Dr. Sung's primary research focuses on the development of novel medical imaging methods and artificial intelligence using magnetic resonance imaging (MRI). In particular, his research group (https://mrrl.ucla.edu/sunglab/) is currently focused on, developing advanced deep learning algorithms and quantitative MRI techniques for early diagnosis, treatment guidance, and therapeutic response assessment for oncologic applications. Such developments can offer more robust and reproducible measures of biologic markers associated with cancers.
R Cao, S Shakeri, X Zhong, AM Bajgiran, SA Mirak, DS Lu, D Enzmann, S Raman, K Sung. Improved Diagnosis of Prostate Cancer via FocalNet. IEEE Transaction on Medical Imaging. 2019. DOI:10.1109/TMI.2019.2901928.
Y Liu, G Yang, SA Mirak, M Hosseiny, A Azadikhah, X Zhong, Y Lee, RE Reiter, SS Raman, K Sung. Automatic Prostate Zonal Segmentation Using Fully Convolutional Network with Feature Pyramid Attention. IEEE Access. 2019. DOI:10.1109/ACCESS.2019.2952534.
H Zheng, Q Miao, Y Liu, F Scalzo, S Raman, K Sung. Integrative Machine Learning Prediction of Prostate Biopsy Results from Negative Multiparametric MRI. Journal of Magnetic Resonance Imaging. 2021. DOI: 10.1002/jmri.27793.
Y Liu, M Qi, C Surawech, H Zheng, D Nguyen, G Yang, S Raman, K Sung. Deep Learning Enables Prostate MRI Segmentation: A Large Cohort Evaluation with Inter-rater Variability Analysis. Frontier in Oncology. 2021. DOI: 10.3389/fonc.2021.801876.
H Zheng, Q Miao, SA Mirak, M Hosseiny, F Scalzo, SS Raman, K Sung. Multiparametric MRI-Based Radiomics Model to Predict Pelvic Lymph Node Invasion for Patients with Prostate Cancer. European Radiology. 2022. DOI: 10.1007/s00330-022-08625-6.