Freehand 3D Ultrasound Imaging Research Articles

Freehand 3D Ultrasound Imaging Based on Probe-mounted Vision and IMU System

ObjectivesFreehand three-dimensional (3D) ultrasound (US) is of great significance for clinical diagnosis and treatment, it is often achieved with the aid of external devices (optical and/or electromagnetic, etc.) that monitor the location and orientation of the US probe. However, this external monitoring is often impacted by imaging environment such as optical occlusions and/or electromagnetic (EM) interference. MethodsTo address the above issues, we integrated a binocular camera and an inertial measurement unit (IMU) on a US probe. Subsequently, we built a tight coupling model utilizing the unscented Kalman algorithm based on Lie groups (UKF-LG), combining vision and inertial information to infer the probe's movement, through which the position and orientation of the US image frame are calculated. Finally, the volume data was reconstructed with the voxel-based hole-filling method. ResultsThe experiments including calibration experiments, tracking performance evaluation, phantom scans, and real scenarios scans have been conducted. The results show that the proposed system achieved the accumulated frame position error of 3.78 mm and the orientation error of 0.36° and reconstructed 3D US images with high quality in both phantom and real scenarios. ConclusionsThe proposed method has been demonstrated to enhance the robustness and effectiveness of freehand 3D US. Follow-up research will focus on improving the accuracy and stability of multi-sensor fusion to make the system more practical in clinical environments.

Application of Freehand 3D Ultrasound Guidance in Percutaneous Transluminal Angioplasty for Autogenous Arteriovenous Fistula Stenosis

Objective: Using freehand three dimensional (3D) ultrasound imaging to evaluate arteriovenous fistula stenosis. Comparing the value of freehand 3D ultrasound and Doppler ultrasound in the application of percutaneous transluminal angioplasty (PTA) treatment for stenosis of an arteriovenous fistula. Methods: A retrospective analysis was conducted on 34 patients with arteriovenous fistula (AVF) stenosis who were treated at the 903RD Hospital of PLA and the Kidney Center of Zhejiang Provincial People's Hospital from August 2021 to August 2022. Based on the different types of surgical assistance, the patients were divided into two groups: the Doppler ultrasound group (Group A, n = 17) and the freehand 3D ultrasound imaging group (Group B, n = 17). Freehand 3D ultrasound and Doppler ultrasound were used to assess the narrowing of arteriovenous fistulas, and images and relevant data were collected before and after the PTA procedure. The differences in the time of puncture and sheath placement, guidewire insertion time, the duration of the procedure, complications, and methods to measure stenosis were compared between the two groups of patients, as well as the technical success rate, the initial patency rate, and the primary patency rates at 1, 3, 6 and 9 months post-surgery. This study discusses the clinical efficacy of using these two types of ultrasound to assist in the PTA treatment of arteriovenous fistula stenosis. Results: The differences in baseline demographics between the conventional ultrasound group (Group A) and the 3D ultrasound group (Group B) were not statistically significant (p > 0.05). The intraoperative guidewire insertion time (4.647 ± 1.347 min vs. 2.824 ± 0.326 min) and the operating times (75.941 ± 7.557 min vs. 59.824 ± 8.175 min) between the two groups were statistically significant (t = 2.788, 3.069, p < 0.01). The technical success rates for the two groups were 94.1% vs. 100%, not statistically significant (t = 1.03, p = 0.31). The first-time patency rates were 88.2% vs. 94.1%, with no statistically significant difference (t = 0.366, p = 0.545). No complications occurred in Group A, while one case of hematoma occurred postoperatively in Group B, with an incidence of 5.9% (1/17), which was not statistically significant (t = 1.03, p > 0.05). Comparing the primary patency rates at 1, 3, 6 and 9 months post-surgery between Groups A and B, there were no statistically significant differences (p > 0.05). However, the patency rates at different time points for Group B were consistently higher than Group A (94.1%, 82.4%, 82.4%, 82.4% vs. 88.2%, 82.4%, 76.5%, 76.5%). Conclusion: Freehand 3D ultrasound imaging can provide more intuitive, high-resolution, and high-definition three-dimensional images, clearly defining the lesion site and vascular structures. Its accuracy in assessing complications of arteriovenous fistulas is similar to that with conventional ultrasound. When used as an adjunct to PTA treatment, its efficacy is equivalent. It can significantly reduce guidewire insertion time and operation time, decrease postoperative recovery time, and alleviate the patients' concerns regarding surgical risks. It can be considered a new method for diagnosing, treating, and patients with AVF stenosis.

