ANALYSIS OF ULTRASOUND IMAGE TEXTURE VIA GENERALIZED RICIAN STATISTICS.

Michael Insana, Robert F. Wagner, Brian S. Garra, David G. Brown, Thomas H. Shawker

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

Abstract

Tissue signatures are obtained from the first and second order statistics of ultrasonic B-scan texture. Laboratory measurements and early clinical results show that the image may be segmented to discriminate between different normal tissues and to detect abnormal conditions based on a three-dimensional feature space. These features describe the intrinsic backscatter properties of the tissues imaged and may be used as the basis of an automatic tissue characterization algorithm.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsHenri H. Arsenault
Place of PublicationBellingham, WA, USA
PublisherSPIE
Pages153-159
Number of pages7
Volume556
ISBN (Print)0892525916
StatePublished - Dec 1 1985
Externally publishedYes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Fingerprint Dive into the research topics of 'ANALYSIS OF ULTRASOUND IMAGE TEXTURE VIA GENERALIZED RICIAN STATISTICS.'. Together they form a unique fingerprint.

  • Cite this

    Insana, M., Wagner, R. F., Garra, B. S., Brown, D. G., & Shawker, T. H. (1985). ANALYSIS OF ULTRASOUND IMAGE TEXTURE VIA GENERALIZED RICIAN STATISTICS. In H. H. Arsenault (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 556, pp. 153-159). SPIE.