Diagnosis and prediction of Brain malfunction Using Hybrid Segmentation Methods
Journal Title: International Research Journal in Global Engineering and Sciences - Year 2016, Vol 1, Issue 3
Abstract
Automatic image segmentation turns severely crucial for the detection of tumor in the processing of medical image. Semi automatic and Manual techniques of segmentation require immense knowledge and time. These drawbacks however has been overcome by the hybrid segmentation, yet there are requirements to develop many techniques that are appropriate for the medical image segmentation .Hence, we generated image segmentation based on hybrid approach making use of the features of threshold segmentation technique and region growing techniques combined. This is followed by the pre-processing stage to give away an accurate extraction of brain tumor with the help of (MRI) Magnetic Resonance Imaging. The threshold segmentation method is made use of for the segmentation. Four types of noise are undergone in the segmented image: Gaussian noise, salt and pepper noise, Poisson noise and speckle noise which are influenced in brain smear image and they are removed using the filters of four types : median filter, mean filter, wiener filter and gaussian filter to test the efficiency of the variety of filters over the various kinds of noise. To estimate the parametric values we can make use of PSNR , NAE ,MSE and NK .
Authors and Affiliations
Pavan Kumar Reddy Y, Fayaz K
Keywords
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