title: Performance improvement of Fresnel beamforming using dual apodization with cross-correlation.
abstract: Fresnel beamforming is a beamforming method that has a delay profile with a shape similar to a physical Fresnel lens. With 4 to 8 transmit channels, 2 receive channels, and a network of single-pole/single-throw switches, Fresnel beamforming can reduce the size, cost, and complexity of a beamformer. The performance of Fresnel beamforming is highly dependent on focal errors resulting from phase wraparound and quantization of its delay profile. Previously, we demonstrated that the performance of Fresnel beamforming relative to delayand- sum (DAS) beamforming is comparable for linear arrays at f-number = 2 and 50% bandwidth. However, focal errors for Fresnel beamforming are larger because of larger path length differences between elements, as in the case of curvilinear arrays compared with linear arrays. In this paper, we present the concept and performance evaluation of Fresnel beamforming combined with a novel clutter suppression method called dual apodization with cross-correlation (DAX) for curvilinear arrays. The contrast-to-noise ratios (CNRs) of Fresnel beamforming followed by DAX are highest at f-number = 3. At f-number = 3, the experimental results show that using DAX, the CNR for Fresnel beamforming improves from 3.7 to 10.6, compared with a CNR of 5.2 for DAS beamforming. Spatial resolution is shown to be unaffected by DAX. At f-number = 3, the lateral beamwidth and axial pulse length for Fresnel beamforming with DAX are 1.44 and 1.00 mm larger than those for DAS beamforming (about 14% and 21% larger), respectively. These experimental results are in good agreement with simulation results.
authors.affiliation: University of Southern California, Biomedical Engineering, Los Angeles, CA, USA.
authors.forename: Man M
authors.initials: MM
authors.lastname: Nguyen
authors.forename: Jesse T
authors.initials: JT
authors.lastname: Yen
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003560:Cysts / Q000000981:diagnostic imaging; D006197:Hair / Q000000981:diagnostic imaging; D006801:Humans; D008954:Models, Biological; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D014463:Ultrasonography / Q000379:methods*