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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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