## 4 Results
### Phantom Experiment
#### 4.2.2 Experimental Cyst Targets  
The second experimental phantom contains two anechoic cyst targets and a speckle background. The B-mode images of the experimental phantom with cyst targets obtained by different beamformers are shown in Figure 11. It can be observed that anechoic cysts in the CPWC+NSVD image have less noise than with CPWC+SVD. Adaptive weighting methods achieve improved image quality because, in their images, noise is suppressed and the boundaries of cyst targets are more easily detectable. However, the images of adaptive weighting methods show visible dark-region artifacts in the background speckle and the image intensity is reduced, especially in the deep region. With the combination with NSVD, in the near region, all the adaptive weighting methods provide reduced dark-region artifacts in the speckle and obtain brighter background speckle. For the deep region, dark-region artifacts become worse in images of adaptive weighting methods with NSVD (\(\beta=2\)). However, when \(\beta=3\), the artifacts in the deep region are reduced and the speckle pattern in the near region is still well-preserved.  
Figure 12 presents the lateral profiles of the two experimental cysts. It is also observed that CPWC+NSVD has an advantage in terms of noise suppression over CPWC and CPWC+SVD. Figure 13 presents the barplot of CR, CNR, and sSNR in experimental cyst target images. CPWC+NSVD outperforms CPWC+SVD and CPWC in terms of CR, and CNR. Compared to CPWC, CPWC+NSVD (\(\beta=3\)) achieves CR improvements of 3.24 dB/2.77 dB (15.3%/42%), and CNR improvements of 0.05/0.16 (3%/17.8%). For CF, by combining with the NSVD filter, CR, CNR, and sSNR achieve improvements of 5.7 dB/7.49 dB (14.2%/43.8%), 0.13/0.19 (10.9%/27.1%), and 0.12/0.12 (10%/14.6%), respectively. For the GCF (\(\beta=3\)), the corresponding improvements are 2.62 dB/4.5 dB (8.1%/37%), 0.16/0.14 (10%/16.5%), and 0.15/0.02 (9.2%/1.7%), while for the SLSC (\(\beta=3\)), the corresponding improvements are 0.66 dB/7.14 dB (1.7%/36.8%), 0.34/0.33 (23.8%/37.9%), and 0.35/0.28 (24.3%/28.6%), respectively. The gCNR improvements in the deep region are more than 0.1 due to the utilization of NSVD. For adaptive weighting methods, NSVD (\(\beta=2\)) and NSVD (\(\beta=3\)) both achieve enhancements of CR, CNR, gCNR, and sSNR. This indicates that adaptive methods can achieve improved image contrast and quality of speckle pattern by combining with the NSVD filter.  
Figure 10: Lateral FWHM in experimental images: (**a**) \(p_{1}(x,z)=(-0.4\) mm, 18 mm), (**b**) average values and standard deviation of all point targets.  
Figure 11: B-mode images of experimental phantom with cyst targets formed by different methods. (**a**) CPWC, (**b**) CPWC+SVD (\(\beta\) = 2), (**c**) CPWC+SVD (\(\beta\) = 3), (**d**) CPWC+NSVD (\(\beta\) = 2), (**e**) CPWC+NSVD (\(\beta\) = 3), (**f**) CF, (**g**) GCF, (**h**) SLSC, (**i**) CF+NSVD (\(\beta\) = 2), (**j**) GCF+NSVD (\(\beta\) = 2), (**k**) SLSC+NSVD (\(\beta\) = 2), (**l**) CF+NSVD (\(\beta\) = 3), (**m**) SCF+NSVD (\(\beta\) = 3), (**n**) SLSC+NSVD (\(\beta\) = 3). The area in the red circle and between the two green circles indicates inside and outside the cyst, respectively, used for calculating CR, CNR, gCNR, and sSNR.  
Figure 12: The lateral profiles of two experimental cysts centered at (**a**) \((x,z)=(0\) mm, 15 mm), (**b**) \((x,z)=(0\) mm, 43 mm).