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Kyunghyun Sung

Researcher at University of California, Los Angeles

Publications -  74
Citations -  2307

Kyunghyun Sung is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Medicine & Flip angle. The author has an hindex of 19, co-authored 65 publications receiving 1788 citations. Previous affiliations of Kyunghyun Sung include Ronald Reagan UCLA Medical Center & University of Southern California.

Papers
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k-t FOCUSS: a general compressed sensing framework for high resolution dynamic MRI.

TL;DR: An extension of k‐t FOCUSS to a more general framework with prediction and residual encoding, where the prediction provides an initial estimate and the residual encoding takes care of the remaining residual signals.
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Deep learning with domain adaptation for accelerated projection-reconstruction MR.

TL;DR: A novel deep learning approach with domain adaptation is proposed to restore high‐resolution MR images from under‐sampled k‐space data to solve the problem of streaking artifact patterns in magnetic resonance imaging.
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Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet

TL;DR: A novel multi-class CNN, FocalNet, is proposed to jointly detect PCa lesions and predict their aggressiveness using Gleason score (GS), which characterizes lesion aggressiveness and fully utilizes distinctive knowledge from mp-MRI.
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Automatic Prostate Zonal Segmentation Using Fully Convolutional Network With Feature Pyramid Attention

TL;DR: In this paper, a novel convolutional neural network (CNN) was designed for automatic segmentation of the prostate transition zone (TZ) and peripheral zone (PZ) on T2-weighted (T2w) 3 Tesla (3T) MRI.
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Measurement and characterization of RF nonuniformity over the heart at 3T using body coil transmission

TL;DR: To measure and characterize variations in the transmitted radio frequency (RF) (B1+) field in cardiac magnetic resonance imaging (MRI) at 3 Tesla, knowledge of the B1+ field is necessary for the calibration of pulse sequences, image‐based quantitation, and signal‐to‐noise ratio (SNR) and contrast‐to-noise ratios (CNR) optimization.