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SAMIR: Sparsity Amplified Iteratively-reweighted Beamforming for High-rsolution Ultrasound Imaging

Mahurkar, AG and Kumar Pokala, P and Singh Thakur, C and Sekhar Seelamantula, C (2019) SAMIR: Sparsity Amplified Iteratively-reweighted Beamforming for High-rsolution Ultrasound Imaging. In: 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019, 12 - 17 May 2019, Brighton, pp. 1045-1049.

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Official URL: https://doi.org/10.1109/ICASSP.2019.8682675

Abstract

In ultrasound imaging, one typically employs delay-and-sum (DAS) beamformers for image reconstruction. An apodization window is used to suppress the side-lobes of an array beam pattern. The application of an apodization window to suppress the side-lobes widens the main-lobe width. We consider a statistical beamformer and present two variants. The signal of interest is modeled as a Laplacian-distributed random variable and additive interference components as Gaussian distributed. The resultant LASSO formulation is known to suffer from underestimation of large signal amplitudes due to the \ell -1-norm regularization. In the first variant, we reformulate the LASSO problem with a minimax-concave penalty (called Sparsity AMplified (SAM)) to contain the bias, thereby enhancing the beamformed image. A closed-form pointwise estimator is obtained for the optimization problem. In the second variant, we propose Sparsity A Mplified Iteratively-Reweighted (SAMIR) beamforming algorithm, which leverages the properties of an apodization function. In SAMIR beamforming, we jointly optimize the cost over the signal of interest and the exmnsic apodization weights. This beamformer results in high-resolution ultrasound images, especially in the lateral direction. The proposed methods are compared with the standard DAS and a recently proposed statistically-modeled beamformer, iMAP, for a different number of plane-wave insonifications. © 2019 IEEE.

Item Type: Conference Paper
Publication: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords: Audio signal processing; Image enhancement; Image reconstruction; Iterative methods; Optimization; Regression analysis; Speech communication; Ultrasonic imaging, Additive interference; Apodization function; Beamforming algorithms; Distributed random variables; High resolution ultrasound; non-convex penalty; Optimization problems; Ultrasound imaging, Beamforming
Department/Centre: Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Date Deposited: 15 Dec 2022 08:15
Last Modified: 15 Dec 2022 08:15
URI: https://eprints.iisc.ac.in/id/eprint/78383

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