The week's pick
Reseach Article
Automatic Brain Tumor Detection and Isolation of Tumor Cells from MRI Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 39 - Number 16 |
| Year of Publication: 2012 |
| Authors: Dipak Kumar Kole, Amiya Halder |
10.5120/4905-7416
|
Dipak Kumar Kole, Amiya Halder . Automatic Brain Tumor Detection and Isolation of Tumor Cells from MRI Images. International Journal of Computer Applications. 39, 16 ( February 2012), 26-30. DOI=10.5120/4905-7416
Abstract
Automatic Brain Tumor Detection refers to the problem of delineating tumorous tissues from MRI images for the purpose of medical diagnosis and surgical planning. The process uses tumor characteristics in images, such as sizes, shapes, locations and intensities for the isolation of the tumor which depends on manual tracing by experts. This paper proposes automatic brain tumor detection and isolation of tumor cells from MRI images using a genetic algorithm (GA) based clustering method, intensity based asymmetric map and region growing technique.
References
- J. C. Bezdek, L. O. Hall and L. P. Clarke, Review of MR Image Segmentation Techniques Using Pattern Recognition, April 1993.
- Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, Pearson Education, 2002.
- Dipak Kumar Kole and Amiya Halder, An efficient dynamic Image Segmentation algorithm using Dynamik GA based clustering, International Journal of Logistics and Supply Chain Management, 2(1), pp. 17-20, 2010.
- Amiya Halder, Soumajit Pramanik and Arindam Kar, Dynamic Image Segmentation using Fuzzy C- means based Genetic Algorithm, International Journal of Computer Application, Vol. 28, No.6,pp.15-20, August 2011.
- S. Murugavalli and V. Rajamani, An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy Technique, Journal of Computer Science 3(11), 2007.
- Payel Ghosh and Melanie Mitchell, Segmentation of Medical Images Using a Genetic Algorithm.
- Xiao Xuan and Quingmin Liao, Statistical Structure Analysis in MRI Brain Tumor Segmentation, Fourth International Conference on Image and Graphics.
- Matthew C. Clark, Lawrence O. Hall, Dmitry B. Goldgof, Robert Velthuizen, F. Reed Murtaugh and Martin S. Silbiger, Unsupervised Brain Tumor Segmentation Using Knowledge-based and Fuzzy Techniques.
- Lynn M. Fletcher-Heath, Lawrence O. Hall, Dmitry B. Goldgof and F. Reed Murtaugh, Automatic Segmentation of Non-Enhancing Brain Tumors in Magnetic Resonance Images.
- D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, 1989.
- Ujjwal Maulik, Sanghamitra Bandyopadhyay, Genetic algorithm-based clustering technique, Elsevier Science Ltd., 1999.
- Qin Ding and Jim Gasvoda, A Genetic Algorithm for Clustering on Image Data, in International Journal of Computational Intelligence Vol-1 No-1, 2004.
- Hwei-Jen Lin, Fu-Wen Yang and Yang-Ta Kao, An Efficient GA-based Clustering Technique, in Tamkang Journal of Science and Engineering Vol-8 No-2, 2005.
- M. Srinivas, Lalit M. Patnaik, Genetic Algorithms: A Survey.
- M. Halkidi, Y. Batistakis and M. Vazirgiannis, On Clustering Validation Techniques, Intelligent Information Systems Journal, Kluwer Publishers, vol. 17(2-3), 107-145, 2001.
- R. H. Turi, Clustering-Based Color Image Segmentation, PhD Thesis, Monash University, Australia, 2001.
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