Author: Main Administrator of this WP

source: © 2011 IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

The frequency response of ultrasonic detectors is commonly calibrated by finding their sensitivity to incident plane waves at discrete frequencies. For certain applications, such as the emerging field of optoacoustic tomography, it is the response to point sources emitting broadband spectra that needs to be found instead. Although these two distinct sensitivity characteristics are interchangeable in the case of a flat detector and a point source at infinity, it is not the case for detectors with size considerably larger than the acoustic wavelength of interest or those having a focused aperture. Such geometries, which are common in optoacoustics, require direct calibration of the acoustic detector using a point source placed in the relevant position. In this paper, we report on novel cross-validating optoacoustic methods for measuring the frequency response of wideband acoustic sensors. The approach developed does not require pre-calibrated hydrophones and therefore can be readily adopted in any existing optoacoustic measurement configuration. The methods are successfully confirmed experimentally by measuring the frequency response of a common piezoelectric detector having a cylindrically focused shape.
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Fig.1 The different 2-D configurations analyzed in this paper for measuring the frequency response of acoustic detectors. The acoustic sources are equal to one in the gray areas and to zero outside them; the detectors are on the far right (point, flat, and curved). a and b denote the lateral and axial dimensions of the acoustic source, respectively; c denotes the distance from the source to the detector; d denotes the vertical length of the detector; and v denotes the speed of sound. (a) A source with a smooth boundary and similar dimensions on the axial and lateral axes and a point detector. The dashed curves represent the two extreme arcs over which the integral in (2) is nonzero. (b) A heuristic description of the integral in (2) and of (c) the spectrum of pδ(r,t) for the geometry in Fig. 1(a). (d)–(f) A rectangular optoacoustic source with point, flat, and curved detectors, respectively. The curved detector is focused on to the middle of the proximal edge of the source. The dashed lines represent the longest distances from any point on the detectors to any point on the proximal edge of the sources.

A. Rosenthal, V. Ntziachristos, and D. Razansky,“Optoacoustic methods for frequency calibration of ultrasonic sensors,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, Vol. 58, pp. 316-326 (2011)

© 2010 IEEE Transactions on Medical Imaging

We present a fast model-based inversion algorithm for quantitative 2-D and 3-D optoacoustic tomography. The algorithm is based on an accurate and efficient forward model, which eliminates the need for regularization in the inversion process while providing modeling flexibility essential for quantitative image formation. The resulting image-reconstruction method eliminates stability problems encountered in previously published model-based techniques and, thus, enables performing image reconstruction in real time. Our model-based framework offers a generalization of the forward solution to more comprehensive optoacoustic propagation models, such as including detector frequency response, without changing the inversion procedure. The reconstruction speed and other algorithmic performances are demonstrated using numerical simulation studies and experimentally on tissue-mimicking optically heterogeneous phantoms and small animals. In the experimental examples, the model-based reconstructions manifested correctly the effect of light attenuation through the objects and did not suffer from the artifacts which usually afflict the commonly used filtered backprojection algorithms, such as negative absorption values.
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Fig.3 Description:(a) A simulated high-resolution optoacoustic source image, representing a map of local laser energy deposition; (b) The acoustic signal that is obtained at a distance of 4 cm from the center of the source image with (dashed-red curve) and without (solid-blue curve) noise; (c) the reconstruction obtained using a model-based inversion for the noise-free data and (d) the difference between the reconstructed and originating image; (e) the reconstruction obtained using a model-based inversion for the noisy data and (f) the difference between the reconstructed and originating image.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Fast semi-analytical model-based acoustic inversion for quantitative optoacoustic tomography”, IEEE Trans. Med. Imag., Vol. 29, pp. 1275-1285 (2010).

