NDLI: Energy and feature-based strategies for estimating the contrast agent concentration in ultrasound medical imaging

Content Provider	IEEE Xplore Digital Library
Author	Sciallero, C. Crocco, M. Trucco, A.
Copyright Year	2012
Description	Author affiliation: Dynatech, University of Genoa, Italy (Sciallero, C.; Trucco, A.) \|\| Istituto Italiano di Tecnologia (IIT), Italy (Crocco, M.)
Abstract	The estimation of the contrast agent concentration is important for the introduction of effective quantification in ultrasound medical diagnoses. This paper focuses on the comparison of three methods for estimating the number of microbubbles in a small volume. An energy-based linear regression approach and a nonlinear regression approach are applied to estimate the microbubble concentration working from the signals backscattered by a contrast agent population. The nonlinear regression approach, based on the support vector machine, is employed assuming either only one feature, the signal energy, or a set of significant features. Synthetic data are used for the training phase and the test of the methods. The results demonstrate that, although the energy-based methods allows to achieve good results in terms of mean estimated values, the adoption of a vector of features significantly reduces the mean square error. The nonlinear regression approach with multidimensional feature vector allows to improve the measurement precision of the bubble concentration.
Starting Page	1
Ending Page	6
File Size	266479
Page Count	6
File Format	PDF
ISBN	9781467320498
ISSN	10637125
e-ISBN	9781467320511
DOI	10.1109/CBMS.2012.6266306
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-20
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation Support vector machines Standards Training Ultrasonic imaging Linear regression Kernel
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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