Minimally invasive surgery using cameras to observe the internal anatomy is the preferred approach to many surgical procedures. Furthermore, other surgical disciplines rely on microscopic images. As a result, endoscopic and microscopic image processing as well as surgical vision are evolving as techniques needed to facilitate computer assisted interventions (CAI). Algorithms that have been reported for such images include 3D surface reconstruction, salient feature motion tracking, instrument detection or activity recognition. However, what is missing so far are common datasets for consistent evaluation and benchmarking of algorithms against each other. As a vision CAI challenge at MICCAI, our aim is to provide a formal framework for evaluating the current state of the art, gather researchers in the field and provide high quality data with protocols for validating endoscopic vision algorithms.

 

Sub-challenges 2018

 

Sub-challenges 2017

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

 

Sub-challenges 2015

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

 

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.