GA and Morphology Based Automated Segmentation of Lungs from CT Scan Images

Author

Jaffar, M. Arfan ; Hussain, Ayyaz ; Nazir, M. ; Mirza, Anwar M. ; Chaudhry, Asmatullah

Author_Institution

Dept. of Comput. Sci., FAST Nat. Univ. of Comput. & Emerging Sci., Islamabad, Pakistan

fYear

2008

fDate

10-12 Dec. 2008

Firstpage

265

Lastpage

270

Abstract

Segmentation is considered an essential step in medical image analysis and classification. In this paper we describe a method for lung segmentation based on Genetic Algorithm (GA) and morphological image processing techniques. We have used Genetic Algorithm to determine the threshold. The proposed system is able to perform fully automatic segmentation of CT scanned lung images. The proposed system can be used as a basic building block for a computer aided diagnosis systems. We have tested our technique against the datasets of different patients received from Aga Khan Medical University, Pakistan.

Keywords

computerised tomography; genetic algorithms; image classification; image segmentation; lung; medical image processing; Aga Khan Medical University; CT scanned lung images; Pakistan; computer aided diagnosis systems; fully automatic segmentation; genetic algorithm; lungs automated segmentation; medical image analysis; medical image classification; morphological image processing techniques; Biomedical imaging; Computed tomography; Genetic algorithms; Image analysis; Image processing; Image segmentation; Lungs; Medical diagnostic imaging; Medical tests; Morphology; and thinning; computer aided diagnosis; segmentation; thresholding;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Modelling Control & Automation, 2008 International Conference on

Conference_Location

Vienna

Print_ISBN

978-0-7695-3514-2

Type

conf

DOI

10.1109/CIMCA.2008.168

Filename

5172636