Dear all: EndoVis has moved here¶

A MICCAI challenge 

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 high-profile 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.

Sub-challenges¶

2022

• 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 RadicalProstatectomy

• SimCol-to-3D:Simulated Colonoscopy data for 3D (scene) reconstruction

• SurgT - a challenge for tissue tracking in surgery

• Explorative: P2ILF - Preoperative to Intraoperative Laparoscopy Fusion

  EndoVis 2022: Structured description of the challenge design

Sub-challenges 2021¶

• HeiSurf: HeiChole Surgical Workflow Analysis and Full Scene Segmentation
• GIANA: Gastrointestinal ImAge ANAlysis
• CholecTriplet2021: Surgical Action Triplet Recognition
• FetReg: Placental Vessel Segmentation and Registration in Fetoscopy
• PETRAW: PEg TRAnsfer Workflow recognition by different modalities
• SimSurgSkill: Objective Surgical Skill Assessment in VR Simulation

EndoVis 2021: Structured description of the challenge design

Sub-challenges 2020¶

• CATARACTS Segmentation
• CATARACTS Workflow
• MIcro-Surgical Anastomose Workflow recognition on training sessions (MISAW)
• Surgical visual domain adaptation: from virtual reality to real, clinical environments (SurgVisDom)

Sub-challenges 2019¶

• Robust Medical Instrument Segmentation (ROBUST-MIS)
• Stereo Correspondence and Reconstruction of Endoscopic Data
• Surgical Workflow and Skill Analysis

Sub-challenges 2018¶

• Gastrointestinal Image ANAlysis (GIANA)
• Surgical Workflow Analysis in the SensorOR
• Robotic Scene Segmentation
• CATARACTS

Sub-challenges 2017¶

Based on a "Call for Data" four sub-challenges were selected:

• Gastrointestinal Image ANAlysis (GIANA)
• Surgical Workflow Analysis in the SensorOR
• Robotic Instrument Segmentation
• Kidney Boundary Detection

Sub-challenges 2015¶

Based on a "Call for Data" four sub-challenges were selected:

• Instrument segmentation and tracking
• Automatic polyp detection in colonoscopy videos
• Early Barrett's cancer detection
• Detection of abnormalities in gastroscopic images

Contact¶

If you have any question regarding to this challenge, please send an email to the following address:

stefanie.speidel@nct-dresden.de

This challenge is endorsed by the International Society for Computer Aided Surgery (ISCAS) and organized by the open source and open data group of ISCAS.