Development of Automatic Assessment Framework for Spine Deformity Using Freehand 3-D Ultrasound Imaging System.

A 3-D ultrasound (US) imaging technique has been studied to facilitate the diagnosis of spinal deformity without radiation. The objective of this article is to propose an assessment framework to automatically estimate spinal deformity in US spine images. The proposed framework comprises four major components, a US spine image generator, a novel transformer-based lightweight spine detector network, an angle evaluator, and a 3-D modeler. The principal component analysis (PCA) and discriminative scale space tracking (DSST) method are first adopted to generate the US spine images. The proposed detector is equipped with a redundancy queries removal (RQR) module and a regularization item to realize accurate and unique detection of spine images. Two clinical datasets, a total of 273 images from adolescents with idiopathic scoliosis, are used for the investigation of the proposed framework. The curvature is estimated by the angle evaluator, and the 3-D mesh model is established by the parametric modeling technique. The accuracy rate (AR) of the proposed detector can be achieved at 99.5%, with a minimal redundancy rate (RR) of 1.5%. The correlations between automatic curve measurements on US spine images from two datasets and manual measurements on radiographs are 0.91 and 0.88, respectively. The mean absolute difference (MAD) and standard deviation (SD) are 2.72° ± 2.14° and 2.91° ± 2.36° , respectively. The results demonstrate the effectiveness of the proposed framework to advance the application of the 3-D US imaging technique in clinical practice for scoliosis mass screening and monitoring.

Automatic Diagnosis of Carotid Atherosclerosis Using a Portable Freehand 3-D Ultrasound Imaging System.

The objective of this study is to develop a deep-learning-based detection and diagnosis technique for carotid atherosclerosis (CA) using a portable freehand 3-D ultrasound (US) imaging system. A total of 127 3-D carotid artery scans were acquired using a portable 3-D US system, which consisted of a handheld US scanner and an electromagnetic (EM) tracking system. A U-Net segmentation network was first applied to extract the carotid artery on 2-D transverse frame, and then, a novel 3-D reconstruction algorithm using fast dot projection (FDP) method with position regularization was proposed to reconstruct the carotid artery volume. Furthermore, a convolutional neural network (CNN) was used to classify healthy and diseased cases qualitatively. Three-dimensional volume analysis methods, including longitudinal image acquisition and stenosis grade measurement, were developed to obtain the clinical metrics quantitatively. The proposed system achieved a sensitivity of 0.71, a specificity of 0.85, and an accuracy of 0.80 for diagnosis of CA. The automatically measured stenosis grade illustrated a good correlation ( r = 0.76) with the experienced expert measurement. The developed technique based on 3-D US imaging can be applied to the automatic diagnosis of CA. The proposed deep-learning-based technique was specially designed for a portable 3-D freehand US system, which can provide a more convenient CA examination and decrease the dependence on the clinician's experience.

Automatic 3D Lamina Curve Extraction from Freehand 3D Ultrasound Data using Sequential Localization Recurrent Convolutional Networks.

