Abstract #4906
Automatic Segmentation Pipeline for Patient-Specific MRI Tissue Models
Angel Torrado-Carvajal 1,2 , Juan A. Hernandez-Tamames 1,2 , Joaquin L. Herraiz 2 , Yigitcan Eryaman 2,3 , Elfar Adalsteinsson 4,5 , Lawrence L. Wald 3,5 , and Norberto Malpica 1,2
1
Dept. of Electronics, Universidad Rey Juan
Carlos, Mostoles, Madrid, Spain,
2
Madrid-MIT
M+Vision Consortium in RLE, MIT, Cambridge,
Massachusetts, United States,
3
Dept.
of Radiology, MGH, Martinos Center for Biomedical
Imaging, Charlestown, Massachusetts, United States,
4
Dept.
of Electrical Engineering and Computer Science, MIT,
Cambridge, Massachusetts, United States,
5
Harvard-MIT
Health Sciences and Technology, MIT, Cambridge,
Massachusetts, United States
Specific absorption rate (SAR) may cause unsafe tissue
heating in High-Field MRI scanners. We propose a
pipeline for patient-specific tissue modeling based only
on MRI data that could enable patient-specific pulse
design in High-Field MRI. We used open-source tools to
automatically segment eleven tissue classes: brain white
matter (WM), gray matter (GM), cerebrospinal fluid
(CSF), cerebellum WM and GM, skull, skin, eyeballs, main
arteries, muscle and fat/cartilage. The method was
tested in 12 healthy subjects, and its accuracy was
confirmed by an expert radiologist. The models are
automatically meshed and exported in a format compatible
with EM simulation software.
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