Papers
3
Total Citations
312
H-Index
3
About
Kyunghyun Sung is a leading researcher in prostate cancer imaging, whose work bridges the gap between advanced MRI technology and clinical pathology. His primary research focuses on developing and validating novel MRI techniques for the non-invasive diagnosis and characterization of prostate cancer (PCa). A major contribution is the development of **FocalNet**, a deep learning framework for joint prostate cancer detection and Gleason score prediction in multi-parametric MRI (mp-MRI). This work, cited over 215 times, directly addresses the critical problem of inter-reader variability by providing quantitative, automated interpretation. Sung has also pioneered microstructural imaging through **diffusion-relaxation correlation spectrum imaging (DR-CSI)** , validating its ability to characterize prostate tissue microstructure against whole-mount digital histopathology. To enable this crucial validation, he engineered a system using **patient-specific 3D-printed molds** to achieve precise spatial alignment between in vivo MRI, ex vivo MRI, and histopathology. This methodological innovation is foundational for correlating imaging biomarkers with ground-truth tissue analysis. Through these combined efforts—from algorithm development to rigorous histopathological validation—Sung is advancing the precision and reliability of MRI-based prostate cancer diagnosis.
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