Volumetric Ultrasound Imaging Research Articles

A Multiplexed 32 × 32 2D Matrix Array Transducer for Flexible Sub-Aperture Volumetric Ultrasound Imaging.

A fully-sampled two-dimensional (2D) matrix array ultrasonic transducer is essential for fast and accurate three-dimensional (3D) volumetric ultrasound imaging. However, these arrays, usually consisting of thousands of elements, not only face challenges of poor performance and complex wiring due to high-density elements and small element sizes but also put high requirements for electronic systems. Current commercially available fully-sampled matrix arrays, dividing the aperture into four fixed sub-apertures to reduce system channels through multiplexing are widely used. However, the fixed sub-aperture configuration limits imaging flexibility and the gaps between sub-apertures lead to reduced imaging quality. In this study, we propose a high-performance multiplexed matrix array by the design of 1-3 piezocomposite and gapless sub-aperture configuration, as well as optimized matching layer materials. Furthermore, we introduce a sub-aperture volumetric imaging method based on the designed matrix array, enabling high-quality and flexible 3D ultrasound imaging with a low-cost 256-channel system. The influence of imaging parameters, including the number of sub-apertures and steering angle on imaging quality was investigated by simulation, in vitro and in vivo imaging experiments. The fabricated matrix array has a center frequency of 3.4 MHz and a -6 dB bandwidth of above 70%. The proposed sub-aperture volumetric imaging method demonstrated a 10% improvement in spatial resolution, a 19% increase in signal-to-noise ratio, and a 57.7% increase in contrast-to-noise ratio compared with the fixed sub-aperture array imaging method. This study provides a new strategy for high-quality volumetric ultrasound imaging with a low-cost system.

Volumetric B-mode ultrasound and Doppler Imaging: Automatic Tracking With One Single Camera.

Vascular diseases may occur in the upper extremities, and the lesions can span the entire length of the blood vessel. One of the most popular methods to identify vascular disorders is ultrasound Doppler imaging. However, traditional two-dimensional (2D) ultrasound Doppler imaging cannot capture the entire length of a long vessel in one image. Medical professionals often have to painstakingly reconstruct three-dimensional (3D) data using 2D ultrasound images to locate the lesions, especially for large blood vessels. 3D ultrasound Doppler imaging can display the morphological structure of blood vessels and the distribution of lesions more directly, providing a more comprehensive view compared to 2D imaging. In this work, we propose a wide-range 3D volumetric ultrasound Doppler imaging system with dual modality, in which a high-definition camera is adopted to automatically track the movement of the ultrasound transducer, simultaneously capturing a corresponding sequence of 2D ultrasound Doppler images. We conducted experiments on human arms using our proposed system and separately with X-ray computerized tomography (X-CT). The comparison results prove the potential value of our proposed system in the diagnosis of arm vascular diseases.

3D Acoustic Wave Sparsely Activated Localization Microscopy With Phase Change Contrast Agents.

The aim of this study is to demonstrate 3-dimensional (3D) acoustic wave sparsely activated localization microscopy (AWSALM) of microvascular flow in vivo using phase change contrast agents (PCCAs). Three-dimensional AWSALM using acoustically activable PCCAs was evaluated on a crossed tube microflow phantom, the kidney of New Zealand White rabbits, and the brain of C57BL/6J mice through intact skull. A mixture of C 3 F 8 and C 4 F 10 low-boiling-point fluorocarbon gas was used to generate PCCAs with an appropriate activation pressure. A multiplexed 8-MHz matrix array connected to a 256-channel ultrasound research platform was used for transmitting activation and imaging ultrasound pulses and recording echoes. The in vitro and in vivo echo data were subsequently beamformed and processed using a set of customized algorithms for generating 3D super-resolution ultrasound images through localizing and tracking activated contrast agents. With 3D AWSALM, the acoustic activation of PCCAs can be controlled both spatially and temporally, enabling contrast on demand and capable of revealing 3D microvascular connectivity. The spatial resolution of the 3D AWSALM images measured using Fourier shell correlation is 64 μm, presenting a 9-time improvement compared with the point spread function and 1.5 times compared with half the wavelength. Compared with the microbubble-based approach, more signals were localized in the microvasculature at similar concentrations while retaining sparsity and longer tracks in larger vessels. Transcranial imaging was demonstrated as a proof of principle of PCCA activation in the mouse brain with 3D AWSALM. Three-dimensional AWSALM generates volumetric ultrasound super-resolution microvascular images in vivo with spatiotemporal selectivity and enhanced microvascular penetration.

