no code implementations • 25 Sep 2023 • Felix Holm, Ghazal Ghazaei, Tobias Czempiel, Ege Özsoy, Stefan Saur, Nassir Navab
Surgical videos captured from microscopic or endoscopic imaging devices are rich but complex sources of information, depicting different tools and anatomical structures utilized during an extended amount of time.
1 code implementation • 11 Jul 2023 • Chantal Pellegrini, Matthias Keicher, Ege Özsoy, Nassir Navab
However, there is limited research on automating structured reporting, and no public benchmark is available for evaluating and comparing different methods.
Ranked #1 on
Structured Report Generation
on Rad-ReStruct
no code implementations • 30 Mar 2023 • Dominik Batić, Felix Holm, Ege Özsoy, Tobias Czempiel, Nassir Navab
In this work, we investigate the need for endoscopy domain-specific pretraining based on downstream objectives.
1 code implementation • 23 Mar 2023 • Chantal Pellegrini, Matthias Keicher, Ege Özsoy, Petra Jiraskova, Rickmer Braren, Nassir Navab
Automated diagnosis prediction from medical images is a valuable resource to support clinical decision-making.
no code implementations • 23 Mar 2023 • Ege Özsoy, Tobias Czempiel, Felix Holm, Chantal Pellegrini, Nassir Navab
The holistic representation of surgical scenes as semantic scene graphs (SGG), where entities are represented as nodes and relations between them as edges, is a promising direction for fine-grained semantic OR understanding.
Ranked #2 on
Scene Graph Generation
on 4D-OR
no code implementations • 20 Mar 2023 • Ege Özsoy, Felix Holm, Tobias Czempiel, Nassir Navab, Benjamin Busam
Although using significantly fewer labels during training, we achieve 74. 12\% of the location-supervised SOTA performance on Visual Genome and even outperform the best method on 4D-OR.
Ranked #1 on
Scene Graph Generation
on 4D-OR
2 code implementations • 13 Feb 2023 • Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma, Aditya Murali, Deepak Alapatt, Armine Vardazaryan, Kun Yuan, Jonas Hajek, Wolfgang Reiter, Amine Yamlahi, Finn-Henri Smidt, Xiaoyang Zou, Guoyan Zheng, Bruno Oliveira, Helena R. Torres, Satoshi Kondo, Satoshi Kasai, Felix Holm, Ege Özsoy, Shuangchun Gui, Han Li, Sista Raviteja, Rachana Sathish, Pranav Poudel, Binod Bhattarai, Ziheng Wang, Guo Rui, Melanie Schellenberg, João L. Vilaça, Tobias Czempiel, Zhenkun Wang, Debdoot Sheet, Shrawan Kumar Thapa, Max Berniker, Patrick Godau, Pedro Morais, Sudarshan Regmi, Thuy Nuong Tran, Jaime Fonseca, Jan-Hinrich Nölke, Estevão Lima, Eduard Vazquez, Lena Maier-Hein, Nassir Navab, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Didier Mutter, Nicolas Padoy
This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection.
Ranked #1 on
Action Triplet Detection
on CholecT50 (Challenge)
1 code implementation • 22 Mar 2022 • Ege Özsoy, Evin Pınar Örnek, Ulrich Eck, Tobias Czempiel, Federico Tombari, Nassir Navab
Towards this goal, for the first time, we propose using semantic scene graphs (SSG) to describe and summarize the surgical scene.
Ranked #3 on
Scene Graph Generation
on 4D-OR
no code implementations • 9 Jun 2021 • Ege Özsoy, Evin Pınar Örnek, Ulrich Eck, Federico Tombari, Nassir Navab
We then use MSSG to introduce a dynamically generated graphical user interface tool for surgical procedure analysis which could be used for many applications including process optimization, OR design and automatic report generation.