Detection of brain stroke in the MRI image using FPGA

Abstract

One of the most important difficulties which doctors face in diagnosing is the analysis and diagnosis of brain stroke in magnetic resonance imaging (MRI) images. Brain stroke is the interruption of blood flow to parts of the brain that causes cell death. To make the diagnosis easier for doctors, many researchers have treated MRI images with some filters by using Matlab program to improve the images and make them more obvious to facilitate diagnosis by doctors. This paper introduces a digital system using hardware concepts to clarify the brain stroke in MRI image. Field programmable gate arrays (FPGA) is used to implement the system which is divided into four phases: preprocessing, adjust image, median filter, and morphological filters alternately. The entire system has been implemented based on Zynq FPGA evaluation board. The design has been tested on two MRI images and the results are compared with the Matlab to determine the efficiency of the proposed system. The proposed hardware system has achieved an overall good accuracy compared to Matlab where it ranged between 90.00% and 99.48%.

Hardware implementation of Sobel edge detection system for blood cells images-based field programmable gate array

“…It is based on calculating the changes of the intensity for the neighbour pixels in the image. ED has been widely used in the field of medical image processing [1]- [4]. In the paper, Anas et al studied the performance of several edge detection methods on different X-ray images [1].…”