An automated Multispectral pixel and image classification system using texture analysis and neural networks

Yi Zheng, David A. Foley, Thomas M. Kinter, James F. Greenleaf

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

1 Scopus citations

Abstract

An automated pixel and image classification system has been developed to identify texture patterns within images after training with representative texture patterns. Multispectral analysis is applied to ultrasound images to form hyperspaces in which texture patterns are clustered. The clusters in the space are produced using run-length and Markovian texture statistics. Several neural network models can be selected to classify patterns. The system has been implemented in C on a Sun workstation in a window environment. It is highly automated and has potential for clinical applications. Texture patterns found in a series of cardiac ultrasound images of a tumor were used to train the system. The tumor was correcdy identified throughout a series of consecutive, closely-space tomographic images.

Original languageEnglish (US)
Title of host publication1992 Ultrasonics Symposium Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1093-1096
Number of pages4
ISBN (Electronic)0780305620
DOIs
StatePublished - Jan 1 1992
Event1992 Ultrasonics Symposium - Tucson, United States
Duration: Oct 20 1992Oct 23 1992

Publication series

NameProceedings - IEEE Ultrasonics Symposium
Volume1992-October
ISSN (Print)1051-0117

Conference

Conference1992 Ultrasonics Symposium
CountryUnited States
CityTucson
Period10/20/9210/23/92

ASJC Scopus subject areas

  • Acoustics and Ultrasonics

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    Zheng, Y., Foley, D. A., Kinter, T. M., & Greenleaf, J. F. (1992). An automated Multispectral pixel and image classification system using texture analysis and neural networks. In 1992 Ultrasonics Symposium Proceedings (pp. 1093-1096). [276007] (Proceedings - IEEE Ultrasonics Symposium; Vol. 1992-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ULTSYM.1992.276007