M
Michael F. Insana
Researcher at University of Illinois at Urbana–Champaign
Publications - 300
Citations - 9647
Michael F. Insana is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Imaging phantom & Viscoelasticity. The author has an hindex of 48, co-authored 295 publications receiving 9247 citations. Previous affiliations of Michael F. Insana include University of Kansas & Food and Drug Administration.
Papers
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Journal ArticleDOI
Selected methods for imaging elastic properties of biological tissues.
TL;DR: This review discusses several methods of estimating tissue hardness using internal or external means of applying stress (force per unit area) and several associated methods of detecting the resulting strain (fractional length change) in an effort to image a tissue mechanical property, such as Young's modulus.
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Thyroid gland tumor diagnosis at US elastography
Andrej Lyshchik,Tatsuya Higashi,Ryo Asato,Shinzo Tanaka,Juichi Ito,Jerome J. Mai,C. Pellot-Barakat,Michael F. Insana,A. B. Brill,Tsuneo Saga,Masahiro Hiraoka,Kaori Togashi +11 more
TL;DR: Elastography is a promising imaging technique that can assist in the differential diagnosis of thyroid gland cancer, and the usefulness of these criteria was not considered to be high because of their low sensitivity.
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Phantom materials for elastography
TL;DR: In this article, a device and procedure for measuring elastic properties of gelatin for elasticity imaging (elastography) was described. And the measured compression forces were comparable to results obtained from finite element analysis when linear elastic media are assumed.
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Describing small-scale structure in random media using pulse-echo ultrasound.
TL;DR: The dependence of the measurement accuracy on the inclusion of shear waves, the wavelength of sound, and medium attenuation are considered, and the implications for describing the structure of biological soft tissues are discussed.
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Statistical properties of radio-frequency and envelope-detected signals with applications to medical ultrasound.
TL;DR: In this paper, first and second-order statistics of complex random signals are reviewed, and an example is taken from rf signal analysis of the backscattered echoes from diffuse scatterers.