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We present an adaptation of the pixel-reassignment technique from confocal fluorescent microscopy to coherent ultrasound imaging. The method, Ultrasound Pixel-Reassignment (UPR), provides a resolution and signal to noise (SNR) improvement in ultrasound imaging by computationally reassigning off-focus signals acquired using traditional plane-wave compounding ultrasonography. We theoretically analyze the analogy between the optical and ultrasound implementations of pixel reassignment, and experimentally evaluate the imaging quality on tissue-mimicking acoustic phantoms. We demonstrate that UPR provides a $25%$ resolution improvement and a $3dB$ SNR improvement in in-vitro scans, without any change in hardware or acquisition scheme.
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This paper introduces a novel technique to estimate tissue displacement in quasi-static elastography. A major challenge in elastography is estimation of displacement (also referred to time-delay estimation) between pre-compressed and post-compressed ultrasound data. Maximizing normalized cross correlation (NCC) of ultrasound radio-frequency (RF) data of the pre- and post-compressed images is a popular technique for strain estimation due to its simplicity and computational efficiency. Several papers have been published to increase the accuracy and quality of displacement estimation based on NCC. All of these methods use spatial windows to estimate NCC, wherein displacement magnitude is assumed to be constant within each window. In this work, we extend this assumption along the temporal domain to exploit neighboring samples in both spatial and temporal directions. This is important since traditional and ultrafast ultrasound machines are, respectively, capable of imaging at more than 30 frame per second (fps) and 1000 fps. We call our method spatial temporal normalized cross correlation (STNCC) and show that it substantially outperforms NCC using simulation, phantom and in-vivo experiments.
Morphological features of small vessels provide invaluable information regarding underlying tissue, especially in cancerous tumors. This paper introduces methods for obtaining quantitative morphological features from microvasculature images obtained by non-contrast ultrasound imaging. Those images suffer from the artifact that limit quantitative analysis of the vessel morphological features. In this paper we introduce processing steps to increase accuracy of the morphological assessment for quantitative vessel analysis in presence of these artifact. Specifically, artificats are reduced by additional filtering and vessel segments obtained by skeletonization of the regularized microvasculature images are further analyzed to satisfy additional constraints, such as diameter, and length of the vessel segments. Measurement of some morphological metrics, such as tortuosity, depends on preserving large vessel trunks that may be broken down into multiple branches. We propose two methods to address this problem. In the first method, small vessel segments are suppressed in the vessel filtering process via adjusting the size scale of the regularization. Hence, tortuosity of the large trunks can be more accurately estimated by preserving longer vessel segments. In the second approach, small connected vessel segments are removed by a combination of morphological erosion and dilation operations on the segmented vasculature images. These methods are tested on representative in vivo images of breast lesion microvasculature, and the outcomes are discussed. This paper provides a tool for quantification of microvasculature image from non-contrast ultrasound imaging may result in potential biomarkers for diagnosis of some diseases.
We present PRETUS -a Plugin-based Real Time UltraSound software platform for live ultrasound image analysis and operator support. The software is lightweight; functionality is brought in via independent plug-ins that can be arranged in sequence. The software allows to capture the real-time stream of ultrasound images from virtually any ultrasound machine, applies computational methods and visualises the results on-the-fly. Plug-ins can run concurrently without blocking each other. They can be implemented in C ++ and Python. A graphical user interface can be implemented for each plug-in, and presented to the user in a compact way. The software is free and open source, and allows for rapid prototyping and testing of real-time ultrasound imaging methods in a manufacturer-agnostic fashion. The software is provided with input, output and processing plug-ins, as well as with tutorials to illustrate how to develop new plug-ins for PRETUS.
We demonstrate single-pixel imaging in the spectral domain by encoding Fourier probe patterns onto the spectrum of a superluminescent laser diode using a programmable optical filter. As a proof-of-concept, we measure the wavelength-dependent transmission of a Michelson interferometer and a wavelength-division multiplexer. Our results open new perspectives for remote broadband measurements with possible applications in industrial, biological or security applications.
The objectives were to develop a novel three-dimensional technology for imaging naturally occurring shear wave (SW) propagation, demonstrate feasibility on human volunteers and quantify SW velocity in different propagation directions. Imaging of natural SWs generated by valve closures has emerged to obtain a direct measurement of cardiac stiffness. Recently, natural SW velocity was assessed in two dimensions on parasternal long axis view under the assumption of a propagation direction along the septum. However, in this approach the source localization and the complex three-dimensional propagation wave path was neglected making the speed estimation unreliable. High volume rate transthoracic acquisitions of the human left ventricle (1100 volume/s) was performed with a 4D ultrafast echocardiographic scanner. Four-dimensional tissue velocity cineloops enabled visualization of aortic and mitral valve closure waves. Energy and time of flight mapping allowed propagation path visualization and source localization, respectively. Velocities were quantified along different directions. Aortic and mitral valve closure SW velocities were assessed for the three volunteers with low standard deviation. Anisotropic propagation was also found suggesting the necessity of using a three-dimensional imaging approach. Different velocities were estimated for the three directions for the aortic (3.4$pm$0.1 m/s, 3.5$pm$0.3 m/s, 5.4$pm$0.7 m/s) and the mitral (2.8$pm$0.5 m/s, 2.9$pm$0.3 m/s, 4.6$pm$0.7 m/s) valve SWs. 4D ultrafast ultrasound alleviates the limitations of 2D ultrafast ultrasound for cardiac SW imaging based on natural SW propagations and enables a comprehensive measurement of cardiac stiffness. This technique could provide stiffness mapping of the left ventricle.
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