Abstract
Always MRI and CT Medical images are noisy so that preprocessing is necessary for enhance these images to assist clinicians and make accurate diagnosis. Firstly, in the proposed method uses two denoising filters (Median and Slantlet) are applied to images in parallel and the best enhanced image gained from both filters is voted by use PSNR and MSE as image quality measurements. Next, extraction of brain tumor from cleaned images is done by segmentation method based on k-mean. The result shows that the proposed method is giving an optimal solution due to denoising method which is based on multiple filter types to obtain best clear images and that is leads to make the extraction of tumor more precision best.
Highlights
1- Introduction Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are the most widely used techniques to provide of differentiation between brain tissues and to diagnose the brain diseases
Madhi and Mohammed, 2018, proposed a program to detect and allocate of brain tumors according to YCbCr segmentation, the results reflected more than 99% better detection rate with speedy processing [11]
This paper proposed the medical image enhancement method consisting of two stages, smoothing and segmentation
Summary
The Median Filter is a non-linear digital filtering technique, often used to remove noise from an image or signal. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image). Median filtering is very widely used in digital image processing because, under certain conditions, it preserves edges while removing noise, has applications in signal processing [12, 13]. W is centered on location [m, n] in the image and identified by the user
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