Scientific Research Publishing

Density Functions and Descriptive Statistics for Distance Measures in Cartesian Space ()

This research provides density functions and descriptive statistics for the distance between points for basic shapes in Cartesian space. Both Euclidean and Rectilinear Distances are determined for ...
IEEE

Accelerating Euclidean Distance Transforms: A Fast and Flexible Approach With Multi-Vendor GPU, Multi-Threading, and Multi-Language Support

Abstract: Euclidean distance transforms are fundamental in image processing and computer vision, with critical applications in medical image analysis and computer graphics. However, existing ...
SciELO

On the eigenvalues of Euclidean distance matrices

In this paper, the notion of equitable partitions (EP) is used to study the eigenvalues of Euclidean distance matrices (EDMs). In particular, EP is used to obtain the characteristic polynomials of ...
Scientific Research Publishing

Saito, T. and Toriwaki, J. (1994) New Algorithms for Euclidean Distance Transformation of an N-Dimensional Digitized Picture with Applications. Pattern Recognition, 27, 1551-1565.

ABSTRACT: Purpose: This study describes a machine-learning approach utilizing patients' anatomical changes to predict parotid mean dose changes in fractionated radiotherapy for head-and-neck cancer, ...
SciELO

Euclidean distance matrices: special subsets, systems of coordinates and multibalanced matrices

Although of interest for over a century, most useful results concerning Euclidean distance matrices (EDMs) have appeared during the last thirty years, motivated by applications to the multidimensional ...
PNAS

Diffusive topology preserving manifold distances for single-cell data analysis

Distortions from traditional dimensionality reduction methods obscure relationships in high-dimensional single-cell data, thus impeding biological insights. We introduce DTNE (diffusive topology ...