Freehand 3D ultrasound imaging is emerging as a promising modality for regular spine exams due to its non-invasiveness and affordability. The laminae landmarks play a critical role in depicting the 3D shape of the spine. However, the extraction of the 3D lamina curves from transverse ultrasound sequences presents a challenging task, primarily attributed to the presence of diverse contrast variations, imaging artifacts, the complex surface of vertebral bones, and the difficulties associated with probe manipulation. This paper proposes Sequential Localization Recurrent Convolutional Networks (SL-RCN), a novel deep learning model that takes the contextual relationships into account and embeds the transformation matrix feature as a 3D knowledge base to enhance accurate ultrasound sequence analysis. The assessment involved the analysis of 3D ultrasound sequences obtained from 10 healthy adult human participants, covering both the lumbar and thoracic regions. The performance of SL-RCN is evaluated through 7-fold cross-validation, employing the leave-one-participant-out strategy. The validity of the AI model training is assessed on test data from 3 participants. Normalized Discrete Fréchet Distance (NDFD) is employed as the main metric to evaluate the disparity of the extracted 3D lamina curves. In contrast to our previous 2D image analysis method, SL-RCN generates reduced left/right mean distance errors from 1.62/1.63mm to 1.41/1.40mm, and NDFDs from 0.5910/0.6389 to 0.4276/0.4567. The increase in the mean NDFD value from 7-fold cross-validation to the test-data experiment is less than 0.05. The experiments demonstrate the SL-RCN's capability in extracting accurate paired smooth lamina landmark curves.

Investigation of 3D Reconstruction Algorithms For Wireless Freehand Ultrasound Imaging System.

The handheld 3D ultrasound imaging technique based on position tracking systems has been rapidly developed and widely applied in recent decades. The objectives of this study are to investigate the performance and accuracy of different 3D reconstruction algorithms including Voxel Nearest Neighbor (VNN), Pose Optimization Based (POB), and Implicit Representation (IR) methods. The high-precision phantom was used as the validation model to measure 2D/3D distance on the reconstructed image volume, and the measurements were evaluated with the true values obtained by caliber. The results indicated that the IR method presented the best reconstruction visualization and the smallest reconstruction errors for different motion cases. It demonstrated that the neural network-based reconstruction method can improve image quality and reduce reconstruction errors for the wireless freehand 3D ultrasound imaging systems.Clinical Relevance- This study validates the accuracy and precision of the different reconstruction algorithms for freehand 3D ultrasound imaging systems.

Recent Advances in Tracking Devices for Biomedical Ultrasound Imaging Applications.

With the rapid advancement of tracking technologies, the applications of tracking systems in ultrasound imaging have expanded across a wide range of fields. In this review article, we discuss the basic tracking principles, system components, performance analyses, as well as the main sources of error for popular tracking technologies that are utilized in ultrasound imaging. In light of the growing demand for object tracking, this article explores both the potential and challenges associated with different tracking technologies applied to various ultrasound imaging applications, including freehand 3D ultrasound imaging, ultrasound image fusion, ultrasound-guided intervention and treatment. Recent development in tracking technology has led to increased accuracy and intuitiveness of ultrasound imaging and navigation with less reliance on operator skills, thereby benefiting the medical diagnosis and treatment. Although commercially available tracking systems are capable of achieving sub-millimeter resolution for positional tracking and sub-degree resolution for orientational tracking, such systems are subject to a number of disadvantages, including high costs and time-consuming calibration procedures. While some emerging tracking technologies are still in the research stage, their potentials have been demonstrated in terms of the compactness, light weight, and easy integration with existing standard or portable ultrasound machines.

A real‐time freehand 3D ultrasound imaging method for scoliosis assessment

Real‐time 3D ultrasound has gained popularity in many fields because it can provide interactive feedback to help acquire high‐quality images or to conduct timely diagnosis. However, no comprehensive study has been reported on such an imaging method for scoliosis evaluation due to the complexity of this application. Meanwhile, the use of radiation‐free assessment of scoliosis is becoming increasingly popular. This study developed a real‐time 3D ultrasound imaging method for scoliosis assessment based on an incremental imaging method. In vivo experiments involving 36 patients with scoliosis were performed to test the performance of the proposed method. This new imaging method achieved a mean incremental frame rate of 82.7 ± 11.0 frames/s. The high repeatability of the intra‐operator test (intraclass correlation coefficient [ICC] = 0.92) and inter‐operator test (ICC = 0.91) demonstrated that the new method was very reliable. The result of spinous process angles obtained by the new method was linearly correlated (y = 0.97x, R 2 = 0.88) with that obtained by conventional 3D reconstruction. These results suggested that the newly developed imaging method can provide real‐time ultrasound imaging for scoliosis evaluation while preserving the comparative image quality of the conventional 3D reconstruction method.

