{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T02:54:36Z","timestamp":1772247276450,"version":"3.50.1"},"reference-count":45,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,21]]},"DOI":"10.1109\/icpr56361.2022.9956530","type":"proceedings-article","created":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T19:34:13Z","timestamp":1669750453000},"page":"5096-5103","source":"Crossref","is-referenced-by-count":5,"title":["Pixel-accurate Segmentation of Surgical Tools based on Bounding Box Annotations"],"prefix":"10.1109","author":[{"given":"George","family":"Leifman","sequence":"first","affiliation":[{"name":"Google Research"}]},{"given":"Amit","family":"Aides","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Tomer","family":"Golany","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Daniel","family":"Freedman","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Ehud","family":"Rivlin","sequence":"additional","affiliation":[{"name":"Google Research"}]}],"member":"263","reference":[{"key":"ref39","first-page":"740","article-title":"Microsoft coco: Common objects in context","author":"lin","year":"2014","journal-title":"European Conference on Computer Vision"},{"key":"ref38","first-page":"483","article-title":"Stacked hourglass networks for human pose estimation","author":"newell","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59716-0_67"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3056354"},{"key":"ref31","first-page":"326","article-title":"Davincigan: Unpaired surgical instrument translation for data augmentation","author":"lee","year":"2019","journal-title":"International Conference on Medical Imaging with Deep Learning"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32254-0_14"},{"key":"ref37","article-title":"Objects as points","author":"zhou","year":"2019"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00693"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-021-02383-4"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59716-0_75"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.05.004"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2837502"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206462"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2017.8123151"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32692-0_65"},{"key":"ref15","author":"community","year":"2018","journal-title":"Blender - a 3D modelling and rendering package"},{"key":"ref16","article-title":"Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery","author":"bodenstedt","year":"2018"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-015-1291-1"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101920"},{"key":"ref19","article-title":"Ternausnet: U-net with vgg11 encoder pre-trained on imagenet for image segmentation","author":"iglovikov","year":"2018"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340816"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00081"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3057884"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.4240\/wjgs.v11.i2.62"},{"key":"ref6","first-page":"314","article-title":"Segmentation and guidance of multiple rigid objects for intra-operative endoscopic vision","author":"doignon","year":"2006","journal-title":"Dynamical Vision"},{"key":"ref29","article-title":"Cyclegan","author":"chen","year":"2020"},{"key":"ref5","first-page":"93","article-title":"Automatic sinus surgery skill assessment based on instrument segmentation and tracking in endoscopic video","author":"lin","year":"2019","journal-title":"International Workshop on Multiscale Multimodal Medical Imaging"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2450831"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s00268-020-05908-1"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","article-title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","volume":"40","author":"chen","year":"2017","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2593957"},{"key":"ref20","article-title":"nnu-net: Self-adapting framework for u-net-based medical image segmentation","author":"isensee","year":"2018"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00342"},{"key":"ref22","first-page":"801","article-title":"Encoder-decoder with atrous separable convolution for semantic image segmentation","author":"chen","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59716-0_57"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00928-1_48"},{"key":"ref41","article-title":"2017 robotic instrument segmentation challenge","author":"allan","year":"2019"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9196905"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1145\/1015706.1015720","article-title":"grabcut&#x201D; interactive foreground extraction using iterated graph cuts","volume":"23","author":"rother","year":"2004","journal-title":"ACM Transactions on Graphics (TOG)"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s11548-019-02003-2"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2019.8856495"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2018.00100"}],"event":{"name":"2022 26th International Conference on Pattern Recognition (ICPR)","location":"Montreal, QC, Canada","start":{"date-parts":[[2022,8,21]]},"end":{"date-parts":[[2022,8,25]]}},"container-title":["2022 26th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9956007\/9955631\/09956530.pdf?arnumber=9956530","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T20:06:40Z","timestamp":1671480400000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9956530\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,21]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/icpr56361.2022.9956530","relation":{},"subject":[],"published":{"date-parts":[[2022,8,21]]}}}