Spatial compression in ultrasound imaging

Abstract

High quality three dimensional ultrasound imaging is typically attained by increasing the amount of sensors, resulting in complex hardware. Compressing measurements before sensing addresses this problem, and could enable new clinical applications. We have developed an analogue compression technique, by positioning a plastic coding mask in front of the aperture, which distorts the ultrasound field by inducing varying local echo delays. This results in a compression of the spatial ultrasound field across the sensor surface, while retaining sufficient information for 3D imaging. Using only a single sensor, complementary measurements can be obtained by rotation of the sensor and the mask to increase the conditioning of the reconstruction problem. In this work, we study a method to optimize the shape of the coding mask. To this end, we define an approximate signal model that captures the ultrasound response of the mask, and use it to pose mask shape optimization as a sensor selection problem. We solve it by relaxing it to a convex problem, as well as by using a greedy selection method. Our simulation results show that these approaches are able to outperform the random design strategy, in particular when mask rotations are included in the problem.

Joint Optimization of Coding Mask and Scan Positions for Compressive Single Sensor Imaging

“…To find a good mask, we want to select one such virtual sensor (or mask thickness level) per channel. In our previous works [11], [12], [20] we show that the final measurement matrix then becomes a summation of matrices:…”

“…Algorithm 1 Greedy position selection algorithm If the sensing positions v are known, we use the mask optimization algorithm we proposed in [20]. To summarize our previous work, the mask surface is first discretized into many small patches, such that the entire mask geometry is known if the mask thickness in each patch is known (we refer to a patch as a 'channel').…”

Coding Mask Design for Single Sensor Ultrasound Imaging

“…In [34], we made a first attempt at mask optimization. There, we proposed a model similar to the one in this work, but using a different convex relaxation, utilizing 1 -reweighting [35].…”