An unsupervised automatic segmentation algorithm for breast tissue classification of dedicated breast computed tomography images.

Journal: Medical physics
Published Date: May 9, 2018

Abstract

PURPOSE: To develop and evaluate a new automatic classification algorithm to identify voxels containing skin, vasculature, adipose, and fibroglandular tissue in dedicated breast CT images.

Authors

  • Marco Caballo
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
  • John M Boone
    Department of Radiology and Biomedical Engineering, University of California Davis Health, 4860 "Y" street, suite 3100 Ellison building, Sacramento, CA, 95817, USA.
  • Ritse Mann
    Diagnostic Image Analysis Group, Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Ioannis Sechopoulos
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.

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