开发开源工具，自动解析肝部血管影像，助力医学研究。
The R-Vessel-X Project
- 用真实与合成数据训练3D血管图像分析模型
- 实现肝部解剖分割与血管增强的开源插件
- 适合医学影像研究者与生物工程团队使用
本技术报告总结了法国国家科研署资助的R-Vessel-X项目（2019–2023年）的主要成果。项目聚焦肝脏3D血管网络的鲁棒提取与理解，利用IRCAD、Bullitt和VascuSynth等公开数据集与工具，构建真实或合成的血管造影图像。核心贡献涵盖3D血管图像的滤波、分割、建模与仿真，特别针对肝脏区域。重点推动开源软件传播：开发了SlicerRVXLiverSegmentation肝部解剖分割插件与Slicer-RVXVesselnessFilters血管增强滤波插件，并推出在线演示平台OpenCCO，支持2D/3D合成血管生成。项目产出覆盖3D血管图像分析多个方向，提供免费开源工具，便于生物医学工程领域后续研究应用。
原文摘要 · Abstract (English)
1) Objectives: This technical report presents a synthetic summary and the principal outcomes of the project R-Vessel-X ("Robust vascular network extraction and understanding within hepatic biomedical images") funded by the French Agence Nationale de la Recherche, and developed between 2019 and 2023. 2) Material and methods: We used datasets and tools publicly available such as IRCAD, Bullitt or VascuSynth toobtain real or synthetic angiographic images. The main contributions lie in the field of 3D angiographic image analysis: filtering, segmentation, modeling and simulation, with a specific focus on the liver. 3) Results: We paid a particular attention to open-source software diffusion of the developed methods, by means of 3D Slicer plugins for the liver anatomy segmentation (SlicerRVXLiverSegmentation) and vesselness filtering (Slicer-RVXVesselnessFilters), and an online demo for the generation of synthetic and realistic vessels in 2D and 3D (OpenCCO). 4) Conclusion: The R-Vessel-X project provided extensive research outcomes, covering various topics related to 3D angiographic image analysis, such as filtering, segmentation, modeling and simulation. We also developed open-source and free softwares so that the research communities in biomedical engineering can use these results in their future research.
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