From lung images to lung models: A review

Author

Lee, S.L.A. ; Kouzani, A.Z. ; Hu, E.J.

Author_Institution

Sch. of Eng.&IT, Deakin Univ., Geelong, VIC

fYear

2008

fDate

1-8 June 2008

Firstpage

2377

Lastpage

2383

Abstract

Automated 3D lung modeling involves analyzing 2D lung images and reconstructing a realistic 3D model of the lung. This paper presents a review of the existing works on automatic formation of 3D lung models from 2D lung images. A common framework for 3D lung modeling is proposed. It consists of eight components: image acquisition, image pre-processing, image segmentation, boundary creation, image recognition, image registration, 3D surface reconstruction, and 3D rendering and visualization. The algorithms used by the existing systems to implement these components are also reviewed.

Keywords

data visualisation; image recognition; image reconstruction; image registration; image segmentation; lung; medical image processing; physiological models; rendering (computer graphics); solid modelling; surface reconstruction; 3D rendering; 3D visualization; automated 3D lung modeling; boundary creation; image acquisition; image preprocessing; image recognition; image reconstruction; image registration; image segmentation; lung images; lung models; realistic 3D model; surface reconstruction; Lungs; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Conference_Location

Hong Kong

ISSN

1098-7576

Print_ISBN

978-1-4244-1820-6

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2008.4634128

Filename

4634128