A Study of anImproved Edge Detection Algorithm for MRI Brain Tumor Images Based on Image Quality Parameters

Abstract

Biomedical imaging with emerging technology plays a vital role in medical diagnosis and treatment. MRI is one such biomedical imaging technology. The incidence of brain tumor in increasing all over the world. Accurate detection of size and location of brain tumor helps in right diagnosis and treatment. In any kind of image processing, image segmentation is a fundamental step. Edge detection is an important technique in the analysis of images, which plays a crucial role in detecting the contour of brain tumor. In this paper, an improved algorithm called the Luminance edge detection algorithm is proposed and compared with the existing edge detection algorithms like Prewitt, Sobel, and Canny for the MRI images of the brain. PSNR and SSIM were calculated to compare the image quality of different edge detection techniques. Results revealed that the PSNR and SSIM values were slightly higher for the images obtained by the Luminance edge detection algorithm when compared to the images obtained by Prewitt, Sobel, and Canny edge detection algorithm. It proves that the proposed algorithm is better than the other edge detection algorithms in producing a quality image of the MRI brain. Hence it can be concluded that the proposed algorithm was better in detecting the contour of brain and brain tumor than the other edge detection techniques.