Evaluating the relationship between objective and subjective image quality in computed tomography using detectability...

Achieving optimal image quality in computed tomography (CT) is essential for accurate diagnosis. This study explores the relationship between objective and subjective image quality, using the detectability index ($d^{\prime}$) as a quantitative performance metric. A 3D-printed anthropomorphic abdominal phantom was used to assess how variations in tube voltage, current, slice thickness, and reconstruction kernel affect image quality. Signal-to-noise ratio, contrast-to-noise ratio, and edge sharpness were evaluated alongside radiologist assessments. A strong correlation between $d^{\prime}$ and subjective quality confirmed $d^{\prime}$ as a reliable predictor of visual image perception. Multiple linear regression identified $d^{\prime}$, object size, and the peak spatial frequency of the noise power spectrum as independent predictors of perceived quality. These results support the integration of $d^{\prime}$ into routine CT image quality evaluation, helping to align technical image parameters with clinical expectations and improve protocol optimization.