CT texture phantom dataset with paired image quality assessments for quantitative imaging

To establish a public repository of computed tomography (CT) texture phantom images paired with objective 3D image quality measurements from multiple scanner models using a diverse range of imaging protocols, facilitating investigations into relationships between image quality and quantitative imaging features. Three specialized CT phantoms were scanned: (1) the Corgi^® phantom for image quality assessment, (2) a radiomics liver phantom, and (3) an open-source 3D-printed texture phantom. Image quality assessment included measurement of contrast-to-noise ratio, 3D modulation transfer function, and 3D noise power spectrum. Data were acquired on four CT scanner models from two manufacturers at five ${\mathrm{CTDI}}_{vol}$ levels (2.05-17.11 mGy) and reconstructed with eight different kernels, yielding 160 total conditions (combinations of scanner, dose, kernel). Data were validated for integrity and completeness, resulting in the exclusion of six conditions. The paired texture phantom and image quality (PTP-IQ) dataset includes: (1) DICOM image series of two texture phantoms acquired across the 154 conditions, as well as (2) image quality metrics derived from each corresponding set of scanner, acquisition and reconstruction settings provided in HDF5 format. This dataset enables the development and validation of harmonization methods for multi-center quantitative imaging studies, investigation of protocol-dependent QIF variability, and optimization of acquisition protocols for radiomics applications. The controlled and systematic study design facilitates isolation of individual protocol effects on quantitative measurements.