Evaluation of 3D Model Segmentation Techniques Based on Animal Anatomy

BACKGROUND: There is a great demand for the extraction of organ models from three-dimensional (3D) medical images in clinical medicine diagnosis and treatment. OBJECTIVE: We aimed to aid doctors in seeing the real shape of human organs more clearly and vividly. METHODS: The method uses the minimum eigenvectors of Laplacian matrix to automatically calculate a group of basic matting components that can properly define the volume image. These matting components can then be used to build foreground images with the help of a few user marks. RESULTS: We propose a direct 3D model segmentation method for volume images. This is a process of extracting foreground objects from volume images and estimating the opacity of the voxels covered by the objects. CONCLUSIONS: The results of segmentation experiments on different parts of human body prove the applicability of this method.

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Graph-cut-based 3D model segmentation for articulated object reconstruction

2011 10th IEEE International Symposium on Mixed and Augmented Reality ◽

10.1109/ismar.2011.6092397 ◽

2011 ◽

Author(s):

Inkyu Han ◽

Hyoungnyoun Kim ◽

Ji-Hyung Park

Keyword(s):

3D Model ◽

Graph Cut ◽

Object Reconstruction ◽

Model Segmentation

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A Novel 3D Model Segmentation Approach

Computer Graphics and Imaging ◽

10.2316/p.2010.679-022 ◽

2010 ◽

Author(s):

Y. Wang ◽

R. Liu ◽

S. Endo ◽

Y. Uehara

Keyword(s):

3D Model ◽

Model Segmentation ◽

Segmentation Approach

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Consistent Mesh Segmentation Based on Shape Diameter Function and EM

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1049-1050.1417 ◽

2014 ◽

Vol 1049-1050 ◽

pp. 1417-1420

Author(s):

Hui Jia ◽

Guo Hua Geng ◽

Jian Gang Zhang

Keyword(s):

Computer Graphics ◽

3D Model ◽

Shape Function ◽

3D Models ◽

Gaussian Mixture ◽

Mesh Segmentation ◽

Shape Similarity ◽

Research Focus ◽

Model Segmentation ◽

New Research

3D model segmentation is a new research focus in the field of computer graphics. The segmentation algorithm of this paper is consistent segmentation which is about a group of 3D model with shape similarity. A volume-based shape-function called the shape diameter function (SDF) is used to on behalf of the characteristics of the model. Gaussian mixture model (GMM) is fitting k Gaussians to the SDF values, and EM algorithm is used to segment 3D models consistently. The experimental results show that this algorithm can effectively segment the 3D models consistently.

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