{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:14:17Z","timestamp":1740132857264,"version":"3.37.3"},"reference-count":21,"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:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":["11975312"],"award-info":[{"award-number":["11975312"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003995","name":"Natural Science Foundation of Anhui Province","doi-asserted-by":"publisher","award":["2108085MF232"],"award-info":[{"award-number":["2108085MF232"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/lsp.2023.3292028","type":"journal-article","created":{"date-parts":[[2023,7,4]],"date-time":"2023-07-04T17:46:46Z","timestamp":1688492806000},"page":"1027-1031","source":"Crossref","is-referenced-by-count":1,"title":["Carotid Lumen Diameter and Intima-Media Thickness Measurement via Boundary-Guided Pseudo-Labeling"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9595-3909","authenticated-orcid":false,"given":"Shimeng","family":"Yang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Anhui University, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1150-088X","authenticated-orcid":false,"given":"Teng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Anhui University, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4444-237X","authenticated-orcid":false,"given":"Yinping","family":"Lv","sequence":"additional","affiliation":[{"name":"Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4670-8456","authenticated-orcid":false,"given":"Yi","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Electrical and Automation, Anhui University, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5184-3230","authenticated-orcid":false,"given":"Shuo","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer and Data Science, Case Western Reserve University, Cleveland, OH, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Towards understanding learning representations: To what extent do different neural networks learn the same representation","volume":"31","author":"wang","year":"0","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref12","first-page":"3519","article-title":"Similarity of neural network representations revisited","author":"kornblith","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref14","first-page":"1","article-title":"Segmentation of natural images using scale-space representations: A linear and a non-linear approach","author":"escoda","year":"0","journal-title":"Proc IEEE 11th Eur Signal Process Conf"},{"key":"ref20","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"0","journal-title":"Proc 18th Int Conf Med Image Comput Comput - Assist Intervention"},{"key":"ref11","first-page":"896","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume":"3","author":"lee","year":"0","journal-title":"Proc Workshop Challenges Representation Learn Int Conf Mach Learn"},{"key":"ref10","first-page":"5049","article-title":"Mixmatch: A holistic approach to semi-supervised learning","author":"berthelot","year":"0","journal-title":"Proc 33rd Int Conf Neural Inf Process Syst"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102040"},{"key":"ref2","article-title":"Re: Comparisons of established risk prediction models for cardiovascular disease: Systematic review","volume":"344","author":"siontis","year":"2021","journal-title":"BMJ"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.21037\/cdt.2019.09.01"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00227"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/rs13112091"},{"article-title":"In defense of pseudo-labeling: An uncertainty-aware pseudo-label selection framework for semi-supervised learning","year":"2021","author":"rizve","key":"ref19"},{"key":"ref18","first-page":"1","article-title":"Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks","author":"ayhan","year":"2018","journal-title":"Med Imag Deep Learn"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3472810"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3468872"},{"key":"ref9","first-page":"596","article-title":"Fixmatch: Simplifying semi-supervised learning with consistency and confidence","author":"sohn","year":"0","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2975798"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.101982"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3067449"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3404374"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/97\/10036333\/10172316.pdf?arnumber=10172316","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T18:34:10Z","timestamp":1693852450000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10172316\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/lsp.2023.3292028","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"type":"print","value":"1070-9908"},{"type":"electronic","value":"1558-2361"}],"subject":[],"published":{"date-parts":[[2023]]}}}