Texture anisotropy in 3-D images

Author

Kovalev, Vassili A. ; Petrou, Maria ; Bondar, Yaroslav S.

Author_Institution

Inst. of Math., Acad. of Sci., Gomel, Byelorussia

Volume

8

Issue

3

fYear

1999

fDate

3/1/1999 12:00:00 AM

Firstpage

346

Lastpage

360

Abstract

Two approaches to the characterization of three-dimensional (3-D) textures are presented: one based on gradient vectors and one on generalized co-occurrence matrices. They are investigated with the help of simulated data for their behavior in the presence of noise and for various values of the parameters they depend on. They are also applied to several medical volume images characterized by the presence of microtextures and their potential as diagnostic tools and tools for quantifying and monitoring the progress of various pathologies is discussed. No firm medical conclusions can be drawn as not enough clinical data are available. The gradient based method appears to be more appropriate for the characterization of microtextures. It also shows more consistent behavior as a descriptor of pathologies than the generalized co-occurrence matrix approach

Keywords

biomedical MRI; diagnostic radiography; feature extraction; gradient methods; image registration; image representation; image texture; matrix algebra; medical image processing; patient monitoring; 3D images; 3D textures; MR images; diagnostic tools; generalized co-occurrence matrices; gradient based method; gradient vectors; image registration; image representation; medical volume images; microtextures; noise; pathologies monitoring; simulated data; texture anisotropy; Anisotropic magnetoresistance; Biomedical imaging; Biomedical monitoring; Bonding; Image analysis; Image texture analysis; Mathematics; Medical diagnostic imaging; Medical simulation; Pathology;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.748890

Filename

748890