MRI Brain Image Enhancement Using XILINX System Generator and DWT

Deshpande, Gouri B.; Ramesha, K

doi:10.9756/bijaip.8039

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…There are many papers deal with the magnetic resonance imaging (MRI) image by using FPGA and these are some examples but not limited to. The authors in [26], [27] use a graphical user interface where the Xilinx system generator and Matlab Simulink are linked together in order to enhance the quality of MRI image. In they fed that Improved image to artificial neural network ANN to be classified if it is normal or abnormal while in [27], they use some parameters such as mean, variance, and standard deviation to classify the tumor.…”

Section: Related Workmentioning

confidence: 99%

Detection of brain stroke in the MRI image using FPGA

2021

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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%.

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Section: Related Workmentioning

confidence: 99%