Surface Parameterization for the Shape Analysis of Tube-Like Objects

2012 ◽  
Vol 239-240 ◽  
pp. 694-699
Author(s):  
Li Feng Yao ◽  
Jian Fei Ouyang ◽  
Xiang Ma
Keyword(s):  
Shape Analysis ◽  
Shape Variation ◽  
Conduction Model ◽  
Shape Information ◽  
Local Shape ◽  
3D Objects ◽  
Surface Parameterization ◽  
Sample Shape ◽  
Latitude Circle ◽  
Global And Local

In bio-medicine and other fields, shape analysis is very important for diagnosis of diseases and prediction of shape variation. This paper focuses on the surface parameterization of tube-like 3D objects to obtain and analyze shape information from a sample shape, including its size and the shape variation between different samples. It can well represent the global and local shape information for statistical analysis and for the construction of Medial Shape Model. Firstly, we extract the axis curve of the object by a heat conduction model. Secondly, we obtain the latitude circles by using the normal planes to cross the surface. Then we get the final parameterized surface with quad-dominant meshes by registering the points of single latitude circle and between different circles through coordinate transformation and alignment. Subsequently, we apply the approach to parameterization of a rib bone.

scholarly journals Mindboggling morphometry of human brains

2016 ◽  
Author(s):  
Arno Klein ◽  
Satrajit S. Ghosh ◽  
Forrest S. Bao ◽  
Joachim Giard ◽  
Yrjö Häme ◽  
...  
Keyword(s):  
Mental Health ◽  
Open Source ◽  
Shape Analysis ◽  
Mental Health Disorders ◽  
Zernike Moments ◽  
Shape Variation ◽  
Shape Information ◽  
Brain Morphometry ◽  
Health Disorders ◽  
Human Brains

AbstractMindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains every conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, and more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggle’s algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available.Author SummaryBrains vary in many ways, including their shape. Analysing differences in shape between brains or changes in brain shape over time has been used to characterize morphology of diseased brains, but these analyses conventionally rely on simple volumetric shape measures. We believe that access to a greater variety of shape measures could provide greater sensitivity and specificity to morphological disturbances, and could aid in diagnosis, tracking, and prediction of the progression of mental health disorders. Mindboggle is open source software that provides neuroscientists (and indeed, anyone interested in computing shapes) tools for computing a variety of shape measures, including area, volume, thickness, curvature, geodesic depth, travel depth, Laplace-Beltrami spectra, and Zernike moments. In addition to algorithmic contributions, we conducted evaluations and applied Mindboggle to conduct the most detailed shape analysis of human brains.

Study of Shape Representation Using Internal Radiated-light Projection

2002 ◽  
Vol 14 (4) ◽  
pp. 357-365
Author(s):  
Takahiro Doi ◽  
◽  
Shigeo Hirose
Keyword(s):  
Shape Representation ◽  
Contour Analysis ◽  
Shape Information ◽  
Local Shape ◽  
3D Objects ◽  
Recent Developments ◽  
Real Objects ◽  
Object Shapes ◽  
Straight Lines ◽  
3D Shapes

Recent developments in 3D sensors have raised the possibility of using them in an increasing number of engineering applications. However, since most 3D sensors, such as the laser range finder, are based on the use of light, which moves in straight lines, the measurement area is limited to the front of an object, making the back an ""invisible"" surface. To calculate such unmeasurable areas, a system that memorizes shapes often encountered in objects and superimposes them on the scene is required. To realize such a type of system, an appropriate 3D shape representation is needed. This representation should 1) be able to handle and compare partial and complete sets of data of object shapes, and 2) operate quickly enough to be applicable to real-time tasks. We developed a novel shape representation framework called ""Internal Radiated-light Projection (IRP)"" to represent and compare 3D objects. This representation projects local shape information of an object on a sphere by imaginary rays from the ""kernel"" of the object. To describe local shape information and arrange shapes properly, we propose Harmonic Contour Analysis (HCA) and the Shape Matrix. These concepts are characterized by 1) simplicity; 2) the use of local shapes and their adjacent information; and, by using the Shape Matrix, 3) the consideration of the effect of gravity and stable poses for objects. In IRP representation, we can categorize objects in known classes and calculate their positions and attitudes. This paper explains the basic concept behind IRP, which is a way of representing local 3D shapes by HCA and categorizing them using the Shape Matrix. We then present experiments in object recognition for both virtual and real objects to demonstrate its efficiency and feasibility.

Computerized detection of pulmonary nodules using a combination of 3D global and local shape information based on helical CT images

2006 ◽  
Author(s):  
Xiangwei Zhang ◽  
Jonathan Stockel ◽  
Matthias Wolf ◽  
Pascal Cathier ◽  
Geoffrey McLennan ◽  
...  
Keyword(s):  
Pulmonary Nodules ◽  
Helical Ct ◽  
Ct Images ◽  
Shape Information ◽  
Local Shape ◽  
Global And Local

scholarly journals Exploring palatal and dental shape variation with 3D shape analysis and geometric deep learning

2021 ◽  
Author(s):  
Nele Nauwelaers ◽  
Harold Matthews ◽  
Yi Fan ◽  
Balder Croquet ◽  
Hanne Hoskens ◽  
...  
Keyword(s):  
Deep Learning ◽  
Shape Analysis ◽  
Shape Variation ◽  
3D Shape ◽  
3D Shape Analysis

Monocular face reconstruction with global and local shape constraints

2015 ◽  
Vol 149 ◽  
pp. 1535-1543 ◽  
Author(s):  
Jian Zhang ◽  
Dapeng Tao ◽  
Xiangjuan Bian ◽  
Xiaosi Zhan
Keyword(s):  
Local Shape ◽  
Shape Constraints ◽  
Face Reconstruction ◽  
Global And Local

A Geometric Morphometric Assessment of Hand Shape and Comparison to the 2D:4D Digit Ratio as a Marker of Sexual Dimorphism

2013 ◽  
Vol 16 (2) ◽  
pp. 590-600 ◽  
Author(s):  
Paul G. Sanfilippo ◽  
Alex W. Hewitt ◽  
Jenny A. Mountain ◽  
David A. Mackey
Keyword(s):  
Sexual Dimorphism ◽  
Geometric Morphometrics ◽  
Shape Analysis ◽  
Twin Studies ◽  
Analytical Techniques ◽  
Shape Variation ◽  
Geometric Morphometric ◽  
Hand Shape ◽  
Physical Traits ◽  
Biological Shape

Twin studies are extremely useful for investigating hypotheses of genetic influence on a range of behavioral and physical traits in humans. Studies of physical traits, however, are usually limited to size-related biological characteristics because it is inherently difficult to quantify the morphological counterpart – shape. In recent years, the development of geometry-preserving analytical techniques built upon multivariate statistical methodologies has produced a new discipline in biological shape analysis known as geometric morphometrics. In this study of hand shape analysis, we introduce the reader already familiar with the field of twin research to the potential utility of geometric morphometrics and demonstrate the cross-discipline applicability of methods. We also investigate and compare the efficacy of the 2D:4D ratio, a commonly used marker of sexual dimorphism, to the fully multivariate approach of shape analysis in discriminating between male and female sex. Studies of biological shape variation utilizing geometric morphometric techniques may be completed with software freely available on the Internet and time invested to master the small learning curve in concepts and theory.

Sign in / Sign up

Export Citation Format

Share Document