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Testing Dataset of Capsule Vision 2024 Challenge

Version 4 2025-01-11, 14:46
Version 3 2024-11-20, 11:30
Version 2 2024-11-20, 11:22
Version 1 2024-10-10, 05:27
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posted on 2025-01-11, 14:46 authored by Palak HandaPalak Handa, Amirreza Mahbod, Florian Schwarzhans, Ramona Woitek, Nidhi Goel, Deepti Chhabra, Shreshtha Jha, Manas Dhir, Pallavi Sharma, Vijav Thakur, Simarpreet Singh Chawla, Dr. Deepak Gunjan, Jagadeesh Kakarla, Balasubramanian Ramanathan

We present the testing dataset to be utilized in the Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy. It is being virtually organized by the Research Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Department of Medicine, Danube Private University, Krems, Austria and Medical Imaging and Signal Analysis Hub (MISAHUB) in collaboration with the 9th International Conference on Computer Vision & Image Processing (CVIP 2024) being organized by the Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Kancheepuram, Chennai, India. Datasets can only be utilized for research purposes.

For more information, please check the following links:

Challenge hosting website: https://misahub2023.github.io/cv2024.html

Challenge arXiv: https://arxiv.org/abs/2408.04940

Challenge Github: https://github.com/misahub2023/Capsule-Vision-2024-Challenge

Update: The challenge has been completed. The ground truth has been released in version 2. For instructions on how to correctly use the ground truth file, please refer to the evaluation folder by the organizing team on the challenge github (link: https://github.com/misahub2023/Capsule-Vision-2024-Challenge.) Test set with with seperated folders of each class label have also been released.

Funding

DST SERB (CRG/2022/001755)

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