{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T07:08:27Z","timestamp":1779347307762,"version":"3.51.4"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:00:00Z","timestamp":1775606400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:00:00Z","timestamp":1775606400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100012913","name":"Tata Consultancy Services","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012913","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,4,8]]},"DOI":"10.1109\/isbi61048.2026.11515683","type":"proceedings-article","created":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T19:48:46Z","timestamp":1779306526000},"page":"1-5","source":"Crossref","is-referenced-by-count":0,"title":["Morphogenetic Field Loss for Unified Medical Image Segmentation"],"prefix":"10.1109","author":[{"given":"Soma","family":"Dasgupta","sequence":"first","affiliation":[{"name":"TCS Research, Tata Consultancy Services,India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Swarnava","family":"Dey","sequence":"additional","affiliation":[{"name":"TCS Research, Tata Consultancy Services,India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Avik","family":"Ghose","sequence":"additional","affiliation":[{"name":"TCS Research, Tata Consultancy Services,India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arijit","family":"Mukherjee","sequence":"additional","affiliation":[{"name":"TCS Research, Tata Consultancy Services,India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arpan","family":"Pal","sequence":"additional","affiliation":[{"name":"TCS Research, Tata Consultancy Services,India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101950"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363547"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.103445"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2018.00100"},{"key":"ref5","first-page":"23803","article-title":"Cross-entropy loss functions: Theoretical analysis and applications","volume-title":"International conference on Machine learning. pmlr","author":"Mao"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00094"},{"key":"ref7","first-page":"379","article-title":"Tversky loss function for image segmentation using 3d fully convolutional deep networks","volume-title":"International workshop on machine learning in medical imaging. Springer","author":"Sadegh","year":"2017"},{"key":"ref8","article-title":"Learning to teach with dynamic loss functions","volume":"31","author":"Wu","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1867"},{"key":"ref10","first-page":"9157","article-title":"Tilting the playing field: Dynamical loss functions for machine learning","volume-title":"International Conference on Machine Learning. PMLR","author":"Ruiz-Garcia"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/s20030723"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_15"},{"key":"ref13","article-title":"Visualizing the loss landscape of neural nets","volume":"31","author":"Li","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/S0092-8240(05)80008-4"},{"key":"ref15","volume-title":"Mrbrains18, grand challenge on mr brain segmentation at miccai 2018","author":"Kuijf","year":"2019"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2019.8759329"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref18","article-title":"Attention u-net: Learning where to look for the pancreas","author":"Oktay","year":"2018","journal-title":"arXiv preprint arXiv"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.107260"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2105.15203"},{"key":"ref22","volume-title":"Omnisegnet: Towards scalable, efficient & universal medical image segmentation","author":"Dasgupta","year":"2025"},{"key":"ref23","article-title":"Sparsesegnet: A boundary-aware lightweight segmentation architecture for skin lesions","volume-title":"The 17th Asian Conference on Machine Learning (Conference Track)","author":"Dasgupta"}],"event":{"name":"2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)","location":"London, United Kingdom","start":{"date-parts":[[2026,4,8]]},"end":{"date-parts":[[2026,4,11]]}},"container-title":["2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11515282\/11515297\/11515683.pdf?arnumber=11515683","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T06:24:26Z","timestamp":1779344666000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11515683\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,8]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/isbi61048.2026.11515683","relation":{},"subject":[],"published":{"date-parts":[[2026,4,8]]}}}