A Landmark-Free Method for Three-Dimensional Shape Analysis

The tools and techniques used in morphometrics have always aimed to transform the physical shape of an object into a concise set of numerical data for mathematical analysis. The advent of landmark-based morphometrics opened new avenues of research, but these methods are not without drawbacks. The ti...

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Bibliographic Details
Published in:PloS one 2016-03, Vol.11 (3), p.e0150368-e0150368
Main Authors: Pomidor, Benjamin J, Makedonska, Jana, Slice, Dennis E
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Automation
Biology and Life Sciences
Computer and Information Sciences
Data processing
Engineering and Technology
Geometric figures
International conferences
Iterative algorithms
Iterative methods
Linear algebra
Mathematical analysis
Medicine and Health Sciences
Methods
Models, Theoretical
Morphometry
Multivariate analysis
Numerical analysis
Physical Sciences
Registration
Research and Analysis Methods
Three dimensional analysis
Transformation
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Summary:The tools and techniques used in morphometrics have always aimed to transform the physical shape of an object into a concise set of numerical data for mathematical analysis. The advent of landmark-based morphometrics opened new avenues of research, but these methods are not without drawbacks. The time investment required of trained individuals to accurately landmark a data set is significant, and the reliance on readily-identifiable physical features can hamper research efforts. This is especially true of those investigating smooth or featureless surfaces. In this paper, we present a new method to perform this transformation for data obtained from high-resolution scanning technology. This method uses surface scans, instead of landmarks, to calculate a shape difference metric analogous to Procrustes distance and perform superimposition. This is accomplished by building upon and extending the Iterative Closest Point algorithm. We also explore some new ways this data can be used; for example, we can calculate an averaged surface directly and visualize point-wise shape information over this surface. Finally, we briefly demonstrate this method on a set of primate skulls and compare the results of the new methodology with traditional geometric morphometric analysis.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0150368