{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T13:18:55Z","timestamp":1771679935073,"version":"3.50.1"},"reference-count":69,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61571314"],"award-info":[{"award-number":["61571314"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cogn. Dev. Syst."],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1109\/tcds.2020.3035572","type":"journal-article","created":{"date-parts":[[2020,11,3]],"date-time":"2020-11-03T21:05:43Z","timestamp":1604437543000},"page":"205-218","source":"Crossref","is-referenced-by-count":31,"title":["Automatic Segmentation of Pneumothorax in Chest Radiographs Based on a Two-Stage Deep Learning Method"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3597-9090","authenticated-orcid":false,"given":"Xiyue","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sen","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Lan","sequence":"additional","affiliation":[{"name":"Winning Health Technology Group Company, Ltd., Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8769-496X","authenticated-orcid":false,"given":"Yuqi","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Chinese University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhui","family":"He","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering, Xidian University, Xi’an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2033-0026","authenticated-orcid":false,"given":"Minghui","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Biomedical Engineering, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5151-6547","authenticated-orcid":false,"given":"Xiao","family":"Han","sequence":"additional","affiliation":[{"name":"Tencent AI Lab, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2018180921"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2016150409"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2933510"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2945362"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2900649"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2019.11.023"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2601622"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1038\/nature21056"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/s41551-018-0324-9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.369"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301590"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00943"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1118\/1.596790"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1117\/12.2083128"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-019-06130-x"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00919-9_29"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2019.2911947"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1117\/12.2292540"},{"key":"ref20","volume-title":"Weakly supervised medical diagnosis and localization from multiple resolutions","author":"Yao","year":"2018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000000341"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1002697"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93000-8_62"},{"key":"ref24","volume-title":"CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning","author":"Rajpurkar","year":"2017"},{"key":"ref25","volume-title":"Large scale automated reading of frontal and lateral chest X-rays using dual convolutional neural networks","author":"Rubin","year":"2018"},{"key":"ref26","volume-title":"Learning to diagnose from scratch by exploiting dependencies among labels","author":"Yao","year":"2017"},{"key":"ref27","first-page":"757","article-title":"Learning to recognize abnormalities in chest X-rays with location-aware dense networks","volume-title":"Proc. Iberoamerican Congr. Pattern Recognit. (CIARP)","author":"Guendel"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3233547.3233573"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00934-2_66"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019191293"},{"key":"ref31","volume-title":"Deep learning for pneumothorax detection and localization in chest radiographs","author":"Goo\u00dfen","year":"2019"},{"key":"ref32","volume-title":"Pneumothorax segmentation: Deep learning image segmentation to predict pneumothorax","author":"Jakhar","year":"2019"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59137-3_23"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM47256.2019.8983004"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CSCI49370.2019.00131"},{"key":"ref36","first-page":"1","article-title":"Chest X-ray pneumothorax segmentation with the multistep post-processing","volume-title":"Proc. Int. Conf. Med. Imag. Deep Learn.","author":"Groza"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/2908517"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32226-7_68"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1134\/s1054661817030269"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2018172322"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref42","volume-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","author":"Tan","year":"2019"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.08.039"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00913"},{"key":"ref47","volume-title":"Rethinking atrous convolution for semantic image segmentation","author":"Chen","year":"2017"},{"key":"ref48","first-page":"1","article-title":"A benchmark for endoluminal scene segmentation of colonoscopy images","volume":"2017","author":"David","year":"2017","journal-title":"J. Healthc. Eng."},{"issue":"6","key":"ref49","first-page":"475","article-title":"Two public chest X-ray datasets for computer-aided screening of pulmonary diseases","volume":"4","author":"Jaeger","year":"2014","journal-title":"Quant Imag. Med. Surg."},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2019.06.005"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44886-1_25"},{"key":"ref52","first-page":"1","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Kingma"},{"key":"ref53","first-page":"1","article-title":"SGDR: Stochastic gradient descent with warm restarts","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Loshchilov"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0197-0"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/S0003-4975(02)03702-5"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.04.025"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2019.8857339"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101619"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2941511"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.09.053"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2290491"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2953727"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00937-3_76"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93000-8_9"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32239-7_49"}],"container-title":["IEEE Transactions on Cognitive and Developmental Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274989\/9732511\/09247293.pdf?arnumber=9247293","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T22:50:12Z","timestamp":1704840612000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9247293\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":69,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tcds.2020.3035572","relation":{},"ISSN":["2379-8920","2379-8939"],"issn-type":[{"value":"2379-8920","type":"print"},{"value":"2379-8939","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3]]}}}