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.

G06T 7/11G06T 7/12A61B 6/032A61B 6/503A61B 8/0883G06T 7/0012G06T2207/10088G06T2207/20081+2 more

Ownership

THE JOHNS HOPKINS UNIVERSITY

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