Parallel Hardware Architecture for Medical Image Processing Using Xilinx-System-Generator

FPGA is increasingly used in latest realizations of real time implementation for a variety of image processing such as medical imaging. In this paper, we present parallel hardware architecture through a co-simulation using the most efficient tool called Xilinx-System-Generator (XSG) which integrated with MATLAB-Simulink and the synthesis tool used is Xilinx-Vivado. We propose a new strategy for FPGA's memory management based on a design of edge detection algorithm already implemented. The goal is to make an optimization for memory use by minimizing the consumption of slices-registers and slices-Luts. This technique was successfully verified in the images obtained and the resource utilization for the proposed architectures show that the new architectures use fewer resources than the existing architecture.