SurgVisDom - Surgical Visual Domain Adaptation 2020
The dataset from this challenge has been released publicly along with the challenge publication. Please see the synapse website link here for more details
Surgical data science is revolutionizing minimally invasive surgery. By developing algorithms to be context-aware, exciting applications to augment surgeons are becoming possible. However, there exist many sensitivities around surgical data (or health data more generally) needed to develop context-aware models. This challenge seeks to explore the potential for visual domain adaptation in surgery to overcome data privacy concerns. In particular, we propose to use video from virtual reality simulation data from clinical-like tasks to develop algorithms to recognize activities and then to test these algorithms on videos of the same task in a clinical setting (i.e., porcine model).
For extended details about this challenge along with data download, please refer to our synapse website here.