General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2011 Vol.3(4): 561-564 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2011.V3.370

Segmentation Algorithm for CT Images Using Morphological Operation and Artificial Neural Network

C. Karthikeyan and B. Ramadoss

Abstract—Segmentation of pulmonary X-ray computed tomography (CT) images is a precursor to most pulmonary image analysis applications. Digital Image Processing is currently a hot research area in medicine and it is believed that they will receive extensive application to biomedical systems in the next few years. In Digital Image Processing, neural networks are ideal in recognizing diseases using scans since there is no need to provide a specific algorithm on how to identify the disease. This paper describes an algorithm to separate the lung tissue from a Chest CT to reduce the amount of data that needs to be analyzed. Our goal is to have a fully automatic algorithm for segmenting the lung tissue, and to separate the two lung sides as well. Fuzzy c-Means clustering is used to segment the lungs. Cleaning is performed to remove air, noise and airways. Finally, a sequence of morphological operations is used to smooth the irregular boundary. The database used for evaluation is taken from a radiology-teaching file. Our current evaluation shows that the applied segmentation algorithm works on a large number of different cases. The textural features were extracted from the segmented lungs and it was given as input to CFBP. The neural networks are used to identify the various lung diseases.

Index Terms—CFBP, Lung Extraction, Lung Diseases, Fuzzy C-means clustering

C. Karthikeyan, Associate Prof. and Head / IT / AVIT, PhD (CSE), Research Scholar, Jawaharlal Nehru Technological University, Hyderabad. India (email: ckarthik2k@gmail.com)
B. Ramadoss, Professor and Head, Department of Computer Applications, National Institute of Technology , Tiruchirappalli, India

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Cite: C. Karthikeyan and B. Ramadoss, "Segmentation Algorithm for CT Images Using Morphological Operation and Artificial Neural Network," International Journal of Computer Theory and Engineering vol. 3, no. 4, pp. 561-564, 2011.


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