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Abstract #1584

MR to pseudo CT conversion:  Combining Deep-Learning and Analytical Image Processing

Florian Wiesinger1, Sandeep Kaushik2, Mathias Engström3, Pauline Hinault4,5, Andrew Leynes6, Mikael Bylund7, David Gensanne8, Tufve Nyholm7, Peder Larson6, and Cristina Cozzini1

1GE Healthcare, Munich, Germany, 2GE Global Research, Bangalore, India, 3GE Healthcare, Stockholm, Sweden, 4LITIS, Rouen, France, 5GE Healthcare, Paris, France, 6Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, 7Umeå University, Umea, Sweden, 8Centre Henri Becquerel, Rouen, France

Here we present an improved method for ZTE to pseudo CT conversion by combining an analytical signal model (i.e. ZTE to CT signal scaling) with Connected Component Analysis (CCA) and Deep Learning (DL) based air vs. bone discrimination. The method is demonstrated for the two main anatomical regions (head&neck and pelvis) and the two main field strengths (1.5T and 3T) of interest.

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