{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T12:32:07Z","timestamp":1787920327407,"version":"build-2784847793"},"reference-count":36,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2020,8,2]],"date-time":"2020-08-02T00:00:00Z","timestamp":1596326400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01CA215718"],"award-info":[{"award-number":["R01CA215718"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2020,9]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>Segmentation of organs\u2010at\u2010risk (OARs) is a weak link in radiotherapeutic treatment planning process because the manual contouring action is labor\u2010intensive and time\u2010consuming. This work aimed to develop a deep learning\u2010based method for rapid and accurate pancreatic multi\u2010organ segmentation that can expedite the treatment planning process.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We retrospectively investigated one hundred patients with computed tomography (CT) simulation scanned and contours delineated. Eight OARs including large bowel, small bowel, duodenum, left kidney, right kidney, liver, spinal cord and stomach were the target organs to be segmented. The proposed three\u2010dimensional (3D) deep attention U\u2010Net is featured with a deep attention strategy to effectively differentiate multiple organs. Performance of the proposed method was evaluated using six metrics, including Dice similarity coefficient (DSC), sensitivity, specificity, Hausdorff distance 95% (HD95), mean surface distance (MSD) and residual mean square distance (RMSD).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The contours generated by the proposed method closely resemble the ground\u2010truth manual contours, as evidenced by encouraging quantitative results in terms of DSC, sensitivity, specificity, HD95, MSD and RMSD. For DSC, mean values of 0.91\u00a0\u00b1\u00a00.03, 0.89\u00a0\u00b1\u00a00.06, 0.86\u00a0\u00b1\u00a00.06, 0.95\u00a0\u00b1\u00a00.02, 0.95\u00a0\u00b1\u00a00.02, 0.96\u00a0\u00b1\u00a00.01, 0.87\u00a0\u00b1\u00a00.05 and 0.93\u00a0\u00b1\u00a00.03 were achieved for large bowel, small bowel, duodenum, left kidney, right kidney, liver, spinal cord and stomach, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The proposed method could significantly expedite the treatment planning process by rapidly segmenting multiple OARs. The method could potentially be used in pancreatic adaptive radiotherapy to increase dose delivery accuracy and minimize gastrointestinal toxicity.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.14386","type":"journal-article","created":{"date-parts":[[2020,7,12]],"date-time":"2020-07-12T13:50:52Z","timestamp":1594561852000},"page":"4316-4324","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["CT\u2010based multi\u2010organ segmentation using a 3D self\u2010attention U\u2010net network for pancreatic radiotherapy"],"prefix":"10.1002","volume":"47","author":[{"given":"Yingzi","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Lei","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yabo","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tonghe","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyang","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Radiology and Imaging Sciences and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojun","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Walter J.","family":"Curran","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tian","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pretesh","family":"Patel","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaofeng","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Winship Cancer Institute Emory University Atlanta GA 30322 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2020,8,2]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21551"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2014.10.015"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13014-019-1275-3"},{"key":"e_1_2_7_5_1","first-page":"e1618","article-title":"Online adaptive radiation therapy: implementation of a new process of care","volume":"9","author":"Lamb J","year":"2017","journal-title":"Cureus"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13014-018-1000-7"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2011.12.073"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2019.01.020"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2018.08.009"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13458"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.04.005"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4962468"},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2003.809139"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2012.02.001"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2265805"},{"key":"e_1_2_7_16_1","doi-asserted-by":"crossref","unstructured":"ChuC OdaM KitasakaT et al.Multi\u2010organ Segmentation Based on Spatially\u2010Divided Probabilistic Atlas from 3D Abdominal CT Images. 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