Acoustic inversion in optoacoustic tomography : A review

A 2D illustration of the effect of the limited-view scenario on the characteristics of the reconstruction under the far-field approximation.

source:© 2013 Current Medical Imaging Reviews

Optoacoustic tomography enables volumetric imaging with optical contrast in biological tissue at depths beyond the optical mean free path by the use of optical excitation and acoustic detection. The hybrid nature of optoacoustic tomography gives rise to two distinct inverse problems: The optical inverse problem, related to the propagation of the excitation light in tissue, and the acoustic inverse problem, which deals with the propagation and detection of the generated acoustic waves. Since the two inverse problems have different physical underpinnings and are governed by different types of equations, they are often treated independently as unrelated problems. From an imaging standpoint, the acoustic inverse problem relates to forming an image from the measured acoustic data, whereas the optical inverse problem relates to quantifying the formed image. This review focuses on the acoustic aspects of optoacoustic tomography, specifically acoustic reconstruction algorithms and imaging-system practicalities. As these two aspects are intimately linked, and no silver bullet exists in the path towards high-performance imaging, we adopt a holistic approach in our review and discuss the many links between the two aspects. Four classes of reconstruction algorithms are reviewed: time-domain (so called back-projection) formulae, frequency-domain formulae, time-reversal algorithms, and model-based algorithms. These algorithms are discussed in the context of the various acoustic detectors and detection surfaces which are commonly used in experimental studies. We further discuss the effects of non-ideal imaging scenarios on the quality of reconstruction and review methods that can mitigate these effects. Namely, we consider the cases of finite detector aperture, limited-view tomography, spatial under-sampling of the acoustic signals, and acoustic heterogeneities and losses.
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Fig. 2 The three most common detection surfaces used in optoacoustic tomography: (a) spherical, (b) cylindrical, and (c) planar. These
detection surfaces may be achieved experimentally by scanning either a single detector or a detector array over the surface. The arrows show
the directions in which a single detectors needs to be scanned. The detector types appropriate for each of these detection surfaces are listed in
(Table 1).

A. Rosenthal, D. Razansky, V. Ntziachristos, “Acoustic inversion in optoacoustic tomography: a review,” Curr. Med. Imaging Rev., Vol. 9, pp. 318-336 (2013).

Optoacoustic determination of the spatial and temporal responses of ultrasound transducers

Validation of the global properties of the hybrid total impulse response

source:© 2013 IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

The characterization of the spatial and frequency response of acoustic detectors is important for enabling accurate optoacoustic imaging. In this work, we developed a hybrid method for the characterization of the spatially dependent response of ultrasound detectors. The method is based on the experimental determination of the receive-mode electrical impulse response (EIR) of the sensor, which is subsequently convolved with the corresponding spatial impulse response (SIR), computed numerically. The hybrid method is shown to have superior performance over purely experimental techniques in terms of accurate determination of the spatial and temporal responses of ultrasonic detectors, in high as well as low sensitivity regions of the sensor. 
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Fig. 1 Effect of the spatial impulse response (SIR) on an optoacoustic signal. (a) Optoacoustic waves emanating from the source at r ′ reach the different points of the transducer, r d1 and r d2 , at different times t1 and t2(c represents the speed of sound). (b) Geometry for the numerical example: the sensor is 1.8 mm along the y direction, 15 mm along the z direction (here the sensor is shown from the side) and it is cylindrically focused to 40 mm. The source is located at 33 mm from the sensor along its median axis x . The relative dimensions have been exaggerated for ease of representation. (c) Simulated optoacoustic signal (solid blue curve) and the distorted signal (dashed red curve) that results after convolution with the SIR at a point out of focus. Inset: SIR used for convolution. (d) Frequency spectra of the simulated signal (solid blue curve) and the signal convolved with the SIR (dashed red curve). Inset: spectrum of the SIR.

M. Á. A. Caballero, A. Rosenthal, A. Bühler, D. Razansky and V. Ntziachristos, “Optoacoustic determination of the spatial and temporal responses of ultrasound transducers,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control, Vol. 60, pp. 1234-1244 (2013).