Sub-aperture ultrafast volumetric ultrasound imaging for fully sampled dual-mode matrix array

Fully sampled dual-mode matrix array ultrasound transducer is capable of performing imaging and therapeutic ultrasound in three dimensions (3D). It is a promising tool for many clinical applications because of its precise multi-focus therapy with imaging guidance by itself. Our team previously designed a 256-element fully sampled dual-mode matrix array transducer, while its imaging quality needs to be further improved. In this work, we propose a high-contrast sub-aperture volumetric imaging strategy to improve the imaging quality of the dual-mode matrix array. We first analyzed the effect of various parameters of sub-aperture imaging on the imaging quality by Field II. Based on the optimized parameters, we compared the resolution and signal to noise ratio (SNR) of sub-aperture imaging with those of full aperture imaging on phantoms and rabbit brain. The experimental results showed the proposed sub-aperture imaging method could obtain a comparable resolution to full aperture imaging. Moreover, the average intensity of noise signal near the wire phantom decreased by about 5 dB and the SNR of tissue phantom image increased by 8 %. The proposed sub-aperture imaging method also enabled clearer and more accurate imaging of the rabbit brain. The obtained results indicate the proposed sub-aperture imaging is a promising method for practical use of a fully sampled dual-mode matrix array for volumetric ultrasound imaging.

High-Frame-Rate Volumetric Porcine Renal Vasculature Imaging.

The aim of this study was to assess the feasibility and imaging options of contrast-enhanced volumetric ultrasound kidney vasculature imaging in a porcine model using a prototype sparse spiral array. Transcutaneous freehand in vivo imaging of two healthy porcine kidneys was performed according to three protocols with different microbubble concentrations and transmission sequences. Combining high-frame-rate transmission sequences with our previously described spatial coherence beamformer, we determined the ability to produce detailed volumetric images of the vasculature. We also determined power, color and spectral Doppler, as well as super-resolved microvasculature in a volume. The results were compared against a clinical 2-D ultrasound machine. Three-dimensional visualization of the kidney vasculature structure and blood flow was possible with our method. Good structural agreement was found between the visualized vasculature structure and the 2-D reference. Microvasculature patterns in the kidney cortex were visible with super-resolution processing. Blood flow velocity estimations were within a physiological range and pattern, also in agreement with the 2-D reference results. Volumetric imaging of the kidney vasculature was possible using a prototype sparse spiral array. Reliable structural and temporal information could be extracted from these imaging results.

Miniaturized Endoscopic 2D US Transducer for Volumetric Ultrasound Imaging of the Auditory System.

In this paper, we focus on the carrying out and validation of minimally invasive three-dimensional (3D) ultrasound (US) imaging of the auditory system, which is based on a new miniaturized endoscopic 2D US transducer. This unique probe consists of a 18 MHz 24 elements curved array transducer with a distal diameter of 4 mm so it can be inserted into the external auditory canal. Typical acquisition is achieved by rotating such a transducer around its own axis using a robotic platform. Reconstruction of a US volume from the set of acquired B-scans during the rotation is then performed using scan-conversion. The accuracy of the reconstruction procedure is evaluated using a dedicated phantom that includes a set of wires as reference geometry. Twelve acquisitions obtained from different probe poses are compared to a micro-computed tomographic model of the phantom, leading to a maximum error of 0.20 mm. Additionally, acquisitions with a cadaveric head highlight the clinical applicability of this set up. Structures of the auditory system such as the ossicles and the round window can be identified from the obtained 3D volumes. These results confirm that our technique enables the accurate imaging of the middle and inner ears without having to deteriorate the surrounding bone. Since US is a real-time, wide available and non-ionizing imaging modality, our acquisition setup could facilitate the minimally invasive diagnosis and surgical navigation for otology in a fast, cost-effective and safe way.

Deep learning based ultrasonic visualization of distal humeral cartilage for image-guided therapy: a pilot validation study.

