{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T02:54:49Z","timestamp":1772247289554,"version":"3.50.1"},"reference-count":19,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2017,3,29]],"date-time":"2017-03-29T00:00:00Z","timestamp":1490745600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"German Federal Ministry of Education and Research (BMBF)","award":["16 5V 7257"],"award-info":[{"award-number":["16 5V 7257"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"published-print":{"date-parts":[[2017,6]]},"DOI":"10.1007\/s11548-017-1565-x","type":"journal-article","created":{"date-parts":[[2017,3,29]],"date-time":"2017-03-29T15:46:24Z","timestamp":1490802384000},"page":"1013-1020","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Addressing multi-label imbalance problem of surgical tool detection using CNN"],"prefix":"10.1007","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2158-823X","authenticated-orcid":false,"given":"Manish","family":"Sahu","sequence":"first","affiliation":[]},{"given":"Anirban","family":"Mukhopadhyay","sequence":"additional","affiliation":[]},{"given":"Angelika","family":"Szengel","sequence":"additional","affiliation":[]},{"given":"Stefan","family":"Zachow","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,3,29]]},"reference":[{"key":"1565_CR1","doi-asserted-by":"crossref","unstructured":"Allan M, Chang PL, Ourselin S, Hawkes DJ, Sridhar A, Kelly J, Stoyanov D (2015) Image based surgical instrument pose estimation with multi-class labelling and optical flow. In: International conference on medical image computing and computer-assisted intervention, Springer, pp 331\u2013338","DOI":"10.1007\/978-3-319-24553-9_41"},{"key":"1565_CR2","doi-asserted-by":"crossref","unstructured":"Blum T, Feu\u00dfner H, Navab N (2010) Modeling and segmentation of surgical workflow from laparoscopic video. In: International conference on medical image computing and computer-assisted intervention, Springer, pp 400\u2013407","DOI":"10.1007\/978-3-642-15711-0_50"},{"issue":"12","key":"1565_CR3","doi-asserted-by":"crossref","first-page":"2603","DOI":"10.1109\/TMI.2015.2450831","volume":"34","author":"D Bouget","year":"2015","unstructured":"Bouget D, Benenson R, Omran M, Riffaud L, Schiele B, Jannin P (2015) Detecting surgical tools by modelling local appearance and global shape. IEEE Trans Med Imaging 34(12):2603\u20132617","journal-title":"IEEE Trans Med Imaging"},{"key":"1565_CR4","doi-asserted-by":"crossref","unstructured":"Charte F, Rivera AJ, del Jesus MJ, Herrera F (2015) Addressing imbalance in multilabel classification: measures and random resampling algorithms. Neurocomputing 163:3\u201316","DOI":"10.1016\/j.neucom.2014.08.091"},{"key":"1565_CR5","volume-title":"To err is human: building a safer health system","author":"MS Donaldson","year":"2000","unstructured":"Donaldson MS, Corrigan JM, Kohn LT (2000) To err is human: building a safer health system, vol 6. National Academies Press, Washington"},{"key":"1565_CR6","doi-asserted-by":"crossref","unstructured":"Gu Z, Gu L, Eils R, Schlesner M, Brors B (2014) circlize implements and enhances circular visualization in R. Bioinformatics. Oxford Univ Press, p btu393","DOI":"10.1093\/bioinformatics\/btu393"},{"key":"1565_CR7","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp 1097\u20131105"},{"issue":"12","key":"1565_CR8","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1109\/TVCG.2014.2346248","volume":"20","author":"A Lex","year":"2014","unstructured":"Lex A, Gehlenborg N, Strobelt H, Vuillemot R, Pfister H (2014) Upset: visualization of intersecting sets. IEEE Trans Visual Comput Graphics 20(12):1983\u20131992","journal-title":"IEEE Trans Visual Comput Graphics"},{"issue":"3","key":"1565_CR9","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1016\/j.media.2010.10.001","volume":"16","author":"N Padoy","year":"2012","unstructured":"Padoy N, Blum T, Ahmadi SA, Feussner