COVID-19 feature detection with deep neural networks trained on simulated lung ultrasound B-mode images
Deep learning has been implemented to detect COVID-19 features in lung ultrasound B-
mode images. However, previous work primarily relied on in vivo images as the training …
mode images. However, previous work primarily relied on in vivo images as the training …
Detection of COVID-19 features in lung ultrasound images using deep neural networks
Abstract Background Deep neural networks (DNNs) to detect COVID-19 features in lung
ultrasound B-mode images have primarily relied on either in vivo or simulated images as …
ultrasound B-mode images have primarily relied on either in vivo or simulated images as …
A Convolutional Neural Network for Ultrasound Plane Wave Image Segmentation With a Small Amount of Phase Array Channel Data
F Zhang, L Luo, Y Zhang, X Gao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Single-angle plane wave has a huge potential in ultrasound high frame rate imaging, which,
however, has a number of difficulties, such as low imaging quality and poor segmentation …
however, has a number of difficulties, such as low imaging quality and poor segmentation …
Improving the quality of monostatic synthetic-aperture ultrasound imaging through deep-learning-based beamforming
E Toffali, E Spairani, A Ramalli… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
In synthetic aperture (SA) ultrasound imaging, either monostatic or multistatic approaches
can be employed. In both cases, in transmission, a single element of the transducer array is …
can be employed. In both cases, in transmission, a single element of the transducer array is …
Ultrasound Image Beamforming Optimization Using a Generative Adversarial Network
Recently, research has been focusing on the development of artificial intelligence
ultrasound beamforming methods to improve the contrast and resolution of B-mode images …
ultrasound beamforming methods to improve the contrast and resolution of B-mode images …