Deep Learning-based Prescription of Cardiac MRI Planes.

ABSTRACT:

Purpose

To develop and evaluate a system to prescribe imaging planes for cardiac MRI based on deep learning (DL)-based localization of key anatomic landmarks.

Materials and methods

Annotated landmarks on 892 long-axis (LAX) and 493 short-axis (SAX) cine steady-state free precession series from cardiac MR images were retrospectively collected between February 2012 and June 2017. U-Net-based heatmap regression was used for localization of cardiac landmarks, which were used to compute cardiac MRI planes. Performance was evaluated by comparing localization distances and plane angle differences between DL predictions and ground truth. The plane angulations from DL were compared with those prescribed by the technologist at the original time of acquisition. Data were split into 80%

SUBMITTER: Blansit K 

PROVIDER: S-EPMC6884027 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature