ENHANCE.PET 1.6k: a whole-/total-body [18F]FDG-PET/CT dataset with CT-derived segmentations
Year: 2025
Type: dataset
Abstract: We present a large whole-body and total-body curated dataset of PET/CT studies, consisting of 1,683 PET/CT images and the corresponding CT-derived segmentations of 130 target regions, including abdominal organs, muscles, bones, cardiac subregions, vessels, adipose tissue, and skeletal muscle around the third lumbar vertebra. This multi-center dataset includes images from individuals without overt disease and patients with a range of malignant and inflammatory pathologies, including arthritis, lymphoma, and melanoma, as well as cancers of the lung, head-neck, and genito-urinary tract.different pathologies (lung cancer, lymphoma, and melanoma). Data are provided in anonymized NIfTI format.A JSON file containing the complete list of segmentations and their corresponding intensities within the multi-class files is available.In addition to the imaging data, non-imaging information is provided in two spreadsheet files. The CT-details.xlsx file contains details on the CT acquisition parameters (e.g., PET/CT system manufacturer and model, kVp, filter type, convolutional kernel, axial pixel size, slice thickness, and focal spot size) for each participant. The PT-details.xlsx file provides the corresponding demographic information (e.g., clinical indication, sex, age, weight, height) as well as PET acquisition parameters (e.g., injected activity, acquisition date and time, radioactivity injection details, image units, slope, intercept, system model and manufacturer).
Source: ScienceDB
Authors: Ferrara, Daria, Pires, Manuel, Gutschmayer, Sebastian, Yu, Josef, Abdelhafez, Yasser Gaber, Abenavoli, Elisabetta, Badawi, Ramsey, Abhijit J. Chaudhari, Chen, Moon S., Cherry, Simon R., Frille, Armin, Geist, Barbara K., Gruenert, Stefan, Hacker, Marcus, Hesse, Swen, Kerkhoff, Teresa, Linder, Pia, Pappisch, Johanna, Smilla Pusitz, Raslan, Osama A., Rausch, Ivo, Siba P. Raychaudhuri, Sabri, Osama, Schmidt, Fabian, Sciagrà, Roberto, Spencer, Benjamin, Guobao Wang, Wirtz, Hubert, Beyer, Thomas, Sundar, Lalith Kumar Shiyam
Institutions: Medical University of Vienna, University of California Davis Medical Center, Azienda Ospedaliero-Universitaria Careggi, UC Davis Comprehensive Cancer Center, Leipzig University, University Hospital Leipzig, University of Tübingen, University of California, Davis, Siemens (Germany), Ludwig-Maximilians-Universität München
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7118357046