Evaluation Methods and Ranking

The evaluation and ranking process for the Mycetoma MicroImage Challenge is designed to rigorously assess algorithms’ performance in both detecting and classifying Mycetoma from histopathological images. This process is crucial for ensuring that the solutions developed by participants are effective and reliable.

The performance of submitted algorithms will be quantitatively assessed using four primary metrics:

1. Sensitivity: Measures the ability of the algorithm to correctly identify true positives, i.e., actual cases of Mycetoma.
2. Specificity: Assesses the algorithm’s ability to identify true negatives, thereby avoiding false positives correctly.
3. Accuracy: Provides an overall measurement of the algorithm’s performance across all test cases.
4. Matthews Correlation Coefficient (MCC): A balanced measure which takes into account true and false positives and negatives and is particularly useful in classes of different sizes.

These metrics were chosen to provide a comprehensive overview of each algorithm’s performance, taking into account various aspects of diagnostic effectiveness.