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Chakrasali, Saritha
- Detection and Classification of Breast Cancer using Support Vector Machine and Artificial Neural Network using Contourlet Transform
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Authors
Affiliations
1 Department of Information Science and Engineering, BNM Institute of Technology, IN
1 Department of Information Science and Engineering, BNM Institute of Technology, IN
Source
ICTACT Journal on Image and Video Processing, Vol 9, No 3 (2019), Pagination: 1966-1971Abstract
The technique of image processing is applied to diagnose breast cancer from digital mammogram image. The proposed work uses Contourlet transform to decompose the given gray-scale image. The spatial (textual and statistical) features are been extracted along with frequency domain coefficients. GLCM is the method used for extracting the feature values. Classification of image using support vector machine or artificial neural network classifiers is performed.Keywords
Mammographic Images, Support Vector Machine (SVM), Feature Extraction, Contourlet Transform (CT), Gray Level Co-Occurrence Matrix (GLCM), Artificial Neural Network (ANN).
References
- Nivedita V. Candade, “Application of Support Vector Machines and Neural Networks in Digital Mammography-A Comparative Study”, PhD Dissertation, Department of Biomedical Engineering, University of South California, 2004.
- A. Papadopolulous, D.I. Fotiadis and A. Likas, “Categorization of Clustered Microcalcification in Digitized Mammograms using Neural Network and Support Vector Machine”, Artificial Intelligence in Medicine, Vol. 34, No. 2, pp. 141-150, 2005.
- Defeng Wang, Lin Shi and Pheng Ann Heng “Automatic Detection of Breast Cancer in Mammograms using Structured Support Vector Machines”, Neurocomputing, Vol. 72, No. 13-15, pp. 3296-3302, 2009.
- Jose Mejia, O. Humberto, V. Osslan and G. Vianey, “The Non-Subsampled Contourlet Transform for Enhancement of Micro-Calcification in Digital Mammograms”, Proceedings of Mexican International Conference on Artificial Intelligence, pp. 292-302, 2009.
- Mohammed J. Islam, A. Majid and A. Maher, “An Efficient Automatic Mass Classification Method in Digitalized Mammograms Using Artificial Neural Network”, International Journal of Artificial Intelligence and Application, Vol. 1, No. 3, pp. 1-13, 2010.
- B. Swapna and Udhav Bhosle, “Image Retrieval using Contourlet Transform”, International Journal of Computer Applications, Vol. 34, No. 5, pp. 37-43, 2011.
- Jin Chang Ren, “ANN v/s SVM which One Performs Better in Classification of MCCS in Mammogram Imaging”, Journal Knowledge-Based Systems, Vol. 26, No. 3, pp. 144-153, 2012.
- H. Girish, N. Pradeep, B. Sreepathi and K. Karibasappa, “Feature Extraction of Mammograms”, International Journal of Bio Information Research, Vol. 4, No. 1, pp. 241-244, 2012.
- Saritha Chakrasali, Ramachandra Murugesan, “A Contourlet Transform Based Versatile Watermarking Algorithm for Medical Images”, Proceedings of International Conference on VLSI, Communication, Advanced Devices, Signals and Systems and Networking, pp. 263-271, 2013.
- Ayoub Arafi, Youssef Safi and Rkia Fajr, “Classification of Mammographic Images using Artificial Neural Networks”, Applied Mathematics Sciences, Vol. 7, No. 89, pp. 4415-4423, 2013.
- S. Anand and R. Aynesh Vijaya Rathna, “Architectural Distortion Detection in Mammogram using Contourlet Transform and Texture Features”, International Journal of Computer Application, Vol. 74, No. 5, pp. 331-344, 2013.
- C. Komal and S. Priti, “Review of Classification of Micro-Calcifications in Digital Mammogram”, International Journal of Computer Science and Information Technologies, Vol. 5, No. 2, pp. 1816-1820, 2014.
- B. Balasuganya, “Contourlet Based Feature Extraction Method for Classification of Breast Cancer using Thermogram Images”, International Journal of Scientific and Engineering Research, Vol. 5, No. 4, pp. 1-7, 2014.
- K. Sankar and K. Nirmala, “An Enhanced Mammogram Diagnosis using Shift-Invariant Transform”, ICTACT Journal on Image and Video Processing, Vol. 5, No. 2, pp. 920-925, 2014.
- Varsha J. Gaikwad, “Detection of Breast Cancer in Mammogram using Support Vector Machine”, International Journal of Scientific Engineering and Research, Vol. 3, No. 2, pp. 8-16, 2016.
- P. Fatemeh and R.K. Hamidreza, “Improvement of Breast Cancer detection using Non Subsampled Contourlet Transform and Super Resolution Technique in Mammographic Images”, Iranian Journal of Medical Physics, Vol. 12, No. 1, pp. 22-35, 2015.
- S. Chakrasali, M. Akshata, B.V. Aparna, S. Donthi and N. Jain, “'A Comparative Study between Contourlet and Wavelet Transform for Medical Image Registration and Fusion”, International Journal of Computer Science and Network Security, Vol. 6, No. 6, pp. 891-898, 2015.
- K. Vani and K. Usha Rani, “Mammogram Classification using Multilayer Perceptron and Support Vector Machine”, International of Computational Sciences and Engineering, Vol. 8, No. 1, pp. 46-51, 2016.
- Kamaldeep Kaur and E. Pooja, “Classification Through Artificial Neural network and SV of Breast Masses Mammograms”, International Journal of Advance Research, Ideas and Innovations in Technology, Vol. 2, No. 4, pp. 1-8, 2016.
- Sonal Naranje, “Early Detection of Breast Cancer using ANN”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, No. 7, pp. 32-42, 2016.
- Ranjit Biswas, Abhijith Nath and Sudiptha Roy “Mammogram Classification Using Gray-Level Co-occurrence Matrix for Diagnosis of Breast Cancer”, Proceedings of International Conference on Micro-Electronics and Telecommunication Engineering, pp. 1-6, 2016.
- P. Samyuktha and D. Sriharsha “Classification of Mammograms using Gray-Level Co-Occurrence Matrix and Support Vector Machine Classifier”, International Journal of Engineering Trends and Technology, Vol. 6, No. 4, pp. 22-28, 2017.
- M .Arfan Jaffar, “Contourlet Transform Domain Based Intelligent Bio-Metric Watermarking System”, International Journal of Computer Science and Network Security, Vol. 17, No. 5, pp. 65-70, 2017.
- M.M. Mehdy, P.Y. Ng, E.F. Shair, N.I. Md Saleh and C. Gomes, “Artificial Neural Networks in Image Processing for Early Detection of Breast Cancer”, Computational and Mathematical Methods in Medicine, Vol. 2017, pp. 1-15, 2017.
- Shankar Thawkar and Ranjana Ingolikar, “Classification of Masses in Digital Mammograms Using Biogeography- based Optimization Technique”, Journal of King Saud University-Computer and Information Sciences, pp. 1-9, 2018.
- Soumya Hundekar and Saritha Chakrasali, “An Observation and Categorization of Breast Cancer utilizing Support Vector and Artificial Neural Networks using Discrete Wavelet Transform”, ICTACT Journal on Soft Computing, Vol. 9, No. 2, pp. 1851-1855, 2019.
- Soumya Hundekar and Saritha Chakrasali, “An Identification of Breast Cancer Disease by using ANN using Contourlet Transform”, International Journal of Scientific Research and Development, Vol. 6, No. 11, pp. 1-8, 2019.