机构：[1]School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.[2]College of Computer and Control Engineering, Minjiang University, Fuzhou 350108, China.
In this paper, a novel deep learning method Mamba-RAYOLO is presented, which can improve detection and classification in the processing and analysis of ECG images in real time by integrating three advanced modules. The feature extraction module in our work with a multi-branch structure during training can capture a wide range of features to ensure efficient inference and rich feature extraction. The attention mechanism module utilized in our proposed network can dynamically focus on the most relevant spatial and channel-wise features to improve detection accuracy and computational efficiency. Then, the extracted features can be refined for efficient spatial feature processing and robust feature fusion. Several sets of experiments have been carried out to test the validity of the proposed Mamba-RAYOLO and these indicate that our method has made significant improvements in the detection and classification of ECG images. The research offers a promising framework for more accurate and efficient medical ECG diagnostics.
基金：
Beijing Institute of Technology Project by the Cancer Institute and Hospital, Chinese Academy of Medical, Project No.: 201920741045; Digital Media Art, Key
Laboratory of Sichuan Province, Sichuan Conservatory of Music, Project No.: 21DMAKL01;supported
by the first batch of industry–university cooperation collaborative education project funded by the Ministry of Education of the People’s Republic of China, 2021, Project No.: 202101071001; and supported
by Minjiang College 2021 school-level scientific research project funding, Project No.: MYK21011.
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2023]版：
大类|3 区综合性期刊
小类|2 区分析化学3 区工程：电子与电气3 区仪器仪表
最新[2023]版：
大类|3 区综合性期刊
小类|2 区分析化学3 区工程：电子与电气3 区仪器仪表
第一作者：
第一作者机构：[1]School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
通讯作者：
推荐引用方式(GB/T 7714)：
Ma Linjuan,Zhang Fuquan.A Novel Real-Time Detection and Classification Method for ECG Signal Images Based on Deep Learning[J].Sensors (Basel, Switzerland).2024,24(16):doi:10.3390/s24165087.
APA：
Ma Linjuan&Zhang Fuquan.(2024).A Novel Real-Time Detection and Classification Method for ECG Signal Images Based on Deep Learning.Sensors (Basel, Switzerland),24,(16)
MLA：
Ma Linjuan,et al."A Novel Real-Time Detection and Classification Method for ECG Signal Images Based on Deep Learning".Sensors (Basel, Switzerland) 24..16(2024)
