Imaging data quality control (QC), processing, and analysis

Quality Control

ADMdx uses rigorous quality control (QC) steps throughout image inspection and processing, both qualitative and quantitative, to screen for numerous sources of noise that can impact the reliability of image data. Principal component analysis variance decomposition is used to objectively identify outliers and understand signal and noise sources in the data.

Download our recent presentation on QC in amyloid PET imaging.


ADMdx applies multiple synergistic analysis techniques including automated volume of interest (VOI) measurement, Statistical Parametric Mapping (SPM), and voxel-based multivariate analysis (NPAIRS) to fully characterize image data.