Accuracy of Noise Magnitude Measurements from Patient CT Images
Purpose Noise magnitude is a main CT image quality indicator. In vivo measurements emerged as a patient-specific methodology to assess and qualify CT noise, yet methods to do so vary. Current noise measurement methods in soft tissues and air surrounding the patient use distinct image segmentations, HU thresholds, and region-of-interests, resulting in noise estimation variations. In this study, we compared two noise magnitude calculation methods against the gold standard ensemble noise in two cohorts of virtually-generated patient images across 36 imaging conditions. Methods 1800 image datasets were generated using a virtual trial platform based on anthropomorphic phantoms (XCAT) and a validated, scanner-specific CT simulator (DukeSim). XCAT phantoms were repeatedly imaged 50 times using Chest and Abdominopelvic protocols, three dose levels, and three reconstruction kernels, using both FBP and IR algorithms. Noise magnitudes were calculated in the air surrounding the patient (An) and soft tissues (GNI) by applying HU<-900 and -300
