Robotic-Assisted Surgery

Collaboration with Laura Bravo and Dr. Nicolás Fernandez, Urology Department, Fundación Santa Fe de Bogotá

semantic segmentation of surgical scenes is a fundamental task that must be solved in the pursuit of autonomous robot-assisted surgeries and image-guided interventions. The objective of this task is to create an automatic method for identifying and spatially limiting the relevant objects in a surgical scene. This task is the first step towards solving computer-aided surgery problems such as overlay and 3D reconstruction of organs, instrument tracking, navigation, and programming of robot arms for precision and strength critical tasks. Our work mostly focuses on footage from robotic-assisted surgery scenes, however the methods developed for natural images are directly applicable to laparoscopic surgery scenes, thus widening the scope and range of applications for our work.

Presentation video


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

Tobias Ross, Annika Reinke, Peter M Full, Martin Wagner, Hannes Kenngott, Martin Apitz, Hellena Hempe, Diana Mindroc-Filimon, Patrick Scholz, Thuy Nuong Tran, Pierangela Bruno, Pablo Arbeláez, Gui-Bin Bian, Sebastian Bodenstedt, Jon Lindström Bolmgren, Laura Bravo-Sánchez, Hua-Bin Chen, Cristina González, Dong Guo, Pål Halvorsen, Pheng-Ann Heng, Enes Hosgor, Zeng-Guang Hou, Fabian Isensee, Debesh Jha, Tingting Jiang, Yueming Jin, Kadir Kirtac, Sabrina Kletz, Stefan Leger, Zhixuan Li, Klaus H Maier-Hein, Zhen-Liang Ni, Michael A Riegler, Klaus Schoeffmann, Ruohua Shi, Stefanie Speidel, Michael Stenzel, Isabell Twick, Gutai Wang, Jiacheng Wang, Liansheng Wang, Lu Wang, Yujie Zhang, Yan-Jie Zhou, Lei Zhu, Manuel Wiesenfarth, Annette Kopp-Schneider, Beat P Müller-Stich, Lena Maier-Hein

Medical image analysis




Our team Uniandes won 5 awards at the Robust Endoscopic Instrument Segmentation Challenge 2019 (ROBUST-MIS) as a part of MICCAI 2019. Our method won first place in the Multiple Instance Detection task, and in the Multiple Instance Segmentation task we won one first place and two second places.

Challenge page | Challenge results

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Recognition as University: Decree 1297 of May 30th, 1964.
Recognition as legal entity: Resolution 28 of February 23, 1949 Minjusticia.

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