Sobel Operator with BayesShrink Wavelet De-Noising for Segmentation of Neurosarcoidosis in Brain MRI Images

Nithin, N and Bongale, Anupkumar M (2013) Sobel Operator with BayesShrink Wavelet De-Noising for Segmentation of Neurosarcoidosis in Brain MRI Images. In: Proc. of IEEE International conference on Advanced Research in Engineering and Technology, ., February 08-09 2013..

[img] PDF
Sobel_Operator_with_BayesShrink_Wavelet.pdf - Published Version
Restricted to Registered users only

Download (729kB) | Request a copy

Abstract

Neurosarcoidosis is a disorder caused due to an unknown situation which gives raise to complication of sarcoidosis. It leads to inflammation in nervous system like brain and spinal cord of human body. This paper proposes a new method for segmenting neurosarcoidosis in brain MRI image using Sobel edge detection over BayesShrink wavelet thresholding. The BayesShrink threshold wavelet acts a boosting technique by mitigating Gaussian white noise appearing the image. The performance of proposed algorithm is evaluated by comparing the segmentation results with the standard Sobel method, Prewitt method, Laplacian of Gaussian method and Canny method of image segmentation techniques. It is clearly observed that the proposed algorithm efficiently segments part of the MRI brain image affected by neurosarcoidosis.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Image processing, Medical Image, Edge Detector
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 19 Mar 2013 06:38
Last Modified: 19 Mar 2013 06:38
URI: http://eprints.manipal.edu/id/eprint/79164

Actions (login required)

View Item View Item