Compact and Wireless Freehand 3D Ultrasound Real-time Spine Imaging System: A pilot study.

The 3D ultrasound reconstruction technology has led to a rapid development of ultrasound spine imaging in recent decades. However, the current imaging apparatus is bulky and not portable. The objective of this study is to develop a new compact and wireless system to offer the real-time visualized spine images during data acquisition. A portable and WI-FI based ultrasound scanner and a compact EM tracking system were assembled to acquire ultrasound transverse frames with location information which could be reconstructed into 3D spine image volume in real-time. The validation was implemented on the 2D coronal images of vertebra phantoms, and the in vivo data acquisition and reconstruction were demonstrated on volunteers. The result showed that the new system could provide reconstructed spine images in real time and the average errors of the reconstructed images were about 1mm (approximate to image pixel size).

GPU-based volume reconstruction for freehand 3D ultrasound imaging.

Volume reconstruction plays an important role in improving image quality for freehand three-dimensional (3D) ultrasound imaging. The kernel regression provides an effective method for volume reconstruction in 3D ultrasound imaging, but it requires heavily computational time-cost. In this paper, a programmable graphic-processor-unit-(GPU) based fast kernel regression method is proposed for freehand 3D ultrasound volume reconstruction. The most significant aspect of our method is the adopting of powerful data-parallel computing capability of GPU to improve the overall efficiency. To produce higher image quality, the results of the kernel regression with various parameter settings is deeply investigated under the help of the fast implementation of the algorithm. Experimental results demonstrate that the computational performance of the proposed GPU-based method can be over 200 times faster than that on CPU. Better image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of 5×5×5 and kernel bandwidth of 1.0.

Freehand three-dimensional ultrasound imaging of carotid artery using motion tracking technology

Ultrasound imaging has been extensively used for determining the severity of carotid atherosclerotic stenosis. In particular, the morphological characterization of carotid plaques can be performed for risk stratification of patients. However, using 2D ultrasound imaging for detecting morphological changes in plaques has several limitations. Due to the scan was performed on a single longitudinal cross-section, the selected 2D image is difficult to represent the entire morphology and volume of plaque and vessel lumen. In addition, the precise positions of 2D ultrasound images highly depend on the radiologists’ experience, it makes the serial long-term exams of anti-atherosclerotic therapies are difficult to relocate the same corresponding planes by using 2D B-mode images. This has led to the recent development of three-dimensional (3D) ultrasound imaging, which offers improved visualization and quantification of complex morphologies of carotid plaques. In the present study, a freehand 3D ultrasound imaging technique based on optical motion tracking technology is proposed. Unlike other optical tracking systems, the marker is a small rigid body that is attached to the ultrasound probe and is tracked by eight high-performance digital cameras. The probe positions in 3D space coordinates are then calibrated at spatial and temporal resolutions of 10μm and 0.01s, respectively. The image segmentation procedure involves Otsu’s and the active contour model algorithms and accurately detects the contours of the carotid arteries. The proposed imaging technique was verified using normal artery and atherosclerotic stenosis phantoms. Human experiments involving freehand scanning of the carotid artery of a volunteer were also performed. The results indicated that compared with manual segmentation, the lowest percentage errors of the proposed segmentation procedure were 7.8% and 9.1% for the external and internal carotid arteries, respectively. Finally, the effect of handshaking was calibrated using the optical tracking system for reconstructing a 3D image.

