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Scientific data · 2026

Sharing a whole-/total-body [18F]FDG-PET/CT dataset with CT-derived segmentations: an ENHANCE.PET initiative.

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Ferrara Daria, Pires Manuel, Gutschmayer Sebastian, Yu Josef, Abdelhafez Yasser G, Abenavoli Elisabetta, Badawi Ramsey D, Chaudhari Abhijit J, Chen Moon S, Cherry Simon R, Frille Armin, Geist Barbara K, Gruenert Stefan, Hacker Marcus, Hesse Swen, Kerkhoff Teresa, Linder Pia, Pappisch Johanna, Pusitz Smilla, Raslan Osama A, Rausch Ivo, Raychaudhuri Siba P, Sabri Osama, Schmidt Fabian P, Sciagrà Roberto, Spencer Benjamin A, Wang Guobao, Wirtz Hubert, Beyer Thomas, Shiyam Sundar Lalith Kumar

Аннотация

We present a large whole-body and total-body curated dataset of dual-modality 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-Positron Emission Tomography/Computed Tomography (PET/CT) studies, consisting of 1,683 PET/CT images and the corresponding CT-derived segmentations of 130 target regions. 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. Target regions were first automatically segmented from CT images using an in-house software and subsequently verified and corrected by physicians-in-training. In total, the segmented regions encompass 130 volumes, including abdominal organs, muscles, bones, cardiac subregions, vessels, adipose tissue, and skeletal muscle around the third lumbar vertebra. PET/CT images and corresponding CT-derived segmentations are provided in anonymized NIfTI format. The dataset can be used for deep learning training, validation, or multi-modality image analysis and thus fills an important gap in available resources to advance the use of PET/CT data in clinical management.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты