The week's pick
Reseach Article
A Modified and Improved Method for Detection of Tumor in Brain Cancer
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 91 - Number 6 |
| Year of Publication: 2014 |
| Authors: Meenakshi Sharma, Simranjit Singh |
10.5120/15883-4489
|
Meenakshi Sharma, Simranjit Singh . A Modified and Improved Method for Detection of Tumor in Brain Cancer. International Journal of Computer Applications. 91, 6 ( April 2014), 5-8. DOI=10.5120/15883-4489
Abstract
The precise information of a tumor plays an important role in the treatment of malignant tumors. The manual segmentation of brain tumors from Magnetic Resonance images (MRI) is time consuming task. Processing of MRI images is one of the parts of this field. The detection and extraction of tumor is done from patient's MRI scan images of the brain. The basic concepts of the image processing are some noise removal functions, segmentation and morphological operations. The modified image segmentation and histogram thresh holding techniques were applied on MRI scan images in order to detect brain tumors. In addition, a region prop and skull is used to detect the tumor in the brain. The proposed method can be successfully applied to detect the contour of the tumor and its geometrical dimension. The result of present paper has been very promising.
References
- S. M. Bhandarkar and P. Nammalwar, "Segmentation of Multispectral MR images Using Hierarchical Self-Organizing Map," Proceedings of Computer-Based medical system CBMS 2001.
- C. A. Parra, K. Iftekharuddin and R. Kozma, "Automated Brain Tumor segmentation and pattern Recoginition using ANN," Computional Intelligence Robotics and Autonomous Systems, 2003.
- Andreas Rimner, Andrei I. Holodny and Fred H. Hochberg,"Perfusion Magnetic Resonance Imaging to Assess Brain Tumor Responses to New Therapies," US neurological disease, 2006.
- V. J. Nagalkar and S. S. Asole, "Brain tumor detection using digital image processing based on soft computing," Journal of Signal and Image Processing , Vol. 3,No. 3, pp. -102-105, 2012
- Mohammad Shajib Khadem, "MRI Brain image segmentation using graph cuts", Master of Science Thesis in Communication Engineering, Department of Signals and Systems, Chalmers University Of Technology, Goteborg, Sweden, 2010.
- Yan Zhu and Hong Yan, "Computerized Tumor Boundary Detection Using a Hopfield Neural Network", IEEE Trans. Medical Imaging, vol. 16, no. 1, pp. 55-67 Feb. 1997.
- Orlando J. Tobias and Rui Seara,"Image Segmentation by Histogram Thresholding Using Fuzzy Sets," IEEE transactions on Image Processing,Vol. 11,NO. 12,PP-1457-1465,DEC 2002.
- Mohamed Lamine Toure, "Advanced Algorithm for Brain Segmentation using Fuzzy to Localize Cancer and Epilepsy Region", International Conference on Electronics and Information Engineering (ICEIE 2010), Vol. no 2.
- Minakshi Sharma, Dr. Sourabh Mukharjee, Artificial Neural Network Fuzzy Inference System (ANFIS) For Brain Tumor Detection
- D. Jayadevappa, S. Srinivas Kuma2, and D. S. Murty,A Hybrid Segmentation Model based on Watershed and Gradient Vector Flow for the Detection of Brain Tumor, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 2, No. 3, September 2009
- Mukesh Kumar, Kamal K. Mehta, A Texture based Tumor detection and automatic Segmentation using Seeded Region Growing Method
- K. Selvanayaki*, Dr. M. Karnan,CAD System for Automatic Detection of Brain Tumor through Magnetic Resonance Image-A Review, K. Selvanayaki et. al. / International Journal of Engineering Science and Technology Vol. 2(10), 2010, 5890-5901
- Nobel A. J and BoukerrouiD. "Ultrasound Image Segmentation: A survey", IEEE Trans On Medical Imaging ,Vol. 25,No. 8,pp. 987-1010.
- Miller P, Astley S. Classification of breast tissue by texture analysis. Image Vision Computer 1992;10:277-282.
- Koss JE, Newman FD, Johnson TK, Krich DL. Abdominal organ segmentation using texture transform and Hopfield neural network. IEEE Trans Med Imaging 1999;18:640
- Manoj K Kowar and Sourabh Yadav, Brain Tumor Detction and Segmentation Using Histogram Thresholding, International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-1, Issue-4, April 2012 16
- Kailash Sinha Shweta Raghuwanshi, An Amend Implementation of Brain Tumor Detection Using Segmentation Based On Artificial Intelligence, International Journal of Digital Application & Contemporary research Website: www. ijdacr. com (Volume 1, Issue 1, August 2012)
- Dina Aboul Dahab, Samy S. A. Ghoniemy, Gamal M. Selim, Automated Brain Tumor Detection and Identification Using Image Processing and Probabilistic Neural Network Techniques
- Garima Garg Sonia Juneja, Extract Area of Tumor through MRI using Optimization Technique with Fuzzy C Means,2012
- Meghana Nagori1, Shivaji Mutkule2, Praful Sonarkar, Detection of Brain Tumor by Mining fMRI Images, International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 4, January 2013
- Dr. N. NandhaGopal, Automatic Detection Of Brain Tumor Through Magnetic Resonance Image, International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 4, April 2013
- Vivek Angoth_, A Novel Wavelet Based Image Fusion for Brain Tumor Detection, international Journal of Computer Vision and Signal Processing, 2(1), 1-7(2013)
- Kadam D B,et. al, An Artificial Neural Network Approach for Brain Tumor Detection Based on Characteristics of GLCM Texture Features.
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