Elastic-net based beamforming in medical ultrasound imaging
Teodora Szasz, Adrian Basarab, Mircea-Florin Vaida, Denis Kouamé
Abstract
Teodora Szasz, Adrian Basarab, Mircea-Florin Vaida, Denis Kouamé
Abstract
This paper presents a new way of addressing beamforming in ultrasound imaging, by formulating it, for each image depth, as an inverse problem solved using elastic-net regularization. This approach was evaluated on both simulated and in vivo data showing a gain in contrast, while maintaining an increased value of the signal-to-noise ratio compared to two standard ultrasound beamforming methods.
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This paper presents a new way of addressing beamforming in ultrasound imaging, by formulating it, for each image depth, as an inverse problem solved using elastic-net regularization. This approach was evaluated on both simulated and in vivo data showing a gain in contrast, while maintaining an increased value of the signal-to-noise ratio compared to two standard ultrasound beamforming methods.
Key concepts: Beamforming, Ultrasound imaging, Ultrasound, Regularization (linguistics), Elastic net regularization, Medical ultrasound, Computer science, Signal-to-noise ratio (imaging)