Acousto-electrical speckle pattern in Lorentz force electrical impedance tomography

Ultrasound speckle is a granular texture pattern appearing in ultrasound imaging. It can be used to distinguish tissues and identify pathologies. Lorentz force electrical impedance tomography is an ultrasound-based medical imaging technique of the tissue electrical conductivity. It is based on the application of an ultrasound wave in a medium placed in a magnetic field and on the measurement of the induced electric current due to Lorentz force. Similarly to ultrasound imaging, we hypothesized that a speckle could be observed with Lorentz force electrical impedance tomography imaging. In this study, we first assessed the theoretical similarity between the measured signals in Lorentz force electrical impedance tomography and in ultrasound imaging modalities. We then compared experimentally the signal measured in both methods using an acoustic and electrical impedance interface. Finally, a bovine muscle sample was imaged using the two methods. Similar speckle patterns were observed. This indicates the existence of an "acousto-electrical speckle" in the Lorentz force electrical impedance tomography with spatial characteristics driven by the acoustic parameters but due to electrical impedance inhomogeneities instead of acoustic ones as is the case of ultrasound imaging

Xampling in Ultrasound Imaging

Recent developments of new medical treatment techniques put challenging demands on ultrasound imaging systems in terms of both image quality and raw data size. Traditional sampling methods result in very large amounts of data, thus, increasing demands on processing hardware and limiting the exibility in the post-processing stages. In this paper, we apply Compressed Sensing (CS) techniques to analog ultrasound signals, following the recently developed Xampling framework. The result is a system with significantly reduced sampling rates which, in turn, means significantly reduced data size while maintaining the quality of the resulting images.Comment: 17 pages, 9 Figures. Introduced in SPIE Medical Imaging Conference, Orlando Florida, 201

Sparsity driven ultrasound imaging

An image formation framework for ultrasound imaging from synthetic transducer arrays based on sparsity-driven regularization functionals using single-frequency Fourier domain data is proposed. The framework involves the use of a physics-based forward model of the ultrasound observation process, the formulation of image formation as the solution of an associated optimization problem, and the solution of that problem through efficient numerical algorithms. The sparsity-driven, model-based approach estimates a complex-valued reflectivity field and preserves physical features in the scene while suppressing spurious artifacts. It also provides robust reconstructions in the case of sparse and reduced observation apertures. The effectiveness of the proposed imaging strategy is demonstrated using experimental data

Flow velocity mapping using contrast enhanced high-frame-rate plane wave ultrasound and image tracking: methods and initial in vitro and in vivo evaluation

Ultrasound imaging is the most widely used method for visualising and quantifying blood flow in medical practice, but existing techniques have various limitations in terms of imaging sensitivity, field of view, flow angle dependence, and imaging depth. In this study, we developed an ultrasound imaging velocimetry approach capable of visualising and quantifying dynamic flow, by combining high-frame-rate plane wave ultrasound imaging, microbubble contrast agents, pulse inversion contrast imaging and speckle image tracking algorithms. The system was initially evaluated in vitro on both straight and carotid-mimicking vessels with steady and pulsatile flows and in vivo in the rabbit aorta. Colour and spectral Doppler measurements were also made. Initial flow mapping results were compared with theoretical prediction and reference Doppler measurements and indicate the potential of the new system as a highly sensitive, accurate, angle-independent and full field-of-view velocity mapping tool capable of tracking and quantifying fast and dynamic flows

