{"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/3d-consistent-robust-segmentation-of-cardiac","title":"3D Consistent & Robust Segmentation of Cardiac Images by Deep Learning with Spatial Propagation","arxiv_id":"1804.09400","date":"2018-04-25","proceeding":null,"authors":["Qiao Zheng","Hervé Delingette","Nicolas Duchateau","Nicholas Ayache"],"abstract":"We propose a method based on deep learning to perform cardiac segmentation on\nshort axis MRI image stacks iteratively from the top slice (around the base) to\nthe bottom slice (around the apex). At each iteration, a novel variant of U-net\nis applied to propagate the segmentation of a slice to the adjacent slice below\nit. In other words, the prediction of a segmentation of a slice is dependent\nupon the already existing segmentation of an adjacent slice. 3D-consistency is\nhence explicitly enforced. The method is trained on a large database of 3078\ncases from UK Biobank. It is then tested on 756 different cases from UK Biobank\nand three other state-of-the-art cohorts (ACDC with 100 cases, Sunnybrook with\n30 cases, RVSC with 16 cases). Results comparable or even better than the\nstate-of-the-art in terms of distance measures are achieved. They also\nemphasize the assets of our method, namely enhanced spatial consistency\n(currently neither considered nor achieved by the state-of-the-art), and the\ngeneralization ability to unseen cases even from other databases.","url_abs":"http://arxiv.org/abs/1804.09400v1","url_pdf":"http://arxiv.org/pdf/1804.09400v1.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":"3d-consistent-robust-segmentation-of-cardiac","repo_url":"https://github.com/julien-zheng/CardiacSegmentationPropagation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"cardiac-segmentation","task_name":"Cardiac Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}