Clipping removal in synthetic aperture ultrasound systems

Clipping of the raw data in ultrasound imaging can significantly impact image quality and diagnostic accuracy. This study introduces a postprocessing technique designed to eliminate clipping in ultrasound scans acquired using synthetic aperture imaging. This study hypothesizes that image performance can be improved by applying this clipping removal algorithm to clipped scans. This algorithm identifies the clipped received signals and removes their contribution to the pixel value. By excluding clipped signals for each pixel, clipping can be removed while preserving the information carried out by non-clipped signals. To test this hypothesis, a phantom and a rat brain ultrasound scan were used. The analysis revealed a trade-off between resolution, contrast, and clipping. Additionaly, an increase in the effective dynamic range of the image when removing the clipping artifact was demonstrated.