Sensorless freehand 3-D ultrasound using regression of the echo intensity

Sensorless volumetric reconstruction of fetal brain freehand ultrasound scans with deep implicit representation

Three-dimensional (3D) ultrasound imaging has contributed to our understanding of fetal developmental processes by providing rich contextual information of the inherently 3D anatomies. However, its use is limited in clinical settings, due to the high purchasing costs and limited diagnostic practicality. Freehand 2D ultrasound imaging, in contrast, is routinely used in standard obstetric exams, but inherently lacks a 3D representation of the anatomies, which limits its potential for more advanced assessment. Such full representations are challenging to recover even with external tracking devices due to internal fetal movement which is independent from the operator-led trajectory of the probe. Capitalizing on the flexibility offered by freehand 2D ultrasound acquisition, we propose ImplicitVol to reconstruct 3D volumes from non-sensor-tracked 2D ultrasound sweeps. Conventionally, reconstructions are performed on a discrete voxel grid. We, however, employ a deep neural network to represent, for the first time, the reconstructed volume as an implicit function. Specifically, ImplicitVol takes a set of 2D images as input, predicts their locations in 3D space, jointly refines the inferred locations, and learns a full volumetric reconstruction. When testing natively-acquired and volume-sampled 2D ultrasound video sequences collected from different manufacturers, the 3D volumes reconstructed by ImplicitVol show significantly better visual and semantic quality than the existing interpolation-based reconstruction approaches. The inherent continuity of implicit representation also enables ImplicitVol to reconstruct the volume to arbitrarily high resolutions. As formulated, ImplicitVol has the potential to integrate seamlessly into the clinical workflow, while providing richer information for diagnosis and evaluation of the developing brain.

Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker

OBJECTIVE

Reconstructing freehand ultrasound in 3D without any external tracker has been a long-standing challenge in ultrasound-assisted procedures. We aim to define new ways of parameterising long-term dependencies, and evaluate the performance.

METHODS

First, long-term dependency is encoded by transformation positions within a frame sequence. This is achieved by combining a sequence model with a multi-transformation prediction. Second, two dependency factors are proposed, anatomical image content and scanning protocol, for contributing towards accurate reconstruction. Each factor is quantified experimentally by reducing respective training variances.

RESULTS

1) The added long-term dependency up to 400 frames at 20 frames per second (fps) indeed improved reconstruction, with an up to 82.4% lowered accumulated error, compared with the baseline performance. The improvement was found to be dependent on sequence length, transformation interval and scanning protocol and, unexpectedly, not on the use of recurrent networks with long-short term modules; 2) Decreasing either anatomical or protocol variance in training led to poorer reconstruction accuracy. Interestingly, greater performance was gained from representative protocol patterns, than from representative anatomical features.

CONCLUSION

The proposed algorithm uses hyperparameter tuning to effectively utilise long-term dependency. The proposed dependency factors are of practical significance in collecting diverse training data, regulating scanning protocols and developing efficient networks.

SIGNIFICANCE

The proposed new methodology with publicly available volunteer data and code for parametersing the long-term dependency, experimentally shown to be valid sources of performance improvement, which could potentially lead to better model development and practical optimisation of the reconstruction application.

Ultrasound Speckle Decorrelation-Based Blood Flow Measurements

Ultrasound imaging is the preferred noninvasive technique to measure blood flow to diagnose cardiovascular disease such as heart failure, carotid stenosis, and renal failure. Conventional ultrasound techniques such as Doppler ultrasound, ultrasound imaging velocimetry, vector Doppler and transverse oscillation beamforming have been used for blood flow velocity profile measurement. However, these techniques were limited to measuring blood flow velocities within the 2-D lateral (across the ultrasound beam) plane of a vessel, and the blood flow velocity profile was derived by assuming that blood vessels have a circular cross-section with axis symmetry. This assumption is incorrect because most vessels have complex geometries, such as tortuosity and branches, and an asymmetric flow profile in the presence of vascular plaque. Consequently, ultrasound speckle decorrelation has been proposed to measure blood flow from transverse views of blood vessels wherein the ultrasound beam is perpendicular to the vessel axis. In this review, we present a summary of recent progress in ultrasound speckle decorrelation-based blood flow measurement techniques.

RecON: Online learning for sensorless freehand 3D ultrasound reconstruction

Sensorless freehand 3D ultrasound (US) reconstruction based on deep networks shows promising advantages, such as large field of view, relatively high resolution, low cost, and ease of use. However, existing methods mainly consider vanilla scan strategies with limited inter-frame variations. These methods thus are degraded on complex but routine scan sequences in clinics. In this context, we propose a novel online learning framework for freehand 3D US reconstruction under complex scan strategies with diverse scanning velocities and poses. First, we devise a motion-weighted training loss in training phase to regularize the scan variation frame-by-frame and better mitigate the negative effects of uneven inter-frame velocity. Second, we effectively drive online learning with local-to-global pseudo supervisions. It mines both the frame-level contextual consistency and the path-level similarity constraint to improve the inter-frame transformation estimation. We explore a global adversarial shape before transferring the latent anatomical prior as supervision. Third, we build a feasible differentiable reconstruction approximation to enable the end-to-end optimization of our online learning. Experimental results illustrate that our freehand 3D US reconstruction framework outperformed current methods on two large, simulated datasets and one real dataset. In addition, we applied the proposed framework to clinical scan videos to further validate its effectiveness and generalizability.

3-D Velocity and Volume Flow Measurement In Vivo Using Speckle Decorrelation and 2-D High-Frame-Rate Contrast-Enhanced Ultrasound

Being able to measure 3-D flow velocity and volumetric flow rate effectively in the cardiovascular system is valuable but remains a significant challenge in both clinical practice and research. Currently, there has not been an effective and practical solution to the measurement of volume flow using ultrasound imaging systems due to challenges in existing 3-D imaging techniques and high system cost. In this study, a new technique for quantifying volumetric flow rate from the cross-sectional imaging plane of the blood vessel was developed by using speckle decorrelation (SDC), 2-D high-frame-rate imaging with a standard 1-D array transducer, microbubble contrast agents, and ultrasound imaging velocimetry (UIV). Through SDC analysis of microbubble signals acquired with a very high frame rate and by using UIV to estimate the two in-plane flow velocity components, the third and out-of-plane velocity component can be obtained over time and integrated to estimate volume flow. The proposed technique was evaluated on a wall-less flow phantom in both steady and pulsatile flow. UIV in the longitudinal direction was conducted as a reference. The influences of frame rate, mechanical index (MI), orientation of imaging plane, and compounding on velocity estimation were also studied. In addition, an in vivo trial on the abdominal aorta of a rabbit was conducted. The results show that the new system can estimate volume flow with an averaged error of 3.65% ± 2.37% at a flow rate of 360 mL/min and a peak velocity of 0.45 m/s, and an error of 5.03% ± 2.73% at a flow rate of 723 mL/min and a peak velocity of 0.8 m/s. The accuracy of the flow velocity and volumetric flow rate estimation directly depend on the imaging frame rate. With a frame rate of 6000 Hz, a velocity up to 0.8 m/s can be correctly estimated. A higher mechanical index (MI = 0.42) is shown to produce greater errors (up to 21.78±0.49%, compared to 3.65±2.37% at MI = 0.19). An in vivo trial, where velocities up to 1 m/s were correctly measured, demonstrated the potential of the technique in clinical applications.

3D freehand ultrasound without external tracking using deep learning

This work aims at creating 3D freehand ultrasound reconstructions from 2D probes with image-based tracking, therefore not requiring expensive or cumbersome external tracking hardware. Existing model-based approaches such as speckle decorrelation only partially capture the underlying complexity of ultrasound image formation, thus producing reconstruction accuracies incompatible with current clinical requirements. Here, we introduce an alternative approach that relies on a statistical analysis rather than physical models, and use a convolutional neural network (CNN) to directly estimate the motion of successive ultrasound frames in an end-to-end fashion. We demonstrate how this technique is related to prior approaches, and derive how to further improve its predictive capabilities by incorporating additional information such as data from inertial measurement units (IMU). This novel method is thoroughly evaluated and analyzed on a dataset of 800 in vivo ultrasound sweeps, yielding unprecedentedly accurate reconstructions with a median normalized drift of 5.2%. Even on long sweeps exceeding 20 cm with complex trajectories, this allows to obtain length measurements with median errors of 3.4%, hence paving the way toward translation into clinical routine.

