Lung Pattern Classification for Interstitial Lung Diseases using ANN-Back Propagation Network
S.Vijayanand1, A. Kumar2, M.Roopa3, S.Jagir Hussain4
1Dr. Vijayanand S, Associate professor Dhanalakshmi College of Engineering Chennai, India.
2A. Kumar, Assistant professor, in Electronics and communication engineering Dhanalakshmi College of Engineering Chennai, India.
3Dr. Roopa M, associate professor, SRMIST, Chennai, India.
4Mr. Jagir Hussain, assistant professor, Dhanalakshmi College of Engineering Chennai, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 26, 2019. | Manuscript published on 30 November, 2019. | PP: 3344-3349 | Volume-8 Issue-4, November 2019. | Retrieval Number: F2792037619/2019©BEIESP | DOI: 10.35940/ijrte.F2792.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Lung infections are the messes that influence the lungs, the organs that empower us to breathe in and it is the most notable illnesses worldwide especially in India. The sicknesses, for instance, pleural radiation and customary lung are distinguished and masterminded in this work. This paper presents a PC helped gathering Method in Computer Tomography (CT) Images of lungs made using ANN-BPN. The inspiration driving the work is to distinguish and arrange the lung illnesses by compelling component extraction through Dual-Tree Complex Wavelet Transform and GLCM Features. The entire lung is assigned from the CT Images and the parameters are resolved from the separated picture. The parameters are resolved using GLCM. We Propose and survey the ANN-Back Propagation Network planned for gathering of ILD structures.
Keywords: Fragment lesion, Fuzzy Clustering, DWT, DTCWT, ANN-BPN.
Scope of the Article: Clustering.