TY - GEN
T1 - Automated segmentation of breast fat-water MR images using empirical analysis
AU - Rosado-Toro, Jose A.
AU - Barr, Tomoe
AU - Galons, Jean Philippe
AU - Marron, Marilyn T.
AU - Stopeck, Alison
AU - Thomson, Cynthia
AU - Altbach, Maria I.
AU - Rodriguez, Jeffrey J.
PY - 2013/10/18
Y1 - 2013/10/18
N2 - Breast density (BD) has been advocated as a risk factor for the development of breast cancer. BD is typically measured from mammograms. However for longitudinal studies of patients at risk, BD can be better assessed using MRI due to the lack of ionizing radiation and the 3D capabilities of the technique. A fat-water (FW) imaging technique called RAD-GRASE was developed to acquire images of the entire breast in a few minutes and can generate fat-fraction maps, which can be used to assess BD. The time consuming manual segmentation on ∼19 slices per exam can be challenging. In this paper, we present a method to automatically segment the breast tissue in FW images and yield FW profiles of the region of interest (ROIs).
AB - Breast density (BD) has been advocated as a risk factor for the development of breast cancer. BD is typically measured from mammograms. However for longitudinal studies of patients at risk, BD can be better assessed using MRI due to the lack of ionizing radiation and the 3D capabilities of the technique. A fat-water (FW) imaging technique called RAD-GRASE was developed to acquire images of the entire breast in a few minutes and can generate fat-fraction maps, which can be used to assess BD. The time consuming manual segmentation on ∼19 slices per exam can be challenging. In this paper, we present a method to automatically segment the breast tissue in FW images and yield FW profiles of the region of interest (ROIs).
KW - automated segmentation
KW - breast MRI
KW - dynamic programming
KW - fat-water MRI
KW - k-means++
UR - http://www.scopus.com/inward/record.url?scp=84890513748&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890513748&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2013.6637803
DO - 10.1109/ICASSP.2013.6637803
M3 - Conference contribution
AN - SCOPUS:84890513748
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1018
EP - 1022
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -