Reconstruction algorithm for improved ultrasound image quality - Madore, Bruno (2012)
A new algorithm is proposed for reconstructing raw RF data into ultrasound images. Prior delay-and-sum beamforming reconstruction algorithms are essentially one-dimensional, as a sum is performed across all receiving elements. In contrast, the present approach is two-dimensional, potentially allowing any time point from any receiving element to contribute to any pixel location. Computer-intensive matrix inversions are performed once-and-for-all ahead of time, to create a reconstruction matrix that can be reused indefinitely for a given probe and imaging geometry. Individual images are generated through a single matrix multiplication with the raw RF data, without any need for separate envelope detection or gridding steps. Raw RF datasets were acquired using a commercially available digital ultrasound engine for three imaging geometries: a 64-element array with a rectangular field-of-view (FOV), the same probe with a sector-shaped FOV, and a 128-element array with rectangular FOV. The acquired data were reconstructed using our proposed method and a delay-and-sum beamforming algorithm, for comparison purposes. Point-spread-function (PSF) measurements from metal wires in a water bath showed the proposed method able to reduce the size of the PSF and/or its spatial integral by about 20 to 38%. Images from a commercially available quality-assurance phantom featured greater spatial resolution and/or contrast when reconstructed with the proposed approach.