Paper
9 May 2002 Automated estimation of breast composition from MR images
Author Affiliations +
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.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Brian E. Chapman, Xiao Hui Wang, and Walter F. Good "Automated estimation of breast composition from MR images", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467150
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KEYWORDS
Breast

Tissues

Image segmentation

Binary data

Chest

Gold

Magnetic resonance imaging

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