{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:09:02Z","timestamp":1764842942455,"version":"3.30.2"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T00:00:00Z","timestamp":1721001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T00:00:00Z","timestamp":1721001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,15]]},"DOI":"10.1109\/embc53108.2024.10781870","type":"proceedings-article","created":{"date-parts":[[2024,12,17]],"date-time":"2024-12-17T19:07:21Z","timestamp":1734462441000},"page":"1-7","source":"Crossref","is-referenced-by-count":1,"title":["Semantic Segmentation Refiner for Ultrasound Applications with Zero-Shot Foundation Models"],"prefix":"10.1109","author":[{"given":"Hedda Cohen","family":"Indelman","sequence":"first","affiliation":[{"name":"GE Healthcare,Research Science & Technology Organization,Dept. of AI\/ML,Haifa,Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elay","family":"Dahan","sequence":"additional","affiliation":[{"name":"GE Healthcare,Research Science & Technology Organization,Dept. of AI\/ML,Haifa,Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angeles M.","family":"Perez-Agosto","sequence":"additional","affiliation":[{"name":"GE Healthcare,Point of Care Ultrasound & Handheld,Dept. of Clinical Applications,Texas,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carmit","family":"Shiran","sequence":"additional","affiliation":[{"name":"GE Healthcare,Point of Care Ultrasound & Handheld,Dept. of Clinical Applications,Wisconsin,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Doron","family":"Shaked","sequence":"additional","affiliation":[{"name":"GE Healthcare,Research Science & Technology Organization,Dept. of AI\/ML,Haifa,Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nati","family":"Daniel","sequence":"additional","affiliation":[{"name":"GE Healthcare,Research Science & Technology Organization,Dept. of AI\/ML,Haifa,Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2018.11.020"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00937-3_16"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00438-z"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0300-7"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-44521-7_3"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.103061"},{"article-title":"Sam-med2d","year":"2023","author":"Cheng","key":"ref8"},{"key":"ref9","article-title":"Rethinking atrous convolution for semantic image segmentation","author":"Chen","year":"2017","journal-title":"ArXiv"},{"key":"ref10","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"Ronneberger","year":"2015"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/n19\u20131423"},{"key":"ref12","first-page":"8821","article-title":"Zero-shot text-to-image generation","volume-title":"Proceedings of the 38th International Conference on Machine Learning, ser. Proceedings of Machine Learning Research","volume":"139","author":"Ramesh"},{"key":"ref13","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Advances in Neural Information Processing Systems","volume":"33","author":"Brown","year":"2020"},{"article-title":"Computer-vision benchmark segment-anything model (sam) in medical images: Accuracy in 12 datasets","year":"2023","author":"He","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102918"},{"article-title":"How to efficiently adapt large segmentation model(sam) to medical images","year":"2023","author":"Hu","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-44824-z"},{"article-title":"Auto-prompting sam for mobile friendly 3d medical image segmentation","year":"2023","author":"Li","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i5.28250"},{"article-title":"LoRA: Low-rank adaptation of large language models","volume-title":"International Conference on Learning Representations","author":"Hu","key":"ref20"},{"article-title":"Cheap lunch for medical image segmentation by fine-tuning sam on few exemplars","year":"2023","author":"Feng","key":"ref21"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/bibm58861.2023.10386032"},{"article-title":"Sam-octa: Prompting segment-anything for octa image segmentation","year":"2023","author":"Chen","key":"ref23"},{"article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","year":"2021","author":"Dosovitskiy","key":"ref24"},{"article-title":"One-shot localization and segmentation of medical images with foundation models","year":"2023","author":"Anand","key":"ref25"},{"article-title":"Sam on medical images: A comprehensive study on three prompt modes","year":"2023","author":"Cheng","key":"ref26"},{"key":"ref27","first-page":"405","article-title":"Clustering by means of medoids","author":"Kaufmann","year":"1987","journal-title":"Data Analysis based on the L1-Norm and Related Methods"},{"key":"ref28","article-title":"Contrastive learning with hard negative samples","author":"Robinson","year":"2020","journal-title":"ArXiv"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2021.108310"},{"article-title":"Contrastive attraction and contrastive repulsion for representation learning","year":"2023","author":"Zheng","key":"ref30"},{"article-title":"Decoupled weight decay regularization","year":"2017","author":"Loshchilov","key":"ref31"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-64803-w"},{"key":"ref33","first-page":"1027","article-title":"K-means++: The advantages of careful seeding","volume-title":"Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms","author":"Arthur"},{"article-title":"Deep residual learning for image recognition","year":"2015","author":"He","key":"ref34"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref36","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","volume-title":"Advances in Neural Information Processing Systems 32","author":"Paszke","year":"2019"}],"event":{"name":"2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","start":{"date-parts":[[2024,7,15]]},"location":"Orlando, FL, USA","end":{"date-parts":[[2024,7,19]]}},"container-title":["2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10781475\/10781494\/10781870.pdf?arnumber=10781870","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T07:20:02Z","timestamp":1734506402000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10781870\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,15]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/embc53108.2024.10781870","relation":{},"subject":[],"published":{"date-parts":[[2024,7,15]]}}}