Published February 10, 2021 | Version v1
Dataset Open

Dataset of patient-derived 3D digital breast phantoms for research in breast computed tomography

  • 1. INFN, sez. di Napoli, Italy
  • 2. Università di Napoli "Federico II" & INFN, sez. di Napoli, Italy
  • 3. Léon Bérard Cancer Center, University of Lyon & CREATiS, University of Lyon, CNRS, France
  • 4. Università di Napoli "Federico II", Italy
  • 5. Department of Medical Equipment, Electronic and Information Technologies in Healthcare, Medical University of Varna, Varna, Bulgaria
  • 6. Department of Radiology, University of California Davis, Sacramento, CA, USA

Description

The dataset includes computational digital breast phantoms derived from high-resolution 3D clinical breast images for the use in virtual clinical trials in 3D X-ray breast imaging. Uncompressed computational breast phantoms for investigations in dedicated breast CT (BCT) were derived from 150 clinical 3D breast images acquired via a dedicated CT scanner at UC Davis (California, USA). All patient studies were performed according to protocols approved by the UC Davis institutional review board and Radiation Use Committee; informed consent was obtained. Each image voxel was classified in one out of the four main materials presented in the field of view: fibro-glandular tissue, adipose tissue, skin tissue and air. Each of the classified materials is represented by one out of four values: 0 for the air, 1 for the adipose tissue, 2 for the glandular tissue and 3 for the skin tissue. For the image classification, a semi-automatic software was adopted.

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