Title :
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
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;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4634128
