NDLI: A multi-parametric segmentation tool dedicated to ultrasonic data

Content Provider	IEEE Xplore Digital Library
Author	Davignon, F. Basset, O. Gimenez, G. Mai, W.
Copyright Year	2002
Description	Author affiliation: CREATIS, Villeurbanne, France (Davignon, F.; Basset, O.; Gimenez, G.)
Abstract	Ultrasound images segmentation can bring very useful information for diagnosis but is a difficult task. We propose in this paper a segmentation tool dedicated to ultrasonic data. Our software is based on a segmentation method that involves both multiresolution and multiparametric approaches. A multiparametric approach ensures the robustness of the method. Therefore, the segmentation tool is based on information connected to echo envelope characterization and acoustical characterization, the latter being calculated from the Radio-Frequency (RF) signal. The RF signal allows to calculate local information related to the acoustical properties of the investigated tissues. Several parametric images are build and involved in the segmentation process. The segmentation software is based on a previously presented method (Boukerroui et al. 2001). A Bayesian approach using a multiresolution Markov random field is implemented. The relevance of the several features calculated is shown by the mean of phantoms build with the FIELD II tool. We also present segmentation results on data provided by a technological platform that provides in-vivo multimodality imaging of small animals such as mice and rats. Results on the segmentation of liver mice ultrasonic data are presented.
Sponsorship	Ultransonics Ferroelectr., & Frequency Control Soc
Starting Page	1761
Ending Page	1764
File Size	163248
Page Count	4
File Format	PDF
ISBN	0780375823
ISSN	10510117
DOI	10.1109/ULTSYM.2002.1192639
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-10-08
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Ultrasonic imaging Signal resolution Radio frequency Mice Robustness RF signals Bayesian methods Markov random fields Imaging phantoms
Content Type	Text
Resource Type	Article

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