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Reseach Article

Sensitivity and Accuracy Comparison of the Algorithms for the Abnormality Extraction of the MRI Slice Images of a GUI based Intelligent Diagnostic Imaging System

Published on February 2013 by A. M. Khan, Jose Alex Mathew, U. C. Niranjan
International Conference on Electronic Design and Signal Processing
Foundation of Computer Science USA
ICEDSP - Number 4
February 2013
Authors: A. M. Khan, Jose Alex Mathew, U. C. Niranjan
0f35ff8d-a1a9-4085-a18f-3ae31612b1a2

A. M. Khan, Jose Alex Mathew, U. C. Niranjan . Sensitivity and Accuracy Comparison of the Algorithms for the Abnormality Extraction of the MRI Slice Images of a GUI based Intelligent Diagnostic Imaging System. International Conference on Electronic Design and Signal Processing. ICEDSP, 4 (February 2013), 1-5.

@article{
author = { A. M. Khan, Jose Alex Mathew, U. C. Niranjan },
title = { Sensitivity and Accuracy Comparison of the Algorithms for the Abnormality Extraction of the MRI Slice Images of a GUI based Intelligent Diagnostic Imaging System },
journal = { International Conference on Electronic Design and Signal Processing },
issue_date = { February 2013 },
volume = { ICEDSP },
number = { 4 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /specialissues/icedsp/number4/10368-1027/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 International Conference on Electronic Design and Signal Processing
%A A. M. Khan
%A Jose Alex Mathew
%A U. C. Niranjan
%T Sensitivity and Accuracy Comparison of the Algorithms for the Abnormality Extraction of the MRI Slice Images of a GUI based Intelligent Diagnostic Imaging System
%J International Conference on Electronic Design and Signal Processing
%@ 0975-8887
%V ICEDSP
%N 4
%P 1-5
%D 2013
%I International Journal of Computer Applications
Abstract

Intelligent diagnostic Imaging System (IDIS) is a developing imaging modality that is beginning to show promise of detecting and characterizing abnormalities of the brain. The abnormalities of the brain are due to Intracranial Neoplasm, Cerebral Infections and Inflammations, Stroke, Cerebral Aneurysms, Vascular Malformations, Central Nervous System Trauma and Neurodegenerative Disorders. The abnormalities are detected mostly by scanning the brain. MRI is an effective technique to find the abnormalities of the brain. This paper is concerned with the development of image processing tools and intelligent algorithms that will automatically detect the abnormalities of the brain and sensitivity and accuracy comparison of the Algorithms for the of abnormality extraction.

References
  1. Ric Harnsberger, Patricia Hudgins, Richard Wiggins, Christian Davidson , Diagnostic Imaging: Head and Neck.
  2. Koen Van Leemput, Frederik Maes, Dirk Vandermeulen, and Paul Suetens, "A Unifying Framework For Partial Volume Segmentation Of Brain MR Images", IEEE Transactions On Medical Imaging, Vol. 22, No. 1, pp. 105 - 119, January 2003.
  3. Julio Carballido-Gamio, Serge J. Belongie, and Sharmila Majumdar, "Normalized Cuts In 3-D For Spinal MRI Segmentation", IEEE Transactions On Medical Imaging, Vol. 23, No. 1, pp. 36 –44, January 2004.
  4. Abdolah Chalechale, Golshah Naghdy, and Alfred Mertins, "Sketch-Based Image Matching Using Angular Partitioning", IEEE Transactions On Systems, Man, And Cybernetics—Part A: Systems And Humans, Vol. 35, No. 1, pp. 28-41, January 2005.
  5. Sokratis Makrogiannis, George Economou, Spiros Fotopoulos, and Nikolaos G. Bourbakis "Segmentation Of Color Images Using Multiscale Clustering And Graph Theoretic Region Synthesis", IEEE Transactions On Systems, Man, And Cybernetics—Part A: Systems And Humans, Vol. 35, No. 2, pp. 224-238, March 2005.
  6. Ying Zhuge, Jayaram K. Udupa, and Punam K. Saha "Vectorial Scale-Based Fuzzy-Connected Image Segmentation" Computer Vision And Image Understanding, 101, pp. 177-193, 2006.
  7. Hemg-Hua Chang, Daniel J. Valentino, Gary R. Duckwiler, and Arthur W. Toga, "Segmentation Of Brain MR Images Using A Charged Fluid Model", IEEE Transactions On Biomedical Engineering, Vol. 54, No. 10, pp. 1798-1813, October 2007.
  8. Francois Chabaf, David M. Hansell, and Guang-Zhong Yang " Computerized Decision Support In Medical Imaging Challenges In Using Image Processing And Automated Feature Extraction For Improving Diagnostic Accuracy", IEEE Engineering In Medicine And Biology, pp. 89-96, September/October 2000.
  9. Chuin-Mu Wang, Clayton Chi-Chang Chen, Yi-Nung Chung, Sheng-Chih Yang, Pau-Choo Chung, Ching-Wen Yang and Chein-I. Chang, "Detection Of Spectral Signatures In Multispectral MR Images For Classification", IEEE Transactions On Medical Imaging, Vol. 22, No. 1, pp. 50-61, January 2003.
  10. Marcelo Kleber Felisberto, Heitor Silverio Lopes, and Tania Mezzadri, "An Object Detection And Recognition System For Weld Bead Extraction From Digital Radiographs", Computer Vision And Image Understanding, 102, pp. 238-249, 2006.
  11. Celia Varela, Pablo G. Tahoces, Arturo J. Mendez, Miguel Souto, and Juan J. Vidal "Computerized Detection Of Breast Masses In Digitized Mammograms", Computers In Biology And Medicine, 37, pp. 214-226, 2007.
  12. Kai-Qi Huang, Qiao Wang, and Zhen-Yang Wu, "Natural Color Image Enhancement And Evaluation Algorithm Based On Human Visual System", Computer Vision And Image Understanding, Elsevier, 103, pp. 52-63, 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Graphical User Interface (gui) Intelligent Diagnostic Imaging System (idis). Magnetic Resonant Imaging (mri) Central Nervous System (cns) Cerebro-spinal Fluid (csf) Fluid Attenuating Inversion Recovery (flair)