The spectral graph wavelet transform (SGWT) has recently been developed to compute
wavelet transforms of functions defined on non-Euclidean spaces such as graphs. By …

Statistical analysis on arbitrary surface meshes such as the cortical surface is an important
approach to understanding brain diseases such as Alzheimer's disease (AD). Surface …

This paper emphasizes the statistical properties of the wavelet transform (WT) and discusses
some examples of applications in medicine and biology. The redundant forms of the …

We present an overview of the various uses of the wavelet transform (WT) in medicine and
biology. We start by describing the wavelet properties that are the most important for …

Morphometric analysis of medical images is playing an increasingly important role in
understanding brain structure and function, as well as in understanding the way in which …

Early diagnosis of Alzheimer's disease plays a key role in understanding the degree of the
patient's mental decline and determining preventive therapies. In this study, we introduce …

We introduce a class of spectral shape signatures constructed from symmetric functions on
the eigenfunctions of the Laplacian exponentially weighted by their eigenvalues. Such a …

Quantitative shape comparison is a fundamental problem in computer vision, geometry
processing and medical imaging. In this paper, we present a spectral graph wavelet …

Early diagnosis of Alzheimer's disease is a major concern due to large portions of the elderly
population it affects and the lack of a standard and effective diagnosis procedure that is …

We represent a shape representation technique using the eigenfunctions of Laplace-
Beltrami (LB) operator and compare the performance with the conventional spherical …