Segmentation of 3D objects from MRI volume data using constrained elastic deformations of flexible Fourier surface models

2005 ◽  
pp. 493-505 ◽  
Author(s):  
G. Székely ◽  
A. Kelemen ◽  
Ch. Brechbühler ◽  
G. Gerig
Keyword(s):  
Volume Data ◽  
Elastic Deformations ◽  
3D Objects ◽  
Surface Models

Segmentation of 2-D and 3-D objects from MRI volume data using constrained elastic deformations of flexible Fourier contour and surface models

1996 ◽  
Vol 1 (1) ◽  
pp. 19-34 ◽  
Author(s):  
Gábor Székely ◽  
András Kelemen ◽  
Christian Brechbühler ◽  
Guido Gerig
Keyword(s):  
Volume Data ◽  
Elastic Deformations ◽  
Surface Models

Generation of Surface Models of 3D Objects From Their Wire-Frame Models

1992 ◽  
Author(s):  
S. Gupta ◽  
A. Shirkhodaie ◽  
A. H. Soni
Keyword(s):  
Common Vertex ◽  
Surface Model ◽  
Edge Information ◽  
Frame Model ◽  
3D Objects ◽  
Wire Frame ◽  
Surface Models ◽  
Plane Passing ◽  
Generate Surface ◽  
The Wire

Abstract This paper presents an algorithm to generate surface models of 3D objects from their wire-frame models. The algorithm firstly, obtains information about edges of the object from the wire-frame model of the object and uses this edge information to generate the pairs. A pair of an object is a combination of two non-collinear edges which have a common vertex. The algorithm then determines the unique plane passing through each pair and groups the coplanar pairs together. Then it sorts each of the groups of coplanar pairs to form one or more loops of edges. Finally for each group of coplanar pairs, all the loops are combined, using a few rules, to form faces of the object. Hence a surface model of the object is generated.

scholarly journals A G-Code Generator for Volumetric Models

2019 ◽  
Vol 9 (18) ◽  
pp. 3868
Author(s):  
Shyh-Kuang Ueng ◽  
Hsuan-Kai Huang ◽  
Hsin-Cheng Huang
Keyword(s):  
Texture Mapping ◽  
Volume Data ◽  
Code Generator ◽  
Volumetric Models ◽  
Surface Models ◽  
Build Time ◽  
G Code ◽  
Input Model ◽  
The Stability ◽  
Printing Direction

In layered manufacturing (LM), slicers are employed to convert input geometric models into G-codes. Conventional slicers accept only surface models as input data. Thus, volumetric models have to be converted into polygonal representations to fit the data format of the slicers. This results in extra computational costs and geometric errors. In this article, we present an efficient slicer aiming to generate G-codes for volumetric models. At first, our slicer computes the printing direction by exploring the inertia tensor of the input model to enhance the stability of the printed part and to decrease the build time. Then, it detects and classifies overhangs in the input model and generates necessary support structures by using a pattern-based method. Thirdly, the proposed slicer divides the input model into the skin and internal regions and cuts the model into 2D images. Subsequently, these images are transformed into toolpaths by utilizing texture mapping and graph traversal methods. Finally, the resultant toolpaths are smoothed to reduce staircases and encoded into G-codes. Test results verify that the proposed slicer produces decent G-codes for volumetric models. Scanned objects hidden in volume data can be directly manufactured without generating intermediate polygonal representations. LM processes become more efficient.

Recognition of partially occluded 3D objects

1989 ◽  
Vol 136 (2) ◽  
pp. 124
Author(s):  
Ming-Hong Chan ◽  
Hung-Tat Tsui
Keyword(s):  
3D Objects ◽  
Partially Occluded
Sign in / Sign up

Export Citation Format

Share Document