Accumulated Angle Factor-Based Beamforming to Improve the Visualization of Spinal Structures in Ultrasound Images

Improvement of 3-D Ultrasound Spine Imaging Technique Using Fast Reconstruction Algorithm

Three-dimensional (3-D) freehand ultrasound (US) imaging has been applied to the investigation of spine deformity. However, it is a challenge for the current 3-D imaging reconstruction algorithms to achieve a balance between image quality and computation time. The objectives of this article are to implement a new fast reconstruction algorithm that can fulfill the request of immediate demonstration and processing for high-quality 3-D spine imaging, and to evaluate the reliability and accuracy of scoliotic curvature measurement when using the algorithm. The fast dot-projection (FDP) algorithm was applied for voxel-based nearest neighbor (VNN), multiple plane interpolation (MPI), and pixel nearest neighbor (PNN) protocols to reduce the reconstruction time. The 3-D image volume was reconstructed from the datasets acquired from scoliotic subjects. The computational cost, image characteristics, and statistical analyses of curve measurements were compared and evaluated among different reconstruction protocols. The results illustrated that the 3-D spine images using the FDP-MPI4 algorithm showed higher brightness (20%), contrast (14%), and signal-to-noise ratio (SNR) (26%) than FDP-VNN. The measurement performed by trainee rater exhibited significant improvement in measurement reliability and accuracy using FDP-MPI4 in comparison with FDP-VNN ( ), and the intraclass correlation coefficient (ICC) of interrater measurement increased from 0.88 to 0.96. The FDP-PNN method could acquire and reconstruct spine images simultaneously and present the results in 1-2 min, which showed the potential to provide the approximate real-time visualization for fast screening.

An adaptive imaging method for ultrasound coherent plane-wave compounding based on the subarray zero-cross factor

Coherent plane-wave compounding (CPWC) has the ability to generate high quality image using the backscattered signals from plane wave emitting at different steer angles. To improve the image quality of CPWC, adaptive weighting techniques have been introduced in the compounding procedure. This paper proposes subarray zeros-cross factor (SZF) for CPWC, and it is used as an adaptive weighting factor to improve image quality. The SZF is calculated based on polarity of plane-wave imaging results with adjacent steering angle to estimate the coherence of plane wave emitting events. It is effective to suppress noise and maintain background speckle pattern. Simulations and experiments were conducted to evaluate the performance of the proposed method. Results demonstrate that the SZF can achieve better performance on contrast ratio (CR) and resolution than traditional CPWC. For simulated cysts, a maximal CR improvement of 125.4% is achieved. For experimental cysts, the maximal CR improvement is 197.9%. Compared with coherence factor (CF) and generalized coherence factor (GCF), SZF can obtain improvements in contrast-to-noise ratio and speckle signal-to-noise ratio at near field and increase CR at far field. In addition, when subarray length L is in the range of [10,12], SZF can obtain satisfying comprehensive performance.

Scoliotic Imaging With a Novel Double-Sweep 2.5-Dimensional Extended Field-of-View Ultrasound

Extended field-of-view ultrasound (US EFOV) imaging is a technique used extensively in the clinical field to attain interpretable panorama of anatomy; 2.5-D US EFOV has recently been proposed for spine imaging. In the original 2.5-D US EFOV, it makes use of a six degrees-of-freedom positional sensor attached to the US probe to record the corresponding position of each B-scan. By combining the positional information and the B-scan images, the 2.5-D EFOV can reconstruct a panorama on a curved image plane when the scanning trajectory of the US probe is curved. In this paper, an improved method based on the Bezier interpolation is proposed to better reconstruct 2.5-D US EFOV imaging, producing the panoramas with smoother texture and higher quality. To make it more applicable for scoliosis patients, we designed a novel method called double-sweep 2.5-D EFOV to better image the spinal tissues and easily compute the Cobb angle. In vitro and in vivo experiments demonstrated that the 2.5-D EFOV images obtained by the proposed method can present anatomical structures of the scanning region accurately.

Region-of-Interest-Based Closed-Loop Beamforming for Spinal Ultrasound Imaging

Clear visualization of spine structures in ultrasound imaging is difficult due to factors such as specular reflection, off-axis energy, and reverberation artifacts. The received channel data from the spine are often tilted even after delay correction, resulting in signal cancellation during the beamforming process. Conventional beamformers are not designed to tackle this issue. This paper proposes a closed-loop beamforming method which feeds back the location of the spine to the beamforming process so that backscattered bone signals can be aligned prior to the beamforming. To suppress the weak soft tissue and reverberation artifacts and increase the contrast of bones, a tensor-based filtering is employed prior to the cross-correlation-based alignment. Directional filtering is also employed to improve the bone surface detection. Phantom studies show improvement on the sharpness of the spine without shape distortion. In vivo results confirm significant contrast improvement of spinal structures. Compared with the conventional delay-and-sum beamforming, the proposed method improves the contrast ratio (CR) of the spine from 0.56 to 0.96. The 6-dB width of bone surfaces is also reduced by 51%.

