International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 4 | Issue 2 | Year 2013 | Article Id. IJCTT-V4I2P127 | DOI : https://doi.org/10.14445/22312803/IJCTT-V4I2P127

Improving Segmentation by Denoising Brain MRI ../images through Interpolation Median Filter in ADTVFCM

Skimpy Garg, Jagpreet Kaur

Citation :

Skimpy Garg, Jagpreet Kaur, "Improving Segmentation by Denoising Brain MRI ../images through Interpolation Median Filter in ADTVFCM," International Journal of Computer Trends and Technology (IJCTT), vol. 4, no. 2, pp. 187-188, 2013. Crossref, https://doi.org/10.14445/22312803/IJCTT-V4I2P127

Abstract

In medical science image segmentation plays a very important role. Medical images need very careful analyses. Detection of minor problem in any body part is sometimes a very difficult task. So to make medical diagnosis to be easy task image segmentation is very helpful as it segment the image into number of parts and the required parts are taken for the study. Brain images are very difficult to analyse because of they are grey scale images i.e there is very small intensity change between pixels of these images. Proposed method is to improve the segmentation results by removing noise using interpolation median filter (IMF) which removes the noise by retaining image details and then performing segmentation using ADTVFCM which provides 0.8653 segmentation accuracy with 39% of noise level but by adding IMF to this segmentation method is expected to give more accuracy.

Keywords

Image segmentation, Interpolation median filter, ADTVFCM.

References

[1] P. Tamije Selvy, Dr. V. Palanisamy and M. Sri Radhai (Nov 2012), “A New Fuzzy C Means for Brain Image Segmentation Using Anisotropic Diffused Regularization”, IJSETR, Volume 1, Issue 5. 
[2] J.S. Bhat and B.N. Jagadale (Oct 2012), “A New Approach for Denoising of an Image Corrupted by Salt & Pepper Noise”, J. Comp & Math Sciences Vol. 3, Issue 5. 
[3] N. Senthilkumaran and R. Rajesh (Dec 2011), “Brain Image Segmentation”, International computing ,vol1(3).
[4] R. C. Gonzalez, Richard E. Woods and Steven L. Eddins “Digital Image Processing Using MATLAB” 2nd ed. 
[5] Ramanpreet Kaur (Oct 2012), “Segmentation in Medical Resonance images to extract the cancerous nodule for early diagnosis on cancer “, IJCT, Volume 3 No. 2. 
[6] Sulaiman Siti Noraini, Nor Ashidi Mat Isa (Nov 2010) “Denoisingbased Clustering Algorithms for Segmentation of Low Level Salt-andPepper Noise-Corrupted Images”, IEEE, Vol. 56, No. 4.
[7] Mussarat Yasmin, Sajjad Mohsin, Muhammad Sharif,, Mudassar Raza and Saleha Masood(2012) “Brain Image Analysis:A survey”, World Applied Science Journal 19(10): 1484-1494, 2012  ISSN 1818-4952. 
[8] Yu-Hsiang Wang “Tutorial: Image segmentation”. 
[9] Yong Yang, Pan Lin, Chongxun Zheng, “An Efficient Statistical Method for Segmentation of Single-Channel Brain MRI”, Fourth International Conference on Computer and Information Technology, 2004.