This talk explores the challenges of medical image quality, highlighting that it cannot be evaluated using objective metrics alone but must consider the visibility of diagnostically important structures and human visual perception. It discusses how integrating perceptual modeling, physics-informed methods, and artificial intelligence can produce more robust, interpretable, and clinically relevant image assessment and enhancement solutions. The presentation also outlines a long-term vision for strengthening collaboration between radiologists and visual information processing researchers to establish sustainable and clinically grounded best practices.