Characterization of ultrasonic backscatter based on generalized entropy

Renata Smolíková; Mark P. Wachowiak; Georgia D. Tourassi; Adel Elmaghraby; Jacek M. Zurada

Characterization of ultrasonic backscatter based on generalized entropy

Renata Smolíková, Mark P. Wachowiak, Georgia D. Tourassi, Adel Elmaghraby, Jacek M. Zurada

Research output: Contribution to journal › Conference article › peer-review

10 Scopus citations

Abstract

This paper presents a novel approach to ultrasound backscatter characterization based on generalized entropy. This approach makes no assumptions about the specific scattering distribution. Low order Renyi and Tsallis entropies have a higher dynamic range than Shannon entropy over a range of scattering conditions, and are therefore useful in estimating scatterer density and regularity. A neural network estimator is constructed to illustrate the validity of this approach.

Original language	English
Pages (from-to)	953-954
Number of pages	2
Journal	Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume	2
State	Published - 2002
Externally published	Yes
Event	Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States Duration: Oct 23 2002 → Oct 26 2002

Keywords

Backscatter
Renyi entropy
Speckle
Tsallis entropy
Ultrasound

Cite this

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title = "Characterization of ultrasonic backscatter based on generalized entropy",

abstract = "This paper presents a novel approach to ultrasound backscatter characterization based on generalized entropy. This approach makes no assumptions about the specific scattering distribution. Low order Renyi and Tsallis entropies have a higher dynamic range than Shannon entropy over a range of scattering conditions, and are therefore useful in estimating scatterer density and regularity. A neural network estimator is constructed to illustrate the validity of this approach.",

keywords = "Backscatter, Renyi entropy, Speckle, Tsallis entropy, Ultrasound",

author = "Renata Smol{\'i}kov{\'a} and Wachowiak, {Mark P.} and Tourassi, {Georgia D.} and Adel Elmaghraby and Zurada, {Jacek M.}",

year = "2002",

language = "English",

volume = "2",

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journal = "Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference",

issn = "0589-1019",

note = "Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) ; Conference date: 23-10-2002 Through 26-10-2002",

}

Characterization of ultrasonic backscatter based on generalized entropy. / Smolíková, Renata; Wachowiak, Mark P.; Tourassi, Georgia D. et al.
In: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, Vol. 2, 2002, p. 953-954.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Characterization of ultrasonic backscatter based on generalized entropy

AU - Smolíková, Renata

AU - Wachowiak, Mark P.

AU - Tourassi, Georgia D.

AU - Elmaghraby, Adel

AU - Zurada, Jacek M.

PY - 2002

Y1 - 2002

N2 - This paper presents a novel approach to ultrasound backscatter characterization based on generalized entropy. This approach makes no assumptions about the specific scattering distribution. Low order Renyi and Tsallis entropies have a higher dynamic range than Shannon entropy over a range of scattering conditions, and are therefore useful in estimating scatterer density and regularity. A neural network estimator is constructed to illustrate the validity of this approach.

AB - This paper presents a novel approach to ultrasound backscatter characterization based on generalized entropy. This approach makes no assumptions about the specific scattering distribution. Low order Renyi and Tsallis entropies have a higher dynamic range than Shannon entropy over a range of scattering conditions, and are therefore useful in estimating scatterer density and regularity. A neural network estimator is constructed to illustrate the validity of this approach.

KW - Backscatter

KW - Renyi entropy

KW - Speckle

KW - Tsallis entropy

KW - Ultrasound

UR - http://www.scopus.com/inward/record.url?scp=0036911062&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0036911062

SN - 0589-1019

VL - 2

SP - 953

EP - 954

JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

T2 - Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS)

Y2 - 23 October 2002 through 26 October 2002

ER -

Characterization of ultrasonic backscatter based on generalized entropy

Abstract

Keywords

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