DOI: 10.5281/zenodo.16820899
title: PTP-IQ: Paired texture phantom & image quality data for CT

description: We present PTP-IQ, a public repository of Paired Texture Phantom and Image Quality data. The dataset consists of paired CT acquisitions of image quality and texture phantoms acquired under identical specified conditions across multiple scanner models and protocols. This dataset uniquely enables researchers to directly correlate traditional image quality metrics (3D modulation transfer function, 3D noise power spectrum, and contrast-to-noise ratio) with QIF measurements, particularly texture features that are inherently sensitive to image quality variations.

 

The details of this dataset have been submitted for review to Medical Physics. We will update the repository with details from the manuscript upon publication.
description: Purpose: 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.

Acquisition and Validation Methods: 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 CTDIvol levels (2.05--17.11 mGy) and reconstructed using eight different kernels, resulting in 160 total conditions (combinations of scanner, dose, kernel). Data were validated for integrity and completeness, which excluded six conditions. 

Data Format and Usage Notes: The paired texture phantom and image quality (PTP-IQ) dataset includes: (a) DICOM image series of two texture phantoms acquired across the 154 conditions, as well as (b) image quality metrics derived from each corresponding set of scanner, acquisition and reconstruction settings provided in HDF5 format.

Potential Applications: 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.
description: Usage

We provide each type of data (DICOM from the radiomics liver phantom, DICOM from the 3D printed texture phantom, and HDF5 files of image quality data) compressed as a *.tar.gz file. 

Additionally, examples.tar.gz contains each type of data for a single CT condition, along with a Jupyter notebook illustrating a basic example of interacting with the data using popular Python packages.

File structure

ptp-iq-dataset/
├── metadata.csv
├── radiomics-liver-phantom/
│   └── {protocol_id}/
│       └── {instance_number}.dcm
├── 3d-printed-texture-phantom/
│   └── {protocol_id}/
│       └── {instance_number}.dcm
├── image-quality-data/
│   └── {protocol_id}.h5
└── examples/
    ├── example-data/    ├── environment.yaml
    └── data_reading_example.ipynb