Abstract #2358
A Real Time Approach to Baseline Library Size Recommendations for Hybrid MB+R Thermometry
Ron Instrella 1 , Michael Marx 1 , and Kim Butts Pauly 2
1
Electrical Engineering, Stanford University,
Stanford, CA, United States,
2
Stanford
University, Stanford, CA, United States
This study presents a simple, preliminary, real-time
temperature processing method for determining
pre-treatment baseline library size recommendations for
Hybrid MB+R Thermometry. Temperature data collected from
3 volunteer brain scans are analyzed using the real-time
method to produce recommendations that are consistent
with retrospective analysis. If implemented clinically,
this method shows promise as a practical approach to
ensuring sufficient baselines are collected
pre-treatment to improve temperature estimates, while
minimizing the amount of time spent scanning.
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