Registration of 3D freehand ultrasound to a bone model for orthopedic procedures of the forearm

PURPOSE

For guidance of orthopedic surgery, the registration of preoperative images and corresponding surgical plans with the surgical setting can be of great value. Ultrasound (US) is an ideal modality for surgical guidance, as it is non-ionizing, real time, easy to use, and requires minimal (magnetic/radiation) safety limitations. By extracting bone surfaces from 3D freehand US and registering these to preoperative bone models, complementary information from these modalities can be fused and presented in the surgical realm.

METHODS

A partial bone surface is extracted from US using phase symmetry and a factor graph-based approach. This is registered to the detailed 3D bone model, conventionally generated for preoperative planning, based on a proposed multi-initialization and surface-based scheme robust to partial surfaces.

RESULTS

36 forearm US volumes acquired using a tracked US probe were independently registered to a 3D model of the radius, manually extracted from MRI. Given intraoperative time restrictions, a computationally efficient algorithm was determined based on a comparison of different approaches. For all 36 registrations, a mean (± SD) point-to-point surface distance of [Formula: see text] was obtained from manual gold standard US bone annotations (not used during the registration) to the 3D bone model.

CONCLUSIONS

A registration framework based on the bone surface extraction from 3D freehand US and a subsequent fast, automatic surface alignment robust to single-sided view and large false-positive rates from US was shown to achieve registration accuracy feasible for practical orthopedic scenarios and a qualitative outcome indicating good visual image alignment.

Low-cost Volumetric Ultrasound by Augmentation of 2D Systems: Design and Prototype

Conventional two-dimensional (2D) ultrasound imaging is a powerful diagnostic tool in the hands of an experienced user, yet 2D ultrasound remains clinically underutilized and inherently incomplete, with output being very operator dependent. Volumetric ultrasound systems can more fully capture a three-dimensional (3D) region of interest, but current 3D systems require specialized transducers, are prohibitively expensive for many clinical departments, and do not register image orientation with respect to the patient; these systems are designed to provide improved workflow rather than operator independence. This work investigates whether it is possible to add volumetric 3D imaging capability to existing 2D ultrasound systems at minimal cost, providing a practical means of reducing operator dependence in ultrasound. In this paper, we present a low-cost method to make 2D ultrasound systems capable of quality volumetric image acquisition: we present the general system design and image acquisition method, including the use of a probe-mounted orientation sensor, a simple probe fixture prototype, and an offline volume reconstruction technique. We demonstrate initial results of the method, implemented using a Verasonics Vantage research scanner.

Freehand 3-D Ultrasound Imaging: A Systematic Review

Two-dimensional ultrasound (US) imaging has been successfully used in clinical applications as a low-cost, portable and non-invasive image modality for more than three decades. Recent advances in computer science and technology illustrate the promise of the 3-D US modality as a medical imaging technique that is comparable to other prevalent modalities and that overcomes certain drawbacks of 2-D US. This systematic review covers freehand 3-D US imaging between 1970 and 2017, highlighting the current trends in research fields, the research methods, the main limitations, the leading researchers, standard assessment criteria and clinical applications. Freehand 3-D US systems are more prevalent in the academic environment, whereas in clinical applications and industrial research, most studies have focused on 3-D US transducers and improvement of hardware performance. This topic is still an interesting active area for researchers, and there remain many unsolved problems to be addressed.

Handheld real-time volumetric imaging of the spine: technology development

Technical difficulties, poor image quality and reliance on pattern identifications represent some of the drawbacks of two-dimensional ultrasound imaging of spinal bone anatomy. To overcome these limitations, this study sought to develop real-time volumetric imaging of the spine using a portable handheld device. The device measured 19.2 cm × 9.2 cm × 9.0 cm and imaged at 5 MHz centre frequency. 2D imaging under conventional ultrasound and volumetric (3D) imaging in real time was achieved and verified by inspection using a custom spine phantom. Further device performance was assessed and revealed a 75-min battery life and an average frame rate of 17.7 Hz in volumetric imaging mode. The results suggest that real-time volumetric imaging of the spine is a feasible technique for more intuitive visualization of the spine. These results may have important ramifications for a large array of neuraxial procedures.

