{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T22:50:04Z","timestamp":1761778204939,"version":"build-2065373602"},"reference-count":19,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T00:00:00Z","timestamp":1737936000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T00:00:00Z","timestamp":1737936000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging. Inform. med."],"DOI":"10.1007\/s10278-024-01349-7","type":"journal-article","created":{"date-parts":[[2025,1,27]],"date-time":"2025-01-27T15:19:55Z","timestamp":1737991195000},"page":"2951-2957","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Validation of UniverSeg for Interventional Abdominal Angiographic Segmentation"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-4145-5471","authenticated-orcid":false,"given":"Michael","family":"Kovalchick","sequence":"first","affiliation":[]},{"given":"Hyeok Jun","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Chad","family":"Klochko","sequence":"additional","affiliation":[]},{"given":"Kundan","family":"Thind","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,27]]},"reference":[{"key":"1349_CR1","doi-asserted-by":"publisher","first-page":"778","DOI":"10.3390\/diagnostics12040778","volume":"12","author":"T Park","year":"2022","unstructured":"Park T, Khang S, Jeong H, Koo K, Lee J, Shin J, Kang HC: Deep learning segmentation in 2D X-ray images and non-rigid registration in multi-modality images of coronary arteries. Diagnostics (Basel) 12:778, 2022.","journal-title":"Diagnostics (Basel)"},{"key":"1349_CR2","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1016\/B978-0-444-63578-5.50101-8","volume":"37","author":"M Ghaffari","year":"2015","unstructured":"Ghaffari M, Hsu CY, Linninger AA:\u00a0Automatic reconstruction and generation of structured hexahedral mesh for non-planar bifurcations in vascular networks. Computer Aided Chemical Engineering 37:635-640, 2015","journal-title":"Computer Aided Chemical Engineering"},{"key":"1349_CR3","doi-asserted-by":"publisher","unstructured":"Chen YC, Lin YC, Wang CP, Lee CY, Lee WJ, Wang TD, Chen CM: Coronary artery segmentation in cardiac CT angiography using 3D multi-channel U-net.\u00a0arXiv. https:\/\/doi.org\/10.48550\/arXiv.1907.12246, July 29, 2019","DOI":"10.48550\/arXiv.1907.12246"},{"key":"1349_CR4","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1002\/jmri.28315","volume":"57","author":"M Asaduddin","year":"2023","unstructured":"Asaduddin M, Roh HG, Kim HJ, Kim EY, Park SH: Perfusion maps acquired from dynamic angiography MRI using deep learning approaches. J Magn Reson Imaging 57:456-469, 2023","journal-title":"J Magn Reson Imaging"},{"key":"1349_CR5","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.3390\/diagnostics13132274","volume":"13","author":"S Kaba","year":"2023","unstructured":"Kaba S, Haci H, Isin A, Ilhan A, Conkbayir C. The application of deep learning for the segmentation and classification of coronary arteries. Diagnostics 13:2274, 2023","journal-title":"Diagnostics"},{"key":"1349_CR6","doi-asserted-by":"publisher","first-page":"18066","DOI":"10.1038\/s41598-021-97355-8","volume":"11","author":"K Iyer","year":"2021","unstructured":"Iyer K, Najarian CP, Fattah AA, Arthurs CJ, Soroushmehr SMR, Subban V, Sankardas MA, Nadakuditi RR, Nallamothu BK, Figueroa CA: AngioNet: a convolutional neural network for vessel segmentation in X-ray angiography. Sci Rep 11:18066, 2021","journal-title":"Sci Rep"},{"key":"1349_CR7","doi-asserted-by":"crossref","unstructured":"Butoi VI, Gonzalez Ortiz JJ, Ma T, Sabuncu MR, Guttag J, Dalca AV: UniverSeg: universal medical image segmentation. In: 2023 IEEE\/CVF International Conference on Computer Vision, Paris, France, 21381\u201321394, 2023","DOI":"10.1109\/ICCV51070.2023.01960"},{"key":"1349_CR8","doi-asserted-by":"crossref","unstructured":"Lopes I, Vu TH, Charette R: Cross-task attention mechanism for dense multi-task learning. In: 2023 IEEE\/CVF Winter Conference on Applications of Computer Vision, Waikoloa, HI, 2328\u20132337, 2023","DOI":"10.1109\/WACV56688.2023.00236"},{"key":"1349_CR9","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1186\/s41747-020-00200-2","volume":"5","author":"OU Aydin","year":"2021","unstructured":"Aydin OU, Taha AA, Hilbert A, Khalil AA, Galinovic I, Fiebach JB, Frey D, Madai VI: On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking. Eur Radiol Exp 5:4, 2021","journal-title":"Eur Radiol Exp"},{"key":"1349_CR10","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee, F., Jaeger, P.F., Kohl, S.A.A.