Optimization of Breast Displacements Estimation in Ultrasound Elastography

Taher Slimi^1*, Ines Marzouk Moussa^2,3, Tarek Kraiem^1,3,4 and Halima Mahjoubi¹

¹University of Tunis El Manar, High Institute of Medical Technologies of Tunis, Laboratory of Biophysics and Medical Technologies, 9th Dr. Zouhair Essafi Street, 1006 Tunis, Tunisia

²University Hospital Center of Monji Slim, Department of Medical Imaging and Radiology, 2046 Marsa, Tunisia

³University of Tunis El Manar, Faculty of Medicine of Tunis, Department of Biophysics, 1007 Rabta, Tunisia

⁴Department of National Radiation Protection Center, Bab Sadoun Children’s Hospital, 1006 Tunisia

*Corresponding Author : Taher Slimi
University of Tunis El Manar, High Institute of Medical Technologies of Tunis, Laboratory of Biophysics and Medical Technologies, 9th Dr. Zouhair Essafi Street, 1006 Tunis, Tunisia
Tel: 00216 22 352 994
E-mail: slimi.taher@hotmail.com

Received: May 19, 2017 Accepted: June 05, 2017 Published: June 10, 2017

Citation: Slimi T, Moussa IM, Kraiem T, Mahjoubi H (2017) Optimization of Breast Displacements Estimation in Ultrasound Elastography. J Diagn Tech Biomed Anal 6:2. doi: 10.4172/2469-5653.1000123

Static ultrasonic breast elastography is a medical imaging technique that produces information related to the elastic properties of breast tissue. However, the image quality in breast elastography is considerably altered by the diffusion of speckle noise in the breast texture leading to disrupt the medical diagnosis. In this perspective, the implementation of a technique for optimizing the tissue displacements estimation is crucial. Therefore, in this paper, we proposed a new method based on the monogenic model, in order to improve the Classical Monogenic Signal (CMS) technique by improving the filtering process, in this context, a filtering step has been applied to the B-mode images and then the filtered B-mode images were integrated into a monogenic model to estimate displacements. Our study was carried out on two models of phantom elasticity sold by the CIRS Company. In vivo 20 B-mode images were also performed corresponding to 20 patients including malignant breast tumors. An accurate and excellent breast tissue displacements estimation image was noted in the results of the proposed technique. Also we noticed the good quality and preservation of the edges tissue. The proposed method provides better values for standard deviation (SD) calculation, greater contrast to noise ratio (CNR), higher peak signal-to-noise ratio (PSNR), excellent structural similarity (SSIM) and much more Fast than CMS and B-Spline (BS). The results of the proposed model are promising and efficient, allowing a rapid estimate. The proposed strategy makes it possible to improve the diagnosis of breast pathologies and helps to establish a more precise and advanced clinical evaluation of the diseases affecting the breast.