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.

Improved elevational and azimuthal motion tracking using sector scans

Ultrasound data motion tracking is widely used to estimate relative tissue/transducer motion, for example in freehand 3-D imaging, in which successive 2-D ultrasound scan planes are registered in a 3-D volume. Speckle-tracking and decorrelation-based methods are used to estimate motion in the azimuthal and elevational planes. However, the performance of speckle-tracking is significantly degraded in sectorscan systems because of point-spread function rotation with lateral motion. In this paper, we develop a new method for joint azimuthal¿elevational motion estimation based on the complex correlation of individual IQ-demodulated sector-scan A-lines arising from tissue motion in 3-D space. We show that our method has performance benefits over both speckle-tracking and decorrelation-based tracking for motion estimation in sector-scan systems, particularly when there is both elevational and azimuthal motion. Motion-tracking efficacy is further demonstrated by improved freehand imaging of a known target (anatomically accurate 3-D-printed lumbar spine model) in a tissue-mimicking phantom, with an rms surface distance error of 1.2 mm, compared with 2.43 mm for conventional methods. These data indicate that the new algorithm is capable of improved tracking performance for sector scan systems, enabling effective freehand 3-D scanning.

A freehand ultrasound elastography system with tracking for in vivo applications

Ultrasound transducers are commonly tracked in modern ultrasound navigation/guidance systems. In this article, we demonstrate the advantages of incorporating tracking information into ultrasound elastography for clinical applications. First, we address a common limitation of freehand palpation: speckle decorrelation due to out-of-plane probe motion. We show that by automatically selecting pairs of radio frequency frames with minimal lateral and out-of-plane motions, combined with a fast and robust displacement estimation technique, greatly improves in vivo elastography results. We also use tracking information and image-quality measures to fuse multiple images with similar strains that are taken from roughly the same location so as to obtain a high-quality elastography image. Finally, we show that tracking information can be used to give the user partial control over the rate of compression. Our methods are tested on a tissue-mimicking phantom, and experiments have been conducted on intraoperative data acquired during animal and human experiments involving liver ablation. Our results suggest that in challenging clinical conditions, our proposed method produces reliable strain images and eliminates the need for a manual search through the ultrasound data in order to find radio frequency pairs suitable for elastography.

Measurement selection in untracked freehand 3D ultrasound

In freehand 3D ultrasound, out-of-plane transducer motion can be estimated via speckle decorrelation instead of using a position tracking device. This approach was recently adapted to arbitrary media by predicting elevational decorrelation curves from local image statistics. However, such adaptive models tend to yield biased measurements in the presence of spatially persistent structures. To account for such failures, this paper introduces a new iterative algorithm for probabilistic fusion and selection of correlation measurements. In experiments with imagery of animal tissue, the approach yields significant accuracy improvements over alternatives which do not apply principled measurement selection.

Tracked ultrasound elastography (TrUE)

This paper presents a robust framework for freehand ultrasound elastography to cope with uncertainties of freehand palpation using the information from an external tracker. In order to improve the quality of the elasticity images, the proposed method selects a few image pairs such that in each pair the lateral and out-of-plane motions are minimized. It controls the strain rate by choosing the axial motion to be close to a given optimum value. The tracking data also enables fusing multiple strain images that are taken roughly from the same location. This method can be adopted for various trackers and strain estimation algorithms. In this work, we show the results for two tracking systems of electromagnetic (EM) and optical tracker. Using phantom and ex-vivo animal experiments, we show that the proposed techniques significantly improve the elasticity images and reduce the dependency to the hand motion of user.

