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A multiparametric and multiresolution segmentation algorithm of 3D ultrasonic data

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4 Author(s)
Boukerroui, D. ; CREATIS, CNRS, Villeurbanne, France ; Basset, O. ; Baskurt, A. ; Gimenez, G.

An algorithm devoted to the segmentation of 3-D ultrasonic data is proposed. The algorithm involves 3-D adaptive clustering based on multiparametric information: the gray-scale intensity of the echographic data, 3-D texture features calculated from the envelope data, and 3-D tissue characterization information calculated from the local frequency spectra of the radio-frequency signals. The segmentation problem is formulated as a maximum a posterior (MAP) estimation problem. A multi-resolution implementation of the algorithm is proposed. The approach is tested on simulated data and on in vivo echocardiographic 3-D data. The results presented in the paper illustrate the robustness and the accuracy of the proposed approach for the segmentation of ultrasonic data.

Published in:

Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on  (Volume:48 ,  Issue: 1 )

Date of Publication:

Jan. 2001

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