3D ultrasound imaging

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Automatic calibration of a robotized 3D ultrasound imaging system by visual servoing

Automatic calibration of a robotized 3D ultrasound imaging system by visual servoing

Campus de Beaulieu, 35042 Rennes Cedex, France Email: Alexandre.Krupa@irisa.fr Abstract— Three-dimensional free-hand ultrasound imaging consists of capturing a set of ultrasound images with a 2D ultra- sound system and their respective locations in order to position them in a 3D reference frame. Usually the clinician performs the acquisition manually through the use of an optical or magnetic localization system attached to the ultrasound probe. To assist the clinician, we propose to use a robotic system to automatically move the ultrasound probe and measure its position. As for manual 3D ultrasound imaging, it is crucial to know precisely the spatial calibration parameters of the ultrasound system in order to perform accurate 3D imaging. Therefore, we propose to automate the spatial calibration procedure. A robotic task is developed to automatically position the ultrasound image on the intersection point of a cross-wire phantom used for spatial calibration. To perform this task, a new visual servoing technique based on 2D ultrasound images is used to control automatically the motion of the ultrasound probe held by a medical robot.
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Multi-line Transmission for 3d Ultrasound Imaging: An Experimental Study

Multi-line Transmission for 3d Ultrasound Imaging: An Experimental Study

Email: emilia.badescu@creatis.insa-lyon.fr Abstract — Achieving a high frame rate in echocardiography is highly important for quantifying the short phases of the cardiac cycle that contain valuable information for medical diagnosis. Additionally, the 3D quantitative assessment of the heart would significantly improve the current measurements used in daily clinical routine. Nevertheless obtaining ultrafast images remains a challenge due to the trade-off between the image quality and a high frame rate, especially when volumetric data is acquired. Among the current ultrafast imaging methods, multi-line- transmit imaging (MLT) provides an increased frame rate but in the same time mostly preserves the image quality. In this paper we present the first real-time experimental implementation of the MLT in 3D ultrasound. The results indicate the potential of 3D MLT for achieving high contrast and resolution while increasing the frame rate. This study thus demonstrates the feasibility of 3D MLT in real-time and extends its possible applications to dynamic cardiac imaging.
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3D Ultrasound Imaging of Residual Limbs With Camera-Based Motion Compensation

3D Ultrasound Imaging of Residual Limbs With Camera-Based Motion Compensation

these technical efforts as it relates to residual limb imaging, which have shown varying levels of success. Of particular relevance were research projects pursued by groups at Wright State University [19]– [21] and Sandia National Labs [22]. Each group independently devel- oped US B-mode systems that construct three-dimensional images of residual limbs. However, to the authors knowledge, due to limitations neither of the teams advanced to the point where their systems are routinely used in clinical practice. As highlighted in Douglas et al. [9], some of the limiting factors of these previous studies include: (i) the mechanical setup of the scan proved cumbersome, (ii) limb motion degraded image resolution and it was difficult to compensate for, and (iii) final results did not allow for accurate differentiation between tissue types. Follow-up studies used image feature-based registration for motion compensation and spatial compounding, but the results did not allow for rapid volumetric imaging [23].
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3D Quantification of Ultrasound Images: Application to Mouse Embryo Imaging In Vivo

3D Quantification of Ultrasound Images: Application to Mouse Embryo Imaging In Vivo

I. I NTRODUCTION Studies of mouse embryo development are now possible with the development of new ultrasound imaging systems [1-3]. Although 2D ultrasound imaging is a very useful tool for physicians, 3D ultrasound imaging methods have been developed since 30 years [4]. Recent studies show a large number of approaches for the acquisition of the volume of data [5-6]. We have chosen to mount the conventional ultrasound 2-D linear array to an external step-by-step motor. The main advantages are the accurate positioning and the parallel slices obtained from the investigated volume. The paper will present first the acquisition method. In section III, the segmentation method is applied to the data. Results are discussed in section IV.
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3D Freehand Ultrasound Reconstruction based on Probe Trajectory

3D Freehand Ultrasound Reconstruction based on Probe Trajectory

1 Introduction Due to its low cost, real time image formation capability and non invasive nature, 2D ultrasound is a popular medical imaging modality. Nevertheless, the lack of 3D information prevents reproductivity, longitudinal follow-up and precise quan- titative measurements. 3D ultrasound imaging addresses these disadvantages in order to obtain an objective representation of the scanned volume. Among the various options to acquire 3D ultrasound, this work focuses on 3D freehand ul- trasound. This technique consists in tracking in the space a standard 2D probe by using 3D localizer (magnetic or optic). The tracking system continuously measures the 3D position and orientation of the probe. Contrary to mechan- ical built-in probes, freehand imaging is cheap, can address a large variety of clinical applications and allows large organs examination. However, the recon- struction step is still an acute problem with regards to computation time and reconstruction quality.
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Regularized Bayesian compressed sensing in ultrasound imaging

