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Hybrid Contrast Enhancement Approach for Medical Image

Published on March 2014 by B.ganesan, G. Yamuna, Sudhir Kumar Suman
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National Conference on Emerging Trends in Information and Communication Technology 2013
Foundation of Computer Science USA
NCETICT - Number 1
March 2014
Authors: B.ganesan, G. Yamuna, Sudhir Kumar Suman
34261f7b-4aaf-414a-8b45-1aee3b770c7f

B.ganesan, G. Yamuna, Sudhir Kumar Suman . Hybrid Contrast Enhancement Approach for Medical Image. National Conference on Emerging Trends in Information and Communication Technology 2013. NCETICT, 1 (March 2014), 9-12.

@article{
author = { B.ganesan, G. Yamuna, Sudhir Kumar Suman },
title = { Hybrid Contrast Enhancement Approach for Medical Image },
journal = { National Conference on Emerging Trends in Information and Communication Technology 2013 },
issue_date = { March 2014 },
volume = { NCETICT },
number = { 1 },
month = { March },
year = { 2014 },
issn = 0975-8887,
pages = { 9-12 },
numpages = 4,
url = { /proceedings/ncetict/number1/15656-1302/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Emerging Trends in Information and Communication Technology 2013
%A B.ganesan
%A G. Yamuna
%A Sudhir Kumar Suman
%T Hybrid Contrast Enhancement Approach for Medical Image
%J National Conference on Emerging Trends in Information and Communication Technology 2013
%@ 0975-8887
%V NCETICT
%N 1
%P 9-12
%D 2014
%I International Journal of Computer Applications
Abstract

Available methods for image contrast enhancement focus mainly on the properties of the image to be processed while excluding any consideration of the observer characteristics. In many applications, especially in the medically related images, effective contrast enhancement for diagnostic purposes can be achieved by including certain basic human visual properties. Available techniques for contrast enhancement pertaining to medical image depend on the image characteristics, hence a hybrid contrast enhancement techniques are preferentially considered for medical image to observe better result. Present work deals with above context for CT scan images with single seed based region growing adaptive enhancement techniques. Experimental result shows that the proposed work gives better performance when compared to the existing techniques.

References
  1. Abhijit Mustafi, P. K. Mahanti " An optimal algorithm for Contrast Enhancement of Dark images using Genetic Algorithm" Springer/Chapter /10. 1007/Computer andInformation science /SCI 208/p. no. 1-8/2009
  2. Dr. Krishna Mohanta,Dr. V. Khanna,"An Efficient Contrast Enhancement of Medical X-ray images-Adaptive RegionGrowing approach" International Journal of Engineering and Computer Science Vol. No. 2-2-2-2013,P. No. 386-390
  3. Roman Leyman, Daniel S. Gaichand " Contrast Enhancement of soft tissues in CT images " Proceedings of SPIE Medical Imaging Conference/2006
  4. Navdeep Kanwal, Akshay Girdhar, " Region based Adaptive contrast enhancement of medical X-ray Images" IEEE Vol. No. 978-1P. no. 4244-5089 /2011
  5. Guang Deng, "A Generalized Unsharp Masking algorithm"IEEE Transactions on Image Processing Vol. No. 20,P. No. 1249-1261/Issue May 2011
  6. Yeganeh. H "A novel approach for Contrast Enhancement based on Histogram Equalization " International Conference on Computer and Communication Engineering May 13-15/2008
  7. Anupiya, Akashdayal " Comparison of hybrid and classical Meta Heuristic for Automatic Image Enhancement "Inter-National Journal of Computer Applications, Vol. 46,No. 2 May'2012
  8. Vincent A. Magnotta, Lee Fried Man " Measurement ofSignal to Noise Ratio and Contrast to Noise Ratio in the FBIRN multicenter Imaging study" Journal of Digital Imaging Vol. No. 1912/P. No. 140-147/10-3-2006
Index Terms

Computer Science
Information Sciences

Keywords

Region Growing Adaptive Histogram Equalization Ct Scan Image Single Seed Pixel