Abstract #4205

Patient-specific Self-supervised Resolution-enhancing Networks for Synthesizing High-resolution Magnetic Resonance Images

Xiaofeng Yang¹, Sagar Mandava², Yang Lei¹, Huiqiao Xie¹, Tonghe Wang³, Justin Roper¹, Tian Liu⁴, and Hui Mao¹

¹Emory University, Atlanta, GA, United States, ²GE Healthcare, Atlanta, GA, United States, ³Memorial Sloan Kettering Cancer Center, New York, NY, United States, ⁴Icahn School of Medicine at Mount Sinai, New York, NY, United States

Synopsis

Keywords: Quantitative Imaging, Data ProcessingThis study aims to develop an efficient and clinically applicable method using patient-specific self-supervised resolution-enhancing network to synthesize the high-resolution information of MR images in the low-resolution direction to generate respective high-resolution MRI.

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