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17 March 2020 Improving B-mode target size estimation using DNN Beamforming (Conference Presentation)
Adam C. Luchies, Brett C. Byram
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Proceedings Volume 11319, Medical Imaging 2020: Ultrasonic Imaging and Tomography; 1131906 (2020) https://doi.org/10.1117/12.2549662
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States
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.
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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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