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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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