Journal of Biomedical and Sustainable Healthcare Applications


Empirical Assessment of Ultrasound Model Based Reconstructive Elasticity Imaging



Journal of Biomedical and Sustainable Healthcare Applications

Received On : 12 April 2021

Revised On : 15 September 2021

Accepted On : 30 October 2021

Published On : 05 July 2022

Volume 02, Issue 02

Pages : 113-123


Abstract


In order to rebuild the spatial distribution of Young's modulus, Elasticity Imaging (EI) employs state-of-the-art imaging technology to quantify the displacement of tissues in response to mechanical stimulation. In this paper, we provide a method for ultrasonic EI that makes use of the Model-Based Reconstruction (MBR) approach to Young's modulus reconstruction. Since the object being imaged has an unusual shape, only the longitudinal element of the strain matrix is employed. The technique is particularly successful in its numerical implementation since it uses an analytic solution to the Elasticity Reconstruction (ER) problem. The categorization of liver hemangiomas and the staging of Deep Venous Thrombosis (DVT) are two potential clinical applications of the model-based approach. In sum, these researches show that model-based prosthetic EI may be useful provided both the item's shape and its neighboring cells are understood, and when specific assertions about the pathologies could be established.


Keywords


Elasticity Imaging (EI), Elasticity Reconstruction (ER), Model-Based Reconstruction (MBR), Deep Venous Thrombi.


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Acknowledgements


We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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No funding was received to assist with the preparation of this manuscript.


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Cite this article


Mashsa Abassi, “Empirical Assessment of Ultrasound Model Based Reconstructive Elasticity Imaging”, Journal of Biomedical and Sustainable Healthcare Applications, vol.2, no.2, pp. 113-123, July 2022. doi: 10.53759/0088/JBSHA202202013.


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© 2022 Mashsa Abassi. 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.