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Improved MLP-NN based approach for Lung Diseases Classification
by
Ramandeep Kaur,
Prince Verma
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 131 - Number 6 |
| Year of Publication: 2015 |
| Authors: Ramandeep Kaur, Prince Verma |
10.5120/ijca2015907472
|
Ramandeep Kaur, Prince Verma . Improved MLP-NN based approach for Lung Diseases Classification. International Journal of Computer Applications. 131, 6 ( December 2015), 22-26. DOI=10.5120/ijca2015907472
@article{
10.5120/ijca2015907472,
author = {
Ramandeep Kaur,
Prince Verma
},
title = { Improved MLP-NN based approach for Lung Diseases Classification },
journal = {
International Journal of Computer Applications
},
issue_date = { December 2015 },
volume = { 131 },
number = { 6 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = {
22-26
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume131/number6/23454-2015907472/
},
doi = { 10.5120/ijca2015907472 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:26:34.278100+05:30
%A Ramandeep Kaur
%A Prince Verma
%T Improved MLP-NN based approach for Lung Diseases Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 6
%P 22-26
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The Data Mining is extracting or mining knowledge from large volume of data. Classification technique is used in different-2 application. In this paper proposes a new classifier utilizing MLP approach by grouping based on nearest neighbor i.e. improved MLP-NN. The MLP-NN approach can handle noisy data and reduce complexity. This technique has been applied for medical diagnosis. This paper analyzes the lung images (i.e. CT-scan images) for identifying and classifying them among the various lung diseases (i.e. bronchitis, emphysema, pleural effusion or normal) using 100 images data set and 80 images data set.
References
- J. Han and M. Kamber, (2000) “Data Mining: Concepts and Techniques,” Morgan Kaufmann.
- Delveen Luqman Abd AL-Nabi, Shereen Shukri Ahmed “Survey on Classification Algorithms for Data Mining:(Comparison and Evaluation)” Computer Engineering and Intelligent Systems Vol.4, No.8, 2013.
- V.Vaithiyanathan, K. Rajeswari, Kapil Tajane, Rahul Pitale “comparison of different classification technique using different datasets” International Journal of Advances in Engineering & Technology, May 2013. ©IJAET.
- Jiawei Han and Micheline Kamber, Data Mining: Concepts and Techniques, Elsevier 2006, ISBN1558609016.
- M. Kantardzic, Data Mining - Concepts, Models, Methods, and Algorithms, IEEE Press, Wiley-Interscience, 2003, ISBN 0-471-22852-4.
- Lin-Yu Tseng and Li-Chin Huang. "An adaptive thresholding method for automatic lung segmentation in CT images." In AFRICON, 2009. AFRICON’09. pp. 1-5. IEEE, 2009.
- Anita Chaudhary and Sonit Sukhraj Singh. "Lung cancer detection on CT images by using image processing." In Computing Sciences (ICCS), 2012 International Conference on, pp. 142-146. IEEE, 2012.
- Shojaii, Rushin, Javad Alirezaie, and Paul Babyn. "Automatic lung segmentation in CT images using watershed transform." In Image Processing, 2005. ICIP 2005. IEEE International Conference on, vol. 2, pp. II-1270. IEEE, 2005.
- K.Devaki and V. MuraliBhaskaran. "Study of computed tomography images of the lungs: A survey." In Recent Trends in Information Technology (ICRTIT), 2011 International Conference On, pp. 837-842. IEEE, 2011.
- Nihad Mesanovic, Svjetlana Mujagic, Haris Huseinagic, and Samir Kamenjakovic. "Application of lung segmentation algorithm to disease quantification from CT images." In System Engineering and Technology (ICSET), 2012 International Conference on, pp. 1-7. IEEE, 2012.
- Yiming Qian, and Weng Guirong. "Lung nodule segmentation using EM algorithm." In Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2014 Sixth International Conference on, vol. 1, pp. 20-23. IEEE, 2014.
- Qixin Gao, , ShengJun Wang, Dazhe Zhao, and Jiren Liu. "Accurate lung segmentation for X-ray CT images." In Natural Computation, 2007. ICNC 2007. Third International Conference on, vol. 2, pp. 275-279. IEEE, 2007.
- Yoshinori Itai, Hyoungseop Kim, Seiji Ishikawa, Shigehiko Katsuragawa, Takayuki Ishida, Katsumi Nakamura, and Akiyoshi Yamamoto. "Automatic segmentation of lung areas based on SNAKES and extraction of abnormal areas." In Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on, pp. 5-pp. IEEE, 2005.
- XindongWu· Vipin Kumar · J. Ross Quinlan · Joydeep Ghosh · Qiang Yang ·Hiroshi Motoda · Geoffrey J. McLachlan · Angus Ng · Bing Liu · Philip S. Yu ·Zhi-Hua Zhou · Michael Steinbach · David J. Hand · Dan Steinberg “Top 10 algorithms in data mining” Springer-Verlag London Limited 2007, 4 December 2007.
- Aaditya Desai And Dr. Sunil Rai “Analysis of Machine Learning Algorithms using WEKA” International Conference & Workshop on Recent Trends in Technology, (TCET) 2012 Proceedings published in International Journal of Computer Applications® (IJCA).
- Misra, Avishkar, Mamatha Rudrapatna, and Arcot Sowmya. "Automatic lung segmentation: a comparison of anatomical and machine learning approaches." In Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004, pp. 451-456. IEEE, 2004
- Dharminder Kumar and Suman “Performance Analysis of Various Data Mining Algorithms: A Review” International Journal of Computer Applications (0975 – 8887) Volume 32– No.6, October 2011.
- Niranjan J. Chatap and Ashish Kr. Shrivastava “A Survey on Various Classification Techniques for Medical Image Data” International Journal of Computer Applications, Volume 97– No.15, July 2014.
- G.Kesavaraj And Dr.S.Sukumaran “A Comparison Study on Performance Analysis of Data Mining Algorithms in Classification of Local Area News Dataset using WEKA Tool” International Journal Of Engineering Sciences &Research Technology 2(10),October 2013.
- M. S. Chen, J. Han, and P. Yu, 1996. Data mining: an overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering, vol. 8, no. 6, pp. 866-883.
- Sang Jun Lee, Keng Siau “A review of data mining techniques” Industrial Management and Data Systems, University of Nebraska-Lincoln Press, USA, pp 41-46, 2001.
- Hye Suk Kim, Hyo-sun Yoon, Kien Nguyen Trung, and Guee Sang Lee. "Automatic lung segmentation in Ct images using anisotropic diffusion and morphology operation." In Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on, pp.557-561.IEEE, 2007.
- S. W. Purnami, A. Embong, J. M. Zain and S. P. Rahayu, “A New Smooth Support Vector Machine and Its Appli- cations in Diabetes Disease Diagnosis,” Journal of Com-puter Science, Vol. 5, No. 12, pp. 1006-1011.
- Ştefan, Raluca-Mariana. "A Comparison of Data Classification Methods." Procedia Economics and Finance 3 (2012): 420-425.
- Salama, G. I., Abdelhalim, M., & Zeid, M. A. E. (2012). Breast cancer diagnosis on three different datasets using multi-classifiers. Breast Cancer (WDBC), 32(569), 2.
- Roy, A., Dutta, D., & Choudhury, K. (2013). Training artificial neural network using particle swarm optimization algorithm. International Journal of Advanced Research in Computer Science and Software Engineering, 3(3), 430-434.
Index Terms
Computer Science
Information Sciences
Keywords