CECGSR: Circular ECG Super-Resolution
Honggui Li, Zhengyang Zhang, Dingtai Li, Sinan Chen, Nahid Md Lokman Hossain, Hantao Lu, Ruobing Wang, Xinfeng Xu, Yinlu Qin, Yuting Feng, Maria Trocan, Dimitri Galayko, Amara Amara, Mohamad Sawan

TL;DR
This paper introduces a novel closed-loop circular ECG super-resolution method that models degradation processes and employs feedback, outperforming traditional open-loop methods in ECG signal reconstruction.
Contribution
It proposes a closed-loop framework for ECG super-resolution, utilizing a feedback mechanism and a Plug-and-Play strategy to enhance signal quality over existing open-loop approaches.
Findings
CECGSR outperforms state-of-the-art open-loop ECGSR algorithms.
The method effectively reduces noise and artifacts in ECG signals.
Simulation results demonstrate improved reconstruction accuracy.
Abstract
Background and Objective: The electrocardiogram (ECG) plays a crucial role in the diagnosis and treatment of various cardiac diseases. ECG signals suffer from low-resolution (LR) due to the use of convenient acquisition devices, as well as internal and external noises and artifacts. Classical ECG super-resolution (ECGSR) methods adopt an open-loop architecture that converts LR ECG signals to super-resolution (SR) ones. According to the theory of automatic control, a closed-loop framework exhibits superior dynamic and static performance compared with its open-loop counterpart. Methods: This paper proposes a closed-loop approach, termed circular ECGSR (CECGSR), which models the degradation process from SR ECG signals to LR ones. The negative feedback mechanism of the closed-loop system is based on the differences between the LR ECG signals. A mathematical loop equation is constructed to…
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Taxonomy
TopicsCardiac Imaging and Diagnostics · Advanced MRI Techniques and Applications · Coronary Interventions and Diagnostics
