Model-based image reconstruction in optoacoustic tomography

The effect of limited tomographic coverage on the quality of the reconstructed image [13]. (a) A reconstruction of a cylindrical phantom with a square inclusion from full-view experimental data. (b) Model-based reconstruction with no regularizarion when only 130º of the projection data is used. (c) Back-projection reconstruction of the phantom in the limited-view scenario. (d) Regularized model-based reconstruction of the phantom in the limited-view scenario.

source:© 2014 Computer Vision in Medical Imaging

Optoacoustic tomography is a powerful hybrid bioimaging method which retains rich optical contrast and diffraction-limited ultrasonic resolution at depths of varying from millimeters to several centimeters in biological tissue irrespective of photon scattering. Optoacoustic imaging is commonly performed with high power optical pulses whose absorption leads to instantaneous temperature increase, thermal expansion and, subsequently, to the generation of a pressure field proportional to the distribution of the absorbed energy. For tomographic data acquisition, the optoacoustically generated waves are detected on a surface surrounding the imaged region. Recovery of the initially generated pressure distribution from the detected tomographic projections, and hence of the optical energy deposition in the tissue, constitutes the inverse problem of optoacoustic tomography, which is often solved using closed-form inversion formulae. However, those closed-form solutions are only exact for ideal detection geometries, which often do not accurately represent the experimental conditions. Model-based image-reconstruction techniques represent an alternative approach to solving the inverse problem that can significantly reduce image artifacts associated with approximated analytical formulae and significantly enhance image quality in non-ideal imaging scenarios. In the model-based reconstruction, a linear forward model is constructed to accurately describe the experimental conditions of the imaging setup. Inversion is performed numerically and may include regularization when the projection data is insufficient. This chapter demonstrates the benefits of the model-based reconstruction approach and describes numerically efficient methods for its implementation.
[Read More…]

Fig. 5 A comparison between back-projection and model-based reconstructions of a mouse heart in a 3D limited view scenario. The reduction of streak aritifacts in the model-based reconstruction
is readily seen in the images.

A. Rosenthal, D. Razansky, V. Ntziachristos, „Model-based image reconstruction in optoacoustic tomography,“ in Computer Vision in Medical Imaging, edited by C.H. Chen; World Scientific Publishing, October 2013.

Spatiospectral denoising framework for multispectral optoacoustic imaging based on sparse signal representation

Denoising of a purely experimental dataset in the case of very strong parasitic noise due to electromagnetic interference

source:© 2014 Medical Physics

Purpose:
One of the major challenges in dynamic multispectral optoacoustic imaging is its relatively low signal‐to‐noise ratio which often requires repetitive signal acquisition and averaging, thus limiting imaging rate. The development of denoising methods which prevent the need for signal averaging in time presents an important goal for advancing the dynamic capabilities of the technology.

Methods:
In this paper, a denoising method is developed for multispectral optoacoustic imaging which exploits the implicit sparsity of multispectral optoacoustic signals both in space and in spectrum. Noise suppression is achieved by applying thresholding on a combined wavelet‐Karhunen–Loève representation in which multispectral optoacoustic signals appear particularly sparse. The method is based on inherent characteristics of multispectral optoacoustic signals of tissues, offering promise for general application in different incarnations of multispectral optoacoustic systems.

Fig. 1 In vivo multispectral optoacoustic measurements used for the creation of noise simulations. (a) and (b) Anatomical image of a mouse brain at an excitation wavelength of 690 nm (a) and 900 nm (b). (c) and (d) Anatomical image of the kidney area of a mouse at an excitation wavelength of 690 nm (c) and 900 nm (d).

Results:
The performance of the proposed method is demonstrated on mouse images acquired in vivo for two common additive noise sources: time‐varying parasitic signals and white noise. In both cases, the proposed method shows considerable improvement in image quality in comparison to previously published denoising strategies that do not consider multispectral information.

