Abstract
In this paper the problem of image texture analysis in the presence of noise is examined from a higher-order statistical perspective. The approach taken involves the use of two dimensional second order Volterra filters where the filter weights are derived from third order cumulants of the two dimensional signal. The specific application contained in this contribution is in mammography, an area in which it is difficult to discern the appropriate features. The paper describes the fundamental issues of the various components of the approach. The results of the entire texture modelling, classification and segmentation scheme contained in this paper are very encouraging. 7 refs, 2 figs.
Stathaki, P T;
Constantinides, A G
[1]
- Signal Processing Section, Department of Electrical and Electronic Engineering, Imperial College, Exhibition Road, London SW7 2BT, UK (United Kingdom)
Citation Formats
Stathaki, P T, and Constantinides, A G.
Two dimensional nonlinear spectral estimation techniques for breast cancer localization.
Cyprus: N. p.,
1994.
Web.
Stathaki, P T, & Constantinides, A G.
Two dimensional nonlinear spectral estimation techniques for breast cancer localization.
Cyprus.
Stathaki, P T, and Constantinides, A G.
1994.
"Two dimensional nonlinear spectral estimation techniques for breast cancer localization."
Cyprus.
@misc{etde_595670,
title = {Two dimensional nonlinear spectral estimation techniques for breast cancer localization}
author = {Stathaki, P T, and Constantinides, A G}
abstractNote = {In this paper the problem of image texture analysis in the presence of noise is examined from a higher-order statistical perspective. The approach taken involves the use of two dimensional second order Volterra filters where the filter weights are derived from third order cumulants of the two dimensional signal. The specific application contained in this contribution is in mammography, an area in which it is difficult to discern the appropriate features. The paper describes the fundamental issues of the various components of the approach. The results of the entire texture modelling, classification and segmentation scheme contained in this paper are very encouraging. 7 refs, 2 figs.}
place = {Cyprus}
year = {1994}
month = {Dec}
}
title = {Two dimensional nonlinear spectral estimation techniques for breast cancer localization}
author = {Stathaki, P T, and Constantinides, A G}
abstractNote = {In this paper the problem of image texture analysis in the presence of noise is examined from a higher-order statistical perspective. The approach taken involves the use of two dimensional second order Volterra filters where the filter weights are derived from third order cumulants of the two dimensional signal. The specific application contained in this contribution is in mammography, an area in which it is difficult to discern the appropriate features. The paper describes the fundamental issues of the various components of the approach. The results of the entire texture modelling, classification and segmentation scheme contained in this paper are very encouraging. 7 refs, 2 figs.}
place = {Cyprus}
year = {1994}
month = {Dec}
}