{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T22:30:11Z","timestamp":1792708211634,"version":"4.5.0"},"reference-count":46,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T00:00:00Z","timestamp":1762646400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T00:00:00Z","timestamp":1762646400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000065","name":"National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS118019"],"award-info":[{"award-number":["R01NS118019"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["RF1NS139370"],"award-info":[{"award-number":["RF1NS139370"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["RF1AG072490"],"award-info":[{"award-number":["RF1AG072490"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006312","name":"BrightFocus Foundation","doi-asserted-by":"publisher","award":["A20201411S"],"award-info":[{"award-number":["A20201411S"]}],"id":[{"id":"10.13039\/100006312","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To propose a spatio\u2010temporal U\u2010Net based network (4DST) that exploits both spatial and dynamic information while avoiding memory\u2010intensive 4D convolutional layers for ASL\u2010based non\u2010contrast enhanced 4\u2010dimensional MR angiography (4D MRA) vessel segmentation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Pulsed ASL\u2010based 4D MRA data were collected on 35 healthy volunteers and 5 arteriovenous malformation patients. Spatial only (2D, 3D) and spatio\u2010temporal U\u2010Net variations (including the proposed 4DST) were tested. Two recently developed methods, including feature\u2010based isolation forest and BRAVE\u2010Net, were used for comparison. Dice\u2010S\u00f8rensen coefficient (DSC), center\u2010line Dice (clDice), Hausdorff distance (HD), precision, accuracy, specificity, and sensitivity were calculated. Sensitivity was analyzed relative to SNR and arterial transit time (ATT) to explore detectability. From graph analysis, total vessel length, number of branches, and number of endpoints were reported.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>4DST achieved the best DSC, clDice, and HD (0.876\u2009\u00b1\u20090.03, 0.865\u2009\u00b1\u20090.02, 6.241\u2009\u00b1\u20090.95, respectively). 4DST outperformed all other models across the SNR range of 1 to 10 and arterial transit time range of 500 to 800\u2009ms in sensitivity. Last, the 4DST segmentations yielded total lengths and the number of branch splits that more closely matched the ground truths compared to the other models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The proposed 4DST network architecture offers an overall improvement in 4D MRA vessel segmentation performance over the compared methods and provides the framework for an end\u2010to\u2010end trainable model for spatio\u2010temporal datasets. Additionally, 4DST requires minimal pre\/post\u2010processing steps, rendering it an attractive solution for pulsed ASL\u2010based 4D MRA vessel segmentation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70173","type":"journal-article","created":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T03:05:32Z","timestamp":1762743932000},"page":"2384-2396","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["<scp>ASL 4D MRA<\/scp>\n                    Intracranial Vessel Segmentation With Deep Learning U\u2010Nets"],"prefix":"10.1002","volume":"95","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0605-9420","authenticated-orcid":false,"given":"Sang Hun","family":"Chung","sequence":"first","affiliation":[{"name":"Department of Radiology Northwestern University Feinberg School of Medicine  Chicago Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zihan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering McCormick School of Engineering, Northwestern University  Evanston Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0889-5629","authenticated-orcid":false,"given":"Tianrui","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Radiology Northwestern University Feinberg School of Medicine  Chicago Illinois USA"},{"name":"Department of Biomedical Engineering McCormick School of Engineering, Northwestern University  Evanston Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3462-6549","authenticated-orcid":false,"given":"Zhitao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology Northwestern University Feinberg School of Medicine  Chicago Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chase S.","family":"Krumpelman","sequence":"additional","affiliation":[{"name":"Department of Radiology Northwestern University Feinberg School of Medicine  Chicago Illinois USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah J.","family":"Moum","sequence":"additional","affiliation":[{"name":"Department of Radiology Northwestern University Feinberg School of Medicine  Chicago Illinois USA"},{"name":"Department of Medical Imaging Ann &amp; Robert H. 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