Endoscopic Vision Challenge 2025
Authors/Creators
- Speidel, National Center for Tumor Diseases Dresden, Germany1
- Maier-Hein, Lena
- Stoyanov, Danail2
- Bodenstedt, Sebastian1
- Reinke, Annika3
- Bano, Sophia2
- Zia, Aneeq4
- Berniker, Max4
- Perreault, Conor4
- Nespolo, Rogerio4
- Jarc, Anthony4
- Jaspers, Tim5
- Claessens, Cris5
- Caetano, Francisco5
- Kusters, Koen5
- Boers, Tim5
- Dehghani, Nikoo5
- van der Sommen, Fons5
- Schmidt, Adam4
- Karaoglu, Mert4
- Mohareri, Omid4
- Hoffmann, Hanna6
- Egger, Jan7
- Hölzle, Frank8
- Röhrig, Rainer8
- Puladi, Behrus8
- 1. National Center for Tumor Diseases Dresden, Germany
- 2. University College London, United Kingdom
- 3. German Cancer Research Center, Germany
- 4. Intuitive Surgical
- 5. Eindhoven University of Technology, Department of Electrical Engineering, VCA Research Group
- 6. NCT Dresden
- 7. Essen
- 8. RWTH Aachen
Description
With the advent of artificial intelligence as key technology in modern medicine, surgical data science (SDS) promises to improve the quality and value of the particular domain of interventional healthcare through capturing, organization, analysis, and modeling of data, thus creating benefit for both patients and medical staff. Holistic SDS concepts span the topics of context-aware perception in and beyond the operating room, data interpretation and real-time assistance or decision support. At the same time, minimally invasive surgery using cameras to observe the internal anatomy has become the state-of-the-art approach to many surgical procedures.
Contributing to the key aspect of perception, endoscopic vision thus constitutes a central component of SDS and computer-assisted interventions. From this arises the necessity for high-quality common datasets that allow the scientific community to perform comparative benchmarking and validation of endoscopic vision algorithms. EndoVis (http://endovis.org/) organizes highprofile international challenges for the comparative validation of endoscopic vision algorithms that focus on different problems each year at MICCAI, comprising various computer vision tasks (classification, segmentation, detection, localization, etc) and subdisciplines ranging from laparoscopy to coloscopy and surgical training. It acts umbrella for several sub-challenges in this field, for the 10th anniversary this year we propose 4 different sub-challenges within EndoVis as well as keynotes from world leading experts in this field:
- SurgVu: Surgical Visual Understanding
- RARE: Recognition of Anomalies in low-pREvalance cancer
- STIR: Surgical Tissue Tracking Using the STIR (Surgical Tattoos in Infrared) Dataset
- OSS: Open Suturing Skills
Files
222-Endoscopic_Vision_Challenge_2025_2025-03-23T20-40-46.pdf
Files
(169.2 kB)
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