Cross-correlation-based image acquisition technique for manually-scanned optical coherence tomography

We present a novel image acquisition technique for Optical Coherence Tomography (OCT) that enables manual lateral scanning. The technique compensates for the variability in lateral scan velocity based on feedback obtained from correlation between consecutive A-scans. Results obtained from phantom samples and biological tissues demonstrate successful assembly of OCT images from manually-scanned datasets despite non-uniform scan velocity and abrupt stops encountered during data acquisition. This technique could enable the acquisition of images during manual OCT needle-guided biopsy or catheter-based imaging, and for assembly of large field-of-view images with hand-held probes during intraoperative in vivo OCT imaging.

Combinatorial and probabilistic fusion of noisy correlation measurements for untracked freehand 3-D ultrasound

In freehand 3-D ultrasound (US), the relative positions of US images are usually measured using a position tracking device despite its cumbersome nature. The probe trajectory can instead be estimated from image data, using registration techniques to recover in-plane motion and speckle decorrelation to recover out-of-plane transformations. The relationship between speckle decorrelation and elevational separation is typically represented by a single curve, estimated from calibration data. Distances read off such a curve are corrupted by bias and uncertainty, and only provide an absolute estimate of elevational displacement. This paper presents a probabilistic model of the relationship between correlation measurements and elevational separation. This representation captures the skewed distribution of distance estimates based on high correlations and the uncertainties attached to each measurement. Multiple redundant correlation measurements can then be integrated within a maximum likelihood estimation framework. This paper also introduces a new method based on the traveling salesman problem for resolving sign ambiguities in data sets resulting from nonmonotonic probe motion and frame intersections. Experiments with real and synthetic US data show that by combining these new methods, out-of-plane US probe motion is recovered with improved accuracy over baseline methods using a deterministic model and fewer measurements.

Freehand 3D ultrasound reconstruction algorithms--a review

Three-dimensional (3D) ultrasound (US) is increasingly being introduced in the clinic, both for diagnostics and image guidance. Although dedicated 3D US probes exist, 3D US can also be acquired with the still frequently used two-dimensional (2D) US probes. Obtaining 3D volumes with 2D US probes is a two-step process. First, a positioning sensor must be attached to the probe; second, a reconstruction of a 3D volume can be performed into a regular voxel grid. Various algorithms have been used for performing 3D reconstruction based on 2D images. Up till now, a complete overview of the algorithms, the way they work and their benefits and drawbacks due to various applications has been missing. The lack of an overview is made clear by confusions about algorithm and group names in the existing literature. This article is a review aimed at explaining and categorizing the various algorithms into groups, according to algorithm implementation. The algorithms are compared based on published data and our own laboratory results. Positive and practical uses of the various algorithms for different applications are discussed, with a focus on image guidance.

Probabilistic speckle decorrelation for 3D ultrasound

Recent developments in freehand 3D ultrasound (US) have shown how image registration and speckle decorrelation methods can be used for 3D reconstruction instead of relying on a tracking device. Estimating elevational separation between untracked US images using speckle decorrelation is error prone due to the uncertainty that plagues the correlation measurements. In this paper, using maximum entropy estimation methods, the uncertainty is directly modeled from the calibration data normally used to estimate an average decorrelation curve. Multiple correlation measurements can then be fused within a maximum likelihood estimation framework in order to reduce the drift in elevational pose estimation over large image sequences. The approach is shown to be effective through empirical results on simulated and phantom US data.

Subsample interpolation strategies for sensorless freehand 3D ultrasound

Freehand 3D ultrasound can be acquired without a position sensor by deducing the elevational probe motion from the interframe speckle decorrelation. However, a freehand scan involves lateral and axial, as well as elevational, probe motion. The lateral sampling is determined by the A-line separation and is relatively sparse: lateral motion tracking therefore requires subsample interpolation. In this paper, we investigate the resilience of lateral interpolation techniques to simultaneous lateral and elevational probe motion. We propose a novel interpolation strategy and, through a series of in vitro experiments, compare its performance with that of established alternatives. The new technique is shown to be superior, limiting interpolation errors to around 5% of the length of the freehand reconstruction.

