Professor, Acting Department Chair, Biomedical Engineering
Qi Lab Website
B.S. Electrical Engineering Tsinghua University, Beijing, China 1993
M.S. Electrical Engineering University of Southern California, Los Angeles 1997
Ph.D. Electrical Engineering University of Southern California, Los Angeles 1998
Biomedical Engineering Graduate Group
Electrical and Computer Engineering Graduate Group
Dr. Jinyi Qi’s research focuses on developing advanced signal and image processing techniques for molecular imaging. One emphasis is on developing statistically based image reconstruction methods for emission tomography. The research involves modeling imaging system response, developing appropriate statistical models, developing optimization algorithms, and analyzing image properties. Current projects include high-resolution image reconstruction, adaptive PET imaging, dynamic PET data analysis, image quality evaluation for system optimization, and information fusion in multimodality imaging.
- J Zhou and J Qi, “Adaptive imaging for lesion detection using a zoom-in PET system,” IEEE Transactions on Medical Imaging, in press.
- MS Tohme and J Qi, “Iterative reconstruction of Fourier-rebinned PET data using sinogram blurring function estimated from point source scans,” Medical Physics, 37:5530-5540, 2010.
- L Fu and J Qi, “A Residual Correction Method for High-Resolution PET Reconstruction with Application to On-the-fly Monte Carlo-Based Model of Positron Range,” Medical Physics, 37(2):704-713, 2010.
- G Wang and J Qi, “Acceleration of direct reconstruction of linear parametric images using nested algorithms,” Physics in Medicine and Biology, 55:1505-1517, 2010.
- J Cheng-Liao and J Qi, “Dynamic PET image segmentation using a multiphase level set method,” Physics in Medicine and Biology, 55:6549-6569, 2010.
- N Cao, RH Huesman, WW Moses, and J Qi, “Detection Performance Analysis for Time-of-Flight PET,” Physics in Medicine and Biology, 55:6931-6950, 2010.
- J Zhou and J Qi, “Theoretical analysis and simulation study of a high-resolution zoom-in PET system,” Physics in Medicine and Biology, 54:5193-5208, 2009.
- G Wang and J Qi, “Generalized algorithms for direct reconstruction of parametric images from dynamic PET data,” IEEE Transactions on Medical Imaging, 28(11):1717-1726, 2009.
- C Li, G Wang, J Qi, and SR Cherry, “PET Guided Three-Dimensional Fluorescence Optical Tomography in Small Animal Imaging,” Optics Letters, 34(19):2933-2035, 2009.
- G Wang, L Schultz, and J Qi, “Statistical image reconstruction for muon tomography using a Gaussian scale mixture model,” IEEE Transactions on Nuclear Science, 56(4):2480-2486, 2009.
- Michel Tohme and J Qi, “Iterative image reconstruction for positron emission tomography based on detector response function estimated from point source measurements,” Physics in Medicine and Biology, 54 (12):3709-3725, 2009.
- L Fu, JR Stickel, R Badawi, and J Qi, “Quantitative Accuracy of Penalized-Likelihood Reconstruction for ROI Activity Estimation,” IEEE Transactions on Nuclear Science, 56 (1):167-172, 2009
- G Wang and J Qi, “Analysis of Penalized Likelihood Image Reconstruction for Dynamic PET Quantification,” IEEE Transactions on Medical Imaging, 28 (4):608-620, 2009.
- G Wang, L Schultz, and J Qi, “Bayesian Image Reconstruction for Improving Detection Performance of Muon Tomography,” IEEE Transactions on Image Processing, 18 (5):1080-1089, 2009.
- C Catana, Y Wu, MS Judenhofer, J Qi, BJ Pichler and SR Cherry, “Simultaneous in vivo Imaging with Positron Emission Tomography and Magnetic Resonance Imaging,” PNAS, 105:3705-3710, 2008.
- G. Wang, L. Fu, and J. Qi, ” Maximum a posteriori reconstruction of Patlak parametric image from sinograms in dynamic PET,” Physics in Medicine and Biology, 53:593-604, 2008.
- J. Qi and R. M. Leahy, “Iterative reconstruction techniques in emission computed tomography,” Physics in Medicine and Biology, 51: R541-R578, 2006 (invited review).