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Proceedings Paper

Automated estimation of breast composition from MR images
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Paper Abstract

We present a simple algorithm for determining the fat fraction in magnetic resonance images of the breast. These computed values are intended to help train neural networks for determining breast composition from x-ray mammograms. The method relies on simple intensity thresholding to form a binary mask followed by morphological dilations and erosions, automated region selection and clustering the tissues within the mask into fat and parenchymal components. Correcting the image intensity nonuniformity due to the spatial sensitivity profile of the breast coil was found to be essential and easily accomplished with homologous filtering. In the absence of large artifacts, the algorithm was able to accurately calculate breast fat fractions.

Paper Details

Date Published: 9 May 2002
PDF: 10 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467150
Show Author Affiliations
Brian E. Chapman, Univ. of Pittsburgh (United States)
Xiao Hui Wang, Univ. of Pittsburgh (United States)
Walter F. Good, Univ. of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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