Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy

TL;DR

The Capsule Vision 2024 Challenge focuses on multi-class abnormality classification in video capsule endoscopy, aiming to advance automated diagnostic tools through a collaborative benchmarking effort.

Contribution

It introduces a new challenge dataset and evaluation framework for multi-class abnormality classification in video capsule endoscopy, fostering progress in medical image analysis.

Findings

Benchmarking results from participating teams

Identification of effective classification methods

Insights into dataset challenges and model performance

Abstract

We present the Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy. It was virtually organized by the Research Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Department of Medicine, Danube Private University, Krems, Austria 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. This document provides an overview of the challenge, including the registration process, rules, submission format, description of the datasets used, qualified team rankings, all team descriptions, and the benchmarking results reported by the organizers.