Improvement of freehand ultrasound calibration accuracy using the elevation beamwidth profile

Main Uncertainties in the RF Ultrasound Scanning Simulation of the Standard Ultrasound Phantoms

Ultrasound echoscopy technologies are continuously evolving towards new modalities including quantitative parameter imaging, elastography, 3D scanning, and others. The development and analysis of new methods and algorithms require an adequate digital simulation of radiofrequency (RF) signal transformations. The purpose of this paper is the quantitative evaluation of RF signal simulation uncertainties in resolution and contrast reproduction with the model of a phased array transducer. The method is based on three types of standard physical phantoms. Digital 3D models of those phantoms are composed of point scatterers representing the weak backscattering of the background material and stronger backscattering from inclusions. The simulation results of echoscopy with sector scanning transducer by Field II software are compared with the RF output of the Ultrasonix scanner after scanning standard phantoms with 2.5 MHz phased array. The quantitative comparison of axial, lateral, and elevation resolutions have shown uncertainties from 9 to 22% correspondingly. The echoscopy simulation with two densities of scatterers is compared with contrast phantom imaging on the backscattered RF signals and B-scan reconstructed image, showing that the main sources of uncertainties limiting the echoscopy RF signal simulation adequacy are an insufficient knowledge of the scanner and phantom’s parameters. The attempt made for the quantitative evaluation of simulation uncertainties shows both problems and the potential of echoscopy simulation in imaging technology developments. The analysis presented could be interesting for researchers developing quantitative ultrasound imaging and elastography technologies looking for simulated raw RF signals comparable to those obtained from real ultrasonic scanning.

Active phantoms: a paradigm for ultrasound calibration using phantom feedback

In ultrasound (US)-guided medical procedures, accurate tracking of interventional tools is crucial to patient safety and clinical outcome. This requires a calibration procedure to recover the relationship between the US image and the tracking coordinate system. In literature, calibration has been performed on passive phantoms, which depend on image quality and parameters, such as frequency, depth, and beam-thickness as well as in-plane assumptions. In this work, we introduce an active phantom for US calibration. This phantom actively detects and responds to the US beams transmitted from the imaging probe. This active echo (AE) approach allows identification of the US image midplane independent of image quality. Both target localization and segmentation can be done automatically, minimizing user dependency. The AE phantom is compared with a crosswire phantom in a robotic US setup. An out-of-plane estimation US calibration method is also demonstrated through simulation and experiments to compensate for remaining elevational uncertainty. The results indicate that the AE calibration phantom can have more consistent results across experiments with varying image configurations. Automatic segmentation is also shown to have similar performance to manual segmentation.

A Generalized Correlation-Based Model for Out-of-Plane Motion Estimation in Freehand Ultrasound

A big challenge in sensorless image-based ultrasound tracking is in the out-of-plane motion estimation. The correlation value of a specific model of speckle known as fully developed speckle (FDS) can be used to estimate the out-of-plane displacement. In real tissue, this kind of pattern is rare and the deviation of speckle pattern from the ideal FDS model diminishes the accuracy of the out-of-plane motion estimation. In this paper a new method for estimation of the out-of-plane motion is proposed. Firstly a closed-form mathematical derivation is provided for the correlation of two RF echo signal patches at different positions. A linear regression model of the ultrasound beam profile is proposed to account for the spatial variability of the ultrasound beam and enhance the accuracy of out-of-plane motion estimation in real tissue. The statistical model of speckle used here is based on the Rician-Inverse Gaussian (RiIG) stochastic process of the speckle formation, which can be considered as a generalized form of the K-distribution with richer parametrization. In this work, for the first time the second-order statistics of the RIG model is used for speckle tracking. This statistical model allows for derivation of a closed-form formulation for the correlation coefficient based on the statistical parameters of every patch. Since the effect of coherency is considered in the RiIG model, it increases the reliability of the out-of-plane motion estimation. The flexibility of the proposed method enables almost any patch through the whole image to be used for the purpose of displacement estimation. The method has been evaluated both on ex vivo and in vivo tissues in various experiments including out-of-plane rotation (tilt, yaw) and free-hand imaging. The overall outcome demonstrates the potential of the proposed method for in vivo tissues.