Paper
16 March 2006 Segmentation of ground glass opacities by asymmetric multi-phase deformable model
Yongseok Yoo, Hackjoon Shim, Il Dong Yun, Kyung Won Lee M.D., Sang Uk Lee
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Abstract
Recently ground glass opacities (GGOs) have become noteworthy in lung cancer diagnosis. It is crucial to define the boundary a GGO accurately and consistently, since the growth rate is the most manifest evidence of its malignancy. The indefinite and irregular boundary of a GGO makes deformable models adequate for its segmentation. Among deformable models a level set method has the ability to handle topological changes. For the exact estimation of GGO's volume change, the pulmonary airways inside GGO should be excluded in its volume estimation, which necessitate the segmentation into more regions than two of the object and the background. Hence, we adopted a multi-phase deformable model of two level set functions and modified its energy functional into an asymmetric form. The main two modifications are the elimination of one region in four regions of the conventional 4-phase deformable model and the prevention of the outer region from spreading out of the initialization. The proposed model segments the input image into three regions of the inner and outer regions, and the background. The GGO tissues are segmented as the inner region and the outer region plays the role of blockade for the inner region not to leak out to adjacent anatomical structures of similar Hounsfield Unit (HU) values. Our experimental results confirmed the feasibility of the proposed method as a pre-processing step for three dimensional (3-D) volume measurement of the GGO.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yongseok Yoo, Hackjoon Shim, Il Dong Yun, Kyung Won Lee M.D., and Sang Uk Lee "Segmentation of ground glass opacities by asymmetric multi-phase deformable model", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614440 (16 March 2006); https://doi.org/10.1117/12.653053
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Cited by 14 scholarly publications.
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KEYWORDS
Image segmentation

Opacity

Glasses

Tumor growth modeling

3D modeling

Tissues

Computed tomography

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