Regularized Bayesian compressed sensing in ultrasound imaging

Index Terms— Ultrasound imaging, compressed sens- ing, Bayesian inference, Markov random field. 1. INTRODUCTION Ultrasound (US) imaging is one of the most popular medi- cal imaging techniques and represents the gold standard in many crucial diagnostic exams such as obstetrics and cardi- ology. The main advantages of US imaging are its relatively low cost, its innocuity for the patient, its ease of use and real time nature. However, the real-time property is sometimes limited by the acquisition time or by the high amount of ac- quired data, especially in 3D ultrasound imaging. Even in 2D applications, a higher frame rate could be beneficial, i.e., for cardiac US monitoring. For this reason, a few research groups have recently started to evaluate the feasibility of US acquisitions using the compressive sampling (CS) framework [1, 2]. In particular, Friboulet et al. have presented in [3] a method for randomly sub-sampling the US raw data (sig- nals before beamforming and classically used in US imag- ing for obtaining the radiofrequency (RF) lines). The idea
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Intraoperative Functional Ultrasound Imaging of Human Brain Activity

Intraoperative Functional Ultrasound Imaging of Human Brain Activity

The subjects performed tasks in a block design paradigm, alternating six blocks of reference conditions and five blocks of tasks, with each block lasting 20 s. A full trial session for one patient, with a mean of 2 different tasks, lasts approximately 8 minutes in total. ESM data were used for ultrasound probe positioning on a targeted functional area. The ultrasound probe was placed in a sterile sleeve filled with sterile ultrasound gel, and the sleeve was placed directly in contact with the cortex after skull and dural opening without any additional coupling liquid. To guarantee its immobility, the ultra- sound probe was fixed to a custom autoclavable stainless steel articulated arm. CBV baseline maps were found to be very stable due to this fixed articulated arm setup. The patients were then asked to perform the specific task that corresponded to the ESM tag in the case of a local anaesthesia. In the case of general anaesthesia, a third person was asked to move or stroke the limb segment of interest.
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Elastic-net based beamforming in medical ultrasound imaging

Elastic-net based beamforming in medical ultrasound imaging

To cite this version : Szasz, Teodora and Basarab, Adrian and Vaida, Mircea- Florin and Kouamé, Denis Elastic-net based beamforming in medical ultrasound imaging. (2016) In: 13th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2016), 13 April 2016 - 16 April 2016 (Prague, Czech Republic).

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Ultrasound Molecular Imaging: How to develop clinical products?

Ultrasound Molecular Imaging: How to develop clinical products?

It has been proposed to exploit the specific property of UCA as strict vascular bed marker to be used for molecular imaging when targeting receptors or proteins of interest are expressed at endothelial level. It is well- known that diseases are accompanied by the expression of various markers at tissue and endothelial levels, the latter being the specific target of targeted UCAs. This is particularly the case for inflammation and angiogenesis (tumor angiogenesis and wound healing) in which the luminal surface of endothelial cells within capillaries and vessels express various well-identified receptors such as selectins, Vascular Cell Adhesion Molecule 1 (VCAM-1), integrins and Vascular Endothelial Growth Factor Receptor (VEGFR).
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3D lens-free imaging of 3D cell culture

3D lens-free imaging of 3D cell culture

1 Overview of the experimental bench These two modes aim at different applications. The θ-mode pretends to be the simplest geometry as the lighting is always normally incident on the sensor, there is no problem of angle relative to the sensor or the different interfaces with differ- ent refractive indices. Moreover, all the angles around the object are theoretically available. Such a geometry is also the one commonly used in tomography and sim- plifies the preliminary studies of the possibility of a 3D lens-free microscope. This geometry could be used in a capsule cytometer, the capsules traveling in capillaries. But this geometry is not adapted for 3D cell cultures in Petri dish which can only be fixed on the experimental bench. This is why the ϕ-mode is also designed in this bench to acquire the first biological data with tilted lighting. Nevertheless one can expect that this geometry will be harder to deal with since one will have to model the tilted propagation of the light. But its main disadvantage is the very limited angular coverage which is limited to roughly ϕ ∈ [−45 ◦ , 45 ◦ ]. Such limitation
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Motion Estimation-Based Image Enhancement in  Ultrasound Imaging

