Other Open Access
Endoscopic Vision Challenge 2022
Aneeq Zia; Xi Liu; Kiran Bhattacharyya; Ziheng Wang; Max Berniker; Anthony Jarc; Chinedu Nwoye; Deepak Alapatt; Aditya Murali; Saurav Sharma; Armine Vardazaryan; Nicolas Padoy; Beatrice Van Amsterdam; Dimitris Psychogyios; Emanuele Colleoni; Danail Stoyanov; Anita Rau; Sophia Bano; Yueming Jin; Joao Cartucho; Stamatia Giannarou; Stefanie Speidel; Lena Maier-Hein; Sebastian Bodenstedt; Annika Reinke; Tobias Roß
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. With EndoVis, we present you a large collection of publicly accessible datasets comprising various computer vision tasks (classification, segmentation, detection, localization,…) and subdisciplines ranging from laparoscopy to coloscopy and surgical training. These datasets can be used for both de novo development as well as validation of methods. EndoVis organizes highprofile international challenges for the comparative validation of endoscopic vision algorithms that focus on different problems each year at MICCAI, thus representing a major driving force of advancements in the field. This year we propose 5 different sub-challenges under the umbrella of EndoVis:
- SurgToolLoc - Endoscopic surgical tool localization by leveraging tool presence labels
- CholecTriplet2022 - Surgical Action Triplet Detection and Localization
- SAR-RARP50 - Instrumentation segmentation and Action Recognition on robotic Radical Prostatectomy
- SimCol-to-3D: Simulated Colonoscopy data for 3D (scene) reconstruction
- SurgT - a challenge for tissue tracking in surgery
| Name | Size | |
|---|---|---|
|
EndoscopicVisionChallenge2022_03-16-2022_10-27-14.pdf
md5:78c01dea09ad6fa7f92c6cbb3cfe189f |
11.1 MB | Download |
| All versions | This version | |
|---|---|---|
| Views | 1,979 | 1,337 |
| Downloads | 1,745 | 1,164 |
| Data volume | 22.3 GB | 13.0 GB |
| Unique views | 1,738 | 1,232 |
| Unique downloads | 1,517 | 1,064 |
- Publication date:
- March 16, 2022
- DOI:
-
- Keyword(s):
- Surgical Vision Endoscopy Classification Detection Segmentation MICCAI Challenge weak learning object detection object localization Surgical activity detection surgical action detection action triplet tool-tissue interaction CholecT50 deep learning laparoscopic video medical image analysis Surgical action recognition Surgical instrument segmentation Prostatectomy Multitask learning Colonoscopy, pose estimation depth estimation Tracking Endoscopy Laparoscopy Robotic surgery Computer Assisted Interventions
- Meeting:
- 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022)
- License (for files):
- Creative Commons Attribution No Derivatives 4.0 International