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Abstract #1403

Bayesian segmentation of dual-echo UTE images for PET/MR attenuation correction

Gaspar Delso 1 , Michael Carl 1 , Florian Wiesinger 2 , Martin Hllner 3 , and Patrick Veit-Haibach 3

1 Global MR Applications & Workflow, GE Healthcare, Waukesha, WI, United States, 2 GE Global Research, Munich, Germany, 3 University Hospital, Zurich, Switzerland

MR-based attenuation correction is a critical component of integrated PET/MR scanners. This is generally achieved by segmenting MR images into a set of tissue classes with known attenuation properties (e.g. bone, fat, soft tissue, lung, air). Ultra-short echo time (UTE) sequences capable of imaging tissues with short T2* times (<1 ms) have been proposed in the past as a means to locate bone tissue1-4. In this study, we used tri-modality PET/CT+MR data from oncology patients to develop an improved classification algorithm for the localization of bone tissue in the head and neck area.

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