Motion Estimation-Based Image Enhancement in Ultrasound Imaging

 Compute the dense motion field as detailed in [22] .  Compensate the motion to obtain ^I nþ1 ðx; yÞ. Once the motion for every image pair is estimated, the HR image can be reconstructed. All the LR images are first expressed in the coordinate frame of the reference image by accumulating the motion computed between successive frames of the sequence, as was performed for echocardiographic images in [23] . The image val- ues are then interpolated on a regular HR grid using the sub-pixel motion information. As stated before, bicubic interpolation is cho- sen because of its low computational complexity and good results. Several studies have investigated the optimal number of LR images to use when reconstructing the HR image [10] . This depends on many parameters, such as the registration accuracy, the imaging model or the total frequency content. Intuitively,
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Strong reflector-based beamforming in ultrasound medical imaging

Strong reflector-based beamforming in ultrasound medical imaging

Beamforming (BF) or spatial filtering [1] enables the selectivity of the acoustic signals reflected from some known positions, while attenuating the signals from other positions. This is classically done by delaying and applying some specific weights to the reflected signals. The applications of BF are versatile to many areas: radar, sonar, imaging, communications, radio astronomy and others. The beamformers can be either data-independent (fixed), or data-dependent (adaptive), depending on the calculation of the weights applied to the output array of the reflected signals. The simplest yet most used data-independent BF method in US imaging is the classical delay-and-sum (DAS) BF, which uses fixed apodization weights to approximate the array response indepen- dent of the array data. Unfortunately, the resolution and the con- trast achievable with DAS are limited. On the other hand, the adaptive beamformers calculate the weights from the statistics of the received data in order to converge to an optimal response.
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Beamforming with sparse prior in ultrasound medical imaging

Beamforming with sparse prior in ultrasound medical imaging

† Technical University of Cluj-Napoca, Romania Email: teodora.szasz@irit.fr Abstract—Nowadays the classical Delay-and-Sum (DAS) beam- former is extensively used in ultrasound imaging due to its low computational characteristics. However, it suffers from high sidelobe level, poor resolution and low contrast. An alternative is the Minimum-Variance (MV) beamformer which results in a higher image quality both in terms of spatial resolution and contrast. Even so, these benefits come at the expense of a higher computation complexity that limits its real-time capabilities. One solution that recently gained noticeable interest is the exploit of the sparsity of the scanned medium. Based on this assumption, we extend the DAS method to yield sparse results by using the Bayesian Information Criterion (BIC). Our realistic simulations demonstrate that the proposed beamforming (BF) method shows better performance than the classical DAS and MV in terms of lateral resolution, sidelobe reduction and contrast.
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Fracture processes imaging in concrete using nonlinear ultrasound

Fracture processes imaging in concrete using nonlinear ultrasound

Fracture processes imaging in concrete using nonlinear ultrasound.. Martin Lott, Marcel Remillieux, Vincent Garnier, T.J1[r]

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Joint compressive sampling and deconvolution in ultrasound medical imaging

Joint compressive sampling and deconvolution in ultrasound medical imaging

In the past few years, several research groups evaluated the application of compressive sampling (CS) theory [1, 2] in US imaging. The main motivation of these studies is to decrease the amount of acquired data or to increase the frame rate in 2D or 3D US imaging [3–6] or in Doppler applications [7, 8]. It has been thus shown that the RF data may be recovered using nonlinear optimization techniques from a few random linear measurements based on its sparse representation in basis such as wavelets, waveatoms, 2D Fourier transform or learning dictionaries [9]. However, the quality of the CS recovered RF images is at most equivalent to the one of standard fully-sampled data. Nevertheless, it is well known that the quality of US images is limited by several physical phenomena related to the acquisition setup. In this context, deconvolution- based post-processing methods have been shown to provide interesting contrast and spatial resolution enhancement in US imaging [10–13]. Based on the first order Born approximation, these deconvolution techniques assume that the RF images are the result of a convolution between the tissue reflectivity function and the imaging system point spread function (PSF). In this work, we propose a novel framework in US imaging, aiming to combine CS and deconvolution problems. Named compressive deconvolution [14], our approach has a double objective of jointly decreasing the amount of data and recon- structing better contrasted and resolved images than the usual RF data.
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Beamforming through regularized inverse problems in ultrasound medical imaging

Beamforming through regularized inverse problems in ultrasound medical imaging

From 1996 to 1998, he was a Senior Engineer with GIP Tours, Tours. From 1998 to 2008, he was initially an Assistant and then an Associate Professor with the University of Tours. He was the Head of the Signal and Image Processing Group from 2000 to 2006 and the Ultrasound Imaging Group from 2006 to 2008 at the Ultrasound and Signal Laboratory, University of Tours. He is currently a Professor with University Paul Sabatier Toulouse 3, Toulouse, France, and a member of the Institut de Recherche en Informatique de Toulouse (IRIT) Laboratory (UMR 5505 of the CNRS), Toulouse. He also leads the Image Comprehension and Processing Group, IRIT. His current research interests include signal and image processing with applications to medical imaging and particularly ultrasound imaging, including high- resolution imaging, image resolution enhancement, Doppler signal processing, detection and estimation with applications to cerebral emboli detection, multidimensional parametric modeling, spectral analysis, inverse problems related to compressed sensing and restoration.
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Molecular Magnetic Resonance and Ultrasound Imaging of Tumor Angiogenesis

