STIR Challenge 2024
Description
The STIR Challenge is designed to quantify methods in deformable tracking, mapping and reconstruction. STIR is a part of EndoVis challenge at MICCAI 2024 (October 6-10, 2024). STIR will be quantified using a non-public test split of the publicly available STIR Dataset. The dataset is a stereo dataset with ground truth labels created using Infrared Tattoos1
Objective
Track points accurately and efficiently in videos
Motivation
Robust tracking and mapping in deformable scenarios is essential to enable downstream tasks in medical computer vision, such as motion compensation, and subtask automation2. A robust means to evaluate these methods for clinical efficacy requires a large labelled dataset, and a standardized evaluation. The STIR challenge provides that.
Example with MFTs3
Here are some examples of a baseline method (MFTs) on the STIR dataset.
Timeline
- April 3 Challenge launch
- October 6-10 MICCAI 2024
Organizers
| Name | Institution |
|---|---|
| Adam Schmidt | Intuitive & UBC |
| Mert Karaoglu | ImFusion & TUM |
| Soham Sinha | NVIDIA |
| Alexander Ladikos | ImFusion |
| Omid Mohareri | Intuitive |
| Simon DiMaio | Intuitive |
| Tim Salcudean | UBC |
Contact
Quick questions about our challenge can be posed via email or slack (recommended). Email adamschmidt@ece.ubc.ca to be added, or register for the challenge above, and be added via your email address.
References
1- Schmidt, Adam, Omid Mohareri, Simon DiMaio, and Septimiu E. Salcudean. “STIR: Surgical Tattoos in Infrared.” IEEE Transactions on Medical Imaging (2024). 2- Schmidt, Adam, Omid Mohareri, Simon DiMaio, Michael C. Yip, Septimiu E. Salcudean. “Tracking and mapping in medical computer vision: A review.” Medical Image Analysis. 2024 Mar 2:103131. 3- Neoral, Michal, Jonáš Šerých, and Jiří Matas. “Mft: Long-term tracking of every pixel.” In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 6837-6847. 2024.