Optimization of Mammary Tissue Displacement in Ultrasound Elastography
Optimization of Mammary Tissue Displacement in Ultrasound Elastography
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Author Info
Halima Mahjoubi Romaissa Tamali Taher Slimi
Corresponding Author
Taher SlimiLaboratory of Techniques and Medical Complexity, Faculty of Medicine, Joseph Fourier University, Grenoble, France
A B S T R A C T
The displacement of mammary tissues in static ultrasound elastography is often contaminated by the speckle noise deteriorating its quality. Several techniques have been developed in this context, in order to treat the noise present in images of breast tissue displacement, the progress of research work in noise processing is always questioned, especially that must be taken into account the trade-off between noise reduction and preservation of breast tissue texture. In this paper, a new strategy has been proposed to reduce speckle noise. The proposed method not only filters the image against noise, but also preserves the details and contours of the tissue texture. The approach developed is based on the coupling between the image reconstructions by filtered back projection (RPF) with an adaptive filter. The proposed model proposed has been validated on an in-vivo database comprising 20 images of the breast tissues displacement. Qualitative and quantitative improvements were noted. By comparing the proposed method with the wavelet technique, we show that it is more efficient in terms of calculating the standard deviation between the pixels (SD), it is better in terms of calculation of the Contrast / Noise ratio (CNR). And is much faster than the wavelet technique. The results of the proposed model are encouraging, and the chosen method is ready to be used in the improvement of images of mammary tissue displacements in ultrasound elastography.
Article Info
Article Type
Research ArticlePublication history
Received: Thu 16, May 2019Accepted: Wed 03, Jul 2019
Published: Fri 19, Jul 2019
Copyright
© 2023 Taher Slimi. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Hosting by Science Repository.DOI: 10.31487/j.RDI.2019.03.07