NIH Postdoctoral fellowship 1999-2001, University of Florida
(http://www.ufl.edu);

National Institutes of Health (http://www.nih.gov)/ NIBIB
(http://www.nibib.nih.gov) R01 Grant 2002-2005

Research Interests

My research interests cover Magnetic Resonance Imaging (MRI) physics, functional MRI (fMRI), Radio-Frequency (RF) coils, electromagnetic (EM) simulation, and biological / biomedical applications of MRI.

1. Magnetic resonance imaging (MRI) is an imaging technique to produce high quality images of the human/animal body. MRI is based on magnetic resonance of nucleus (e.g. 1H or proton) to obtain chemical and physical information about molecules. In medical practice, MRI is used to distinguish pathological tissue (such as a tumor) from normal tissue. MRI scan is harmless since it uses strong magnetic fields and non-ionizing radiation in the radio frequency range, compared to CT scans and X-rays which involve doses of ionizing radiation. Also, MRI provides a high contrast resolution of the soft tissue.
2. Functional MRI (fMRI) is a neuro-imaging method of using MRI to measure the hemo-dynamic response related to neural activity in the human brain. Improvement of accuracy and reliability of fMRI measurement is the goal of my group. fMRI is an inter-disciplinary research, including physics, psychology, statistics, and neuro-anatomy.
3. Contrast-enhanced MRI (CEMRI) using paramagnetic nano-particles has been the subject of extensive research since 1990s. Novel CE-MRI applications using biocompatible and biodegradable nano-particles in bio-imaging include cancer diagnosis and treatment evaluation, drug delivery, molecular and cellular imaging area etc.

Recent Publications

Cheng, H., Zhao, Q., Duensing, R., Edelstein, B. et al. “SmartPhantom: an fMRI simulator”, Magnetic Resonance Imaging, 24 (2006) 301-313.

Zhao, Q., Principe, J., Fitzsimmons, J., Bradley, M., and Lang, P.(2002) “An information-theoretic approach to functional Magnetic Resonance Imaging activation analysis.” Chapter 9, Bio-computing, edited by P. Pardalos and J. Principe, Kluwer Academic Publishers, 2002.

Zhao, Q., Principe, J.C., Bradley, M.M., Lang, P.J. (2000). “fMRI Analysis: Distribution divergence measure based on quadratic entropy”. NeuroImage, 11 (5) S521.

Principe, J., Xu, D., Zhao, Q., and J. Fisher III (2000). “Learning from examples with information-theoretic criteria”. Journal of VLSI Signal Processing Systems 26 (2000) 61-77.

Zhao, Q., Conway, T., White, K., and Crosson, B. “Test-retest Reliability of functional MRI using Smart Phantom” (submitted to NeuroImage)

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