Multi-channel deep learning model diagnoses the cause of LVH

A new study sees the development of a fully automatic framework for the diagnosis of the cause of left ventricular hypertrophy (LVH) via cardiac cine images. The fully automatic myocardium segmentation and spatial-temporal morphology feature-based LVH etiology diagnosis deep learning framework model was able to show a favorable and robust performance in diagnosing the cause of LVH, which could be used as a noninvasive tool, thus helping with clinical decisions.

Key points

• Multi-view cine images provide a potential etiology diagnosis tool for LVH.
• AI-based myocardium spatial–temporal features extracted from images is helpful in diagnosis.
• AI demonstrated higher accuracy and greater robustness with human experience added.

Article: Multi-channel deep learning model-based myocardial spatial–temporal morphology feature on cardiac MRI cine images diagnoses the cause of LVH

Authors: Kaiyue Diao, Hong-qing Liang, Hong-kun Yin, Ming-jing Yuan, Min Gu, Peng-xin Yu, Sen He, Jiayu Sun, Bin Song, Kang Li & Yong He

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Insights into Imaging