In Vivo Measurement of the Human Lumbar Spine Using Magnetic Resonance Imaging to Ultrasound Registration

OBJECTIVE

This study aimed to refine a magnetic resonance imaging (MRI)-ultrasound registration (ie, alignment) technique to make noninvasive, nonionizing, 3-dimensional measurement of the lumbar segmental motion in vivo.

METHODS

Five healthy participants participated in this validation study. We scanned the lumbar region of each participant 5 times using an ultrasound probe while he or she kept a prone lying posture on a plinth. Participant-specific models of L1-L5 were constructed from magnetic resonance (MR) images and aligned with the 3-dimensional ultrasound dataset of each scan using 4 variants of MRI-ultrasound registration approach (simplified intensity-based registration [1] with and [2] without including the transverse processes and their surrounding soft tissues [denoted as TP complex]; and hierarchical intensity-based registration [3] with and [4] without including the TP complex). The robustness and precision of these registration approaches were compared.

RESULTS

Although all registration approaches converged to a similar solution, excluding the TP complex improved the percentage of successful registration from 92% to 100%. There was no significant difference in the precision among the 4 MRI-ultrasound registration variants. For the simplified intensity-based registration without including the TP complex, average precision at each degree of freedom was 1.33° (flexion-extension), 2.48° (lateral bending), 1.32° (axial rotation), 2.15 mm (left/right), 1.08 mm (anterior-posterior), and 1.16 (superior-inferior), respectively.

CONCLUSION

Given that using simplified intensity-based MRI-ultrasound registration can substantially streamline the registration process and excluding the TP complex would improve the robustness of the registration, we conclude that this combination is the method of choice for in vivo human applications.

The Effect of Dynamic Range Alterations in the Estimation of Contrast

Many adaptive beamformers claim to produce images with increased contrast, a feature that could enable a better detection of lesions and anatomical structures. Contrast is often quantified using the contrast ratio (CR) and the contrast-to-noise ratio (CNR). The estimation of CR and CNR can be affected by dynamic range alterations (DRAs), such as those produced by a trivial gray-level transformation. Thus, we can form the hypothesis that contrast improvements from adaptive beamformers can, partly, be due to DRA. In this paper, we confirm this hypothesis. We show evidence on the influence of DRA on the estimation of CR and CNR and on the fact that several methods in the state of the art do alter the DR. To study this phenomenon, we propose a DR test (DRT) to estimate the degree of DRA and we apply it to seven beamforming methods. We show that CR improvements correlate with DRT with [Formula: see text] in simulated data and [Formula: see text] in experiments. We also show that DRA may lead to increased CNR values, under some circumstances. These results suggest that claims on lesion detectability, based on CR and CNR values, should be revised.

An adaptive beamforming method for ultrasound imaging based on the mean-to-standard-deviation factor

The beamforming performance has a large impact on image quality in ultrasound imaging. Previously, several adaptive weighting factors including coherence factor (CF) and generalized coherence factor (GCF) have been proposed to improved image resolution and contrast. In this paper, we propose a new adaptive weighting factor for ultrasound imaging, which is called signal mean-to-standard-deviation factor (SMSF). SMSF is defined as the mean-to-standard-deviation of the aperture data and is used to weight the output of delay-and-sum (DAS) beamformer before image formation. Moreover, we develop a robust SMSF (RSMSF) by extending the SMSF to the spatial frequency domain using an altered spectrum of the aperture data. In addition, a square neighborhood average is applied on the RSMSF to offer a more smoothed square neighborhood RSMSF (SN-RSMSF) value. We compared our methods with DAS, CF, and GCF using simulated and experimental synthetic aperture data sets. The quantitative results show that SMSF results in an 82% lower full width at half-maximum (FWHM) but a 12% lower contrast ratio (CR) compared with CF. Moreover, the SN-RSMSF leads to 15% and 10% improvement, on average, in FWHM and CR compared with GCF while maintaining the speckle quality. This demonstrates that the proposed methods can effectively improve the image resolution and contrast.