Segmentation of the Lungs from Chest X-Rays: A Simplified Computer Aided Approach
Prashant A. Athavale1, H. D. Kattimani2, P. S. Puttaswamy3

1Prashant A. Athavale, Department of Electrical & Electronics Engineering BMS Institute of Technology & Management, Bengaluru, India.
2H. D. Kattimani, Department of Electrical & Electronics Engineering BMS Institute of Technology & Management, Bengaluru, India.
3Dr.P. S. Puttaswamy, Department of Electrical & Electronics Engineering, PES College of Engineering, Mandya, India.

Manuscript received on 24 September 2018 | Revised Manuscript received on 30 September 2018 | Manuscript published on 30 November 2018 | PP: 220-223 | Volume-7 Issue-4, November 2018 | Retrieval Number: E1832017519©BEIESP
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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: The lungs reflect the health condition of a person, and hence it has been imaged and analysed by diagnosticians for over a century, and it requires knowledge and experience. The human observer’s time and effort could be used productively if the lung image analysis is automated. This is especially true in case of screening of the lung chest x-rays. The lung segmentation is by default the first of a series of steps to analyse and interpret the images using a computer. One of the traditional approaches to segmentation of the lungs has been the use of statistical models, and the other is the rule based approach. This paper proposes a fusion method to segment the lungs on chest x-rays, as this modality of imaging is low cost, easy to operate, and gives first-hand information required for diagnosis. The results that are obtained are fast and promising accuracy has been documented. The entire approach can be extended to any organ on a medical image, or any object of interest in a general segmentation problem
Keywords: Lungs Segmentation, Active Shape Models, Computer Aided Diagnosis, Morphological Operation.

Scope of the Article: Advanced Computer Networking