Sensorless freehand 3D ultrasound in real tissue: Speckle decorrelation without fully developed speckle

It has previously been demonstrated that freehand 3D ultrasound can be acquired without a position sensor by measuring the elevational speckle decorrelation from frame to frame. However, this requires that the B-scans contain significant amounts of fully developed speckle. In this paper, we show that this condition is rarely satisfied in scans of real tissue, which instead exhibit fairly ubiquitous coherent scattering. By examining the axial and lateral correlation functions, we propose an heuristic technique to quantify the amount of coherency at each point in the B-scans. This leads to an adapted elevational decorrelation scheme which allows for the coherent scattering. Using the adapted scheme, we demonstrate markedly improved reconstructions of animal tissue in vitro.

Modeling ultrasound imaging as a linear, shift-variant system

We solve the equation that governs acoustic wave propagation in an inhomogeneous medium to show that the radio-frequency (RF) ultrasound signal can be expressed as the result of filtering the scatterer field with a point-spread function. We extend the analysis to make the link between the RF ultrasound signal and the representation of ultrasound scatterers as vectors with small magnitude and random phase in the complex plane. Others have previously performed parts of this analysis. The contribution of the present paper is to provide a single, coherent treatment emphasizing the assumptions that have to be made and the physical consequences of the models derived. This leads to insights into the interaction of monopole and dipole scattering, useful techniques for simulating and analyzing speckle statistics in the complex plane and a new expression for the normalized covariance of the analytic RF ultrasound signal in terms of the complex envelope of the point-spread function.

Speckle classification for sensorless freehand 3-D ultrasound

Despite being a valuable tool for volume measurement and the analysis of complex geometry, the need for an external position sensor is holding up the clinical exploitation of freehand 3-D ultrasound. Some sensorless systems have been developed, using speckle decorrelation for out-of-plane distance estimation, but their accuracy is still not as good as that of sensor-based systems. Here, we examine the widely held belief that accuracy can be improved by limiting the distance measurements to patches of ultrasound data containing fully developed speckle. Without speckle detection, we observe that scan separation is systematically underestimated by 33.1% in biological tissue. We describe a number of speckle detectors and show that they reduce the underestimate to about 25%. We conclude that speckle classification can improve the quality of distance estimation, but not sufficiently to achieve accurate, metric reconstruction of the insonified volume.

A review of calibration techniques for freehand 3-D ultrasound systems

Three-dimensional (3-D) ultrasound (US) is an emerging new technology with numerous clinical applications. Ultrasound probe calibration is an obligatory step to build 3-D volumes from 2-D images acquired in a freehand US system. The role of calibration is to find the mathematical transformation that converts the 2-D coordinates of pixels in the US image into 3-D coordinates in the frame of reference of a position sensor attached to the US probe. This article is a comprehensive review of what has been published in the field of US probe calibration for 3-D US. The article covers the topics of tracking technologies, US image acquisition, phantom design, speed of sound issues, feature extraction, least-squares minimization, temporal calibration, calibration evaluation techniques and phantom comparisons. The calibration phantoms and methods have also been classified in tables to give a better overview of the existing methods.

Processing and visualizing three-dimensional ultrasound data

This paper describes techniques for the visualization and processing of three-dimensional (3D) ultrasound data. The nature of such data demands specialized algorithms, which differ from those employed for other medical imaging modalities. In this paper, the emphasis is placed on generic processing techniques, which are relevant across a wide range of 3D ultrasound application domains.

A review of calibration techniques for freehand 3-D ultrasound systems

Three-dimensional (3-D) ultrasound (US) is an emerging new technology with numerous clinical applications. Ultrasound probe calibration is an obligatory step to build 3-D volumes from 2-D images acquired in a freehand US system. The role of calibration is to find the mathematical transformation that converts the 2-D coordinates of pixels in the US image into 3-D coordinates in the frame of reference of a position sensor attached to the US probe. This article is a comprehensive review of what has been published in the field of US probe calibration for 3-D US. The article covers the topics of tracking technologies, US image acquisition, phantom design, speed of sound issues, feature extraction, least-squares minimization, temporal calibration, calibration evaluation techniques and phantom comparisons. The calibration phantoms and methods have also been classified in tables to give a better overview of the existing methods.

