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Pixel-level quality assessment can significantly enhance the reliability of fundus image evaluations, with the new EFIQA-CP method leading the way in explainability and performance.
FORCE achieves a remarkable 79% increase in success rates for VLA models while eliminating the need for costly human interventions during training.
EFIQA achieves superior image quality assessment by leveraging anatomical knowledge, offering spatial insights without the need for labeled data.
