Restoration of ultrasonic images using non-linear system identification and deconvolution (regular paper)

Restoration of ultrasonic images using non-linear system identification and deconvolution (regular paper). Hourani, M., Basarab, A., Kouamé, D., Girault, J., & Tourneret, J. In IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2018), Washington, 04/04/2018-07/04/2018, pages 1166–1169, http://www.ieee.org/, April, 2018. IEEE : Institute of Electrical and Electronics Engineers.

Paper abstract bibtex

This paper studies a new ultrasound image restoration method based on a non-linear forward model. A Hammerstein polynomial-based non-linear image formation model is considered to identify the system impulse response in baseband and around the second harmonic. The identification process is followed by a joint deconvolution technique minimizing an appropriate cost function. This cost function is constructed from two data fidelity terms exploiting the linear and non-linear model components, penalized by an additive-norm regularization enforcing sparsity of the solution. An alternating optimization approach is considered to minimize the penalized cost function, allowing the tissue reflectivity function to be estimated. Results on synthetic ultrasound images are finally presented to evaluate the algorithm performance.

@InProceedings{ Ho2018.3,
author = {Hourani, Mohamad and Basarab, Adrian and Kouam\'e, Denis and Girault, Jean-Marc and Tourneret, Jean-Yves},
title = "{Restoration of ultrasonic images using non-linear system identification and deconvolution (regular paper)}",
booktitle = "{IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2018), Washington, 04/04/2018-07/04/2018}",
year = {2018},
month = {April},
publisher = {IEEE : Institute of Electrical and Electronics Engineers},
address = {http://www.ieee.org/},
pages = {1166--1169},
language = {anglais},
URL = {https://doi.org/10.1109/ISBI.2018.8363778 - https://oatao.univ-toulouse.fr/24698/},
abstract = {This paper studies a new ultrasound image restoration method based on a non-linear forward model. A Hammerstein polynomial-based non-linear image formation model is considered to identify the system impulse response in
baseband and around the second harmonic. The identification process is followed by a joint deconvolution technique minimizing an appropriate cost function. This cost function is constructed from two data fidelity terms exploiting
the linear and non-linear model components, penalized by an additive-norm regularization enforcing sparsity of the solution. An alternating optimization approach is considered to minimize the penalized cost function, allowing the
tissue reflectivity function to be estimated. Results on synthetic ultrasound images are finally presented to evaluate the algorithm performance.}
}

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