Biomedical image texture analysis based on high-order fractals

Huinian Xiao, A. Chu, Kerrie S. Holton, Richard A. Robb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Since the fractal dimension alone is not sufficient to characterize natural texture, we explore higher order geometry to accurately identify texture in biomedical images. The calculation of the fractal dimension set is based on the texture description: known as the Pseudo Matrix of the Fractal (PMF). In our research, the variants of the PMF are tested, a set of the fractal parameters are defined, and different discriminant functions are investigated. A new approach to texture classification is described. Using vectors derived from the PMF, the inner products of these normalized vectors obtained from the training groups and the test image form the measures for classification. This method is easily implemented and produces reliable classification results. The new algorithm significantly simplifies the calculation of the fractal dimension set, and the classification of texture in medical images becomes more sensitive and specific. Preliminary results have demonstrated an improved accuracy in classification on one group of eight types of realistic texture data and one set of MRI brain data.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Place of PublicationBellingham, WA, United States
PublisherPubl by Int Soc for Optical Engineering
Pages649-659
Number of pages11
Volume1660
Editionpt 1
ISBN (Print)081940814X
StatePublished - 1992
EventBiomedical Image Processing and Three-Dimensional Microscopy. Part 1 (of 2) - San Jose, CA, USA
Duration: Feb 10 1991Feb 13 1991

Other

OtherBiomedical Image Processing and Three-Dimensional Microscopy. Part 1 (of 2)
CitySan Jose, CA, USA
Period2/10/912/13/91

Fingerprint

Image texture
Fractals
fractals
textures
Textures
Fractal dimension
matrices
Magnetic resonance imaging
Brain
brain
education
Geometry
products
geometry

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Xiao, H., Chu, A., Holton, K. S., & Robb, R. A. (1992). Biomedical image texture analysis based on high-order fractals. In Proceedings of SPIE - The International Society for Optical Engineering (pt 1 ed., Vol. 1660, pp. 649-659). Bellingham, WA, United States: Publ by Int Soc for Optical Engineering.

Biomedical image texture analysis based on high-order fractals. / Xiao, Huinian; Chu, A.; Holton, Kerrie S.; Robb, Richard A.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 1660 pt 1. ed. Bellingham, WA, United States : Publ by Int Soc for Optical Engineering, 1992. p. 649-659.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Xiao, H, Chu, A, Holton, KS & Robb, RA 1992, Biomedical image texture analysis based on high-order fractals. in Proceedings of SPIE - The International Society for Optical Engineering. pt 1 edn, vol. 1660, Publ by Int Soc for Optical Engineering, Bellingham, WA, United States, pp. 649-659, Biomedical Image Processing and Three-Dimensional Microscopy. Part 1 (of 2), San Jose, CA, USA, 2/10/91.
Xiao H, Chu A, Holton KS, Robb RA. Biomedical image texture analysis based on high-order fractals. In Proceedings of SPIE - The International Society for Optical Engineering. pt 1 ed. Vol. 1660. Bellingham, WA, United States: Publ by Int Soc for Optical Engineering. 1992. p. 649-659
Xiao, Huinian ; Chu, A. ; Holton, Kerrie S. ; Robb, Richard A. / Biomedical image texture analysis based on high-order fractals. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 1660 pt 1. ed. Bellingham, WA, United States : Publ by Int Soc for Optical Engineering, 1992. pp. 649-659
@inproceedings{2ac489098a814d89a63f48dcc8e4343b,
title = "Biomedical image texture analysis based on high-order fractals",
abstract = "Since the fractal dimension alone is not sufficient to characterize natural texture, we explore higher order geometry to accurately identify texture in biomedical images. The calculation of the fractal dimension set is based on the texture description: known as the Pseudo Matrix of the Fractal (PMF). In our research, the variants of the PMF are tested, a set of the fractal parameters are defined, and different discriminant functions are investigated. A new approach to texture classification is described. Using vectors derived from the PMF, the inner products of these normalized vectors obtained from the training groups and the test image form the measures for classification. This method is easily implemented and produces reliable classification results. The new algorithm significantly simplifies the calculation of the fractal dimension set, and the classification of texture in medical images becomes more sensitive and specific. Preliminary results have demonstrated an improved accuracy in classification on one group of eight types of realistic texture data and one set of MRI brain data.",
author = "Huinian Xiao and A. Chu and Holton, {Kerrie S.} and Robb, {Richard A.}",
year = "1992",
language = "English (US)",
isbn = "081940814X",
volume = "1660",
pages = "649--659",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "Publ by Int Soc for Optical Engineering",
edition = "pt 1",

}

TY - GEN

T1 - Biomedical image texture analysis based on high-order fractals

AU - Xiao, Huinian

AU - Chu, A.

AU - Holton, Kerrie S.

AU - Robb, Richard A.

PY - 1992

Y1 - 1992

N2 - Since the fractal dimension alone is not sufficient to characterize natural texture, we explore higher order geometry to accurately identify texture in biomedical images. The calculation of the fractal dimension set is based on the texture description: known as the Pseudo Matrix of the Fractal (PMF). In our research, the variants of the PMF are tested, a set of the fractal parameters are defined, and different discriminant functions are investigated. A new approach to texture classification is described. Using vectors derived from the PMF, the inner products of these normalized vectors obtained from the training groups and the test image form the measures for classification. This method is easily implemented and produces reliable classification results. The new algorithm significantly simplifies the calculation of the fractal dimension set, and the classification of texture in medical images becomes more sensitive and specific. Preliminary results have demonstrated an improved accuracy in classification on one group of eight types of realistic texture data and one set of MRI brain data.

AB - Since the fractal dimension alone is not sufficient to characterize natural texture, we explore higher order geometry to accurately identify texture in biomedical images. The calculation of the fractal dimension set is based on the texture description: known as the Pseudo Matrix of the Fractal (PMF). In our research, the variants of the PMF are tested, a set of the fractal parameters are defined, and different discriminant functions are investigated. A new approach to texture classification is described. Using vectors derived from the PMF, the inner products of these normalized vectors obtained from the training groups and the test image form the measures for classification. This method is easily implemented and produces reliable classification results. The new algorithm significantly simplifies the calculation of the fractal dimension set, and the classification of texture in medical images becomes more sensitive and specific. Preliminary results have demonstrated an improved accuracy in classification on one group of eight types of realistic texture data and one set of MRI brain data.

UR - http://www.scopus.com/inward/record.url?scp=0026965721&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026965721&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0026965721

SN - 081940814X

VL - 1660

SP - 649

EP - 659

BT - Proceedings of SPIE - The International Society for Optical Engineering

PB - Publ by Int Soc for Optical Engineering

CY - Bellingham, WA, United States

ER -