\u00a0et al.\u00a0nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation.\u00a0Nat Methods\u00a018, 203\u2013211 (2021).","journal-title":"Nat Methods"},{"key":"1349_CR11","doi-asserted-by":"crossref","unstructured":"Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander\u00a0C Berg, Wan-Yen Lo, et\u00a0al: Segment Anything.arXiv:2304.02643, 2023.","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"1349_CR12","unstructured":"Weiyi Xie, Nathalie Willems, Shubham Patil, Yang Li, Mayank Kumar: SAM Fewshot Finetuning for Anatomical Segmentation in Medical Images. arXiv: 2407.04651v1, 05 Jul 2024"},{"key":"1349_CR13","first-page":"527","volume":"31","author":"O Sener","year":"2018","unstructured":"Sener O, Koltun V: Multi-task learning as multi-objective optimization. Advances in Neural Information Processing Systems 31:527-538, 2018","journal-title":"Advances in Neural Information Processing Systems"},{"key":"1349_CR14","doi-asserted-by":"publisher","first-page":"321","DOI":"10.14740\/jocmr3356w","volume":"10","author":"DF Pinal-Garcia","year":"2018","unstructured":"Pinal-Garcia DF, Nuno-Guzman CM, Gonzalez-Gonzalez ME, Ibarra-Hurtado TR: The celiac trunk and its anatomical variations: a cadaveric study. J Clin Med Res 10:321-329, 2018","journal-title":"J Clin Med Res"},{"key":"1349_CR15","doi-asserted-by":"publisher","first-page":"6138659","DOI":"10.1155\/2016\/6138659","volume":"2016","author":"D Drobnjak","year":"2016","unstructured":"Drobnjak D, Munch IC, Gl\u00fcmer C, Faerch K, Kessel L, Larsen M, Veiby NC: Retinal vessel diameters and their relationship with cardiovascular risk and all-cause mortality in the Inter99 Eye Study: a 15-year follow-up. J Ophthalmol 2016:6138659, 2016","journal-title":"J Ophthalmol"},{"key":"1349_CR16","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1016\/S0735-1097(84)80219-3","volume":"4","author":"FH Burbank","year":"1984","unstructured":"Burbank FH, Brody WR, Bradley BR: Effect of volume and rate of contrast medium injection on intravenous digital subtraction angiographic contrast medium curves. J Am Coll Cardiol 4:308-315, 1984","journal-title":"J Am Coll Cardiol"},{"key":"1349_CR17","doi-asserted-by":"publisher","first-page":"e14266","DOI":"10.1002\/acm2.14266","volume":"25","author":"X Wang","year":"2024","unstructured":"Wang X, Hao Y, Duan Y, Yang D: A deep learning approach to remove contrast from contrast-enhanced CT for proton dose calculation. J Appl Clin Med Phys 25:e14266, 2024","journal-title":"J Appl Clin Med Phys"},{"key":"1349_CR18","doi-asserted-by":"publisher","first-page":"202","DOI":"10.18178\/ijmlc.2021.11.3.1036","volume":"11","author":"K Sriwong","year":"2021","unstructured":"Sriwong K, Kerdprasop K, Kerdprasop N: The study of noise effect on CNN-based deep learning from medical images. Int J Mach Learn Comput 11:202-207, 2021","journal-title":"Int J Mach Learn Comput"},{"key":"1349_CR19","doi-asserted-by":"publisher","first-page":"156","DOI":"10.5152\/dir.2016.16230","volume":"23","author":"D Aberle","year":"2017","unstructured":"Aberle D, Charles H, Hodak S, O'Neill D, Oklu R, Deipolyi AR: Optimizing care for the obese patient in interventional radiology. Diagn Interv Radiol 23:156-162, 2017","journal-title":"Diagn Interv Radiol"}],"container-title":["Journal of Imaging Informatics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-024-01349-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10278-024-01349-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-024-01349-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T22:48:33Z","timestamp":1761778113000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10278-024-01349-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,27]]},"references-count":19,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["1349"],"URL":"https:\/\/doi.org\/10.1007\/s10278-024-01349-7","relation":{},"ISSN":["2948-2933"],"issn-type":[{"type":"electronic","value":"2948-2933"}],"subject":[],"published":{"date-parts":[[2025,1,27]]},"assertion":[{"value":"5 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 November 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}