{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:25:23Z","timestamp":1776086723226,"version":"3.50.1"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["20K11873"],"award-info":[{"award-number":["20K11873"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3280831","type":"journal-article","created":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T17:39:49Z","timestamp":1685381989000},"page":"1-1","source":"Crossref","is-referenced-by-count":11,"title":["MLP-UNet: Glomerulus Segmentation"],"prefix":"10.1109","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9544-5971","authenticated-orcid":false,"given":"Franchis N","family":"Saikia","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6421-8186","authenticated-orcid":false,"given":"Yuji","family":"Iwahori","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Chubu University, Kasugai, Japan"}]},{"given":"Taisei","family":"Suzuki","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Nagoya City University East Medical Center, Nagoya, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2152-5466","authenticated-orcid":false,"given":"M. K.","family":"Bhuyan","sequence":"additional","affiliation":[{"name":"Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9118-230X","authenticated-orcid":false,"given":"Aili","family":"Wang","sequence":"additional","affiliation":[{"name":"Higher Education Key Laboratory for Measuring and Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9046-7151","authenticated-orcid":false,"given":"Boonserm","family":"Kijsirikul","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.kint.2020.07.044"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2020.104231"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.4103\/2153-3539.186902"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"5314","DOI":"10.1109\/TPAMI.2022.3206148","article-title":"ResMLP: Feedforward networks for image classification with data-efficient training","volume":"45","author":"touvron","year":"2023","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ekir.2019.04.008"},{"key":"ref37","first-page":"1","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.5566\/ias.v19.p105-108"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87193-2_4"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.97"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1111\/j.1523-1755.2004.00836.x"},{"key":"ref33","first-page":"24261","article-title":"MLP-mixer: An all-MLP architecture for vision","volume":"34","author":"tolstikhin","year":"2021","journal-title":"Proc 35th Conf Neural Inf Process Syst"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2019.105273"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-015-0739-1"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87193-2_2"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2930068"},{"key":"ref38","article-title":"Fully transformer networks for semantic image segmentation","author":"wu","year":"2021","journal-title":"arXiv 2106 04108"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCE55644.2022.9852066"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-60964-5_73"},{"key":"ref23","first-page":"2474","article-title":"Glomerulus extraction by using genetic algorithm for edge patching","author":"ma","year":"2009","journal-title":"Proc IEEE Congr Evol Comput"},{"key":"ref26","article-title":"ImageNet-21K pretraining for the masses","author":"ridnik","year":"2021","journal-title":"arXiv 2104 10972"},{"key":"ref25","article-title":"YOLOv3: An incremental improvement","author":"redmon","year":"2018","journal-title":"arXiv 1804 02767"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1038\/s41586-019-1629-x","article-title":"The human body at cellular resolution: The NIH human biomolecular atlas program","volume":"574","author":"lin","year":"2019","journal-title":"Nature"},{"key":"ref22","article-title":"ConvMLP: Hierarchical convolutional MLPs for vision","author":"li","year":"2021","journal-title":"arXiv 2109 04454"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref27","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-019-0106-0"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2009.2034865"},{"key":"ref9","first-page":"630","article-title":"Identity mappings in deep residual networks","author":"he","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref4","article-title":"TransUNet: Transformers make strong encoders for medical image segmentation","author":"chen","year":"2021","journal-title":"arXiv 2102 04306"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1681\/ASN.2017111210"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref5","article-title":"An image is worth 16×16words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020","journal-title":"arXiv 2010 11929"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00681"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/6514899\/10138195.pdf?arnumber=10138195","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T12:23:12Z","timestamp":1729513392000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10138195\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3280831","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}