{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T21:28:25Z","timestamp":1770845305792,"version":"3.50.1"},"reference-count":33,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T00:00:00Z","timestamp":1759622400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,5]],"date-time":"2025-10-05T00:00:00Z","timestamp":1759622400000},"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":[[2025,10,5]]},"DOI":"10.1109\/smc58881.2025.11343591","type":"proceedings-article","created":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T20:54:44Z","timestamp":1769633684000},"page":"388-393","source":"Crossref","is-referenced-by-count":0,"title":["SAM-BrainFocus: A Multi-scale Boundary-Refined Framework for Precise Brain Tumor Segmentation"],"prefix":"10.1109","author":[{"given":"Yuyu","family":"Chen","sequence":"first","affiliation":[]},{"given":"Ziyi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yufang","family":"Dong","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2538465"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21492"},{"key":"ref3","article-title":"T1-contrast enhanced mri generation from multi-parametric mri for glioma patients with latent tumor conditioning","author":"Eidex","year":"2024"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"issue":"2","key":"ref5","first-page":"143","article-title":"Mri brain tumor segmentation network using multi-scale non-local self-attention","volume-title":"Computer Systems and Applications","volume":"33","author":"Zhang","year":"2024"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-30695-9"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref8","first-page":"135","article-title":"Multimodal medical image segmentation using multi-scale context-aware network","volume-title":"Neurocomputing","volume":"486","author":"Wang","year":"2022"},{"key":"ref9","first-page":"101504","article-title":"Deep learning for medical image segmentation: State-of-the-art advancements and challenges","volume-title":"Informatics in Medicine Unlocked","volume":"47","author":"Rayed","year":"2024"},{"issue":"3","key":"ref10","article-title":"A review of deep-learning-based medical image segmentation methods","volume-title":"Sustainability","volume":"13","author":"Liu","year":"2021"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87193-2_11"},{"key":"ref13","article-title":"U-net in medical image segmentation: A review of its applications across modalities","author":"Neha","year":"2024"},{"key":"ref14","article-title":"Mri tumor segmentation with densely connected 3d cnn","volume":"abs\/1802.02427","author":"Chen","year":"2018"},{"key":"ref15","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-72114-4_47","article-title":"nnu-net revisited: A call for rigorous validation in 3d medical image segmentation","author":"Isensee","year":"2024"},{"key":"ref16","article-title":"Swin-unet: Unet-like pure transformer for medical image segmentation","author":"Cao","year":"2021"},{"key":"ref17","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108238","article-title":"Segment anything model for medical image segmentation: Current applications and future directions","author":"Zhang","year":"2024"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102918"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.103061"},{"key":"ref20","article-title":"Medical sam adapter: Adapting segment anything model for medical image segmentation","author":"Wu","year":"2023"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-44824-z"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9341234"},{"key":"ref23","article-title":"Prototype-driven and multi-expert integrated multi-modal mr brain tumor image segmentation","author":"Zhang","year":"2023"},{"key":"ref24","first-page":"103723","article-title":"Multi-view dynamic facial action unit detection","volume-title":"Image and Vision Computing","volume":"122","author":"Romero","year":"2022"},{"key":"ref25","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.114468","article-title":"MIAFEx: An Attention-based Feature Extraction Method for Medical Image Classification","author":"Ramos-Soto","year":"2025"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"key":"ref27","article-title":"Deep residual learning for image recognition","author":"He","year":"2015"},{"key":"ref28","article-title":"Densely connected convolutional networks","author":"Huang","year":"2018"},{"key":"ref29","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2019"},{"key":"ref30","doi-asserted-by":"crossref","DOI":"10.1109\/ICCVW60793.2023.00273","article-title":"Comprehensive multimodal segmentation in medical imaging: Combining yolov8 with sam and hq-sam models","author":"Pandey","year":"2023"},{"key":"ref31","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-58452-8_13","article-title":"End-to-end object detection with transformers","author":"Carion","year":"2020"},{"key":"ref32","doi-asserted-by":"crossref","DOI":"10.1109\/CVPR.2017.106","article-title":"Feature pyramid networks for object detection","author":"Lin","year":"2017"},{"key":"ref33","first-page":"169","article-title":"Hybridised loss functions for improved neural network generalisation","author":"Dickson","year":"2022"}],"event":{"name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","location":"Vienna, Austria","start":{"date-parts":[[2025,10,5]]},"end":{"date-parts":[[2025,10,8]]}},"container-title":["2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11342430\/11342431\/11343591.pdf?arnumber=11343591","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T20:50:26Z","timestamp":1770843026000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11343591\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,5]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/smc58881.2025.11343591","relation":{},"subject":[],"published":{"date-parts":[[2025,10,5]]}}}