UBC PET/MR Imaging Program

Ju-Chieh (Kevin) Cheng, PhD

PET/MRI PHYSICIST, RESEARCH SCIENTIST

Contact Info:
 
Phone: 604-827-2945
 

Dr. Ju-Chieh (Kevin) Cheng is the PET/MRI physicist of the UBC PET/MR imaging facility. Kevin has a great deal of experience in working with both small animal and human PET scanners as well as clinical PET/MRI systems. Kevin is also an image reconstruction expert who has developed several advanced reconstruction methods which achieve noise reduction while minimizing bias for both static and dynamic PET imaging as well as improving quantitative corrections for PET/CT and PET/MRI systems. 

 

Education: 

PDF, Wolfson Molecular Imaging Centre, University of Manchester 

PDF, VU University Medical Center Amsterdam 

PDF, Mallinckrodt Institute of Radiology – Washington University in St. Louis 

Ph.D. in Physics, University of British Columbia 

M.Sc. in Physics, University of British Columbia 

B.Sc. in Physics, University of British Columbia 

 

Affiliation: 

Pacific Parkinson’s Research Centre, University of British Columbia 

Department of Physics and Astronomy, University of British Columbia 

  

Research interest/topics: 

PET image reconstruction, quantitative PET corrections, intrinsic data-driven noise reduction, deep learning guided image quality enhancements 

  

Recent Publications: 

  1. J.-C. Cheng, E. Reimers, and V. Sossi, HYPR4D Kernel Method With an Unsupervised 2.5SD+0.5TD Deep Learning Assisted Kernel Matrix, IEEE Trans. Rad. Plas. Med. Sci., 2024. 
  2. M. Matarazzo et al., Misfolded protein deposits in Parkinson’s disease and Parkinson’s disease-related cognitive impairment, a [11C]PBB3 study, npj Parkinson’s Disease, 2024. 
  3. C. Bevington, J. Hanania, G. Ferraresso, J.-C. Cheng, A. Pavel, D. Su, A. J. Stoessl, and V. Sossi, Novel voxelwise residual analysis of [11C]raclopride PET data improves detection of low-amplitude dopamine release, J. Cereb. Blood Flow Metab., 2023. 
  4. E. Reimers, J.-C. Cheng, and V. Sossi, Deep-Learning-Aided Intraframe Motion Correction for Low-Count Dynamic Brain PET, IEEE Trans. Rad. Plas. Med. Sci., 2023. 
  5. J.-C. Cheng, C. Bevington, and V. Sossi, HYPR4D kernel method on TOF PET data with validations including image‑derived input function, EJNMMI Physics, 2022. 
  6. C. Bevington, J.-C. Cheng, and V. Sossi, A 4-D Iterative HYPR Denoising Operator Improves PET Image Quality, IEEE Trans. Rad. Plas. Med. Sci., 2022. 
  7. J. G. Mannheim, J.-C. Cheng, et al., Cross-validation study between the HRRT and the PET component of the SIGNA PET/MRI system with focus on neuroimaging, EJNMMI Physics, 2021. 
  8. J.-C. Cheng, C. Bevington, A. Rahmim, I. Klyuzhin, J. Matthews, R. Boellaard, and V. Sossi, Dynamic PET Image Reconstruction Utilizing Intrinsic Data-Driven HYPR4D De-noising Kernel, Med. Phys., 2021 (Editor’s Choice). 
  9. I. Klyuzhin, C. Bevington, J.-C. Cheng, and V. Sossi, Detection of transient neurotransmitter response using personalized neural networks, Phys. Med. Biol., 2020. 
  10. C. Bevington, J.-C. Cheng, I. Klyuzhin, M. Cherkasova, C. Winstanley, and V. Sossi, A Monte Carlo approach for improving transient dopamine release detection sensitivity, J. Cereb. Blood Flow Metab., 2020. 
  11. I. Klyuzhin, J.-C. Cheng, C. Bevington, and V. Sossi, Use of a Tracer-Specific Deep Artificial Neural Net to Denoise Dynamic PET Images, IEEE Trans. Med. Imag., 2019. 
  12. V. Sossi, J.-C. Cheng, and I. Klyuzhin, Imaging in Neurodegeneration: Movement Disorders, IEEE Trans. Rad. Plas. Med. Sci., 2018. 
  13. J.-C. Cheng, J. Matthews, V. Sossi, J. Anton-Rodriguez, A. Salomon, and R. Boellaard, Incorporating HYPR De-noising within Iterative PET Reconstruction (HYPR-OSEM), Phys. Med. Biol., 2017. 
  14. J.-C. Cheng, A. Salomon, M. Yaqub, and R. Boellaard, Investigation of Practical Initial Attenuation Image Estimates in TOF-MLAA Reconstruction for PET/MR, Med. Phys., 2016 (Editor’s Choice).