Noureddine Ait Ali
ABSTRACT
Given the continuous increase of the data size to be processed, the need for the information manipulation' speed (acquisition, processing, and analysis) has become increasingly necessary in many areas. In brain imaging, diagnostic systems provide large amounts of data in 2D and 3D with different modalities. Nevertheless, in front of the technological limitation and the development of the microprocessors speed, in recent years, researchers have moved to parallelism as an alternative to design algorithms running on distributed systems, computing grids or massively parallel systems. With the advent of the GP-GPU concept (General Purpose - Graphical Processing Unit), which means the use of graphic cards (originally designed for graphic rendering) for general computing, several researchers are oriented towards this new use of GPUs to dispense the microprocessor CPUs expensive treatment portions of their sequential algorithms. In this paper a comparative study of two parallel implementation of bias correction FCM (BCFCM) and Spatial FCM (SFCM) has been done in term of robustness and efficiency
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