source:© 2009 IEEE Transactions on Medical Imaging

We report on a new quantification methodology of optoacoustic tomographic reconstructions under heterogeneous illumination conditions representative of realistic whole-body imaging scenarios. Our method relies on the differences in the spatial characteristics of the absorption coefficient and the optical energy density within the medium. By using sparse-representation based decomposition, we exploit these different characteristics to extract both the absorption coefficient and the photon density within the imaged object from the optoacoustic image. In contrast to previous methods, this algorithm is not based on the solution of theoretical light transport equations and it does not require explicit knowledge of the illumination geometry or the optical properties of the object and other unknown or loosely defined experimental parameters, leading to highly robust performance. The method was successfully examined with numerically and experimentally generated data and was found to be ideally suited for practical implementations in tomographic schemes of varying complexity, including multiprojection illumination systems and multispectral optoacoustic tomography (MSOT) studies of tissue biomarkers. [Read More…]

Fig. 2 Demonstration of the iterative algorithm in [9] for recovering the absorption coefficient out of PAT images. (a) Absorption coefficient, (b) the optoacoustic image, and (c) the reconstruction of the iterative algorithm when the scattering coefficient is known exactly. (d) The reconstruction by the iterative algorithm when the scattering coefficient contains a 3% error. The result demonstrate the vulnerability of forward-model-based inversion schemes to even small modeling inaccuracies.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Quantitative optoacoustic signal extraction using sparse signal representation”, IEEE Trans. Med. Imag., Vol. 28, pp. 1997-2006 (2009).

source: © 2012 Optical Society of America

Optical fibers have long been recognized as a promising technology for remote sensing of ultrasound. Nonetheless, very little is known about the characteristics of their spatial response, which is significantly affected by the strong acoustic mismatches between the fiber and surrounding medium. In this Letter, a new method is demonstrated for wideband spatial acoustic characterization of optical fibers. The method is based on the excitation of a point-like acoustic source via the opto-acoustic effect, while a miniature fiber sensor is implemented by a ?-phase-shifted fiber Bragg grating. Despite the relative complexity of acoustic wave propagation in the fiber, its spatial sensitivity in the high frequency band (6–30 MHz) exhibited an orderly pattern, which can be described by a simple model. This property reveals new possibilities for high-performance imaging using fiber-based ultrasound sensors, where knowledge of the sensor’s spatial sensitivity map is generally required.[Read More…]

Fig. 1. (a) Schematic side-view illustration of the fiber sensor and the acoustic source (SD, sensitivity distribution of the sensor; FBG, fiber Bragg grating); (b) a cross section of the fiber.

A. Rosenthal, M. Á. A. Caballero,S. Kellnberger, D. Razansky and V. Ntziachristos, “Spatial characterization of the response of a silica optical fiber to wideband ultrasound,” Opt. Lett. Vol. 37, pp. 3174-3176 (2012).

source: © 2014 Journal of Visualized Experiments

Wideband Optical Detector of Ultrasound for Medical Imaging Applications

Optical sensors of ultrasound are a promising alternative to piezoelectric techniques, as has been recently demonstrated in the field of optoacoustic imaging. In medical applications, one of the major limitations of optical sensing technology is its susceptibility to environmental conditions, e.g. changes in pressure and temperature, which may saturate the detection. Additionally, the clinical environment often imposes stringent limits on the size and robustness of the sensor. In this work, the combination of pulse interferometry and fiber-based optical sensing is demonstrated for ultrasound detection. Pulse interferometry enables robust performance of the readout system in the presence of rapid variations in the environmental conditions, whereas the use of all-fiber technology leads to a mechanically flexible sensing element compatible with highly demanding medical applications such as intravascular imaging. In order to achieve a short sensor length, a pi-phase-shifted fiber Bragg grating is used, which acts as a resonator trapping light over an effective length of 350 µm. To enable high bandwidth, the sensor is used for sideway detection of ultrasound, which is highly beneficial in circumferential imaging geometries such as intravascular imaging. An optoacoustic imaging setup is used to determine the response of the sensor for acoustic point sources at different positions.
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Figure 1. The optical setup used for ultrasound detection. The sensing element is a pi-phase-shifted fiber Bragg grating, and the read-out system is based on pulse interferometry.