Development of a portable 3D ultrasound imaging system for musculoskeletal tissues

3D ultrasound is a promising imaging modality for clinical diagnosis and treatment monitoring. Its cost is relatively low in comparison with CT and MRI, no intensive training and radiation protection is required for its operation, and its hardware is movable and can potentially be portable. In this study, we developed a portable freehand 3D ultrasound imaging system for the assessment of musculoskeletal body parts. A portable ultrasound scanner was used to obtain real-time B-mode ultrasound images of musculoskeletal tissues and an electromagnetic spatial sensor was fixed on the ultrasound probe to acquire the position and orientation of the images. The images were digitized with a video digitization device and displayed with its orientation and position synchronized in real-time with the data obtained by the spatial sensor. A program was developed for volume reconstruction, visualization, segmentation and measurement using Visual C++ and Visualization toolkits (VTK) software. A 2D Gaussian filter and a Median filter were implemented to improve the quality of the B-scan images collected by the portable ultrasound scanner. An improved distance-weighted grid-mapping algorithm was proposed for volume reconstruction. Temporal calibrations were conducted to correct the delay between the collections of images and spatial data. Spatial calibrations were performed using a cross-wire phantom. The system accuracy was validated by one cylinder and two cuboid phantoms made of silicone. The average errors for distance measurement in three orthogonal directions in comparison with micrometer measurement were 0.06+/-0.39, -0.27+/-0.27, and 0.33+/-0.39 mm, respectively. The average error for volume measurement was -0.18%+/-5.44% for the three phantoms. The system has been successfully used to obtain the volume images of a fetus phantom, the fingers and forearms of human subjects. For a typical volume with 126 x 103 x 109 voxels, the 3D image could be reconstructed from 258 B-scans (640 x 480 pixels) within one minute using a portable PC with Pentium IV 2.4 GHz CPU and 512 MB memories. It is believed that such a portable volume imaging system will have many applications in the assessment of musculoskeletal tissues because of its easy accessibility.

Tissue Doppler gated (TDOG) dynamic three-dimensional ultrasound imaging of the fetal heart

Dynamic three-dimensional (3D) ultrasound imaging of the fetal heart is difficult due to the absence of an electrocardiogram (ECG) signal for synchronization between loops. In this study we introduce tissue Doppler gating (TDOG), a technique in which tissue Doppler data are used to calculate a gating signal. We have applied this cardiac gating method to dynamic 3D reconstructions of the heart of eight fetuses aged 20-24 weeks. The gating signal was derived from the amplitude and frequency contents of the tissue Doppler signal. We used this signal as a replacement for ECG in a 3D-volume reconstruction and visualization, utilizing techniques established in ECG-gated 3D echocardiography. The reliability of the TDOG signal for fetal cardiac cycle detection was experimentally investigated. Simultaneous recordings of tissue Doppler of the heart and continuous wave (CW) spectral Doppler of the umbilical artery (UA) were performed using two independent ultrasound systems, and the TDOG signal from one system was compared to the Doppler spectrum data from the other system. Each recording consisted of a two-dimensional (2D) sector scan, transabdominally and slowly tilted by the operator, covering the fetal heart over approximately 40 cardiac cycles. The total angle of the sweep was estimated by recording a separate loop through the center of the heart, in the elevation direction of the sweep.3D reconstruction and visualization were performed with the EchoPAC-3D software (GE Medical Systems). The 3D data were visualized by showing simultaneous cineloops of three 2D slices, as well as by volume projections running in cineloop. Synchronization of B-mode cineloops with the TDOG signal proved to be sufficiently accurate for reconstruction of high-quality dynamic 3D data. We show one example of a B-mode recording with a frame rate of 96 frames/s over 20 seconds. The reconstruction consists of 31 volumes, each with 49 tilted frames. With the fetal heart positioned 5-8 cm from the transducer, the sampling distances were approximately 0.15 mm in the beam direction, 0.33 degrees approximately 0.37 mm azimuth and 0.45 degrees approximately 0.51 mm elevation. From this single dataset we were able to generate a complete set of classical 2D views (such as four-chamber, three-vessel and short-axis views as well as those of the ascending aorta, aortic and ductal arches and inferior and superior venae cavae) with high image quality adequate for clinical use.