{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T11:04:15Z","timestamp":1785323055234,"version":"3.55.0"},"reference-count":28,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T00:00:00Z","timestamp":1747008000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003397","name":"Huazhong University of Science and Technology","doi-asserted-by":"publisher","award":["2022B36"],"award-info":[{"award-number":["2022B36"]}],"id":[{"id":"10.13039\/501100003397","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82272109"],"award-info":[{"award-number":["82272109"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82102028"],"award-info":[{"award-number":["82102028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015640","name":"Tongji Hospital","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100015640","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Hubei Province Natural Science Foundation","doi-asserted-by":"publisher","award":["2024AFB656"],"award-info":[{"award-number":["2024AFB656"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.mri.2025.110418","type":"journal-article","created":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T19:15:20Z","timestamp":1747077320000},"page":"110418","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"C","title":["Accelerating prostate rs-EPI DWI with deep learning: Halving scan time, enhancing image quality, and validating in vivo"],"prefix":"10.1016","volume":"121","author":[{"given":"Peipei","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoyan","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chanyuan","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liming","family":"Xia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangde","family":"Min","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.mri.2025.110418_bb0005","first-page":"12","article-title":"Cancer statistics, 2024","volume":"74","author":"Siegel","year":"2024","journal-title":"CA Cancer J Clin"},{"issue":"1","key":"10.1016\/j.mri.2025.110418_bb0010","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.eururo.2015.08.052","article-title":"PI-RADS prostate imaging - reporting and data system: 2015, version 2","volume":"69","author":"Weinreb","year":"2016","journal-title":"Eur Urol"},{"issue":"3","key":"10.1016\/j.mri.2025.110418_bb0015","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.eururo.2019.02.033","article-title":"Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2","volume":"76","author":"Turkbey","year":"2019","journal-title":"Eur Urol"},{"issue":"2","key":"10.1016\/j.mri.2025.110418_bb0020","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.euo.2023.08.002","article-title":"Diagnostic performance of prostate-specific antigen density for detecting clinically significant prostate cancer in the era of magnetic resonance imaging: a systematic review and meta-analysis","volume":"7","author":"Wang","year":"2024","journal-title":"Eur Urol Oncol"},{"key":"10.1016\/j.mri.2025.110418_bb0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2020.109161","article-title":"Advanced diffusion weighted imaging of the prostate: comparison of readout-segmented multi-shot, parallel-transmit and single-shot echo-planar imaging","volume":"130","author":"Klingebiel","year":"2020","journal-title":"Eur J Radiol"},{"issue":"1","key":"10.1016\/j.mri.2025.110418_bb0030","doi-asserted-by":"crossref","first-page":"70","DOI":"10.2214\/AJR.14.13489","article-title":"Feasibility study of 3-T DWI of the prostate: readout-segmented versus single-shot echo-planar imaging","volume":"205","author":"Li","year":"2015","journal-title":"AJR Am J Roentgenol"},{"issue":"3","key":"10.1016\/j.mri.2025.110418_bb0035","doi-asserted-by":"crossref","first-page":"474","DOI":"10.3390\/diagnostics13030474","article-title":"Feasibility of simultaneous multislice acceleration technique in readout-segmented echo-planar diffusion-weighted imaging for assessing rectal cancer","volume":"13","author":"Zhou","year":"2023","journal-title":"Diagnostics (Basel)"},{"issue":"12","key":"10.1016\/j.mri.2025.110418_bb0040","doi-asserted-by":"crossref","first-page":"7985","DOI":"10.1007\/s00330-024-10883-5","article-title":"Image quality of whole-body diffusion MR images comparing deep-learning accelerated and conventional sequences","volume":"34","author":"Ponsiglione","year":"2024","journal-title":"Eur Radiol"},{"issue":"1","key":"10.1016\/j.mri.2025.110418_bb0045","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1186\/s13244-024-01686-9","article-title":"Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion","volume":"15","author":"Zhang","year":"2024","journal-title":"Insights Imaging"},{"issue":"10","key":"10.1016\/j.mri.2025.110418_bb0050","doi-asserted-by":"crossref","first-page":"4171","DOI":"10.1016\/j.acra.2024.02.049","article-title":"Deep learning accelerated brain diffusion-weighted MRI with super resolution processing","volume":"31","author":"Altmann","year":"2024","journal-title":"Acad Radiol"},{"issue":"3","key":"10.1016\/j.mri.2025.110418_bb0055","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1002\/jmri.29139","article-title":"Deep learning k-space-to-image reconstruction facilitates high spatial resolution and scan time reduction in diffusion-weighted imaging breast MRI","volume":"60","author":"Sauer","year":"2024","journal-title":"J Magn Reson Imaging"},{"issue":"1","key":"10.1016\/j.mri.2025.110418_bb0060","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1186\/s13244-022-01321-5","article-title":"Comparison of a deep learning-accelerated T2-weighted turbo spin echo sequence and its conventional counterpart for female pelvic MRI: reduced acquisition times and improved image quality","volume":"13","author":"Ren","year":"2022","journal-title":"Insights Imaging"},{"issue":"11","key":"10.1016\/j.mri.2025.110418_bb0065","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1097\/RLI.0000000000000988","article-title":"Deep learning-accelerated