{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:09:32Z","timestamp":1774541372680,"version":"3.50.1"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"NIH","award":["R01DK135597(Huo)"],"award-info":[{"award-number":["R01DK135597(Huo)"]}]},{"name":"NIH"},{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["DK56942(ABF)"],"award-info":[{"award-number":["DK56942(ABF)"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NIH NIDDK","award":["DK56942"],"award-info":[{"award-number":["DK56942"]}]},{"name":"NIH","award":["R01DK135597"],"award-info":[{"award-number":["R01DK135597"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Biomed. Eng."],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1109\/tbme.2023.3260739","type":"journal-article","created":{"date-parts":[[2023,3,23]],"date-time":"2023-03-23T17:45:00Z","timestamp":1679593500000},"page":"2636-2644","source":"Crossref","is-referenced-by-count":33,"title":["Omni-Seg: A Scale-Aware Dynamic Network for Renal Pathological Image Segmentation"],"prefix":"10.1109","volume":"70","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6300-8518","authenticated-orcid":false,"given":"Ruining","family":"Deng","sequence":"first","affiliation":[{"name":"Department of Computer Science, Vanderbilt University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8609-3556","authenticated-orcid":false,"given":"Quan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Vanderbilt University, USA"}]},{"given":"Can","family":"Cui","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Vanderbilt University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1848-079X","authenticated-orcid":false,"given":"Tianyuan","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Vanderbilt University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0163-0007","authenticated-orcid":false,"given":"Jun","family":"Long","sequence":"additional","affiliation":[{"name":"Big Data Institute, Central South University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2401-5026","authenticated-orcid":false,"given":"Zuhayr","family":"Asad","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Vanderbilt University, USA"}]},{"given":"R. Michael","family":"Womick","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of North Carolina at Chapel Hill, USA"}]},{"given":"Zheyu","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Vanderbilt University, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3698-8527","authenticated-orcid":false,"given":"Agnes B.","family":"Fogo","sequence":"additional","affiliation":[{"name":"Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, USA"}]},{"given":"Shilin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4265-7492","authenticated-orcid":false,"given":"Haichun","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2096-8065","authenticated-orcid":false,"given":"Yuankai","family":"Huo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Vanderbilt University, Nashville, TN, USA"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.kint.2020.07.044"},{"key":"ref12","first-page":"11","article-title":"Multiscale 3-dimensional pathology findings of COVID-19 diseased lung using high-resolution cleared tissue microscopy","volume":"10","author":"li","year":"2020","journal-title":"BioRxiv"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1681\/ASN.2019020144"},{"key":"ref14","article-title":"U-Net ensemble model for segmentation inhistopathology images","author":"li","year":"2019"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/BF00584220"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00949-6_14"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_43"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00125"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.2215\/CJN.08370812"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI52829.2022.9761582"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-021-00830-w"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2021.04.048"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00946-5_22"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0654-x"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1038\/s41593-020-00787-0"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2791488"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9414164"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.2986926"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2903562"},{"key":"ref49","author":"andrews","year":"2010","journal-title":"FastQC A Quality Control Tool for High Throughput Sequence Data"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.10.097"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2677499"},{"key":"ref9","first-page":"532","article-title":"Computer aided analysis of prostate histopathology images to support a refined Gleason grading system","volume":"10133","author":"ren","year":"0","journal-title":"Proc Med Imag Image Process"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106291"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1111\/apt.16100","article-title":"Digital pathology: Accurate technique for quantitative assessment of histological features in metabolic-associated fatty liver disease","volume":"53","author":"marti-aguado","year":"2021","journal-title":"Alimentary Pharmacology and Therapeutics"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajpath.2021.05.005"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0193056"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","article-title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","volume":"40","author":"chen","year":"2017","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-021-11814-y"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-16-8129-5_27"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref36","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"0","journal-title":"Proc Int Conf Med Image Comput Comput - Assist Interv"},{"key":"ref31","first-page":"215","article-title":"Iterative learning to make the most of unlabeled and quickly obtained labeled data in histology","volume":"102","author":"gupta","year":"0","journal-title":"Proc Int Conf Med Imag Deep Learn &#x2013;Full Paper Track"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1117\/12.2611177"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.2215\/CJN.07830621"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.ekir.2019.04.008"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.23151"},{"key":"ref1","first-page":"8121","article-title":"Renal biopsy for medical renal disease: Indications and contraindications","volume":"23","author":"bandari","year":"2016","journal-title":"Can J Urol"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3001036"},{"key":"ref38","article-title":"Med3D: Transfer learning for 3D medical image analysis","author":"chen","year":"2019"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging4010020"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2018.11.002"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0018-3"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2019.105273"},{"key":"ref20","first-page":"304","article-title":"Omni-Seg: A single dynamic network for multi-label renal pathology image segmentation using partially labeled data","author":"deng","year":"0","journal-title":"Proc Int Conf Med Imag Deep Learn"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0271161"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.17305\/bjbms.2022.8318"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1681\/ASN.2020050597"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2021.101930"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-17798-0_32"}],"container-title":["IEEE Transactions on Biomedical Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10\/10235284\/10079171.pdf?arnumber=10079171","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,9]],"date-time":"2023-12-09T13:57:17Z","timestamp":1702130237000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10079171\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":51,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tbme.2023.3260739","relation":{},"ISSN":["0018-9294","1558-2531"],"issn-type":[{"value":"0018-9294","type":"print"},{"value":"1558-2531","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9]]}}}