SurgT:  Surgical Tracking

Part of the Endoscopic Vision Challenge

Paper: https://arxiv.org/abs/2302.03022

Description

Visual tracking involves following a bounding box throughout a video sequence. This is a crucial task in Computer-Assisted Interventions (CAI), with a range of applications including soft tissue deformation estimation, lesion tracking, augmented reality and robotic visual servoing. Medical applications require accurate trackers that are robust in challenging conditions prevalent in surgery. Hence prior to being utilized in real-world practice, tissue trackers need to be evaluated in large and diverse datasets that capture multiple challenging conditions. The general problem of tracking has been well studied within the computer vision community, focusing on natural scenes i.e. VOT. However, datasets for the same challenge in surgical scenes are still lacking. Hence, there is a dire need for a large publicly available dataset for benchmarking tissue trackers in surgery, for fueling development in this area and improving surgery. To address this, we propose the SurgT challenge, a new first-of-a-kind collection of tools and datasets for training and benchmarking tissue trackers in surgery.

Important Dates

Prizes

        🥇 RTX 3080 Ti GPU for the 1st place
        🥈 $1,000 for the 2nd place
        🥉 $500 for 3rd place

Sponsors