Ultrasound is widely used for image-guided therapy (IGT) in many surgical fields, thanks to its various advantages, such as portability, lack of radiation and real-time imaging. This article presents the first attempt to utilize multiple deep learning algorithms in distal humeral cartilage segmentation for dynamic, volumetric ultrasound images employed in minimally invasive surgery. The dataset, consisting 5,321 ultrasound images were collected from 12 healthy volunteers. These images were randomly split into training and validation sets in an 8:2 ratio. Based on deep learning algorithms, 9 semantic segmentation networks were developed and trained using our dataset at Southern University of Science and Technology Hospital in September 2022. The performance of the networks was evaluated based on their segmenting accuracy and processing efficiency. Furthermore, these networks were implemented in an IGT system to assess their feasibility in 3-dimentional imaging precision. In 2D segmentation, Medical Transformer (MedT) showed the highest accuracy result with a Dice score of 89.4%, however, the efficiency in processing images was relatively lower at 2.6 frames per second (FPS). In 3D imaging, the average root mean square (RMS) between ultrasound (US)-generated models based on the networks and magnetic resonance imaging (MRI)-generated models was no more than 1.12 mm. The findings of this study indicate the technological feasibility of a novel method for real-time visualization of distal humeral cartilage. The increased precision of ultrasound calibration and segmentation are both important approaches to improve the accuracy of 3D imaging.

Fast volumetric ultrasound facilitates high-resolution 3D mapping of tissue compartments.

Volumetric ultrasound imaging has the potential for operator-independent acquisition and enhanced field of view. Panoramic acquisition has many applications across ultrasound; spanning musculoskeletal, liver, breast, and pediatric imaging; and image-guided therapy. Challenges in high-resolution human imaging, such as subtle motion and the presence of bone or gas, have limited such acquisition. These issues can be addressed with a large transducer aperture and fast acquisition and processing. Programmable, ultrafast ultrasound scanners with a high channel count provide an unprecedented opportunity to optimize volumetric acquisition. In this work, we implement nonlinear processing and develop distributed beamformation to achieve fast acquisition over a 47-centimeter aperture. As a result, we achieve a 50-micrometer -6-decibel point spread function at 5 megahertz and resolve in-plane targets. A large volume scan of a human limb is completed in a few seconds, and in a 2-millimeter dorsal vein, the image intensity difference between the vessel center and surrounding tissue was ~50 decibels, facilitating three-dimensional reconstruction of the vasculature.

Costas Sparse 2-D Arrays for High-Resolution Ultrasound Imaging.

Two-dimensional arrays enable volumetric ultrasound imaging but have been limited to small aperture size and hence low resolution due to the high cost and complexity of fabrication, addressing, and processing associated with large fully addressed arrays. Here, we propose Costas arrays as a gridded sparse 2-D array architecture for volumetric ultrasound imaging. Costas arrays have exactly one element for every row and column, such that the vector displacement between any pair of elements is unique. These properties ensure aperiodicity, which helps eliminate grating lobes. Compared with previously reported works, we studied the distribution of active elements based on an order-256 Costas layout on a wider aperture ( 96 λ×96 λ at 7.5 MHz center frequency) for high-resolution imaging. Our investigations with focused scanline imaging of point targets and cyst phantoms showed that Costas arrays exhibit lower peak sidelobe levels compared with random sparse arrays of the same size and offer comparable performance in terms of contrast compared with Fermat spiral arrays. In addition, Costas arrays are gridded, which could ease the manufacturing and has one element for each row/column, which enables simple interconnection strategies. Compared with state-of-the-art matrix probes, which are commonly 32×32 , the proposed sparse arrays achieve higher lateral resolution and a wider field of view.

Doppler and Pair-wise Optical Flow Constrained 3D Motion Compensation for 3D Ultrasound Imaging.

Volumetric (3D) ultrasound imaging using a 2D matrix array probe is increasingly developed for various clinical procedures. However, 3D ultrasound imaging suffers from motion artifacts due to tissue motions and a relatively low frame rate. Current Doppler-based motion compensation (MoCo) methods only allow 1D compensation in the in-range dimension. In this work, we propose a new 3D-MoCo framework that combines 3D velocity field estimation and a two-step compensation strategy for 3D diverging wave compounding imaging. Specifically, our framework explores two constraints of a round-trip scan sequence of 3D diverging waves, i.e., Doppler and pair-wise optical flow, to formulate the estimation of the 3D velocity fields as a global optimization problem, which is further regularized by the divergence-free and first-order smoothness. The two-step compensation strategy is to first compensate for the 1D displacements in the in-range dimension and then the 2D displacements in the two mutually orthogonal cross-range dimensions. Systematical in-silico experiments were conducted to validate the effectiveness of our proposed 3D-MoCo method. The results demonstrate that our 3D-MoCo method achieves higher image contrast, higher structural similarity, and better speckle patterns than the corresponding 1D-MoCo method. Particularly, the 2D cross-range compensation is effective for fully recovering image quality.

3D Transcranial Ultrasound Localization Microscopy in the Rat Brain With a Multiplexed Matrix Probe.

