Sparse Image Reconstruction for Contrast Enhanced Cardiac Ultrasound using Diverging Waves

Assessing cardiac function with trans-thoracic ultrasound is a challenging task, mainly due to its fast motion and its anatomical position which only allows for a narrow intercostal imaging window. These factors often lead to the use of diverging waves, even when contrast agents are employed. While capable of achieving a very high frames rate, an acquisition with diverging waves from a narrow aperture suffers from serious image quality degradation. In this regard, it is often impossible to mitigate this problem using common processing methods, such as coherent compounding. In this study, we cast the problem of reconstructing the contrast enhanced ultrasound images as regularised inverse problem, analogous to the compressed sensing one, where the sensing matrix is fundamentally described by the delay operator associated with the time of flight. The results show that this framework can improve the Signal to Noise Ratio (SNR) of the image by up to 5.85dB compared to delay and sum (DAS) and is therefore a promising way to reconstruct contrast enhanced cardiac images. The experiments also highlight that the way noise is modelled has a significant impact on the final image quality.