Presentation
17 March 2020 Improving B-mode target size estimation using DNN Beamforming (Conference Presentation)
Adam C. Luchies, Brett C. Byram
Author Affiliations +
Abstract
B-mode ultrasound displays hyperechoic and hypoechoic targets as larger and smaller, respectively, compared to the true structure. A method to correct for this distortion would enable B-mode to better represent the true structure. For this work, we investigated training DNN beamformers to reduce this B-mode sizing distortion. Aperture domain DNN beamformers were trained using training data generated from simulated anechoic cysts. The DNN beamformers were trained to suppress signals originating from inside the cyst and to preserve signals originating from outside the cyst. The results suggest that DNN beamformers can be trained to reduce B-mode sizing distortions.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Adam C. Luchies and Brett C. Byram "Improving B-mode target size estimation using DNN Beamforming (Conference Presentation)", Proc. SPIE 11319, Medical Imaging 2020: Ultrasonic Imaging and Tomography, 1131906 (17 March 2020); https://doi.org/10.1117/12.2549662
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KEYWORDS
Beam analyzers

Phased arrays

Distortion

Ultrasonography

Optical simulations

Renal calculi

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