{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-r-vessel-x-project","title":"The R-Vessel-X Project","arxiv_id":"2501.10068","date":"2025-01-17","proceeding":null,"authors":["Abir Affane","Mohamed Amine Chetoui","Jonas Lamy","Guillaume Lienemann","Raphaël Peron","P. Beaurepaire","Guillaume Dollé","Marie-Ange Lèbre","Benoit Magnin","Odyssée Merveille","Mathilde Morvan","Phuc Ngo","Thibault Pelletier","Hugo Rositi","Stéphanie Salmon","Julien Finet","Bertrand Kerautret","Nicolas Passat","Antoine Vacavant"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2501.10068v1","url_pdf":"https://arxiv.org/pdf/2501.10068v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-r-vessel-x-project","repo_url":"https://github.com/r-vessel-x/slicerrvxliversegmentation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null},{"paper_slug":"the-r-vessel-x-project","repo_url":"https://github.com/r-vessel-x/slicerrvxvesselnessfilters","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"anatomy","task_name":"Anatomy"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[{"method_slug":"attention","method_name":"Attention"},{"method_slug":"diffusion","method_name":"Diffusion"},{"method_slug":"focus","method_name":"Focus"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}