Providing values of adjacent voxel with vtkDiscreteMarchingCubes

2016 ◽  
Author(s):  
Roman Grothausmann
Keyword(s):  
Marching Cubes ◽  
Local Neighborhood

The contribution to VTK presented in this article is an extension to vtk::vtkDiscreteMarchingCubes to also create vtk::vtkPointData scalars containing the value of the adjacent voxel. These can be used to remove regions of the marching-cubes 1 mesh depending on the local neighborhood. The extension is based on the code of vtkDiscreteMarchingCubes of VTK-6.3.0 and is available on GitLab https://gitlab.kitware.com/vtk/vtk/merge_requests/889 (and GitHub https://github.com/Kitware/VTK/pull/18).

CPU-GPU Rendering of CT Scan Images for Vertebra Reconstruction from CT Scan Images with a Calibration Policy

2020 ◽  
pp. 1-5
Author(s):  
Usman Khan ◽  
Usman Khan ◽  
AmanUllah Yasin ◽  
Imran Shafi ◽  
Muhammad Abid
Keyword(s):  
3D Reconstruction ◽  
Ct Scan ◽  
Surface Reconstruction ◽  
3D Visualization ◽  
Cervical Vertebra ◽  
Marching Cubes ◽  
Affine Transform ◽  
Visualization Techniques ◽  
Visualization Algorithms ◽  
Gpu Implementation

In this work GPU implementation of classic 3D visualization algorithms namely Marching Cubes and Raycasting has been carried for cervical vertebra using VTK libraries. A proposed framework has been introduced for efficient and duly calibrated 3D reconstruction using Dicom Affine transform and Python Mayavi framework to address the limitation of benchmark visualization techniques i.e. lack of calibration, surface reconstruction artifacts and latency.

Identifying porphyry-Cu geochemical footprints using local neighborhood statistics in Baft area, Iran

2021 ◽  
Author(s):  
Saeid Ghasemzadeh ◽  
Abbas Maghsoudi ◽  
Mahyar Yousefi
Keyword(s):  
Porphyry Cu ◽  
Local Neighborhood

Data-Agnostic Local Neighborhood Generation

2020 ◽  
Author(s):  
Riccardo Guidotti ◽  
Anna Monreale
Keyword(s):  
Local Neighborhood

Dual-Primal Mesh Optimization for Polygonized Implicit Surfaces With Sharp Features

2002 ◽  
Vol 2 (4) ◽  
pp. 277-284 ◽  
Author(s):  
Yutaka Ohtake ◽  
Alexander G. Belyaev
Keyword(s):  
Adaptive Mesh ◽  
Implicit Surfaces ◽  
Marching Cubes ◽  
Triangle Mesh ◽  
Implicit Surface ◽  
Weighted Vertex ◽  
Visualization Toolkit ◽  
Object Oriented Approach ◽  
Speed And Accuracy ◽  
Dual Mesh

A new method for improving polygonizations of implicit surfaces with sharp features is proposed. The method is based on the observation that, given an implicit surface with sharp features, a triangle mesh whose triangles are tangent to the implicit surface at certain inner triangle points gives a better approximation of the implicit surface than the standard Marching Cubes mesh [Lorensen, W.E., and Cline, H.E., 1987, Computer Graphics (Proceedings of SIGGRAPH ’87), 21(3), pp. 163–169] (in our experiments we use VTK Marching Cubes [Schroeder, W., Martin, K., and Lorensen, W., 1998, The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics, Prentice Hall]). First, given an initial triangle mesh, its dual mesh composed of the triangle centroids is considered. Then the dual mesh is modified such that its vertices are placed on the implicit surface and the mesh dual to the modified dual mesh is considered. Finally the vertex positions of that “double dual” mesh are optimized by minimizing a quadratic energy measuring a deviation of the mesh normals from the implicit surface normals computed at the vertices of the modified dual mesh. In order to achieve an accurate approximation of fine surface features, these basic steps are combined with adaptive mesh subdivision and curvature-weighted vertex resampling. The proposed method outperforms approaches based on the mesh evolution paradigm in speed and accuracy.

Steganographic Method with High Visual Concealment in Wavelet Domain

2013 ◽  
Vol 281 ◽  
pp. 47-50
Author(s):  
Zhi Hong Chen
Keyword(s):  
Wavelet Transformation ◽  
Experimental Results ◽  
Wavelet Domain ◽  
Wavelet Coefficients ◽  
Local Neighborhood ◽  
The Impact

In this paper we propose a new steganographic method, which based on wet paper codes and wavelet transformation. The method is designed to embed secret messages in images' wavelet coefficients and depends on images' texture characters in local neighborhood. The receivers can extract secret bits from carrier images only by some matrix multiplications without knowing the formulas written by senders, which further improves steganographic security and minimizes the impact of embedding changes. The experimental results show that our proposed method has good robust and visual concealment performance and proves out it's a practical steganographic algorithm.

Sex Offender Reintegration: Consequences of the Local Neighborhood Context

2012 ◽  
Vol 39 (1) ◽  
pp. 109-124 ◽  
Author(s):  
Keri B. Burchfield ◽  
William Mingus
Keyword(s):  
Sex Offender ◽  
Neighborhood Context ◽  
Local Neighborhood ◽  
Offender Reintegration

Probabilistic Marching Cubes

2011 ◽  
Vol 30 (3) ◽  
pp. 931-940 ◽  
Author(s):  
Kai Pöthkow ◽  
Britta Weber ◽  
Hans-Christian Hege
Keyword(s):  
Marching Cubes

Revisiting Local Neighborhood Methods in Machine Learning

2021 ◽  
Author(s):  
Sarath Shekkizhar ◽  
Antonio Ortega
Keyword(s):  
Machine Learning ◽  
Local Neighborhood

Adaptive local neighborhood range based firefly algorithm for link prediction

2021 ◽  
Author(s):  
P Srilatha ◽  
Somula Ramasubbareddy ◽  
Devulapalli Sudheer
Keyword(s):  
Link Prediction ◽  
Firefly Algorithm ◽  
Local Neighborhood

Global-local neighborhood based network representation for citation recommendation

2022 ◽  
Author(s):  
Xiaoyan Cai ◽  
Nanxin Wang ◽  
Libin Yang ◽  
Xin Mei
Keyword(s):  
Network Representation ◽  
Local Neighborhood
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