Abstract #3214
A Comparison Between Three-Point Dixon Sequences and Label Fusion Techniques for Water-Fat Separation in High-Field MRI Local SAR Estimation
Angel Torrado-Carvajal 1,2 , Esra A. Turk 2,3 , Joaquin L. Herraiz 2,3 , Yigitcan Eryaman 2,4 , Juan A. Hernandez-Tamames 1,2 , Elfar Adalsteinsson 5,6 , Larry L. Wald 4,6 , and Norberto Malpica 1,2
1
Medical Image Analysis and Biometry Lab,
Universidad Rey Juan Carlos, Mostoles, Madrid, Spain,
2
Madrid-MIT
M+Vision Consortium, Madrid, Spain,
3
Research
Laboratory of Electronics, Massachusetts Institute of
Technology, Cambridge, MA, United States,
4
Martinos
Center for Biomedical Imaging, Dept. of Radiology, MGH,
Charlestown, MA, United States,
5
Dept.
of Electrical Engineering and Computer Science,
Massachusetts Institute of Technology, Cambridge, MA,
United States,
6
Harvard-MIT
Health Sciences and Technology, Massachusetts Institute
of Technology, Cambridge, MA, United States
In this work we compare the results of B1+ field and SAR
distribution obtained by using patient-specific 3PD
images and two label fusion estimation approaches over a
T1-weighted volume for fat and water segmentation. B1+
field distributions were found to be almost the same for
the three models. An IDEAL label-fusion approach
provides very similar SAR distribution results to the
patient-specific approach. A CT label-fusion approach
provides an increased SAR distribution map. The use of
label fusion techniques to estimate the fat and water
separation in MRI images allows an accurate segmentation
with a similar accuracy as patient-specific 3PD
sequences.
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