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Methodology
This has two stages, first is pre-processing of given MRI image and after that segmentation and
then morphological operations.
• Input image
• Multiparameter Calculations
• Segmentation o brain tumor using Region of Interest command
Image Processing Techniques
Median Filtering for Noise Removal
Is a non-linear filtering technique used for noise removal. It is used to remove salt and pepper
noise from the converted gray scale image. It replaces the intensity values of the center pixel with
the median of the intensity values in the neighbourhood of that pixel. Median filters are particularly
effective in the presence of impulse noise.
Various De-noising Filters
Mean Filter- Based on average value of pixels
Median Filter – Based on the median value of pixels
Wiener Filter – Based on inverse filtering in frequency
Hybrid Filter – Combination of median and wiener filter
Modified hybrid median filter – Combination of mean and median Filter
Morphology Based De-noising- Based on Morphological opening and closing Operations.
Image Enhancement
Poor contrast is one of the defects found in acquired image. The effect of that defect has great
impact on the contrast of image. When contrast is poor the contrast enhancement method plays an
important role. The gray level of each pixel is scaled to improve the contrast. Contrast
enhancements improve the visualization of the MRI image.
Edge Detection
Is an image processing technique for finding the boundaries of objects with in images. It works
by detecting discontinuities in brightness. It is used for image segmentation and data extraction in
areas such as image processing, computer vision, and machine vision.
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