• Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge 

      Ross, Tobias; Reinke, Annika; M. Full, Peter; Wagner, Martin; Kenngott, Hannes; Apitz, Martin; Hempe, Hellena; Mindroc Filimon, Diana; Scholz, Patrick; Tran, Thuy Nuong; Bruno, Pierangela; Arbeláez, Pablo; Bian, Gui-Bin; Bodenstedt, Sebastian; Lindström Bolmgren, Jon; Bravo-Sánchez, Laura; Chen, Hua-Bin; González, Cristina; Guo, Dong; Halvorsen, Pål; Heng, Pheng-Ann; Hosgor, Enes; Hou, Zeng-Guang; Isensee, Fabian; Jha, Debesh; Jiang, Tingting; Jin, Yueming; Kirtac, Kadir; Kletz, Sabrina; Leger, Stefan; Li, Zhixuan; H. Maier-Hein, Klaus; Ni, Zhen-Liang; Riegler, Michael; Schoeffmann, Klaus; Shi, Ruohua; Speidel, Stefanie; Stenzel, Michael; Twick, Isabell; Wang, Gutai; Wang, Jiacheng; Wang, Liansheng; Wang, Lu; Zhang, Yujie; Zhou, Yan-Jie; Zhu, Lei; Wiesenfarth, Manuel; Kopp-Schneider, Annette; P. Müller-Stich, Beat; Maier-Hein, Lena (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-28)
      Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and roboticassisted interventions. While numerous methods for detecting, segmenting and tracking of medical instruments based on endoscopic video images have been proposed in the literature, key limitations remain to be addressed: Firstly, robustness, that is, the reliable performance of state-of-the-art methods ...