Conclusions:
The suggested denoising methodology can achieve noise suppression with minimal signal loss and considerably outperforms previously proposed denoising strategies, holding promise for advancing the dynamic capabilities of multispectral optoacoustic imaging while retaining image quality.
[Read More…]

S. Tzoumas, A, Rosenthal, C. Lutzweiler, D. Razansky, and V. Ntziachristos, “Spatiospectral denoising framework for multispectral optoacoustic imaging based on sparse signal representation,” Med. Phys., Vol. 41 (2014).

Wideband optical detector of ultrasound for medical imaging applications

An illustration of the optoacoustic setup used for measuring the acoustic response of the optical detector

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.
[Read More…]

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).

Characterization of the spatio-temporal response of optical fiber sensors: scattering of spherical waves from a layered cylinder

Experimental arrangement: An opto-acoustical source (R=50 μm) is scanned parallel to a FBG sensor in a distance of d

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.
[Read More…]

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).

Sensitive interferometric detection of ultrasound for clinical imaging applications

A schematic of the system

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.
[Read More…]

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).

Embedded ultrasound sensor in a silicon-on-insulator photonic platform

The signals obtained for four linear scans of the sensor

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. 
[Read More…]

(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).

Characterization of the Spatio-temporal Response of Optical Fiber Sensors to Incident Spherical Waves

source: © 2014 The Journal of the 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.  [Read more…]

Fig. 1 Problem statement: 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.

István A. Veres, Peter Burgholzer, Thomas Berer, Amir Rosenthal, Georg Wissmeyer, and Vasilis Ntziachristos,”Characterization of the spatio-temporal response of optical fiber sensors to incident spherical waves,” The Journal of the Acoustical Society of America 135, 1853 (2014)

Multiscale Multispectral Optoacoustic Tomography by a Stationary Wavelet Transform Prior to Unmixing

Multiscale view of perfusion imaging in the extremities.

source: © 2014  IEEE Transactions on Medical Imaging. 

Multispectral optoacoustic tomography (MSOT) utilizes broadband ultrasound detection for imaging biologically-relevant optical absorption features at a range of scales. Due to the multiscale and multispectral features of the technology, MSOT comes with distinct requirements in implementation and data analysis. In this work, we investigate the interplay between scale, which depends on ultrasonic detection frequency, and optical multispectral spectral analysis, two dimensions that are unique to MSOT and represent a previously unexplored challenge. We show that ultrasound frequency-dependent artifacts suppress multispectral features and complicate spectral analysis. In response, we employ a wavelet decomposition to perform spectral unmixing on a per-scale basis (or per ultrasound frequency band) and showcase imaging of fine-scale features otherwise hidden by low frequency components. We explain the proposed algorithm by means of simple simulations and demonstrate improved performance in imaging data of blood vessels in human subjects.  [Read more…]

Fig. 5 A simulated example. Each of the single wavelength images (a), which contain negative values, is decomposed by SWT and individually reconstructed (inverse SWT=ISWT ), as shown in (b). It can be observed in this particular case that the fine scale features are mainly captured in the detail coefficients, while the coarse scale features are mainly captured in the level three approximation. NNLS is applied per scale and the resulting oxyhemoglobin and deoxyhemoglobin images are shown (c). These images compare favorably with the “ground truth” images (d), which are the HbO2 and Hb distributions used to generate the data, but with negative values truncated. The images obtained by the conventional approach (e), NNLS without SWT, do not resemble the “ground truth” because of the effect of negative value artifacts. The example applies the Daubechies wavelet with two vanishing moments and a three level decomposition.

Adrian Taruttis , Amir Rosenthal , Marcin Kacprowicz , Neal C. Burton , Vasilis Ntziachristos, “Multiscale multispectral optoacoustic tomography by a stationary wavelet transform prior to unmixing,” IEEE transactions on medical imaging, Volume 33, Issue 5, Pages 1194-1202