Ultrasound Localization Microscopy (ULM) provides images of the microcirculation in-depth in living tissue. However, its implementation in two-dimension is limited by the elevation projection and tedious plane-by-plane acquisition. Volumetric ULM alleviates these issues and can map the vasculature of entire organs in one acquisition with isotropic resolution. However, its optimal implementation requires many independent acquisition channels, leading to complex custom hardware. In this article, we implemented volumetric ultrasound imaging with a multiplexed 32 × 32 probe driven by a single commercial ultrasound scanner. We propose and compare three different sub-aperture multiplexing combinations for localization microscopy in silico and in vitro with a flow of microbubbles in a canal. Finally, we evaluate the approach for micro-angiography of the rat brain. The "light" combination allows a higher maximal volume rate than the "full" combination while maintaining the field of view and resolution. In the rat brain, 100,000 volumes were acquired within 7 min with a dedicated ultrasound sequence and revealed vessels down to 31 μm in diameter with flows from 4.3 mm/s to 28.4 mm/s. This work demonstrates the ability to perform a complete angiography with unprecedented resolution in the living rat's brain with a simple and light setup through the intact skull. We foresee that it might contribute to democratize 3D ULM for both preclinical and clinical studies.

Aortic Valve Leaflet Shape Synthesis With Geometric Prior From Surrounding Tissue.

Even though the field of medical imaging advances, there are structures in the human body that are barely assessible with classical image acquisition modalities. One example are the three leaflets of the aortic valve due to their thin structure and high movement. However, with an increasing accuracy of biomechanical simulation, for example of the heart function, and extense computing capabilities available, concise knowledge of the individual morphology of these structures could have a high impact on personalized therapy and intervention planning as well as on clinical research. Thus, there is a high demand to estimate the individual shape of inassessible structures given only information on the geometry of the surrounding tissue. This leads to a domain adaptation problem, where the domain gap could be very large while typically only small datasets are available. Hence, classical approaches for domain adaptation are not capable of providing sufficient predictions. In this work, we present a new framework for bridging this domain gap in the scope of estimating anatomical shapes based on the surrounding tissue's morphology. Thus, we propose deep representation learning to not map from one image to another but to predict a latent shape representation. We formalize this framework and present two different approaches to solve the given problem. Furthermore, we perform a proof-of-concept study for estimating the individual shape of the aortic valve leaflets based on a volumetric ultrasound image of the aortic root. Therefore, we collect an ex-vivo porcine data set consisting of both, ultrasound volume images as well as high-resolution leaflet images, evaluate both approaches on it and perform an analysis of the model's hyperparameters. Our results show that using deep representation learning and domain mapping between the identified latent spaces, a robust prediction of the unknown leaflet shape only based on surrounding tissue information is possible, even in limited data scenarios. The concept can be applied to a wide range of modeling tasks, not only in the scope of heart modeling but also for all kinds of inassessible structures within the human body.

Validation of Automated Ultrasound-based Registration for Navigated Scaphoid Fixation

Abstract Fractures of the scaphoid bone may be treated in a minimally-invasive fashion. Conventionally, fluoroscopy is required to guide the placement of an osteosynthesis screw. In this work, an alternative method based on volumetric ultrasound is validated. Methods: The fully automatic and fast image processing pipeline involves two machine learning architectures for segmentation and registration. A pre-operatively acquired 3D bone model is registered to the 3D bone surface segmented from the intra-operative ultrasound. Screw positioning is planned in an automated fashion and evaluated in an in-vitro setting: Volumetric ultrasound images of a 3D-printed phantom of a human wrist are acquired for 22 different probe poses. For 220 test runs with different initial displacements, the resulting screw placement within a defined safe zone is evaluated. If the screw lies within the safe zone, its placement is assumed to be successful. Results: An isolated analysis of the registration results in a surface distance error of the registered meshes of 0.49 ± 0.01mm, with successful screw placement in all of the evaluated 220 test runs. The full pipeline, combining segmentation and registration, achieves a mean surface distance error of 0.79 ± 0.37mm, leading to successful screw placements for 149 out of 220 test runs. Poses not suited for the registration could be determined. Excluding these from the analysis, 139 out of 160 test runs are successful. Conclusion: The method proves to be promising when evaluating the registration alone, even given the challenging setup of sub-optimal probe positions. The experiments also demonstrate that further improvement regarding the segmentation is necessary.

