Ultrasound DAM Filtering for Clutter Suppression

The patent divides the aperture into two complementary subsets (odd and even apertures) and processes them separately through parallel beamforming paths. This segmentation allows the system to avoid complex per-channel data access by processing subset sums independently, resolving the contradiction between achieving good image contrast and simplifying hardware implementation.

The patent creates a simplified copy of the beamforming process that operates on pre-summed subset data rather than requiring access to individual channel data. This copying approach maintains the essential functionality of adaptive weighting while dramatically reducing hardware complexity by working with aggregated subset sums instead of raw channel data.

The patent performs preliminary beamforming to compute the odd and even aperture subset sums before the adaptive weighting stage. This preliminary action prepares the data in advance, allowing the subsequent clutter suppression to operate on pre-computed values rather than requiring real-time access to individual channel data, thereby reducing computational load while maintaining suppression effectiveness.

The patent introduces odd and even aperture subset sums as intermediary variables that mediate between the raw channel data and the final adaptive weighting computation. These intermediaries aggregate channel information in advance, serving as a bridge that reduces the computational burden of the subsequent weighting operations while preserving the necessary information for effective clutter suppression.

The patent extracts and eliminates the need for complex image processing steps such as cross-correlation, thresholding, and spatial smoothing by directly incorporating the aperture subset selection and median computation into the beamforming process itself. This extraction removes unnecessary processing stages, achieving effective clutter filtering while significantly reducing processing time.

The patent converts what would traditionally be harmful complex processing requirements into a beneficial simplified workflow by using the complementary aperture subset structure to naturally suppress clutter through the median operation. The complexity that would normally be needed for clutter filtering is transformed into a straightforward subset-based approach that achieves filtering without time-consuming post-processing steps.