Description of Research Expertise
Dr. Song is a biomedical engineer with a strong background in MRI physics and expertise in various areas of MRI engineering. Dr. Song has extensive experience in developing novel dynamic imaging strategies in MRI. For over a decade, his research has focused on the development of dynamic contrast-enhanced (DCE-) MRI strategies based on novel radial data acquisition and reconstruction methods that allow ultra-rapid dynamic imaging at both high spatial and high temporal resolutions. Utilizing the golden angle radial acquisition strategy, Dr. Song also developed and implemented effective strategies to retrospectively compensate for respiratory motion in DCE-MRI. The technique also permits the reconstruction of the dynamic series to be highly flexible, allowing many of the decisions regarding spatial/temporal resolution to be made retrospectively and optimally. These strategies are currently being utilized for the assessment of treatment effects in various tumors, including lung, liver, breast, kidney and ovarian/fallopian tube. The methods he has developed have also been utilized in other areas of research, including rapid non-contrast enhanced dynamic MRA and fast tissue T1 mapping. Dr. Song collaborates with clinicians in various departments within Penn’s School of Medicine and other institutions, including the Departments of Medicine, Obstetrics and Gynecology, Neurology, and Radiation Oncology. The scope of training under Dr. Song’s guidance includes understanding the various tumor perfusion models, MRI physics, MRI pulse sequence programming and image post-processing.
Selected Publications
Li Y, Joaquim MR, Pickup S, Song HK, Zhou R, Fan Y: Learning ADC maps from accelerated radial k-space diffusion-weighted MRI in mice using a deep CNN-transformer model Magnetic Resonance in Medicine 91 (1): 105-117,2024.
Kamona N, Jones BC, Lee H, Song HK, Rajapakse CS, Wagner CS, Bartlett SP, Wehrli FW: Cranial bone imaging using ultrashort echo-time bone-selective MRI as an alternative to gradient-echo based "black-bone" techniques Magnetic Resonance Materials in Physics, Biology and Medicine 37 (1): 83-92,2024.
Vu BD, Kamona N, Kim Y, Ng JJ, Jones BC, Wehrli FW, Song HK, Bartlett SP, Lee H, Rajapakse CS: Three contrasts in 3 min: Rapid, high-resolution, and bone-selective UTE MRI for craniofacial imaging with automated deep-learning skull segmentation Magnetic Resonance in Medicine Online ahead of print : 2024.
Jones BC, Wehrli FW, Kamona N, Deshpande RS, Vu BD, Song HK, Lee H, Grewal RK, Chan TJ, Witschey WR, MacLean MT, Josselyn NJ, Iyer SK, Al Mukaddam M, Snyder PJ, Rajapakse CS: Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning Bone 171 : 116743,2023.
Jones BC, Lee H, Cheng CC, Al Mukaddam M, Song HK, Snyder PJ, Kamona N, Rajapakse CS, Wehrli FW: MRI Quantification of Cortical Bone Porosity, Mineralization, and Morphologic Structure in Postmenopausal Osteoporosis Radiology 307 (2): e221810,2023.
Romanello Joaquim M, Furth EE, Fan Y, Song HK, Pickup S, Cao J, Choi H, Gupta M, Cao Q, Shinohara R, McMenamin D, Clendenin C, Karasic TB, Duda J, Gee JC, O'Dwyer PJ, Rosen MA, Zhou R: DWI Metrics Differentiating Benign Intraductal Papillary Mucinous Neoplasms from Invasive Pancreatic Cancer: A Study in GEM Models Cancers 14 (16): 4017,2022.
Zimmerman CE, Khandelwal P, Xie L, Lee H, Song HK, Yushkevich PA, Vossough A, Bartlett SP, Wehrli FW: Automatic Segmentation of Bone Selective MR Images for Visualization and Craniometry of the Cranial Vault Academic Radiology 29 : S98-S106,2022.
Pickup S, Romanello M, Gupta M, Song HK, Zhou R: Dynamic Contrast-Enhanced MRI in the Abdomen of Mice with High Temporal and Spatial Resolution Using Stack-of-Stars Sampling and KWIC Reconstruction Tomography 8 (5): 2113-2128,2022.
Tianming Du, HonggangZhang, YuemengLi, StephenPickup, MarkRosen, RongZhou, Hee KwonSong, Yong Fan: Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation Medical Image Analysis 72 : 2021.
Cao J, Song HK, Yang H, Castillo V, Chen J, Clendenin C, Rosen M, Zhou R, Pickup S: Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer Tomography 7 (1): 66-79,2021.