIVERSITY