We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

Study on Effect of MRI Scanner on Brain Tumour Detection

by Vandana Shah, Vijay Chourasia, R.v.skhirsagar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 4
Year of Publication: 2015
Authors: Vandana Shah, Vijay Chourasia, R.v.skhirsagar
10.5120/21531-4527

Vandana Shah, Vijay Chourasia, R.v.skhirsagar . Study on Effect of MRI Scanner on Brain Tumour Detection. International Journal of Computer Applications. 121, 4 ( July 2015), 33-37. DOI=10.5120/21531-4527

@article{ 10.5120/21531-4527,
author = { Vandana Shah, Vijay Chourasia, R.v.skhirsagar },
title = { Study on Effect of MRI Scanner on Brain Tumour Detection },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 4 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number4/21531-4527/ },
doi = { 10.5120/21531-4527 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:07:35.839313+05:30
%A Vandana Shah
%A Vijay Chourasia
%A R.v.skhirsagar
%T Study on Effect of MRI Scanner on Brain Tumour Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 4
%P 33-37
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Now a day the technology took the paradigm shift in the area of medical field. It is now easy to diagnose the biological problems through different medical devices like CT scan, MRI, and X-rays etc. Tumor is an uncontrolled development of tissues in any piece of the body. Mind tumor is naturally genuine and life-debilitating due to its character in the constrained space of the intracranial hole. By and large, CT output or MRI that is coordinated into intracranial depression delivers a complete picture of cerebrum and this picture is outwardly analyzed by the doctor for identification and determination of mind tumor. In India 1. 5 to 3 Tesla scanners are mostly used. But both have different Magnetic field effect. Because of the the different strength of Magnetic field there is a possibility of noise present in the image. This can create problem in detection of the accurate determination of location and size of tumor. Hiding patient information for further analysis is also very crucial for the confidentiality. security algorithm takes care for the hidden system and analysis of the patient. The survey identifies the efficient algorithm for finding the accurate tumor and also identifies its normality.

References
  1. Comaniciu, D. ; Meer, P. , "Mean shift: a robust approach toward feature space analysis," Pattern Analysis and Machine Intelligence, IEEE Transactions on pattern analysis and machine intelligence, vol. 24, no. 5, pp. 603-619, May 2002.
  2. Wenbing Tao, Hai Jin, Yimin Zhang, "Colour Image Segmentation Based on Mean Shift and Normalized Cuts", IEEE Transactions on systems, man, and cybernetics—part b: cybernetics, vol. 37, no. 5, pp. 1382-1389,October, 2007.
  3. Raffaele Gaetano, Giuseppe Scarpa, And Giovanni Poggi, "Hierarchical Texture-Based Segmentation Of Multiresolution Remote-Sensing Images. " IEEE Transactions on geoscience and remote sensing, vol. 47, no. 7, pp. 2129-2141, July 2009
  4. Cedric Wemmert, Anne Puissant, Germain Forestier, and Pierre Gancarski, "Multiresolution Remote Sensing Image Clustering," IEEE Geoscience And Remote Sensing Letters, vol. 6, no. 3,pp. 533-537, July 2009.
  5. Pilar Jarabo-Amores, Manuel Rosa-Zurera, David de la Mata-Moya, Raul Vicen-Bueno, and Saturnino Maldonado-Bascon, "Spatial-Range Mean-Shift Filtering and Segmentation Applied to SAR Images. ", IEEE Transactions On Instrumentation And Measurement, vol. 60, no. 2,pp. 584-597, February 2011.
  6. Yu-Hsiang Wang, "Tutorial: Image Segmentation", Graduate Institute of Communication Engineering National Taiwan University, Taipei, Taiwan, ROC, Website: www. mathworks. com
  7. Ajala Funmilola A, Oke O. A, Adedeji T. O, Alade O. M, Adewusi E. A, " Fuzzy k-c-means Clustering Algorithm for Medical Image Segmentation", Journal of Information Engineering and Applications, ISSN 2224-5782 (print) ISSN 2225-0506 (online)Vol 2, No. 6, 2012.
  8. Thu Huong Nguyen Fakultät Informatik –TU Dresden, "MEAN SHIFT SEGMENTATION", Proseminar "Aufgabenstellungen der Bildanalyse und Mustererkennung„
  9. Ms. Salve Amrapali Kishanrao,Mr. Salve Avinash P. ,Mr. Salve Vilas P. , "Color Image Segmentation using MSNC Algorithm", International Journal of Engineering Research & Technology (IJERT) ,ISSN: 2278-0181, Vol. 2 Issue 9, September – 2013.
  10. Md. Zain, Aryati Binti Bakri,Mahadi Bin Bahari, Pm Dr. Naomie Binti Salim, "Feasibility Study Of Fuzzy Clustering Techniques In Chemical Database For Compound Classification", Universiti Teknologi Malaysia,2006.
  11. Chapter 11 Non-Parametric Techniques. http://www. byclb. com/TR/Tutorials/neural_networks/ch11_1. htm
  12. Jiawei Han,Vipin Kumar, "Clustering" ,CIS 601 Fall 2004Longin Jan Latecki. , Website: http://www-users. cs. umn. edu/~kumar/csci5980/index. html
  13. Benjamin James Bush, " Fuzzy Clustering Techniques: Fuzzy C-Means and Fuzzy Min-Max Clustering Neural Networks", SSIE 617 Term Paper, Fall 2012.
  14. Dr. Mike Spann, "Image Segmentation",EE4H, M. Sc 0407191 Computer Vision, Website:http://www. eee. bham. ac. uk/spannm
  15. Zhaozheng Yin, "Mean shift and feature selection", Spring 2005
  16. Bohyung Han, "Mean-Shift Algorithm and Its Application", Website: bhhan@cs. umd. edu
  17. Leow Wee Kheng, "Mean Shift Tracking", National University of Singapore.
  18. Comaniciu and Meer, "Mean Shift analysis and applications", Proc. ICCV 1999.
  19. Texas A&M University Website: http://www. research. cs. tamu. edu
  20. S. Sulochana , R. Vidhya , " Image Denoising using Adaptive Thresholding in Framelet Transform Domain ",(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 3, 2012
  21. J. Mohan, V. Krishnaveni, Yanhui Guo, "A survey on the magnetic resonance image denoising methods", Biomedical Signal Processing and Control, Vol. 9, pp. 56-69, Elsevier, 2014
  22. Sachin D Ruikar, Dharmpal D Doye, "Wavelet Based Image Denoising Technique", (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, pp. 49-53,March 2011
  23. Yan Shi, Xiaoyuan Yang, and Yuhua Guo, "Translation Invariant Directional Framelet Transform Combined With Gabor Filters for Image Denoising", IEEE Transactions On Image Processing, Vol. 23, pp. 44-55, January 2014
  24. India Times Website: http://timesofindia. indiatimes. com/ home/science/Radiation-may-cause-brain-tumours-later-in-life/articleshow/45043087. cms
  25. About Brain Tumors: A Primer for Patients and Caregivers. http://www. abta. org/secure/about-brain-tumors-a-primer. pdf
  26. AatmaJyoti MRI Centre, Surat Manav Seva Sangh, "Chhanyado" Sanchalit, New civil Hospital, Majuragate, Surat, Gujarat, India.
  27. Image database: http://www. hopkinsmedicine. org/ healthlibrary/GetImage. aspx?ImageId=161365. gif
  28. Image database: http://www. stanfordchildrens. org/ contentpublic/topic/images/07/161407. gif
Index Terms

Computer Science
Information Sciences

Keywords

MRI image Tesla Discrete Wavelet Transform Neural Network