Region-Adaptive Null Subtraction Imaging Using Generalized Coherence Factor for Coherent Plane Wave Compounding

Abstract

Coherent plane wave compounding (CPWC) is a widely used technique for ultrafast ultrasound imaging. However, the unfocused beams limit its image quality. The null subtraction imaging (NSI) has been proposed to improve its image quality. However, the image’s contrast, resolution, and speckle quality depend on the variable DC offset parameter. Since NSI employs a fixed offset in a single image, a trade-off arises among these three aspects. To address this issue, a region-adaptive NSI (raNSI) is proposed in this work. In raNSI, a modified generalized coherence factor (GCF) is used to identify different regions within an image. raNSI then applies different offset to points in the identified different regions. The neighborhood statistics-based cleaning (NSBC) algorithm is applied to eliminate unexpected outliers in the selected offsets. The effectiveness of raNSI is demonstrated through simulated, experimental and in vivo datasets. The phantom experimental results show that comparing with NSI with an offset of 1, the contrast ratio (CR), speckle signal-to-noise ratio (sSNR) and contrast-to-noise ratio (gCNR) of the proposed raNSI are improved by 57.94 dB, 0.19 and 0.0327, respectively, while passing the Kolmogorov-Smirnov test—confirming that its speckle pattern remains intact. Furthermore, the lateral resolution is enhanced by 6.9%. It indicates that raNSI can achieve high resolution and high contrast while preserving the speckle pattern well. In addition, raNSI has shown the potential to reduce the number of required plane waves by a factor of five.