{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T19:55:29Z","timestamp":1766087729964},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T00:00:00Z","timestamp":1610236800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,10]],"date-time":"2021-01-10T00:00:00Z","timestamp":1610236800000},"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":[[2021,1,10]]},"DOI":"10.1109\/icpr48806.2021.9413051","type":"proceedings-article","created":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T02:15:54Z","timestamp":1620267354000},"source":"Crossref","is-referenced-by-count":3,"title":["BCAU-Net: A Novel Architecture with Binary Channel Attention Module for MRI Brain Segmentation"],"prefix":"10.1109","author":[{"given":"Yongpei","family":"Zhu","sequence":"first","affiliation":[{"name":"Graduate School at Shenzhen, Tsinghua University,dept. of Biomedical Engineering,Shenzhen,China,518055"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zicong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Institute of Natural Sciences, Shanghai Jiao Tong University,Shanghai,China,200240"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guojun","family":"Liao","sequence":"additional","affiliation":[{"name":"The University of Texas at Arlington,dept. of Mathematics,Arlington,USA,76019"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kehong","family":"Yuan","sequence":"additional","affiliation":[{"name":"Graduate School at Shenzhen, Tsinghua University,dept. of Biomedical Engineering,Shenzhen,China,518055"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Spatial pyramid pooling in deep convolutional networks for visual recognition","author":"he","year":"2014","journal-title":"ECCV"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2548501"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2016.7493515"},{"key":"ref13","first-page":"424","article-title":"3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation","author":"\u00e7i\u00e7ek","year":"2016","journal-title":"Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref15","article-title":"Tensorflow: Large-scale machine learning on heterogeneous distributed systems","author":"martin","year":"0","journal-title":"unpublished"},{"key":"ref16","author":"francois","year":"2015"},{"key":"ref17","article-title":"Adam: a method for stochastic optimization","author":"kingma","year":"2014","journal-title":"Computer Science"},{"key":"ref18","first-page":"2998","article-title":"Parallel multi-dimensional lstm, with application to fast biomedical volumetric image segmentation","author":"stollenga","year":"2015","journal-title":"Computer Science"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-015-0068-x"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.04.041"},{"key":"ref3","article-title":"CBAM: Convolutional Block Attention Module","author":"woo","year":"2018","journal-title":"ECCV"},{"key":"ref6","first-page":"234","article-title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","author":"ronneberger","year":"2015","journal-title":"Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref5","article-title":"Squeeze and Excite","author":"roy","year":"0","journal-title":"Guided Few-Shot Segmentation of Volumetric Images unpublished"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2015.7301312"},{"key":"ref7","first-page":"421","article-title":"Concurrent spatial and channel ‘squeeze & excitation’ in fully convolutional networks","author":"roy","year":"2018","journal-title":"MICCAI"},{"key":"ref2","first-page":"192","author":"wang","year":"2019","journal-title":"Mixed-Supervised Dual-Network for Medical Image Segmentation in Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-017-9983-4"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref20","article-title":"Attention U-Net: Learning Where to Look for the Pancreas","author":"oktay","year":"2018","journal-title":"MIDL"},{"key":"ref21","article-title":"Connection Sensitive Attention U - NET for Accurate Retinal Vessel Segmentation","author":"li","year":"0","journal-title":"unpublished"}],"event":{"name":"2020 25th International Conference on Pattern Recognition (ICPR)","location":"Milan, Italy","start":{"date-parts":[[2021,1,10]]},"end":{"date-parts":[[2021,1,15]]}},"container-title":["2020 25th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9411940\/9411911\/09413051.pdf?arnumber=9413051","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T00:09:19Z","timestamp":1659485359000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9413051\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,10]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/icpr48806.2021.9413051","relation":{},"subject":[],"published":{"date-parts":[[2021,1,10]]}}}