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Implementation on FPGA Circuit of the Medical Image Processing Algorithms within the Framework of Assistance to the Medical Diagnosis

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The main interest of this paper is the classification Algorithms of a Magnetic Resonance Imaging (MRI) of the human brain developed in a Very High speed integrated circuit of Description Language (VHDL) in order to implement it on Field Programmable Gate Array circuit (FPGA) within the framework of assistance to the diagnosis. Neuronal networks of a Learning Vector Quantization (LVQ) type were used. The training of LVQ is done in MATLAB in order to exploit synoptic weights of the neurons as a database for classification algorithm which will be implemented on cyclone II FPGA circuit of Altera development card (DE2). The purpose of this work is to achieve a real time hardware implementation with higher performance in both size and speed.
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Classification; FPGA; Medical Image Processing; Neuronal Networks; VHDL

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