Tissue Reflectivity Function Restoration from Fundamental and Harmonic Ultrasound Images (regular paper). Hourani, M., Basarab, A., Kouamé, D., & Tourneret, J. In Workshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS 2019), Toulouse, 01/07/2019-04/07/2019, pages (on line), http://www.inp-toulouse.fr, 2019. INPT : Institut National Polytechnique de Toulouse.
Tissue Reflectivity Function Restoration from Fundamental and Harmonic Ultrasound Images (regular paper) [link]Paper  abstract   bibtex   
This paper addresses the problem of ultrasound (US) image restoration. In contrast to most of the existing approaches that only take into account fundamental radiofrequency (RF) data, the proposed method also considers harmonic US images. An algorithm based on the alternating direction of multipliers method (ADMM) is proposed to solve the joint deconvolution problem. Simulation results show the interest of the proposed approach when compared to classical US image restoration schemes based only on fundamental data.
@InProceedings{ Ho2019.1,
author = {Hourani, Mohamad and Basarab, Adrian and Kouam\'e, Denis and Tourneret, Jean-Yves},
title = "{Tissue Reflectivity Function Restoration from Fundamental and Harmonic Ultrasound Images (regular paper)}",
booktitle = "{Workshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS 2019), Toulouse, 01/07/2019-04/07/2019}",
year = {2019},
publisher = {INPT : Institut National Polytechnique de Toulouse},
address = {http://www.inp-toulouse.fr},
pages = {(on line)},
language = {anglais},
URL = {https://www.irit.fr/~Adrian.Basarab/img/Spars2019_MH.pdf - https://oatao.univ-toulouse.fr/26242/},
abstract = {This paper addresses the problem of ultrasound (US) image restoration. In contrast to most of the existing approaches that only take into account fundamental radiofrequency (RF) data, the proposed method also considers
harmonic US images. An algorithm based on the alternating direction of multipliers method (ADMM) is proposed to solve the joint deconvolution problem. Simulation results show the interest of the proposed approach when compared to
classical US image restoration schemes based only on fundamental data.}
}

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