Visualization of tissue elasticity by magnetic resonance elastography

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

13 Scopus citations

Abstract

A newly developed magnetic resonance imaging technique can directly visualize propagating acoustic strain waves in tissue-like materials [1, 2]. By estimating the local wavelength of the acoustic wave pattern, quantitative values of shear modulus can be calculated and images generated that depict tissue elasticity or stiffness. Since tumors are significantly stiffer than normal tissue (the basis of their detection by palpation), this technique may have potential for “palpation by imaging,” with possible application to the detection of tumors in breast, liver, kidney, and prostate. We describe the local wavelength estimation algorithm, study its properties, and show a variety of sample results.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages63-68
Number of pages6
Volume1131
ISBN (Print)3540616497, 9783540616498
StatePublished - 1996
Event4th International Conference on Visualization in Biomedical Computing, VBC 1996 - Hamburg, Germany
Duration: Sep 22 1996Sep 25 1996

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1131
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Conference on Visualization in Biomedical Computing, VBC 1996
CountryGermany
CityHamburg
Period9/22/969/25/96

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Manduca, A., Muthupillai, R., Rossman, J., Greenleaf, J. F., & Ehman, R. L. (1996). Visualization of tissue elasticity by magnetic resonance elastography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1131, pp. 63-68). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1131). Springer Verlag.