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http://dx.doi.org/10.15701/kcgs.2017.23.2.1

Accelerating Medical Image Processing on Integrated GPU Using OpenCL  

Kim, Beom-Jun (Dept. of Computer Engineering, Inha Univ.)
Shin, Byeong-seok (Dept. of Computer Engineering, Inha Univ.)
Publication Information
Journal of the Korea Computer Graphics Society / v.23, no.2, 2017 , pp. 1-10 More about this Journal
Abstract
A variety of filters are applied to improve the quality of noise and low resolution medical images. This is necessary to reduce the radiation dose of the patient and to improve the utilization of the conventional spherical imaging equipment. In the conventional method, it is common to perform filtering using the CPU of the PC. However, it is difficult to produce results in real time by applying various calculations and filters to high-resolution human images using only the CPU performance of a PC used in a hospital. In this paper, we analyze the structure and performance of Intel integrated GPU in CPU and propose a method to perform image filtering using OpenCL parallel processing function. By applying complex filters with high computational complexity to medical images, high quality images can be generated in real time.
Keywords
Medical Image; SLM(Shared Local Memory); integrated GPU; L3 cache;
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