The effect of different cross-correlation methods on the dual apodization with cross-correlation algorithm

We have recently presented a new method to suppress side lobes and clutter in ultrasound imaging called dual apodization with cross-correlation or DAX. This method uses two apodization functions in receive mode which yield point spread functions with very similar main lobes but different side lobes and clutter. These similarities and differences are quantified by using normalized cross-correlation of the radio frequency (RF) data in the axial direction. These cross-correlation coefficients serve as a pixel-by-pixel weighting or filter to pass main lobe dominated signals and suppress clutter dominated signals. In this paper, we investigate the effect of different cross-correlation methods and cross-correlation segment size on contrast-to-noise ratio (CNR) using the DAX algorithm. When using 1-D axial cross-correlation, an axial segment size of 1.73 mm gave us the highest CNR with 125% improvement. Using 1-D lateral cross-correlation showed a 91% improvement in CNR with a segment size of 1.05 mm. 2-D cross-correlation showed a 145% improvement with segment size of 1.2 mm axially by 0.45 mm laterally. A simulation using a cylindrical 1.5 mm diameter anechoic cyst located at 30 mm depth embedded in a 3-D phantom of scatterers gave us a CNR improvement of 52% with 2-D cross-correlation. Lastly, using an excised sheep heart, DAX was able to improve CNR by at least 77%.