Real-Time Volumetric Ultrasound Research Platform with 1024 Parallel Transmit and Receive Channels

Volumetric ultrasound imaging is of great importance in many medical fields, especially in cardiology, but also in therapy monitoring applications. For development of new imaging technologies and scanning strategies, it is crucial to be able to use a hardware platform that is as free and flexible as possible and does not restrict the user in his research in any way. For this purpose, multi-channel ultrasound systems are particularly suitable, as they are able to control each individual element of a matrix array without the use of a multiplexer. We set out to develop a fully integrated, compact 1024-channel ultrasound system that provides full access to all transmission parameters and all digitized raw data of each transducer element. For this purpose, we synchronize four research scanners of our latest “DiPhAS” ultrasound research system generation, each with 256 parallel channels, all connected to a single PC on whose GPUs the entire signal processing is performed. All components of the system are housed in a compact, movable 19-inch rack. The system is designed as a general-purpose platform for research in volumetric imaging; however, the first-use case will be therapy monitoring by tracking radiation-sensitive ultrasound contrast agents.

High Frame Rate Volumetric Imaging of Microbubbles Using a Sparse Array and Spatial Coherence Beamforming.

Volumetric ultrasound imaging of blood flow with microbubbles enables a more complete visualization of the microvasculature. Sparse arrays are ideal candidates to perform volumetric imaging at reduced manufacturing complexity and cable count. However, due to the small number of transducer elements, sparse arrays often come with high clutter levels, especially when wide beams are transmitted to increase the frame rate. In this study, we demonstrate with a prototype sparse array probe and a diverging wave transmission strategy, that a uniform transmission field can be achieved. With the implementation of a spatial coherence beamformer, the background clutter signal can be effectively suppressed, leading to a signal to background ratio improvement of 25 dB. With this approach, we demonstrate the volumetric visualization of single microbubbles in a tissue-mimicking phantom as well as vasculature mapping in a live chicken embryo chorioallantoic membrane.

A Dual-Mode 2D Matrix Array for Ultrasound Image-Guided Noninvasive Therapy.

Focused ultrasound (FUS) lacks reliable real-time image guidance, which hinders the development of non-invasive ultrasound treatment in many important clinical applications. A dual-mode ultrasound array, capable of both imaging and therapy offers a new and reliable strategy for image-guided ultrasound therapy applications. The strategy has the advantages of real-time use, low cost, portability and inherent registration between imaging and therapeutic coordinate systems. In this work, a dual-mode two-dimensional (2D) matrix array with 1 MHz center frequency and 256 elements for ultrasound image-guided non-invasive therapy is reported. The array can provide three-dimensional (3D) volumetric ultrasound imaging and 3D focus control. Ultrasound imaging and therapeutic applications for the brain of small animals demonstrated the multi-functional capability of the dual-mode 2D matrix array. A method of rat brain positioning based on ultrasound imaging was proposed and verified. Transcranial ultrasound image-guided blood-brain barrier (BBB) opening of multiple-targets was achieved in vivo, using the proposed dual-mode 2D array. The obtained results indicate that the dual-mode 2D matrix array is a promising method for practical use in ultrasound image-guided non-invasive therapy applications.

Quantitative Evaluation of an Automated Cone-Based Breast Ultrasound Scanner for MRI-3D US Image Fusion.

Breast cancer is one of the most diagnosed types of cancer worldwide. Volumetric ultrasound breast imaging, combined with MRI can improve lesion detection rate, reduce examination time, and improve lesion diagnosis. However, to our knowledge, there are no 3D US breast imaging systems available that facilitate 3D US - MRI image fusion. In this paper, a novel Automated Cone-based Breast Ultrasound System (ACBUS) is introduced. The system facilitates volumetric ultrasound acquisition of the breast in a prone position without deforming it by the US transducer. Quality of ACBUS images for reconstructions at different voxel sizes (0.25 and 0.50 mm isotropic) was compared to quality of the Automated Breast Volumetric Scanner (ABVS) (Siemens Ultrasound, Issaquah, WA, USA) in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and resolution using a custom made phantom. The ACBUS image data were registered to MRI image data utilizing surface matching and the registration accuracy was quantified using an internal marker. The technology was also evaluated in vivo. The phantom-based quantitative analysis demonstrated that ACBUS can deliver volumetric breast images with an image quality similar to the images delivered by a currently commercially available Siemens ABVS. We demonstrate on the phantom and in vivo that ACBUS enables adequate MRI-3D US fusion. To our conclusion, ACBUS might be a suitable candidate for a second-look breast US exam, patient follow-up, and US guided biopsy planning.

