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Quant Imaging Med Surg. 2012 Sep;2(3):188-206. doi: 10.3978/j.issn.2223-4292.2012.08.02.

A survey of GPU-based medical image computing techniques.

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  • 1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China; ; CUHK Shenzhen Research Institute, Shenzhen, Guangdong Province, P.R. China; ; Shenzhen Institute of Advanced Integration Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, P.R. China.


Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine.


Graphics processing unit (GPU); high-performance computing; image registration; image segmentation; image visualization

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