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

Important Updates

Training dataset has been released. Check KEY LINKS.
Registrations are now OPEN. HURRY, APPLY!

Goal

The aim of the challenge is to provide an opportunity for the development, testing and evaluation of AI models for automatic classification of abnormalities captured in video capsule endoscopy (VCE) video frames. It promotes the development of vendor-independent and generalized AI-based models for automatic abnormality classification pipeline with 10 class labels:

Angioectasia
Bleeding
Erosion
Erythema
Foreign body
Lymphangiectasia
Polyp
Ulcer
Worms
Normal

Data

Training and Validation Data

The training and validation datasets have been released and are accessible here.

Testing Data

The test dataset will be released on October 11, 2024.

Evaluation

Goal Metric

Mean AUC

Other Metrics

AUC-ROC
Specificity
Mean Specificity
Sensitivity
Mean Sensitivity
F1 score
Mean F1 score
Average precision
Mean average precision

Submission Instructions and Rules

The detailed submission instructions and challenge rules are available on ArXiv.
The sample codes are available on GitHub for your reference.
The sample submission report is available on Overleaf.

Prizes

Cash prize sponsored by the 9^th International Conference on Computer Vision & Image Processing (CVIP 2024).
- 1^st Prize: 200 €
- 2^nd Prize: 150 €
- 3^rd Prize: 100 €
E-certificate to top three winning teams.
Co-authorship in the challenge summary paper for top 4 teams.
Opportunity to showcase work at CVIP 2024.