{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:14:54Z","timestamp":1740100494281,"version":"3.37.3"},"reference-count":31,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T00:00:00Z","timestamp":1634428800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T00:00:00Z","timestamp":1634428800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T00:00:00Z","timestamp":1634428800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,17]]},"DOI":"10.1109\/smc52423.2021.9659170","type":"proceedings-article","created":{"date-parts":[[2022,1,6]],"date-time":"2022-01-06T20:34:35Z","timestamp":1641501275000},"page":"2775-2780","source":"Crossref","is-referenced-by-count":0,"title":["A Non-local Hierarchical Refinement Fully Convolutional Network for COVID-19 Infected Region Segmentation"],"prefix":"10.1109","author":[{"given":"Hongyu","family":"Wang","sequence":"first","affiliation":[]},{"given":"Nan","family":"Mu","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Heng","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.39"},{"key":"ref30","first-page":"3","article-title":"UNet++: A nested U-Net architecture for medical image segmentation","author":"zhou","year":"2019","journal-title":"Proceedings of Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1080\/07391102.2020.1788642"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.3023246"},{"key":"ref12","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention"},{"key":"ref13","first-page":"1","author":"chen","year":"2020","journal-title":"Residual attention u-net for automated multi-class segmentation of covid-19 chest ct images"},{"key":"ref14","first-page":"1","article-title":"Automatic COVID ? 19 CT segmentation using U-Net integrated spatial and channel attention mechanism","author":"zhou","year":"2020","journal-title":"International Journal of Imaging Systems and Technology"},{"key":"ref15","first-page":"1","author":"m\u00fcller","year":"2020","journal-title":"Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-Net"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3001810"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3000314"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2996645"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00250"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00887"},{"key":"ref4","first-page":"1","author":"hemdan","year":"2020","journal-title":"COVIDX-Net A Framework of Deep Learning Classifiers to Diagnose COVID-19 in X-Ray Images"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00766"},{"key":"ref3","first-page":"1","author":"narin","year":"2020","journal-title":"Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks"},{"key":"ref6","first-page":"1","author":"shan","year":"2020","journal-title":"Lung infection quantification of COVID-19 in CT images with deep learning"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00404"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020201544"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.05.014"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3001810"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103792"},{"key":"ref9","first-page":"1","author":"barstugan","year":"2020","journal-title":"Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020201160"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2020.3013418"},{"key":"ref22","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proceedings of the International Conference on Learning Representations"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2020.106922"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104543"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref26","first-page":"1","author":"cohen","year":"2020","journal-title":"Covid-19 image data collection Prospective predictions are the future"},{"article-title":"COVID-19 CT segmentation dataset","year":"2020","author":"jenssen","key":"ref25"}],"event":{"name":"2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","start":{"date-parts":[[2021,10,17]]},"location":"Melbourne, Australia","end":{"date-parts":[[2021,10,20]]}},"container-title":["2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9658572\/9658575\/09659170.pdf?arnumber=9659170","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:56:32Z","timestamp":1652201792000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9659170\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,17]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/smc52423.2021.9659170","relation":{},"subject":[],"published":{"date-parts":[[2021,10,17]]}}}