Two Sample Test for Extrinsic Antimeans on Planar Kendall Shape Spaces with an Application to Medical Imaging

07/09/2021
by   Aaid Algahtani, et al.
0

In this paper one develops nonparametric inference procedures for comparing two extrinsic antimeans on compact manifolds. Based on recent Central limit theorems for extrinsic sample antimeans w.r.t. an arbitrary embedding of a compact manifold in a Euclidean space, one derives an asymptotic chi square test for the equality of two extrinsic antimeans. Applications are given to distributions on complex projective space CP^k-2 w.r.t. the Veronese-Whitney embedding, that is a submanifold representation for the Kendall planar shape space. Two medical imaging analysis applications are also given.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/01/2019

Anti-MANOVA on Compact Manifolds with Applications to 3D Projective Shape Analysis

Methods of hypotheses testing for equality of extrinsic antimeans on com...
research
09/29/2019

A new bound for smooth spline spaces

For a planar simplicial complex Delta contained in R^2, Alfeld-Schumaker...
research
06/05/2008

A Nonparametric Approach to 3D Shape Analysis from Digital Camera Images - I. in Memory of W.P. Dayawansa

In this article, for the first time, one develops a nonparametric method...
research
10/02/2022

A Kernel Measure of Dissimilarity between M Distributions

Given M ≥ 2 distributions defined on a general measurable space, we intr...
research
04/15/2020

Extended source imaging, a unifying framework for seismic medical imaging

We present three imaging modalities that live on the crossroads of seism...
research
01/03/2018

Differential Geometry for Model Independent Analysis of Images and Other Non-Euclidean Data: Recent Developments

This article provides an exposition of recent methodologies for nonparam...
research
01/22/2019

Aggregated Pairwise Classification of Statistical Shapes

The classification of shapes is of great interest in diverse areas rangi...

Please sign up or login with your details

Forgot password? Click here to reset