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A fast hand motor hotspot determination method based on neuroimaging in transcranial magnetic stimulation | |
Xinle Cheng1,2![]() ![]() ![]() | |
2024-03 | |
会议名称 | 2024 3rd International Conference on Image, Signal Processing and Pattern Recognition(ISPP2024) |
会议日期 | 2024/03/08 - 2024/03/10 |
会议地点 | 中国·昆明市 |
出版者 | SPIE |
摘要 | Transcranial magnetic stimulation (TMS) stands as a widely employed neuromodulation technique for addressing various brain disorders. The hand motor hotspot (hMHS) holds particular significance in TMS applications, serving to ascertain personalized treatment targets and stimulation intensity. However, the conventional determination of hMHS remains time-consuming. Our objective was to expedite the identification of hMHS solely based on neuroimaging data. In this investigation, we pinpointed the hMHS on the cortical surface in depressed patients utilizing TMS-derived data and magnetic resonance imaging (MRI) data. Employing the kernel density estimation method, we developed a probability map for hMHS, subsequently utilizing a machine learning (ML) model to discern subjects suitable for the probability map application. The hMHS probability map was established, and the vertex with the highest probability was designated as the group hMHS. For subjects closely aligning with the group hMHS, direct application of the hMHS probability map was feasible. Conversely, for other subjects, our ML model, trained on cortical structure data of the sulci, could identify them. Our method achieved an 88% accuracy in hMHS determination and, when compared to traditional methods, exhibited an average time-saving of approximately 50%. In conclusion, our proposed method offers an efficient and rapid solution for hMHS identification during TMS treatment. |
关键词 | transcranial magnetic stimulation hand motor hotspot neuroimage machine learning |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 脑网络分析 |
国重实验室规划方向分类 | 脑启发多模态智能模型与算法 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/56632 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Zhengyi Yang |
作者单位 | 1.Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 3.Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China 4.NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xinle Cheng,Mingzhu Li,Xuefeng Lu,et al. A fast hand motor hotspot determination method based on neuroimaging in transcranial magnetic stimulation[C]:SPIE,2024. |
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