Qianqian's Research Homepage
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Qianqian Fang, Ph.D.
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Primary Research Interest
near-infrared (NIR) biomedical imaging, image reconstruction algorithms, optical systems, microwave imaging, computational physics (electromagnetics), FDTD, FEM, phase unwrapping, parallel computing
Education
Ph.D. in Biomedical Engineering(Sep. 2000-Dec. 2004)
Thayer School of Engineering, Dartmouth College,
Hanover, NH, 03755
B.Eng. in Electrical Engineering(Sep. 1995-Jul. 1999)
Institute of Electrical Engineering,
Univ. of Electronic Sci. & Tech. of China (UESTC),
Chengdu, Sichuan, China
Project
Ph.D. Dissertation
Title: Computational Methods for Microwave Medical Imaging
Thesis Committee: Paul Meaney, Keith Paulsen, William Lotko, Eric Miller
Abstract:
Medical imaging methods have become increasingly important in diagnosing
diseases and assisting therapeutic treatment. In particular, early detection of
breast cancer is considered as a critical factor in reducing the mortality rate
of women. In the U.S. alone, roughly one in seven women will develop breast
cancer during their lifetime and breast cancer accounts for the second highest
mortality rate among women cancer deaths. Within the various alternative breast
imaging modalities being investigated to improve breast cancer detection,
microwave imaging is attractive due to the high dielectric property contrast
between the cancerous and the normal tissue and has received significant
interest over the last decade. The investigation into two-dimensional microwave
imaging at the Thayer School of Engineering, Dartmouth College, began in the
early 1990's where the first clinical microwave imaging system was brought
online at the Dartmouth-Hitchcock Medical Center (DHMC) in 1999.
Although the two dimensional microwave imaging has shown great promise, the
image quality is essentially compromised by the various approximations
associated with operating in 2D. In this thesis, we focus on the theoretical
aspects of the nonlinear tomographic image reconstruction problem with
particular emphasis on developing efficient numerical algorithms for 3D
microwave imaging. An incremental approach was devised to assess this progress.
The concept of the dual-mesh was generalized and served as an organizing theme
from which the computational efficiency of various forward field modelling
methods were investigated. These methods included the 2D finite element coupled
with boundary element methods and the 2D FDTD method with its extension to 3D
space. Significant effort was spent on optimizing the 3D forward model in order
to reconstruct images efficiently. Additional reconstruction techniques such as
the adjoint method, the nodal adjoint approximation as well as a
multiple-frequency dispersion reconstruction algorithm were developed to enhance
both the speed and quality of the recovered images. An in-depth analysis of the
Jacobian matrix was performed in the context of investigating various important factors
including the resolution limit and the impact of system parameters on image
quality. Additionally, a mathematical theory encompassing the properties of the
phase unwrapping integral and its use with respect to our log-magnitude/phase
form (LMPF) imaging algorithm was developed and discussed with particular
attention to microwave scattering nulls.
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Non-research Interests
Non-computer related:
travel, ping-pong, soccer, badminton, photography, stamp collection, movie, music, Chinese calligraphy and painting
Computer related:
application development (C/C++,perl,matlab,javascript), GUI design, computer graphics, web design
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