Landmark-free, parametric hypothesis tests regarding two-dimensional contour shapes using coherent point drift registration and statistical parametric mapping

This paper proposes a computational framework for automated, landmark-free hypothesis testing of 2D contour shapes (i.e., shape outlines), and implements one realization of that framework. The proposed framework consists of point set registration, point correspondence determination, and parametric f...

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Bibliographic Details
Published in:PeerJ. Computer science 2021-05, Vol.7, p.e542-e542, Article e542
Main Authors: Pataky, Todd C, Yagi, Masahide, Ichihashi, Noriaki, Cox, Philip G
Format: Article
Language:English
Subjects:
2D shape analysis
Algorithms
Classical hypothesis testing
Computer Vision
Contours
Data processing
Datasets
Fourier analysis
Geometry
Hypotheses
Hypothesis testing
Mathematical analysis
Mathematical models
Mathematical statistics
Morphology
Morphometrics
Parameter sensitivity
Power
Principal components analysis
Registration
Scientific Computing and Simulation
Sensitivity analysis
Shape
Shape effects
Spatial registration
Statistical analysis
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Summary:This paper proposes a computational framework for automated, landmark-free hypothesis testing of 2D contour shapes (i.e., shape outlines), and implements one realization of that framework. The proposed framework consists of point set registration, point correspondence determination, and parametric full-shape hypothesis testing. The results are calculated quickly (
ISSN:2376-5992
2376-5992
DOI:10.7717/peerj-cs.542