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Auto-WCEBleedGen Challenge
Automatic Detection and Classification of Bleeding and Non-Bleeding frames in Wireless Capsule Endoscopy
Note : can download trained models from latest releases
Table of Contents
- Introduction
- Evaluation Results
- Classification Report
- Detection
- Validation Dataset Results
- Classification
- Detection
- Interpretability Plots
- Testing Dataset Results
- Test Dataset 1
- Test Dataset 2
Introduction
This README provides an overview of the Auto-WCEBleedGen Challenge project, which focuses on the automatic detection and classification of bleeding and non-bleeding frames in wireless capsule endoscopy.
Evaluation Results
Classification Report
These results are evaluated using validation data.
| Precision | Recall | F1-Score | Support | |
|---|---|---|---|---|
| Bleeding | 1.00 | 1.00 | 1.00 | 258 |
| Non-Bleeding | 1.00 | 1.00 | 1.00 | 265 |
| Accuracy | 1.00 | 523 | ||
| Macro Avg | 1.00 | 1.00 | 1.00 | 523 |
| Weighted Avg | 1.00 | 1.00 | 1.00 | 523 |
Detection
| Metric | Value |
|---|---|
| Average Precision | 0.81742 |
| Mean Average Precision | 0.57529 |
| Intersection over Union | 0.67174 |