Superresolution spatial compounding techniques with application to 3D breast ultrasound imaging

Standard spatial compounding, via averaging acquisitions from different angles, has proved to be an efficient technique for speckle pattern reduction in ultrasound B-mode images. However, the resulting images may be blurred due to the averaging of point spread functions and the misalignment of the different views. These blurring artefacts result in a loss of important anatomical features that may be critical for medical diagnosis. In this paper, we evaluate some spatial compounding techniques, focusing on how to combine the different acquisitions. The evaluated methods are: weighed averaging, wavelet coefficient fusion and multiview deconvolution. To some extent, these techniques take into account the limitations of spatial compounding, by proposing alternative fusion methods that can reduce speckle artefacts while preserving standard spatial resolution and anatomical features. We experimented these compounding methods with synthetic images to show that these advanced techniques could outperform traditional averaging. In particular, multiview deconvolution techniques performed best, showing improvement in respect to averaging (6.81 dB) for realistic levels of speckle noise and spatial degradation. Wavelet fusion technique ranked second (2.25 dB), and weighted average third (0.70 dB). On the other hand, weighted averaging was the least time consuming, followed by wavelet fusion (x2) and multiview deconvolution (x5). Wavelet fusion offered an interesting trade-off between performance and computational cost. Experiments on 3D breast ultrasound imaging, showed consistent results with those obtained on synthetic images. Tissue was linearly scanned with a 2D probe in different directions, and volumes were compounded using the aforementioned techniques. This resulted in a high-resolution volume, with better tissue delineation and less speckle patterning.