{"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/a-fully-convolutional-neural-network-for-1","title":"A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRI","arxiv_id":"1604.00494","date":"2016-04-02","proceeding":null,"authors":["Phi Vu Tran"],"abstract":"Automated cardiac segmentation from magnetic resonance imaging datasets is an\nessential step in the timely diagnosis and management of cardiac pathologies.\nWe propose to tackle the problem of automated left and right ventricle\nsegmentation through the application of a deep fully convolutional neural\nnetwork architecture. Our model is efficiently trained end-to-end in a single\nlearning stage from whole-image inputs and ground truths to make inference at\nevery pixel. To our knowledge, this is the first application of a fully\nconvolutional neural network architecture for pixel-wise labeling in cardiac\nmagnetic resonance imaging. Numerical experiments demonstrate that our model is\nrobust to outperform previous fully automated methods across multiple\nevaluation measures on a range of cardiac datasets. Moreover, our model is fast\nand can leverage commodity compute resources such as the graphics processing\nunit to enable state-of-the-art cardiac segmentation at massive scales. The\nmodels and code are available at\nhttps://github.com/vuptran/cardiac-segmentation","url_abs":"http://arxiv.org/abs/1604.00494v3","url_pdf":"http://arxiv.org/pdf/1604.00494v3.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":"a-fully-convolutional-neural-network-for-1","repo_url":"https://github.com/vuptran/cardiac-segmentation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"a-fully-convolutional-neural-network-for-1","repo_url":"https://github.com/mad2001/cardiac_ucla","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"a-fully-convolutional-neural-network-for-1","repo_url":"https://github.com/modelhub-ai/cardiac-fcn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"cardiac-segmentation","task_name":"Cardiac Segmentation"},{"task_slug":"management","task_name":"Management"},{"task_slug":null,"task_name":"Right Ventricle Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1604.00494","atlas_url":"https://app.syntology.ai/?focus=1604.00494","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1604.00494"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/modelhub-ai/cardiac-fcn","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/vuptran/cardiac-segmentation","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/mad2001/cardiac_ucla","reach":{"status":"ok"}}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"03d3db29257c607a","entry":"shrink_case","repo":"vuptran/cardiac-segmentation","repo_kind":"official","path":"train_sunnybrook.py","file_url":"https://github.com/vuptran/cardiac-segmentation/blob/HEAD/train_sunnybrook.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"03d3db29257c607a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}