{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T08:36:02Z","timestamp":1790325362834,"version":"4.1.0"},"reference-count":53,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T00:00:00Z","timestamp":1748390400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000070","name":"National Institute of Biomedical Imaging and Bioengineering","doi-asserted-by":"publisher","award":["R01\u2010EB029431"],"award-info":[{"award-number":["R01\u2010EB029431"]}],"id":[{"id":"10.13039\/100000070","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":[[2025,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Deformable image registration (DIR) is an enabling technology in many diagnostic and therapeutic tasks. Despite this, DIR algorithms have limited clinical use, largely due to a lack of benchmark datasets for quality assurance during development. DIRs of intra\u2010patient abdominal CTs are among the most challenging registration scenarios due to significant organ deformations and inconsistent image content. To support future algorithm development, here we introduce our first\u2010of\u2010its\u2010kind abdominal CT DIR benchmark dataset, comprising large numbers of highly accurate landmark pairs on matching blood vessel bifurcations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Acquisition and Validation Methods<\/jats:title>\n                    <jats:p>Abdominal CT image pairs of 30 patients were acquired from several publicly available repositories as well as the\u00a0authors\u2019 institution with IRB approval. The two CTs of each pair were originally acquired for the same patient but on\u00a0different days. An image processing workflow was developed and applied to each CT image pair: (1) Abdominal organs were segmented with a deep learning model, and image intensity within organ masks was overwritten. (2) Matching image patches were manually identified between two CTs of each image pair. (3) Vessel bifurcation landmarks were labeled on one image of each image patch pair. (4) Image patches were deformably registered, and landmarks were projected onto the second image. (5) Landmark pair locations were refined manually or with an automated process. This workflow resulted in 1895 total landmark pairs, or 63 per case on average. Estimates of the landmark pair accuracy using digital phantoms were 0.7\u00a0mm\u00a0\u00b1\u00a01.2\u00a0mm.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Format and Usage Notes<\/jats:title>\n                    <jats:p>\n                      The data are published in Zenodo at\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/doi.org\/10.5281\/zenodo.14362785\">https:\/\/doi.org\/10.5281\/zenodo.14362785<\/jats:ext-link>\n                      . Instructions for use can be found at\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/deshanyang\/Abdominal-DIR-QA\">https:\/\/github.com\/deshanyang\/Abdominal\u2010DIR\u2010QA<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Potential Applications<\/jats:title>\n                    <jats:p>This dataset is a first\u2010of\u2010its\u2010kind for abdominal DIR validation. The number, accuracy, and distribution of landmark pairs will allow for robust validation of DIR algorithms with precision beyond what is currently available.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.17907","type":"journal-article","created":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T01:10:02Z","timestamp":1748481002000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A vessel bifurcation landmark pair dataset for abdominal CT deformable image registration (DIR) validation"],"prefix":"10.1002","volume":"52","author":[{"given":"Edward R.","family":"Criscuolo","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Duke University  Durham North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhendong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Duke University  Durham North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yao","family":"Hao","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Washington University School of Medicine  St. Louis Missouri USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deshan","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology Duke University  Durham North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,5,28]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.12256"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev\u2010bioeng\u2010071910\u2010124649"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/46\/3\/201"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.47739\/2333\u20107095\/1042"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.3857\/roj.2017.00325"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2007.01.038"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/53\/17\/005"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2008.07.001"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.2839103"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2008.04.013"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev\u2010bioeng\u2010070909\u2010105249"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2014.06.045"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.06.030"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13162"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2009.06.031"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2015.01.007"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2011.2163944"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/58\/18\/6481"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1120\/jacmp.v14i1.4066"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1120\/jacmp.v14i1.3834"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1093\/jrr\/rrt093"},{"key":"e_1_2_9_23_1","unstructured":"VandemeulebrouckeJ SarrutD ClarysseP The POPI\u2010model a point\u2010validated pixel\u2010based breathing thorax model. 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