liver diffusion-weighted imaging: intraindividual comparison and additional phantom study of free-breathing and respiratory-triggering acquisitions","volume":"58","author":"Kim","year":"2023","journal-title":"Invest Radiol"},{"issue":"9","key":"10.1016\/j.mri.2025.110418_bb0070","doi-asserted-by":"crossref","first-page":"4575","DOI":"10.1109\/JBHI.2022.3193299","article-title":"Multiple B-value model-based residual network (MORN) for accelerated high-resolution diffusion-weighted imaging","volume":"26","author":"Wang","year":"2022","journal-title":"IEEE J Biomed Health Inform"},{"key":"10.1016\/j.mri.2025.110418_bb0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118632","article-title":"Deep learning based multiplexed sensitivity-encoding (DL-MUSE) for high-resolution multi-shot DWI","volume":"244","author":"Zhang","year":"2021","journal-title":"Neuroimage"},{"key":"10.1016\/j.mri.2025.110418_bb0080","series-title":"MSSNet: Multi-Scale-Stage Network for&nbsp;Single Image Deblurring. Computer Vision \u2013 ECCV 2022 Workshops: Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part II","author":"Kim","year":"2023"},{"key":"10.1016\/j.mri.2025.110418_bb0085","series-title":"Enhanced Deep Residual Networks for Single Image Super-resolution","author":"Lim","year":"2017"},{"key":"10.1016\/j.mri.2025.110418_bb0090","series-title":"SwinIR: Image Restoration Using Swin Transformer","author":"Liang","year":"2021"},{"key":"10.1016\/j.mri.2025.110418_bb0095","article-title":"Intelligent three-dimensional reconstruction algorithm-based ultrasound-guided nerve block in intraoperative anesthesia and postoperative analgesia of orthopedic surgery","volume":"2022","author":"Liu","year":"2022","journal-title":"Comput Math Methods Med"},{"issue":"3","key":"10.1016\/j.mri.2025.110418_bb0100","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1002\/jmri.28065","article-title":"Readout-segmented echo-planar diffusion-weighted MR imaging improves the differentiation of breast cancer receptor statuses compared with conventional diffusion-weighted imaging","volume":"56","author":"Zhong","year":"2022","journal-title":"J Magn Reson Imaging"},{"issue":"6","key":"10.1016\/j.mri.2025.110418_bb0105","doi-asserted-by":"crossref","first-page":"1055","DOI":"10.3174\/ajnr.A6079","article-title":"Readout-segmented echo-planar DWI for the detection of cholesteatomas: correlation with surgical validation","volume":"40","author":"Fischer","year":"2019","journal-title":"AJNR Am J Neuroradiol"},{"issue":"7","key":"10.1016\/j.mri.2025.110418_bb0110","doi-asserted-by":"crossref","first-page":"2258","DOI":"10.1007\/s00261-023-03937-7","article-title":"Feasibility of high-resolution readout-segmented echo-planar imaging with simultaneous multislice imaging in assessing rectal cancer","volume":"48","author":"Huang","year":"2023","journal-title":"Abdom Radiol (NY)"},{"issue":"2","key":"10.1016\/j.mri.2025.110418_bb0115","doi-asserted-by":"crossref","first-page":"640","DOI":"10.1007\/s00330-020-07193-x","article-title":"Evaluation of trigeminal nerve tractography using two-fold-accelerated simultaneous multi-slice readout-segmented echo planar diffusion tensor imaging","volume":"31","author":"Koh","year":"2021","journal-title":"Eur Radiol"},{"key":"10.1016\/j.mri.2025.110418_bb0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2022.110428","article-title":"Clinical feasibility of accelerated diffusion weighted imaging of the abdomen with deep learning reconstruction: comparison with conventional diffusion weighted imaging","volume":"154","author":"Bae","year":"2022","journal-title":"Eur J Radiol"},{"issue":"6","key":"10.1016\/j.mri.2025.110418_bb0125","doi-asserted-by":"crossref","first-page":"853","DOI":"10.1097\/RCT.0000000000001622","article-title":"Accelerated diffusion-weighted magnetic resonance imaging of the liver at 1.5 T with deep learning-based image reconstruction: impact on image quality and lesion detection","volume":"48","author":"Ginocchio","year":"2024","journal-title":"J Comput Assist Tomogr"},{"issue":"2","key":"10.1016\/j.mri.2025.110418_bb0130","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1148\/radiol.204097","article-title":"Deep learning reconstruction of diffusion-weighted MRI improves image quality for prostatic imaging","volume":"303","author":"Ueda","year":"2022","journal-title":"Radiology"},{"key":"10.1016\/j.mri.2025.110418_bb0135","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.mri.2022.06.014","article-title":"Feasibility of accelerated whole-body diffusion-weighted imaging using a deep learning-based noise-reduction technique in patients with prostate cancer","volume":"92","author":"Tajima","year":"2022","journal-title":"Magn Reson Imaging"},{"issue":"2","key":"10.1016\/j.mri.2025.110418_bb0140","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.210059","article-title":"Clinical assessment of deep learning-based super-resolution for 3D volumetric brain MRI","volume":"4","author":"Rudie","year":"2022","journal-title":"Radiol Artif Intell"}],"container-title":["Magnetic Resonance Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0730725X2500102X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0730725X2500102X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T02:12:34Z","timestamp":1762308754000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0730725X2500102X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":28,"alternative-id":["S0730725X2500102X"],"URL":"https:\/\/doi.org\/10.1016\/j.mri.2025.110418","relation":{},"ISSN":["0730-725X"],"issn-type":[{"value":"0730-725X","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Accelerating prostate rs-EPI DWI with deep learning: Halving scan time, enhancing image quality, and validating in vivo","name":"articletitle","label":"Article Title"},{"value":"Magnetic Resonance Imaging","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.mri.2025.110418","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"110418"}}