High speed processing of biomedical images using programmable gpu
Jin Young Hong, May Dongmei Wang · 2005
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 bioorganism. To accurately quantify these objects, shape-independent image processing techniques are needed. One of such techniques is level set (LS) method. However, its application to large size images 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, GPU-LS, to process large size of biomedical images. In this paper, we report how we perform LS processing utilizing features of advanced graphics hardware. Comparing CPU-LS and GPU-LS, we have achieved average 12-13 times increase in processing speed.