Molecular Magnetic Resonance and Ultrasound Imaging of Tumor Angiogenesis

Seeking out and identifying imaging biomarkers for early cancer diagnosis and the evaluation of patient response to therapy requires an improvement in the specificity of imaging techniques. This study explores in vivo neo-angiogenesis as- sessment using molecular mechanisms through target molec- ular Magnetic Resonance (MR) and Ultrasound (US). In this context, our study examines and compares the use of both imaging technics, targeting the same integrin in a mouse xeno graft tumor model. Following xeno transplantation of human renal cell carcinoma (Human A498), thirteen nude mice were injected with ανβ3-targeted and non-targeted Contrast Agents (CA) for MR and US use, respectively. CA binding to the tar- geted receptor was measured through Dynamic Susceptibility Contrast MR imaging and Differential Targeted Enhancement (DTE) US imaging. The specificities and co location of both targeted CAs were studied throughout the tumor, in both hypo- and hyper-vascularized areas.
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Joint compressive sampling and deconvolution in ultrasound medical imaging

Joint compressive sampling and deconvolution in ultrasound medical imaging

In the past few years, several research groups evaluated the application of compressive sampling (CS) theory [1, 2] in US imaging. The main motivation of these studies is to decrease the amount of acquired data or to increase the frame rate in 2D or 3D US imaging [3–6] or in Doppler applications [7, 8]. It has been thus shown that the RF data may be recovered using nonlinear optimization techniques from a few random linear measurements based on its sparse representation in basis such as wavelets, waveatoms, 2D Fourier transform or learning dictionaries [9]. However, the quality of the CS recovered RF images is at most equivalent to the one of standard fully-sampled data. Nevertheless, it is well known that the quality of US images is limited by several physical phenomena related to the acquisition setup. In this context, deconvolution- based post-processing methods have been shown to provide interesting contrast and spatial resolution enhancement in US imaging [10–13]. Based on the first order Born approximation, these deconvolution techniques assume that the RF images are the result of a convolution between the tissue reflectivity function and the imaging system point spread function (PSF). In this work, we propose a novel framework in US imaging, aiming to combine CS and deconvolution problems. Named compressive deconvolution [14], our approach has a double objective of jointly decreasing the amount of data and recon- structing better contrasted and resolved images than the usual RF data.
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Semi-Blind Deconvolution for Resolution Enhancement in Ultrasound Imaging

Semi-Blind Deconvolution for Resolution Enhancement in Ultrasound Imaging

Index Terms— Resolution enhancement, deconvolution, ultrasound, alternating direction method of multipliers. 1. INTRODUCTION Compared with other medical imaging modalities such as, e.g., X-ray computed tomography (CT), ultrasound (US) imaging is a non-invasive, cost-effective, and harmless modal- ity commonly used in the detection of various pathologies and in the assessment of blood flow velocity. US imaging has now become a standard procedure for medical diagnosis such as breast cancer early detection [ 1 , 2 ]. However, compared with other medical imaging modalities such as magnetic resonance imaging (MRI), the resolution of US images depends on the working frequency and is very low. Additionally, the resolu- tion is degraded due to the presence of an intrinsic noise (i.e., the speckle), the geometry of ultrasound transducers, and the system impulse response or point spread function (PSF). US image resolution improvement is generally achieved by optimizing the imaging device, e.g., [ 3 , 4 ]. Because these techniques are often highly device- and frequency- dependent, an alternative to perform this task is to con- sider post-processing resolution enhancement techniques. A few works have investigated such techniques in US imaging and the PSF estimation, a key step in the deconvolution ap- proaches, is still an ongoing challenge.
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Ultrafast imaging of in vivo muscle contraction using ultrasound

Ultrafast imaging of in vivo muscle contraction using ultrasound

ventional ultrasonic probe. The sequence consists in emitting a single plane wave pulse. Ultrasonic echoes backscattered by tissue heterogeneities are then stored in memories. These ultrasonic raw data are processed in a posttreatment to create images with submillimetric resolution by applying a conven- tional beam formation 共time delay and sum operations兲 in the receive mode. Finally, consecutive echographic images are compared using one dimensional cross correlation along the ultrasound beam axis in order to compute their axial relative displacements 7 共note that “axial” terminology refers to the ultrasonic beam z direction and not to the fibers’ main axis, see Fig. 1 兲. This method enables us to measure relative dis-
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