3D freehand ultrasound reconstruction using a piecewise smooth Markov random field

In this paper, we introduce a novel three-dimensional (3D) reconstruction framework for ultrasound images using a piecewise smooth Markov random field (MRF) model from irregularly spaced B-scan images obtained by freehand scanning. Freehand 3D ultrasound imaging is a useful system for various clinical applications, including image-guided surgeries and interventions, as well as diagnoses, due to the variety of its scan ranges and relatively low cost. The reconstruction process performs a key role in this system because its sampling irregularities may cause undesired artifacts, and ultrasound images generally suffer from noise and distortions. However, traditional approaches are based on simple geometric interpolations, such as pixel-based or distance-weighted methods, which are sensitive to sampling density and speckle noise. These approaches generally have an additional limitation of smoothing objects boundaries. To reduce speckle noise and preserve boundaries, we devised a piecewise smooth (PS) MRF model and developed its optimization algorithm. In our framework, we can easily apply an individual noise level for each image pixel, which is specified by the characteristics of an ultrasound probe, and possibly, the lateral and axial positions of an image. As a result, the reconstructed volume has sharp object boundaries with reduced speckle noise and artifacts. Our PS-MRF model provides simple segmentation results within a reconstruction framework that is useful for various purposes, such as clear visualization. The corresponding optimization methods have also been developed, and we tested a virtual phantom and a physical phantom model. Experimental results show that our method outperforms existing methods in terms of interpolation and segmentation accuracy. With this method, all computations can be performed with practical time consumption and with an appropriate resolution, via parallel computing using graphic processing units.

Real-time freehand 3D ultrasound imaging

Real-time freehand 3D ultrasound (US) has attracted much attention in clinical practices because it provides interactive feedback to help the clinicians acquire not only high-quality images but also timely information of the scanning area, which is necessary in intraoperative examinations. In this study, we developed a real-time freehand 3D US imaging system which can obtain volume reconstruction and visualisation during data acquisition at real-time level. Based on two popular algorithms, i.e. squared distance weighted interpolation (SDW) and Bezier interpolation, we designed corresponding parallel computing methods that were implemented on the graphics processing unit (GPU) to incrementally reconstruct and display the tissues being scanned using Visualisation toolkits (VTK). With a typical B-scan image size of 302 × 268 at an acquisition rate of 25 Hz and a preset volume size of 90 × 81 × 192, the system achieved an incremental reconstruction-visualisation rate of up to 32 frames/s and 119 frames/s for the SDW and Bezier algorithms, respectively, achieving the real-time 3D US.

Quantitative Assessment of Variational Surface Reconstruction from Sparse Point Clouds in Freehand 3D Ultrasound Imaging during Image-Guided Tumor Ablation

Surface reconstruction for freehand 3D ultrasound is used to provide 3D visualization of a VOI (volume of interest) during image-guided tumor ablation surgery. This is a challenge because the recorded 2D B-scans are not only sparse but also non-parallel. To solve this issue, we established a framework to reconstruct the surface of freehand 3D ultrasound imaging in 2011. The key technique for surface reconstruction in that framework is based on variational interpolation presented by Greg Turk for shape transformation and is named Variational Surface Reconstruction (VSR). The main goal of this paper is to evaluate the quality of surface reconstructions, especially when the input data are extremely sparse point clouds from freehand 3D ultrasound imaging, using four methods: Ball Pivoting, Power Crust, Poisson, and VSR. Four experiments are conducted, and quantitative metrics, such as the Hausdorff distance, are introduced for quantitative assessment. The experiment results show that the performance of the proposed VSR method is the best of the four methods at reconstructing surface from sparse data. The VSR method can produce a close approximation to the original surface from as few as two contours, whereas the other three methods fail to do so. The experiment results also illustrate that the reproducibility of the VSR method is the best of the four methods.

A novel Bayesian-based nonlocal reconstruction method for freehand 3D ultrasound imaging

Freehand three-dimensional (3D) ultrasound imaging is an important medical imaging modality in computer-assisted clinical diagnosis and image-guided intervention. In this paper, we present a novel Bayesian-based nonlocal method for the accurate volume reconstruction of freehand 3D ultrasound imaging with irregularly spaced B-scans. In the algorithm, each pixel is represented as the Gamma distribution which corresponds to the speckle noise generated by the interaction of the acoustic wave with the tissues. The variational reconstruction functional is associated with a nonlocal denoising term and a nonlocal inpainting term. To suppress speckle noise in the ultrasound image, the observed data is filtered via nonlocal total variation method firstly. The nonlocal denoising model is adapted to the speckle noise by substituting the Pearson distance-based weight function for the Gaussian weight function. To interpolate the missing data, a new inpainting scheme derived from the nonlocal means filter and its implementation based on fast marching method are introduced to fill the empty regions. This makes interpolation of missing data more accurate and effective. The Pearson distance function derived from the Bayesian estimator is not only used for speckle reduction, but also serves as weight function for building nonlocal means-based inpainting algorithm. Experimental results on synthetic cube data, in-vitro ultrasound abdominal phantom and in-vivo liver of human subject and comparisons with some classical and recent algorithms are used to demonstrate its improvement in both speckle suppression and edge preservation in 3D ultrasound reconstruction.

