开源工具链统一胎儿脑MRI分析流程，提升可复现性。
Fetpype: An Open-Source Pipeline for Reproducible Fetal Brain MRI Analysis
- 模块化设计整合运动校正、超分辨率重建等多步处理
- 支持从原始T2加权图像到体积与皮层表面输出的全流程处理
- 专为科研与临床设计，提升胎儿神经影像分析效率
胎儿脑磁共振成像对评估宫内神经发育至关重要。然而，由于胎儿运动、信噪比低以及需要复杂的多步骤处理流程，胎儿MRI分析仍面临技术挑战。这些流程通常包括运动校正、超分辨率重建、组织分割和皮层表面提取。尽管各步骤有专用工具，但将其整合为稳健、可复现且用户友好的端到端工作流仍很困难。这种碎片化限制了研究间的可复现性，并阻碍先进胎儿神经影像方法在科研与临床中的应用。Fetpype通过提供标准化、模块化且可复现的框架，实现了从原始T2加权扫描到衍生体积与表面输出的统一处理流程。该工具已在GitHub公开：https://github.com/fetpype/fetpype。
原文摘要 · Abstract (English)
Fetal brain magnetic resonance imaging (MRI) is crucial for assessing neurodevelopment in utero. However, fetal MRI analysis remains technically challenging due to fetal motion, low signal-to-noise ratio, and the need for complex multi-step processing pipelines. These pipelines typically include motion correction, super-resolution reconstruction, tissue segmentation, and cortical surface extraction. While specialized tools exist for each individual processing step, integrating them into a robust, reproducible, and user-friendly end-to-end workflow remains difficult. This fragmentation limits reproducibility across studies and hinders the adoption of advanced fetal neuroimaging methods in both research and clinical contexts. Fetpype addresses this gap by providing a standardized, modular, and reproducible framework for fetal brain MRI preprocessing and analysis, enabling researchers to process raw T2-weighted acquisitions through to derived volumetric and surface-based outputs within a unified workflow. Fetpype is publicly available on GitHub at https://github.com/fetpype/fetpype.
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