Informational modeling of tissue-like materials using ultrasound

Cameron Hoerig, Jamshid Ghaboussi, Michael Insana

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


The correlation between disease pathology and tissue stiffness can be exploited to detect and potentially diagnose abnormal tissue states. Elastography is an imaging modality that attempts to image tissue stiffness by measuring local displacements caused by an applied force and calculating a strain map. Some elasticity imaging techniques attempt to assign a material parameter, such as Young's or shear modulus, to the imaged region in an effort to increase specificity. Unfortunately, the inversion techniques require many simplifying assumptions which lead to errors in the parameter estimates. One possible solution to increase accuracy in estimation is to first build an empirical model of the tissue using measured force-displacement data, thus eliminating the need for a priori assumptions. We propose the use of informational models for this purpose.

Original languageEnglish (US)
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)9781479923748
StatePublished - Jul 21 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: Apr 16 2015Apr 19 2015

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452


Other12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/TerritoryUnited States


  • Elasticity Imaging
  • Machine Learning
  • Neural Networks

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging


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