Publications by authors named "Linsheng Cheng"
Article Synopsis
- This study aims to improve the understanding and diagnosis of cardiac diseases by reconstructing myocardial transmembrane potential (TMP) from body surface potential mapping.
- A new methodology is introduced that combines convolutional neural networks with traditional optimization methods to accurately estimate TMP distribution.
- Experiments show that this approach effectively reconstructs TMP, which could enhance diagnosis and treatment in cardiology, showcasing its potential to advance healthcare.
Noninvasive Cardiac Transmembrane Potential Imaging via Global Features Based FISTA Network.
Annu Int Conf IEEE Eng Med Biol Soc
November 2021
Noninvasive electrophysiological imaging plays an important role in the clinical diagnosis and treatment of heart diseases over recent years. Transmembrane potential (TMP) is one of the most important cardiac physiological signals, which can be used to diagnose heart disease such as premature beat and myocardial infarction. Considering the nonlocal self-similarity of TMP distribution and integrating traditional optimization strategy into deep learning, we proposed a novel global features based Fast Iterative Shrinkage/Thresholding network, named as GFISTA-Net.
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