High-Quality Plane Wave Compounding using Convolutional Neural Networks

International audience; Single plane wave (PW) imaging produces ultrasound (US) images of poor quality at high frame rates (ultrafast). High-quality PW imaging usually relies on the coherent compounding of several successive steered emissions (typically more than ten), which in turn results in a decreased frame rate. We propose a new strategy to reduce the number of emitted PWs by learning a compounding operation from data, i.e. by training a convolutional neural network (CNN) to reconstruct high quality images using a small number of transmissions. We present experimental evidence that this approach is promising, as we were able to produce high-quality images from only 3 PWs, competing in terms of contrast ratio and lateral resolution with the standard compounding of 31 PWs (10x speed-up factor).