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BRIQA: Balanced Reweighting in Image Quality Assessment of Pediatric Brain MRI

arXiv · · Notable

CV Healthcare Research Arabic AI

Summary

This paper introduces BRIQA, a new method for automated assessment of artifact severity in pediatric brain MRI, which is important for diagnostic accuracy. BRIQA uses gradient-based loss reweighting and a rotating batching scheme to handle class imbalance in artifact severity levels. Experiments show BRIQA improves average macro F1 score from 0.659 to 0.706, especially for Noise, Zipper, Positioning and Contrast artifacts.

Keywords

MRI · image quality assessment · artifact detection · machine learning · MBZUAI

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