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Medical Physics, PhysicsOther Titles: Senior Medical Physicist, BC Cancer Agency, Centre for the Southern Interior
Graduate student supervisor
Cone beam CT image optimization; novel imaging applications in radiation therapy.
Research Interests & Projects
CT & Cone Beam CT Image Quality Optimization
CT has been widely used in many areas of medical applications. Now CBCT is also used for image guided radiation therapy. There exist a wide range of acquisition technical spaces for image quality optimization for the specific imaging application. I am working on developing image quality metric and optimizing acquisition parameters on the CT simulators to provide better depiction of patient anatomy for treatment planning. Similar method can be extended to diagnostic CT procedures to provide better trade-off points between image quality and patient dose.
Detective Quantum Efficiency (DQE) has been widely accepted as the benchmark for assessing the image quality provided by an x-ray imaging detector. It is a tool used extensively in industry and scientific communities for x-ray imaging detector design considerations and technology development. However, detector is simply one of the many components in an x-ray imaging system contributing to the final image quality. We are interested in expanding the concept and methodology of DQE to a system level that includes the impacts from all the components in an x-ray imaging system. It can be used to identify the weakest link in the imaging chain of the system as well as optimization for each of the system components. Coupled with sensitivity analysis, it can also be used to identify individual component improvement opportunities that make most economical sense.
Novel x-ray Imaging Detector Design
In digital x-ray imaging detector technology, one common design component that is most crucial to image quality is the detection layer used to interact with incoming x-rays. Whether it is a phosphor or a photoconductor, this layer for x-ray interaction/detection determines the fundamental and inherent image quality of the detector system. All the other components of the detector systems designed at best are to preserve (instead of degrading) the initial image quality provided by the x-ray interaction/detection layer. We are interested in modeling the novel designs of the x-ray interaction/detection layer to understand the various image quality trade-off from the different designs as well as to maximize the DQE.
Digital Breast Tomosynthesis
Breast Tomosynthesis provides the technology that has the potential to overcome the difficulty in identify cancer from the overlaying breast tissue in a traditional 2D projection mammogram. However, even with the current state-of-art system, the manufactures have not been able to prove its clinical advantages over tradition 2D mammograms. We are interested in understanding the image quality degradation process of the 3D reconstruction in generating the tomosynthesis slices. Each of the 2D projection mammograms used to generate tomosynthesis slices is typically acquired at much lower dose level and therefore has higher electronic and x-ray quantum noise than those of a traditional 2D mammogram. Furthermore, there is an additional spatial blurring inherent to the 3D back projection process. I am also interested in researching novel technique in overcoming several of these shortcomings.
Mammography has been the gold standard for breast cancer detection. With the advent of digital technology, digital mammography provides new and exciting opportunity to further improve the most quality demanding image modality. With the advantage of decoupling the image acquisition and image display for digital systems, it is now possible to optimize the image acquisition parameters for digital mammography independent of the image display. Currently, many image acquisition parameters used on most of the digital mammography systems were simply inherited from the practice of film/screen mammography. With current world wide adoption of digital mammography, there is a great interest in how best use of these digital mammography systems. I am working on identifying new x-ray technique factors may or may not available on current commercial systems for different breast conditions for optimal image quality per radiation risk.
Our research focuses on trajectory treatment plan optimization and treatment delivery verification. The current plan optimization algorithms are incapable to utilize the additional degrees of freedom and would require exponentially longer optimization time. This N dimensional problem requires new optimization techniques to fully exploit the benefit of trajectory based treatments. Before trajectory based treatments can be used clinically, new treatment delivery verification tools are necessary. We are investigating different solutions such as Monte Carlo simulations and film dosimetry.