{"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-densely-convolutional-networks-for","title":"3D Densely Convolutional Networks for Volumetric Segmentation","arxiv_id":"1709.03199","date":"2017-09-11","proceeding":null,"authors":["Toan Duc Bui","Jitae Shin","Taesup Moon"],"abstract":"In the isointense stage, the accurate volumetric image segmentation is a\nchallenging task due to the low contrast between tissues. In this paper, we\npropose a novel very deep network architecture based on a densely convolutional\nnetwork for volumetric brain segmentation. The proposed network architecture\nprovides a dense connection between layers that aims to improve the information\nflow in the network. By concatenating features map of fine and coarse dense\nblocks, it allows capturing multi-scale contextual information. Experimental\nresults demonstrate significant advantages of the proposed method over existing\nmethods, in terms of both segmentation accuracy and parameter efficiency in\nMICCAI grand challenge on 6-month infant brain MRI segmentation.","url_abs":"http://arxiv.org/abs/1709.03199v2","url_pdf":"http://arxiv.org/pdf/1709.03199v2.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-densely-convolutional-networks-for","repo_url":"https://github.com/tbuikr/3D_DenseSeg","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"caffe2","reach":null}],"tasks":[{"task_slug":"brain-segmentation","task_name":"Brain Segmentation"},{"task_slug":"image-segmentation","task_name":"Image Segmentation"},{"task_slug":"infant-brain-mri-segmentation","task_name":"Infant Brain Mri Segmentation"},{"task_slug":"mri-segmentation","task_name":"MRI segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}