Reconstruction of freehand 3D ultrasound based on kernel regression.

IntroductionFreehand three-dimensional (3D) ultrasound has the advantages of flexibility for allowing clinicians to manipulate the ultrasound probe over the examined body surface with less constraint in comparison with other scanning protocols. Thus it is widely used in clinical diagnose and image-guided surgery. However, as the data scanning of freehand–style is subjective, the collected B-scan images are usually irregular and highly sparse. One of the key procedures in freehand ultrasound imaging system is the volume reconstruction, which plays an important role in improving the reconstructed image quality.System and methodsA novel freehand 3D ultrasound volume reconstruction method based on kernel regression model is proposed in this paper. Our method consists of two steps: bin-filling and regression. Firstly, the bin-filling step is used to map each pixel in the sampled B-scan images to its corresponding voxel in the reconstructed volume data. Secondly, the regression step is used to make the nonparametric estimation for the whole volume data from the previous sampled sparse data. The kernel penalizes distance away from the current approximation center within a local neighborhood.Experiments and resultsTo evaluate the quality and performance of our proposed kernel regression algorithm for freehand 3D ultrasound reconstruction, a phantom and an in-vivo liver organ of human subject are scanned with our freehand 3D ultrasound imaging system. Root mean square error (RMSE) is used for the quantitative evaluation. Both of the qualitative and quantitative experimental results demonstrate that our method can reconstruct image with less artifacts and higher quality.ConclusionThe proposed kernel regression based reconstruction method is capable of constructing volume data with improved accuracy from irregularly sampled sparse data for freehand 3D ultrasound imaging system.

A Freehand 3D Ultrasound Imaging System using Open-Source Software Tools with Improved Edge-Preserving Interpolation

Ultrasound imaging is widely employed in various medical procedures. Most ultrasound procedures are performed with conventional 2D ultrasound systems, but visualizing the 3D anatomy using 2D ultrasound images is often challenging. This paper describes the use of open-source software tools to develop a freehand system for synthesizing high-quality 3D ultrasound volumes using electromagnetic tracking. In the proposed system, the spatial transformation between the 2D ultrasound images and the electromagnetic sensor attached to the ultrasound transducer was performed using an accurate spatial calibration method. A new interpolation method, called the edge-preserving distance-weighted (EPDW), is employed to reconstruct the 3D ultrasound volumes. The performance of the system is evaluated by performing a set of phantom experiments. The results showed that the reconstructed 3D ultrasound volumes have sub-millimeter accuracy. Moreover, the ultrasound volumes synthesized using the EPDW method demonstrated improved edge preservation compared with a previous interpolation method.

Freehand 3D Ultrasound to Measure Thrombus Volume in Patients with Acute Deep-Vein Thrombosis