A. Rosenthal, S. Kellnberger, M. Omar, D. Razansky, V. Ntziachristos, “Wideband optical detector of ultrasound for medical imaging applications,” J. Vis. Exp., Vol. 87 (2014).

source: © 2014 Acoustical Society of America

In this study a theoretical framework for calculating the acoustic response of optical fiber-based ultrasound sensors is presented. The acoustic response is evaluated for optical fibers with several layers of coating assuming a harmonic point source with arbitrary position and frequency. First, the fiber is acoustically modeled by a layered cylinder on which spherical waves are impinged. The scattering of the acoustic waves is calculated analytically and used to find the normal components of the strains on the fiber axis. Then, a strain-optic model is used to calculate the phase shift experienced by the guided mode in the fiber owing to the induced strains. The framework is showcased for a silica fiber with two layers of coating for frequencies in the megahertz regime, commonly used in medical imaging applications. The theoretical results are compared to experimental data obtained with a sensing element based on a pi-phase-shifted fiber Bragg grating and with photoacoustically generated ultrasonic signals.
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Spherical waves generated from a point source scatter from the optical fiber which is located at a distance of d from the source. The radii of the glass fiber and the coatings are 62.5, 110, and 130 μm, respectively.

A. Veres, Amir Rosenthal, P. Burgholzer, V. Ntziachristos, and T. Berer, „Characterization of the spatio-temporal response of optical fiber sensors: scattering of spherical waves from a layered cylinder,” J. Acoust. Soc. Am. Vol. 135, pp. 1853-1862 (2014).

source: © 2014 Laser & Photonics Reviews

Miniaturized optical detectors of ultrasound represent a promising alternative to piezoelectric technology and may enable new minimally invasive clinical applications, particularly in the field of optoacoustic imaging. However, the use of such detectors has so far been limited to controlled lab environments, and has not been demonstrated in the presence of mechanical disturbances, common in clinical imaging scenarios. Additionally, detection sensitivity has been inherently limited by laser noise, which hindered the use of sensing elements such as optical fibers, which exhibit a weak response to ultrasound. In this work, coherence‐restored pulse interferometry (CRPI) is introduced – a new paradigm for interferometric sensing in which shot‐noise limited sensitivity may be achieved alongside robust operation. CRPI is implemented with a fiber‐based resonator, demonstrating over an order of magnitude higher sensitivity than that of conventional 15 MHz intravascular ultrasound probes. The performance of the optical detector is showcased in a miniaturized all‐optical optoacoustic imaging catheter.
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Experimental demonstration of ultrasound detection in turbulent water using coherence restored pulse interferometry (CRFI) with passive demodulation. (a) Schematic description of the setup used to test CRPI for detecting ultrasound under a strong external disturbance. (b) The resonance shift measured with the passive‐demodulation scheme when the water pump was on. The inset shows one of the ultrasound signals measured under the volatile environmental conditions.

A. Rosenthal, S.Kellnberger, D. Bozhko, A. Chekkoury, M. Omar, D. Razansky, and V. Ntziachristos, “Sensitive interferometric detection of ultrasound for clinical imaging applications,” Las. Photonics Rev., Vol. 8, pp. 450-457 (2014).

source: © 2014 Applied Physics Letters

A miniaturized ultrasound sensor is demonstrated in a silicon-on-insulator platform. The sensor is based on a π-phase-shifted Bragg grating formed by waveguide corrugation. Ultrasound detection is performed by monitoring shifts in the resonance frequency of the grating using pulse interferometry. The device is characterized by measuring its response to a wideband acoustic point source generated using the optoacoustic effect. Experimental results show that the sensor’s response is dominated by the formation of surface acoustic waves. 
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(a) A schematic, top-view description of the π-WBG (not to scale). w = 500 nm is the waveguide width, Δw = 40 nm is the corrugation depth, L = 250 μm is the length of the grating, and Λ = 320 nm is the period length. (b) A cross-sectional view of the SOI waveguide. (c) An illustration of the fiber coupling to the π-WBG. (d) The transmission spectrum of the connectorized π-WBG device. The inset shows the transmission notch magnified. (e), (f) Schematic drawings depicting the acoustic-characterization experiment for the π-WBG sensor.

A. Rosenthal, M. Omar, H. Estrada, D. Razansky, V. Ntziachristos, „Embedded ultrasound sensor in a silicon-on-insulator photonic platform,” Appl. Phys. Lett. Vol. 104, pp. 021116 (2014).