{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T17:39:37Z","timestamp":1742924377201,"version":"3.40.3"},"publisher-location":"Wiesbaden","reference-count":10,"publisher":"Springer Fachmedien Wiesbaden","isbn-type":[{"type":"print","value":"9783658253257"},{"type":"electronic","value":"9783658253264"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-658-25326-4_41","type":"book-chapter","created":{"date-parts":[[2019,2,6]],"date-time":"2019-02-06T01:42:34Z","timestamp":1549417354000},"page":"191-196","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Workflow Phase Detection in Fluoroscopic Images Using Convolutional Neural Networks"],"prefix":"10.1007","author":[{"given":"Nikolaus","family":"Arbogast","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tanja","family":"Kurzendorfer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katharina","family":"Breininger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Mountney","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Toth","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Srinivas A.","family":"Narayan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Maier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,2,7]]},"reference":[{"issue":"4","key":"41_CR1","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1016\/j.ejvs.2013.06.012","volume":"46","author":"C.D. Bicknell","year":"2013","unstructured":"Bicknell C. Occupational radiation exposure and the vascular interventionalist. Eur J Vasc Endovasc Surg. 2013;46(4):431.","journal-title":"European Journal of Vascular and Endovascular Surgery"},{"issue":"2","key":"41_CR2","doi-asserted-by":"publisher","first-page":"297","DOI":"10.2106\/JBJS.H.00407","volume":"91","author":"Brian D Giordano","year":"2009","unstructured":"Giordano BD, Baumhauer JF, Morgan TL, et al. Patient and surgeon radiation exposure: comparison of standard and mini-C-arm uoroscopy. J Bone Joint Surg Am. 2009;91(2):297\u2013304.","journal-title":"The Journal of Bone and Joint Surgery-American Volume"},{"issue":"2","key":"41_CR3","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1161\/CIRCULATIONAHA.113.005425","volume":"130","author":"Jason N. Johnson","year":"2014","unstructured":"Johnson JN, Hornik CP, Li JS, et al. Cumulative radiation exposure and cancer risk estimation in children with heart disease. Circ. 2014;130(2):161\u2013167.","journal-title":"Circulation"},{"key":"41_CR4","unstructured":"DiPietro R, Stauder R, Kayis E, et al. Automated surgical-phase recognition using rapidly-deployable sensors. Proc MICCAI Workshop M2CAI. 2015;."},{"key":"41_CR5","doi-asserted-by":"crossref","unstructured":"Twinanda AP, Yengera G, Mutter D, et al. RSDNet: learning to predict remaining surgery duration from laparoscopic videos without manual annotations. \n                  arXiv:180203243\n                  \n                . 2018;.","DOI":"10.1109\/TMI.2018.2878055"},{"key":"41_CR6","unstructured":"Alhrishy M, Toth D, Narayan SA, et al. A machine learning framework for context specific collimation and workflow phase detection. Comput Methods Biomech Biomed Engin. 2018;."},{"key":"41_CR7","unstructured":"Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks. Adv Neural Inf Process Syst. 2012; p. 1097\u20131105."},{"key":"41_CR8","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, et al. Deep residual learning for image recognition. Proc CVPR. 2016; p. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"41_CR9","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, et al. Delving deep into rectifiers: surpassing human-level performance on imagenet classification. Proc ICCV. 2015; p. 1026\u20131034.","DOI":"10.1109\/ICCV.2015.123"},{"issue":"8","key":"41_CR10","doi-asserted-by":"publisher","first-page":"1221","DOI":"10.1007\/s11548-018-1779-6","volume":"13","author":"Katharina Breininger","year":"2018","unstructured":"Breininger K, Albarqouni S, Kurzendorfer T, et al. Intraoperative stent segmentation in X-ray uoroscopy for endovascular aortic repair. Int J Comput Assist Radiol Surg. 2018;13(8).","journal-title":"International Journal of Computer Assisted Radiology and Surgery"}],"container-title":["Informatik aktuell","Bildverarbeitung f\u00fcr die Medizin 2019"],"original-title":[],"language":"de","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-658-25326-4_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,18]],"date-time":"2019-05-18T06:02:21Z","timestamp":1558159341000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-658-25326-4_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783658253257","9783658253264"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-658-25326-4_41","relation":{},"ISSN":["1431-472X"],"issn-type":[{"type":"print","value":"1431-472X"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"7 February 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}