Neural estimation of scatterer density in ultrasound

Renata Smoliková; Mark P. Wachowiak; Georgia D. Tourassi; Jacek M. Zurada

Neural estimation of scatterer density in ultrasound

Renata Smoliková, Mark P. Wachowiak, Georgia D. Tourassi, Jacek M. Zurada

Research output: Contribution to conference › Paper › peer-review

3 Scopus citations

Abstract

Ultrasonic backscatter can provide information on the density of scatterers within biological media, and is therefore an important tool in tissue characterization. In this paper, a novel neural network approach to estimate scatterer density from generalized entropy is proposed. Neural estimation compares favorably with nonlinear least-squares models.

Original language	English
Pages	1696-1701
Number of pages	6
State	Published - 2002
Externally published	Yes
Event	2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States Duration: May 12 2002 → May 17 2002

Conference

Conference	2002 International Joint Conference on Neural Networks (IJCNN '02)
Country/Territory	United States
City	Honolulu, HI
Period	05/12/02 → 05/17/02

Cite this

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title = "Neural estimation of scatterer density in ultrasound",

abstract = "Ultrasonic backscatter can provide information on the density of scatterers within biological media, and is therefore an important tool in tissue characterization. In this paper, a novel neural network approach to estimate scatterer density from generalized entropy is proposed. Neural estimation compares favorably with nonlinear least-squares models.",

author = "Renata Smolikov{\'a} and Wachowiak, {Mark P.} and Tourassi, {Georgia D.} and Zurada, {Jacek M.}",

year = "2002",

language = "English",

pages = "1696--1701",

note = "2002 International Joint Conference on Neural Networks (IJCNN '02) ; Conference date: 12-05-2002 Through 17-05-2002",

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TY - CONF

T1 - Neural estimation of scatterer density in ultrasound

AU - Smoliková, Renata

AU - Wachowiak, Mark P.

AU - Tourassi, Georgia D.

AU - Zurada, Jacek M.

PY - 2002

Y1 - 2002

N2 - Ultrasonic backscatter can provide information on the density of scatterers within biological media, and is therefore an important tool in tissue characterization. In this paper, a novel neural network approach to estimate scatterer density from generalized entropy is proposed. Neural estimation compares favorably with nonlinear least-squares models.

AB - Ultrasonic backscatter can provide information on the density of scatterers within biological media, and is therefore an important tool in tissue characterization. In this paper, a novel neural network approach to estimate scatterer density from generalized entropy is proposed. Neural estimation compares favorably with nonlinear least-squares models.

UR - http://www.scopus.com/inward/record.url?scp=0036079754&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0036079754

SP - 1696

EP - 1701

T2 - 2002 International Joint Conference on Neural Networks (IJCNN '02)

Y2 - 12 May 2002 through 17 May 2002

ER -

Neural estimation of scatterer density in ultrasound

Abstract

Conference

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