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Abstract #0970

Real-Time T1/PRF-Based MR Thermometry Using Deep Learning and VFA-mFFE for Guidance of HIFU Treatment

Jong-Min Kim1,2,3, You-Jin Jeong1,2,3, Han-Jae Cheong1,2,3, Jae-Won Yoo1,2,3, Jeong-Hee Kim2,4, Chulhyun Lee5, and Chang-Hyun Oh1,2,3,6

1Department of Electronics and Information, Korea University, Seoul, Korea, Republic of, 2Korea Artificial Organ Center, Korea University, Seoul, Korea, Republic of, 3ICT Convergence Technology for Health and Safety, Korea University, Sejong, Korea, Republic of, 4Research Institute for Advanced Industrial Technology, Korea University, Sejong, Korea, Republic of, 5Bioimaging Research Team, Korea Basic Science Institute, Chungcheongbuk-do, Korea, Republic of, 6Correspoding author,, Seoul, Korea, Republic of

MR temperature mapping of adipose and aqueous tissues is crucial in ensuring the safety and efficacy of HIFU treatment in regions of the body where the adipose and aqueous tissues are treated. We suggest a simultaneous and real-time temperature mapping method for adipose and aqueous tissues by using deep learning and multi-echo fast field echo with variable flip angle. Additionally, an image reconstruction method to obtain the temperature maps from the undersampled data obtained in the treatment stage is proposed by additionally using the high-resolution image obtained in the planning stage.

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