An efficient data mining technique with applications in multivariate image analysis

Author

Laskaris, N. ; Fotopoulos, S.

Author_Institution

Dept. of Phys., Patras Univ., Greece

Volume

2

fYear

1997

fDate

2-4 Jul 1997

Firstpage

1103

Abstract

The “curse of dimensionality” complicates the analysis of multiparameter images. The application of a data mining technique, as a tool to resolve the image puzzle, is the subject of this study. This well developed technique is a sequential planing procedure, based on the minimal spanning tree of the data. It is armed with a Hopfield neural network implementation and, being computationally efficient, appears to be very attractive for image understanding tasks. Integrated in a GUI environment, it can be a useful prelude to the subsequent image analysis

Keywords

Hopfield neural nets; graphical user interfaces; image processing; tree data structures; GUI environment; Hopfield neural network; computationally efficient method; data mining technique; image understanding; minimal spanning tree; multiparameter images; multivariate image analysis; sequential planing procedure; Data mining; Graphical user interfaces; Hopfield neural networks; Image analysis; Image resolution; Magnetic resonance imaging; Physics; Planing; Space technology; Tree graphs;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Signal Processing Proceedings, 1997. DSP 97., 1997 13th International Conference on

Conference_Location

Santorini

Print_ISBN

0-7803-4137-6

Type

conf

DOI

10.1109/ICDSP.1997.628558

Filename

628558