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Abstract #1466

Impact of tissue image segmentation errors on SAR

Asha Singanamalli1, Matthew Tarasek1, Qin Liu2, Desmond Yeo1, and Thomas Foo1

1GE Global Research, Niskayuna, NY, United States, 2GE Healthcare, Waukesha, WI, United States

In this study, we evaluate the sensitivity of peak and global SAR to false positive (FP) and false negative (FN) errors in segmentation for three major brain tissue types: Gray Matter (GM), White Matter (WM) and Cerebrospinal Fluid (CSF). Voxel probability maps of GM, WM and CSF are thresholded at various intervals to generate multiple anatomical head models from a simulated T1w MRI dataset. FP and FN errors in segmentation are evaluated for each anatomical model with respect to the ground truth. Electromagnetic simulations are performed to relate these errors to peak and global SAR values at 3T.

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