Survey of ultrasound practice amongst podiatrists in the UK

Background: Ultrasound in podiatry practice encompasses musculoskeletal ultrasound imaging, vascular hand-held Doppler ultrasound and therapeutic ultrasound. Sonography practice is not regulated by the Health and Care Professions Council (HCPC), with no requirement to hold a formal qualification. The College of Podiatry does not currently define ultrasound training and competencies. This study aimed to determine the current use of ultrasound, training received and mentorship received and/or provided by podiatrists using ultrasound. Methods: A quantitative study utilising a cross-sectional, on-line, single-event survey was undertaken within the UK. Results: Completed surveys were received from 284 podiatrists; 173 (70%) use ultrasound as part of their general practice, 139 (49%) for musculoskeletal problems, 131 (46%) for vascular assessment and 39 (14%) to support their surgical practice. Almost a quarter (n=62) worked for more than one organisation; 202 (71%) were employed by the NHS and/or private sector (n=118, 41%). Nearly all (93%) respondents report using a hand-held vascular Doppler in their daily practice; 216 (82%) to support decisions regarding treatment options, 102 (39%) to provide diagnostic reports for other health professionals, and 34 (13%) to guide nerve blocks. Ultrasound imaging was used by 104 (37%) respondents primarily to aid clinical decision making (n=81) and guide interventions (steroid injections n=67; nerve blocks n=39). Ninety-three percent stated they use ultrasound imaging to treat their own patients, while others scan at the request of other podiatrists (n=28) or health professionals (n=18). Few use ultrasound imaging for research (n=7) or education (n=2). Only 32 (11%) respondents (n=20 private sector) use therapeutic ultrasound to treat patients presenting with musculoskeletal complaints, namely tendon pathologies. Few respondents (18%) had completed formal post-graduate CASE (Consortium for the Accreditation of Sonographic Education) accredited ultrasound courses. Forty (14%) respondents receive ultrasound mentorship; the majority from fellow podiatrists (n=17) or medical colleagues (n=15). Over half (n=127) who do not have ultrasound mentorship indicated they would like a mentor predominantly for ultrasound imaging. Fifty-five (19%) report they currently provide ultrasound mentorship for others. Conclusions: Understanding the scope of ultrasound practice, the training undertaken and the requirements for mentorship will underpin the development of competencies and recommendations defined by the College of Podiatry to support professional development and ensure safe practice.</p

Deep Learning for Accelerated Ultrasound Imaging

In portable, 3-D, or ultra-fast ultrasound (US) imaging systems, there is an increasing demand to reconstruct high quality images from limited number of data. However, the existing solutions require either hardware changes or computationally expansive algorithms. To overcome these limitations, here we propose a novel deep learning approach that interpolates the missing RF data by utilizing the sparsity of the RF data in the Fourier domain. Extensive experimental results from sub-sampled RF data from a real US system confirmed that the proposed method can effectively reduce the data rate without sacrificing the image quality.Comment: Invited paper for ICASSP 2018 Special Session for "Machine Learning in Medical Imaging: from Measurement to Diagnosis

Mathematical Analysis of Ultrafast Ultrasound Imaging

This paper provides a mathematical analysis of ultrafast ultrasound imaging. This newly emerging modality for biomedical imaging uses plane waves instead of focused waves in order to achieve very high frame rates. We derive the point spread function of the system in the Born approximation for wave propagation and study its properties. We consider dynamic data for blood flow imaging, and introduce a suitable random model for blood cells. We show that a singular value decomposition method can successfully remove the clutter signal by using the different spatial coherence of tissue and blood signals, thereby providing high-resolution images of blood vessels, even in cases when the clutter and blood speeds are comparable in magnitude. Several numerical simulations are presented to illustrate and validate the approach.Comment: 25 pages, 13 figure

Sparsity-driven sparse-aperture ultrasound imaging

We propose an image formation algorithm for ultrasound imaging based on sparsity-driven regularization functionals. We consider data collected by synthetic transducer arrays, with the primary motivating application being nondestructive evaluation. Our framework involves the use of a physical optics-based forward model of the observation process; the formulation of an optimization problem for image formation; and the solution of that problem through efficient numerical algorithms. Our sparsity-driven, model-based approach achieves the preservation of physical features while suppressing spurious artifacts. It also provides robust reconstructions in the case of sparse observation apertures. We demonstrate the effectiveness of our imaging strategy on real ultrasound data