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Abstract #3922

Deep learning-based slice resolution for improved slice coverage in abdominal T2 mapping

Eze Ahanonu1, Zhiyang Fu1,2, Kevin Johnson2, Rohit Philip1, Diego R Martin3, Maria Altbach2,4, and Ali Bilgin1,2,4
1Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States, 2Medical Imaging, University of Arizona, Tucson, AZ, United States, 3Radiology, Houston Methodist Hospital, Houston, TX, United States, 4Biomedical Engineering, University of Arizona, Tucson, AZ, United States

Synopsis

This study presents a deep learning based technique for slice super resolution in RADTSE T2 mapping. The proposed method may be used to accelerate full liver imaging, while maintaining sufficient through-plane resolution for detection of small pathologies.

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Abstract Presentation Video

Keywords