Share Email Print
cover

Proceedings Paper

A 1D wavelet filtering for ultrasound images despeckling
Author(s): Sonia Dahdouh; Mathieu Dubois; Emmanuelle Frenoux; Angel Osorio
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Ultrasound images appearance is characterized by speckle, shadows, signal dropout and low contrast which make them really difficult to process and leads to a very poor signal to noise ratio. Therefore, for main imaging applications, a denoising step is necessary to apply successfully medical imaging algorithms on such images. However, due to speckle statistics, denoising and enhancing edges on these images without inducing additional blurring is a real challenging problem on which usual filters often fail. To deal with such problems, a large number of papers are working on B-mode images considering that the noise is purely multiplicative. Making such an assertion could be misleading, because of internal pre-processing such as log compression which are done in the ultrasound device. To address those questions, we designed a novel filtering method based on 1D Radiofrequency signal. Indeed, since B-mode images are initially composed of 1D signals and since the log compression made by ultrasound devices modifies noise statistics, we decided to filter directly the 1D Radiofrequency signal envelope before log compression and image reconstitution, in order to conserve as much information as possible. A bi-orthogonal wavelet transform is applied to the log transform of each signal and an adaptive 1D split and merge like algorithm is used to denoise wavelet coefficients. Experiments were carried out on synthetic data sets simulated with Field II simulator and results show that our filter outperforms classical speckle filtering methods like Lee, non-linear means or SRAD filters.

Paper Details

Date Published: 12 March 2010
PDF: 9 pages
Proc. SPIE 7629, Medical Imaging 2010: Ultrasonic Imaging, Tomography, and Therapy, 762907 (12 March 2010); doi: 10.1117/12.844388
Show Author Affiliations
Sonia Dahdouh, Lab. d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, CNRS (France)
Mathieu Dubois, Lab. d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, CNRS (France)
Emmanuelle Frenoux, Lab. d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, CNRS (France)
Angel Osorio, Lab. d'Informatique pour la Mécanique et les Sciences de l'Ingénieur, CNRS (France)


Published in SPIE Proceedings Vol. 7629:
Medical Imaging 2010: Ultrasonic Imaging, Tomography, and Therapy
Jan D'hooge; Stephen A. McAleavey, Editor(s)

© SPIE. Terms of Use
Back to Top