高精度脑部MRI去脸化工具，99.9%成功率且保留脑结构。
A generalisable head MRI defacing pipeline: Evaluation on 2,566 meningioma scans
- 融合图谱配准与脑区掩码，实现自动去脸化。
- 在2566例脑膜瘤扫描中成功率达99.92%，仅2例失败。
- 保持脑组织结构高度一致，相似度达0.9975，适合医学研究共享。
可靠的MRI去脸化技术对于保护患者隐私并维持脑部解剖结构完整性至关重要，有利于科研协作。现有方法常存在去脸不全或脑组织退化问题。本文提出一种鲁棒、可泛化的高分辨率MRI去脸化流程，结合图谱配准与脑区掩码。在包含2,566例异构临床脑膜瘤扫描数据上评估，视觉检查成功率达99.92%（2,564/2,566）。脑区掩码自动提取结果与原始图像对比，Dice相似系数为0.9975 ± 0.0023，表明优异的解剖结构保留效果。源代码已公开于https://github.com/cai4cai/defacing_pipeline。
原文摘要 · Abstract (English)
Reliable MRI defacing techniques to safeguard patient privacy while preserving brain anatomy are critical for research collaboration. Existing methods often struggle with incomplete defacing or degradation of brain tissue regions. We present a robust, generalisable defacing pipeline for high-resolution MRI that integrates atlas-based registration with brain masking. Our method was evaluated on 2,566 heterogeneous clinical scans for meningioma and achieved a 99.92 per cent success rate (2,564/2,566) upon visual inspection. Excellent anatomical preservation is demonstrated with a Dice similarity coefficient of 0.9975 plus or minus 0.0023 between brain masks automatically extracted from the original and defaced volumes. Source code is available at https://github.com/cai4cai/defacing_pipeline.
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