Objective —Current imaging techniques are limited in their ability to quantify thrombus burden, progression, or resolution in patients with acute deep-vein thrombosis (DVT). These assessments are critical measures of therapeutic success when thrombolytic or thrombectomy treatment protocols are used for DVT. We have developed a novel freehand three-dimensional (3D) ultrasound method to measure thrombus volume. In this study, we evaluated the reliability of this new technology. Methods —We studied consecutive hospital inpatients with a first episode of acute DVT. Treatment decisions were not influenced by the study protocol. A combination of routine imaging in grayscale, color-flow, and power-Doppler modes along-with freehand 3D volumetric imaging with a linear transducer attached to an external tracking sensor was performed using a personal computer–based ultrasound scanner. Image-processing software loaded on the personal computer was used to process and reconstruct the serial cross-sectional images of the affected veins and outlined thrombus into a composite 3D image. Imaging and processing was performed twice by one sonographer, and repeated once by another sonographer. Results —The mean age of patients was 56.7 ± 15 years; 40% were women. A total of 70% of DVTs were in the lower extremity and 60% received anticoagulation. Thrombus volume was reliably determined by our protocol. The mean inter- and intraobserver differences in measurements were −0.09 ± 0.59 cm3 and 0.23 ± 0.43 cm3 (mean ± SD), which were well within 2 SD (Bland Altman statistics) of the mean volumes. Measurements of the second sonographer correlated well with those of the first (regression slope = 0.95 ± 0.07, p = 0.001) and those of the first observation correlated with the second observation performed by the same sonographer (regression slope = 0.91 ± 0.03, p = 0.001). Interrater agreement was good between the two sonographers (kappa = 0.71) and between two measurements by the same sonographer (kappa = 0.82). Conclusions —We have developed a novel freehand 3D-ultrasound imaging technique and protocol that reliably measures venous thrombus volume. There is good agreement in measurements between two observers and repeated measurements by one observer. The technique can be readily adapted for routine clinical practice. This protocol will be of increasing value as the appreciation for the deleterious effects of residual thrombus after DVT increases; and the use of aggressive thrombus removal treatments for acute DVT increases.

Differential strain patterns of the human Achilles tendon determined in vivo with freehand three-dimensional ultrasound imaging

The human Achilles tendon (AT) has often been considered to act as a single elastic structure in series with the muscles of the triceps surae. As such it has been commonly modelled as a Hookean spring of uniform stiffness. However, the free AT and the proximal AT have distinctly different structures that lend themselves to different elastic properties. This study aimed to use three-dimensional freehand ultrasound imaging to determine whether the proximal AT and the free AT exhibit different elastic behaviour during sub-maximal, fixed-end contractions of the triceps surae. Six male and five female participants (mean ± s.d. age=27 ± 5 years) performed fixed position contractions of the plantar-flexors on an isokinetic dynamometer at 50% of their maximum voluntary contraction in this position. Freehand three-dimensional ultrasound imaging was used to reconstruct the free-tendon and proximal AT at rest and during contraction. The free-tendon exhibited significantly (P=0.03) greater longitudinal strain (5.2 ± 1.7%) than the proximal AT (2.6 ± 2.0%). The lesser longitudinal strain of the proximal AT was linked to the fact that it exhibited considerable transverse (orthogonal to the longitudinal direction) strains (5.0 ± 4%). The transverse strain of the proximal AT is likely due to the triceps surae muscles bulging upon contraction, and thus the level of bulging may influence the elastic behaviour of the proximal AT. This might have implications for the understanding of triceps surae muscle-tendon interaction during locomotion, tendon injury mechanics and previous measurements of AT elastic properties.

Speckle suppression and contrast enhancement in reconstruction of freehand 3D ultrasound images using an adaptive distance-weighted method

In three-dimensional (3D) freehand ultrasound (US), reconstructing a set of B-scans into a regular voxel array is the key procedure for consequent visualization and analysis. This paper presents a new adaptive interpolation algorithm for computing the voxel array to suppress speckle noises and enhance contrast. The local statistics of homogeneous regions including mean and variance were measured and the ratio of variance to mean was used as homogeneity criteria. For the computation of each voxel, the interpolation method was adaptively determined with respect to its local statistics. If the neighbouring pixels of a voxel satisfied the homogeneity criterion, its value was computed with an arithmetic mean filter. Otherwise, the voxel was probably locating in an inhomogeneous region and an adaptive distance-weighted (ADW) interpolation method was employed to compute its value. A resolution phantom and a subject’s forearm were reconstructed using the proposed algorithm and two other well-known methods – conventional distance-weighted (DW) and voxel nearest neighbourhood (VNN) interpolations. The comparison results demonstrated that the adaptive interpolation algorithm was able to suppress speckles, preserve edges and enhance contrast effectively for the volume reconstruction.