engleski

GPU Implementation of a Medical Imaging Data Compression Algorithm

In this paper an algorithm for compressing medical images on GPUs is described and its energy consumption and computational performance analyzed. The objectives of this implementation are to reduce the demands of storing medical pictures, improve the execution time and reduce the consumption of electrical energy. The compression algorithm is based on a computationally complex prediction model of pixels and a contextual coding of the given prediction errors. The above implementation is compared with a serial implementation and with an implementation in a stream programming model in terms of execution time and electrical energy consumption. Experimental results show improvements in execution speed and savings in consumption of electrical energy using the proposed implementation

Medical Visual Data Compression; General Purpose GPU Programming; Lossless Coding Parallelization; Data-Intensive Computing

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