Ziyi Zheng
Ph.D Student
SPIE Involvement:
Author | Instructor
Publications (2)

Proceedings Article | 17 March 2011
Proc. SPIE. 7961, Medical Imaging 2011: Physics of Medical Imaging
KEYWORDS: Signal to noise ratio, 3D image reconstruction, CT reconstruction, Lung, Radiotherapy, Data acquisition, Image quality, Computed tomography, Reconstruction algorithms, Nonlinear filtering

Proceedings Article | 27 February 2010
Proc. SPIE. 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
KEYWORDS: Visual process modeling, X-ray computed tomography, CT reconstruction, Data modeling, Visualization, X-rays, 3D modeling, Volume rendering, Statistical modeling, Model-based design

Course Instructor
SC829: MIC-GPU: High-Performance Computing for Medical Imaging on Programmable Graphics Hardware (GPU)
Advanced graphics boards have become a standard ingredient in any mid-range and high-end PC, and aside from enabling stunning interactive graphics effects in computer games, their rich programmability allows speedups (over CPU-based code) of 1-2 orders of magnitude also in general-purpose computations. This course explains, in gentle ways, how to exploit this powerful computing platform to accelerate various popular medical imaging applications, such as CT, MRI, image processing, and data visualization. It begins by introducing the basic GPU architecture and its programming model, which establishes a solid understanding on how general computing tasks must be structured and implemented on the GPU to achieve the desired high speedups. Next, it examines a number of standard 2D and 3D medical imaging operators, such as filtering, sampling, statistical analysis, transforms, projectors, etc, and explains how these can be effectively accelerated on the GPU. Finally, it puts this all together by describing the full GPU-accelerated computing pipeline for a representative set of medical imaging applications, such as analytical and iterative CT, MRI, image enhancement chains, and volume visualization.
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