Impact of Edge Detection Algorithms in Medical Image Processing

Imaging technology in Medicine let the doctors to see the interior portions of the body for easy diagnosis. It also helped doctors to make keyhole surgeries for reaching the interior parts without really opening too much of the body. Noise in medical images appears in an image from a variety sources or it is the random variation of brightness or color information in images. Edge detection is a common process in the treatment of medical images and it is a very useful task for object recognition of human organs. Edge detection also show where shadows fall in an image or any other distinct change in the intensity of an image due to noise effects. In this paper we evaluated the performance of different edge detection algorithms; Canny, Prewitt, LOG, and Laplacian with and without adding filer such as wiener and median. The statement of effectiveness in removing noise and preserving important information in medical image is identified by using quality measurements like PSNR and MSE. Results show that the best algorithm for displaying edge and removing salt & pepper noise is the Prewitt Algorithm after using the median filter. Additionally, it was found that the best algorithm for displaying edge and removing Gaussian noise is the Canny algorithm after using the median filter.