High-Contrast and -Resolution 3-D Ultrasonography with a Clinical Linear Transducer Array Scanned in a Rotate-Translate Geometry

We proposed a novel solution for volumetric ultrasound imaging using single-side access 3-D synthetic aperture scanning of a clinical linear array. This solution is based on an advanced scanning geometry and a software-based ultrasound platform. The rotate-translate scanning scheme increases the elevation angular aperture by pivoting the array (−45° to 45°) around its array axis (axis along the row of its elements) and then scans the imaged object for each pivoted angle by translating the array perpendicularly to the rotation axis. A theoretical basis is presented so that the angular and translational scan sampling periods can be best adjusted for any linear transducer array. We experimentally implemented scanning with a 5-MHz array. In vitro characterization was performed with phantoms designed to test resolution and contrast. Spatial resolution assessed based on the full-width half-maximum of images from isolated microspheres was increased by a factor of 3 along the translational direction from a simple translation scan of the array. Moreover, the resolution was uniform over a cross-sectional area of 4.5 cm2. Angular sampling periods were optimized and tapered to decrease the scan duration while maintaining image contrast (contrast at the center of a 5-mm cyst on the order of −26 dB for 4° angular period and a scan duration of 10 s for a 9-cm3 volume). We demonstrated that superior 3-D ultrasound imaging can be obtained with a clinical array using our scanning strategy. This technique offers a promising and flexible alternative to development of costly matrix arrays toward the development of sensitive volumetric ultrasonography.

Deep Learning for US Image Quality Assessment Based on Femoral Cartilage Boundary Detection in Autonomous Knee Arthroscopy.

Knee arthroscopy is a complex minimally invasive surgery that can cause unintended injuries to femoral cartilage or postoperative complications, or both. Autonomous robotic systems using real-time volumetric ultrasound (US) imaging guidance hold potential for reducing significantly these issues and for improving patient outcomes. To enable the robotic system to navigate autonomously in the knee joint, the imaging system should provide the robot with a real-time comprehensive map of the surgical site. To this end, the first step is automatic image quality assessment, to ensure that the boundaries of the relevant knee structures are defined well enough to be detected, outlined, and then tracked. In this article, a recently developed one-class classifier deep learning algorithm was used to discriminate among the US images acquired in a simulated surgical scenario on which the femoral cartilage either could or could not be outlined. A total of 38 656 2-D US images were extracted from 151 3-D US volumes, collected from six volunteers, and were labeled as "1" or as "0" when an expert was or was not able to outline the cartilage on the image, respectively. The algorithm was evaluated using the expert labels as ground truth with a fivefold cross validation, where each fold was trained and tested on average with 15 640 and 6246 labeled images, respectively. The algorithm reached a mean accuracy of 78.4% ± 5.0, mean specificity of 72.5% ± 9.4, mean sensitivity of 82.8% ± 5.8, and mean area under the curve of 85% ± 4.4. In addition, interobserver and intraobserver tests involving two experts were performed on an image subset of 1536 2-D US images. Percent agreement values of 0.89 and 0.93 were achieved between two experts (i.e., interobserver) and by each expert (i.e., intraobserver), respectively. These results show the feasibility of the first essential step in the development of automatic US image acquisition and interpretation systems for autonomous robotic knee arthroscopy.

Versatile Low-Cost Volumetric 3D Ultrasound Imaging Using Gimbal-Assisted Distance Sensors and an Inertial Measurement Unit.

This study aims at creating low-cost, three-dimensional (3D), freehand ultrasound image reconstructions from commercial two-dimensional (2D) probes. The low-cost system that can be attached to a commercial 2D ultrasound probe consists of commercial ultrasonic distance sensors, a gimbal, and an inertial measurement unit (IMU). To calibrate irregular movements of the probe during scanning, relative position data were collected from the ultrasonic sensors that were attached to a gimbal. The directional information was provided from the IMU. All the data and 2D ultrasound images were combined using a personal computer to reconstruct 3D ultrasound image. The relative position error of the proposed system was less than 0.5%. The overall shape of the cystic mass in the breast phantom was similar to those from 2D and sections of 3D ultrasound images. Additionally, the pressure and deformations of lesions could be obtained and compensated by contacting the probe to the surface of the soft tissue using the acquired position data. The proposed method did not require any initial marks or receivers for the reconstruction of a 3D ultrasound image using a 2D ultrasound probe. Even though our system is less than $500, a valuable volumetric ultrasound image could be provided to the users.