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Abstract #3720

Fast and Robust Framework for PET-MR Attenuation Map Generation with Joint MR Bias Estimation and Tissue Segmentation

Dattesh D. Shanbhag1, Sheshadri Thiruvenkadam1, Sandeep Kaushik1, Gaspar Delso2, Scott D. Wollenweber3, Sonal Ambwani3, Rakesh Mullick1, Florian Wiesinger4

1GE Global Research, Bangalore, Karanataka, India; 2GE Healthcare, Glattbrugg, Zurich, Switzerland; 3GE Healthcare, Waukesha, WI, United States; 4GE Global Research, Garching b. Munchen, Bavaria, Germany

MR-based PET attenuation correction (AC) is a prerequisite for quantitative PET and a key determining factor for the success of PET/MR. RF shading with phased array coils results in segmentation based MR-AC map generation failure. In this work we present a novel approach for MR-AC map generation within the phase field based framework based on joint estimation/correction of the RF shading and tissue segmentation maps using Dixon MRI images. The method provides for parameter variation resilient body contour and tissue class segmentation, obviates the need to re-tune the algorithm for specific cohort of data acquisition and coils and results in simplified workflow for PET-MR attenuation map generation.