Abstract #1086
Automatic segmentation of breast images using clustering and dynamic programming
Jos Angel Rosado-Toro 1 , Tomoe Barr 2 , Marilyn T Marron 3 , Jean-Phillipe Galons 4 , Patricia Thompson 3 , Alison Stopeck 3 , Jeffrey Joel Rodrguez 5 , and Mara I Altbach 4
1
Electrical and Computer Engineering,
University of Arizona, Tucson, Arizona, United States,
2
Biomedical
Engineering, University of Arizona, Tucson, AZ, United
States,
3
Arizona
Cancer Center, University of Arizona, Tucson, Arizona,
United States,
4
Medical
Imaging, University of Arizona, Tucson, Arizona, United
States,
5
Electrical
and Computer Engineering, University of Arizona, Tucson,
Arizon, United States
A fully automated breast segmentation algorithm has been
developed to segment the breast anatomy using various
types of imaging pulse sequences. The segmentation first
finds the chest and breast pixels using a clustering
technique. Next it removes the chest pixels using a
dynamic programming technique on the vertical gradient.
Then it removes the skin pixels using a thinning
algorithm and finally it splits the two breasts using a
morphological technique. The performance of the
algorithm is evaluated on 202 breast imaging slices
using manually traced breast outlines as reference.
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