A User-friendly Tool for Semi-automated Segmentation and Surface Extraction from Color Volume Data Using Geometric Feature-space Operations

2008 ◽  
pp. 153-170 ◽  
Author(s):  
Tetyana Ivanovska ◽  
Lars Linsen
Keyword(s):  
Feature Space ◽  
Geometric Feature ◽  
Automated Segmentation ◽  
Volume Data ◽  
Surface Extraction ◽  
Space Operations ◽  
User Friendly

Out-of-core adaptive iso-surface extraction from binary volume data

2014 ◽  
Vol 76 (6) ◽  
pp. 593-608 ◽  
Author(s):  
Ricardo Uribe Lobello ◽  
Florent Dupont ◽  
Florence Denis
Keyword(s):  
Volume Data ◽  
Surface Extraction

Geometric Surface Features Applied to Volumetric CAE Mesh Models

2005 ◽  
Author(s):  
Yifan Chen ◽  
Basavaraj Tonshal ◽  
Ali Saeed
Keyword(s):  
Large Scale ◽  
Geometric Feature ◽  
Direct Modeling ◽  
Modeling Paradigm ◽  
Model Independent ◽  
User Friendly ◽  
Geometric Surface ◽  
Mesh Models ◽  
Modeling Clay ◽  
Blending Function

In this paper, we discuss a way to extend a geometric surface feature framework known as Direct Surface Manipulation (DSM) into a volumetric mesh modeling paradigm that can be directly adopted by large-scale CAE applications involving models made of volumetric elements, multiple layers of surface elements or both. By introducing a polynomial-based depth-blending function, we extend the classic DSM mathematics into a volumetric form. The depth-blending function possesses similar user-friendly features as DSM basis functions permitting ease-of-control of the continuity and magnitude of deformation along the depth of deformation. Practical issues concerning the implementation of this technique are discussed in details and implementation results are shown demonstrating the versatility of this volumetric paradigm for direct modeling of complex CAE mesh models. In addition, the notion of a model-independent, volumetric-geometric feature is introduced. Motivated by modeling clay with sweeps and templates, a model-independent, catalog-able volumetric feature can be created. Deformation created by such a feature can be relocated, reoriented, duplicated, mirrored, pasted, and stored independent of the model to which it was originally applied. It can serve as a design template, thereby saving the time and effort to recreate it for repeated uses on different models (frequently seen in CAE-based Design of Experiments study).

scholarly journals A New Straightforward Method for Automated Segmentation of Trabecular Bone from Cortical Bone in Diverse and Challenging Morphologies

2021 ◽  
Author(s):  
Eva C. Herbst ◽  
Alessandro A. Felder ◽  
Lucinda A. E. Evans ◽  
Sara Ajami ◽  
Behzad Javaheri ◽  
...  
Keyword(s):  
Cortical Bone ◽  
Skeletal Structure ◽  
Automated Segmentation ◽  
Micro Computed Tomography ◽  
X Ray ◽  
Straightforward Method ◽  
Successful Separation ◽  
And Function ◽  
Automated Protocol ◽  
User Friendly

AbstractMany physiological, biomechanical, evolutionary and clinical studies that explore skeletal structure and function require successful separation of trabecular from cortical compartments of a bone that has been imaged by X-ray micro-computed tomography (microCT) prior to analysis. Separation is often time-consuming, involves user bias and needs manual sub-division of these two similarly radio-opaque compartments. We have developed an objective, automated protocol which reduces user bias and enables straightforward, user-friendly segmentation of trabecular from cortical bone without requiring sophisticated programming expertise. This method can conveniently be used as a “recipe” in commercial programmes (Avizo herein) and applied to a variety of datasets. Here, we characterise and share this recipe, and demonstrate its application to a range of murine and human bone types, including normal and osteoarthritic specimens, and bones with distinct embryonic origins and spanning a range of ages. We validate the method by testing inter-user bias during the scan preparation steps and confirm utility in the architecturally challenging analysis of growing murine epiphyses. We also report details of the recipe, so that other groups can readily re-create a similar method in open access programs. Our aim is that this method will be adopted widely to create a more standardized and time efficient method of segmenting trabecular and cortical bone.

Surface Extraction from Multi-field Particle Volume Data Using Multi-dimensional Cluster Visualization

2008 ◽  
Vol 14 (6) ◽  
pp. 1483-1490 ◽  
Author(s):  
Lars Linsen ◽  
Tran Van Long ◽  
Paul Rosenthal ◽  
Stephan Rosswog
Keyword(s):  
Volume Data ◽  
Particle Volume ◽  
Surface Extraction ◽  
Cluster Visualization

Integration of volume decompression and out-of-core iso-surface extraction from irregular volume data

2006 ◽  
Vol 22 (4) ◽  
pp. 249-265 ◽  
Author(s):  
Chuan-Kai Yang ◽  
Tzi-Cker Chiueh
Keyword(s):  
Volume Data ◽  
Surface Extraction
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