H, Berger MO, Navab N (2012) Statistical modeling and recognition of surgical workflow. Med Image Anal 16(3):632\u2013641","journal-title":"Med Image Anal"},{"key":"1565_CR10","unstructured":"Raju A, Wang S, Huang J (2016) M2cai surgical tool detection challenge report. http:\/\/camma.u-strasbg.fr\/m2cai2016\/reports\/Raju-Tool.pdf"},{"issue":"1","key":"1565_CR11","first-page":"33","volume":"5","author":"M Sahu","year":"2016","unstructured":"Sahu M, Moerman D, Mewes P, Mountney P, Rose G (2016a) Instrument state recognition and tracking for effective control of robotized laparoscopic systems. Int J Mech Eng Rob Res 5(1):33","journal-title":"Int J Mech Eng Rob Res"},{"key":"1565_CR12","unstructured":"Sahu M, Mukhopadhyay A, Szengel A, Zachow S (2016b) Tool and phase recognition using contextual CNN features. arXiv preprint arXiv:1610.08854"},{"key":"1565_CR13","doi-asserted-by":"crossref","unstructured":"Sechidis K, Tsoumakas G, Vlahavas I (2011) On the stratification of multi-label data. In: Joint European conference on machine learning and knowledge discovery in databases, Springer, pp 145\u2013158","DOI":"10.1007\/978-3-642-23808-6_10"},{"key":"1565_CR14","doi-asserted-by":"crossref","unstructured":"Speidel S, Benzko J, Krappe S, Sudra G, Azad P, M\u00fcller-Stich BP, Gutt C, Dillmann R (2009) Automatic classification of minimally invasive instruments based on endoscopic image sequences. In: SPIE medical imaging, International society for optics and photonics, p 72,610A","DOI":"10.1117\/12.811112"},{"key":"1565_CR15","doi-asserted-by":"crossref","unstructured":"Sznitman R, Becker C, Fua P (2014) Fast part-based classification for instrument detection in minimally invasive surgery. In: International conference on medical image computing and computer-assisted intervention, Springer, pp 692\u2013699","DOI":"10.1007\/978-3-319-10470-6_86"},{"key":"1565_CR16","unstructured":"Twinanda AP, Mutter D, Marescaux J, de\u00a0Mathelin M, Padoy N (2016a) Single- and multi-task architectures for tool presence detection challenge at M2CAI 2016. arXiv preprint arXiv:1610.08851"},{"key":"1565_CR17","doi-asserted-by":"crossref","unstructured":"Twinanda AP, Shehata S, Mutter D, Marescaux J, de\u00a0Mathelin M, Padoy N (2016b) Endonet: a deep architecture for recognition tasks on laparoscopic videos. arXiv preprint arXiv:1602.03012","DOI":"10.1109\/TMI.2016.2593957"},{"issue":"11\u201312","key":"1565_CR18","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1177\/0278364907083395","volume":"26","author":"S Voros","year":"2007","unstructured":"Voros S, Long JA, Cinquin P (2007) Automatic detection of instruments in laparoscopic images: a first step towards high-level command of robotic endoscopic holders. Int J Rob Res 26(11\u201312):1173\u20131190","journal-title":"Int J Rob Res"},{"issue":"7","key":"1565_CR19","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1016\/j.media.2013.04.007","volume":"17","author":"L Zappella","year":"2013","unstructured":"Zappella L, B\u00e9jar B, Hager G, Vidal R (2013) Surgical gesture classification from video and kinematic data. Med Image Anal 17(7):732\u2013745","journal-title":"Med Image Anal"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11548-017-1565-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-017-1565-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-017-1565-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T06:15:47Z","timestamp":1568960147000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11548-017-1565-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,3,29]]},"references-count":19,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2017,6]]}},"alternative-id":["1565"],"URL":"https:\/\/doi.org\/10.1007\/s11548-017-1565-x","relation":{},"ISSN":["1861-6410","1861-6429"],"issn-type":[{"value":"1861-6410","type":"print"},{"value":"1861-6429","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,3,29]]}}}