{"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/multi-task-learning-for-left-atrial","title":"Multi-Task Learning for Left Atrial Segmentation on GE-MRI","arxiv_id":"1810.13205","date":"2018-10-31","proceeding":null,"authors":["Chen Chen","Wenjia Bai","Daniel Rueckert"],"abstract":"Segmentation of the left atrium (LA) is crucial for assessing its anatomy in\nboth pre-operative atrial fibrillation (AF) ablation planning and\npost-operative follow-up studies. In this paper, we present a fully automated\nframework for left atrial segmentation in gadolinium-enhanced magnetic\nresonance images (GE-MRI) based on deep learning. We propose a fully\nconvolutional neural network and explore the benefits of multi-task learning\nfor performing both atrial segmentation and pre/post ablation classification.\nOur results show that, by sharing features between related tasks, the network\ncan gain additional anatomical information and achieve more accurate atrial\nsegmentation, leading to a mean Dice score of 0.901 on a test set of 20 3D MRI\nimages. Code of our proposed algorithm is available at\nhttps://github.com/cherise215/atria_segmentation_2018/.","url_abs":"http://arxiv.org/abs/1810.13205v1","url_pdf":"http://arxiv.org/pdf/1810.13205v1.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":"multi-task-learning-for-left-atrial","repo_url":"https://github.com/cherise215/atria_segmentation_2018","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"anatomy","task_name":"Anatomy"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"multi-task-learning","task_name":"Multi-Task Learning"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1810.13205","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}