HIGH SPEED PROCESSING OF BIOMEDICAL IMAGES USING PROGRAMMABLE GPU (WA-L2)

Author(s) : Jin Young Hong (Human Computer Interaction Master Program, USA) May D. Wang (The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, USA)

Abstract : In this paper, we report our research results on high speed processing of large size biomedical images. The biomedical images usually contain various shapes of bio-organism. To accurately quantify these objects, shape-independent image processing techniques are needed. Level set (LS) is such a good candidate in terms of tracking various shape features. However, its application to large size image is constrained by the extremely high computational cost. This is because a set of numerical simulations has to be performed repeatedly on every pixel of an image, and the general-purpose central processing unit (CPU) has only one execution core and limited memory bandwidth. Thus, we researched for techniques that can perform a large number of iterative tasks effectively. As a result, we designed and developed a graphics processing unit (GPU) based level set (LS) algorithm to process large size of biomedical images. In this paper, we explain the detail of using graphics hardware and present the image processing results achieved by our GPU-LS. Comparing CPU-LS and GPU-LS, we illustrate 12-13 times increase in processing speed.

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