@inproceedings{db0b115bbafc4bb9b97541c258af3a3b,
title = "An OPM-MEG source localization evaluation method based on dry phantom",
abstract = "This study addresses the lack of known magnetic source references for evaluating the localization accuracy of OPM-MEG systems by proposing a physical dry phantom based on equivalent current dipoles. The phantom incorporates 50 dipoles with well-defined positions and orientations, allowing flexible multi-angle arrangements and controllable excitation signals, thereby providing a known magnetic source reference for system performance assessment. Based on this phantom, MEG forward model and source localization algorithm were investigated and experimentally validated using a 29-channel OPM system. Results demonstrated an average localization error of about 10 mm for the dipole positions, confirming the effectiveness of the proposed model as an evaluation tool. This work establishes a reusable experimental foundation and methodological support for localization performance evaluation, system calibration, and maintenance of multi-channel OPM-MEG systems.",
keywords = "Atomic Magnetometer, Dry Phantom, LCMV, Magnetoencephalography, Source Localization",
author = "Shengjie Qi and Shuhao Cui and Shuncheng Xue and Tengyue Long and Xinda Song",
note = "Publisher Copyright: {\textcopyright} 2026 SPIE.; International Conference on Computer Vision and Image Computing, CVIC 2025 ; Conference date: 21-11-2025 Through 23-11-2025",
year = "2026",
month = feb,
day = "13",
doi = "10.1117/12.3107273",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Luis Gomez and Zahid Akhtar",
booktitle = "International Conference on Computer Vision and Image Computing, CVIC 2025",
address = "美国",
}