Optoacoustic determination of spatio-temporal responses of ultrasound sensors

source: © 2013 IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

The characterization of the spatial and frequency response of acoustic detectors is important for enabling accurate optoacoustic imaging. In this work, we developed a hybrid method for the characterization of the spatially dependent response of ultrasound detectors. The method is based on the experimental determination of the receive-mode electrical impulse response (EIR) of the sensor, which is subsequently convolved with the corresponding spatial impulse response (SIR), computed numerically. The hybrid method is shown to have superior performance over purely experimental techniques in terms of accurate determination of the spatial and temporal responses of ultrasonic detectors, in high as well as low sensitivity regions of the sensor.  [Read more…]

Fig. 1 Effect of the spatial impulse response (SIR) on an optoacoustic signal. (a) Optoacoustic waves emanating from the source at r ′ reach the different points of the transducer, r d1 and r d2 , at different times t1 and t2(c represents the speed of sound). (b) Geometry for the numerical example: the sensor is 1.8 mm along the y direction, 15 mm along the z direction (here the sensor is shown from the side) and it is cylindrically focused to 40 mm. The source is located at 33 mm from the sensor along its median axis x . The relative dimensions have been exaggerated for ease of representation. (c) Simulated optoacoustic signal (solid blue curve) and the distorted signal (dashed red curve) that results after convolution with the SIR at a point out of focus. Inset: SIR used for convolution. (d) Frequency spectra of the simulated signal (solid blue curve) and the signal convolved with the SIR (dashed red curve). Inset: spectrum of the SIR.

Miguel Angel Araque Caballero , Amir Rosenthal , Andreas Buehler , Daniel Razansky , Vasilis Ntziachristos,”Optoacoustic determination of spatio-temporal responses of ultrasound sensors,” IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control ( Volume: 60 , Issue: 6 , June 2013 )

Modeling the shape of cylindrically focused transducers in three-dimensional optoacoustic tomography

source: © 2013 Journal of Biomedical Optics

Cross sectional tomographic systems based on cylindrically focused transducers are widely used in optoacoustic (photoacoustic) imaging due to important advantages they provide such as high-cross sectional resolution, real-time imaging capacity, and high-throughput performance. Tomographic images in such systems are commonly obtained by means of two-dimensional (2-D) reconstruction procedures assuming point-like detectors, and volumetric (whole-body) imaging is performed by superimposing the cross sectional images for different positions along the scanning direction. Such reconstruction strategy generally leads to in-plane and out-of-plane artifacts as well as significant quantification errors. Herein, we introduce two equivalent full three-dimensional (3-D) models capable of accounting for the shape of cylindrically focused transducers. The performance of these models in 3-D reconstructions considering several scanning positions is analyzed in this work. Improvements of the results rendered with the introduced reconstruction procedure as compared with the 2-D-based approach are described and discussed for simulations and experiments with phantoms and biological tissues.  [Read more…]

Fig. 2 Full-view tomographic geometry for the simulations and experiments. The ROI is depicted by the red cuboid. The blue points represent the positions of the centers of the cylindrically focused detectors. All the transducer positions lie on the surface of a cylinder with radius 2.54 cm.

Daniel Queirós, Xose Luis Dean-Ben, Andreas Buehler, Daniel Razansky, Amir Rosenthal, Vasilis Ntziachristos,”Modeling the shape of cylindrically focused transducers in three-dimensional optoacoustic tomography,” J. of Biomedical Optics, 18(7), 076014 (2013)

Weighted model-based optoacoustic reconstruction in acoustic scattering media

source: © 2013 Physics in Medicine & Biology

Model-based optoacoustic inversion methods are capable of eliminating image artefacts associated with the widely adopted back-projection reconstruction algorithms. Yet, significant image artefacts might also occur due to reflections and scattering of optoacoustically-induced waves from strongly acoustically-mismatched areas in tissues. Herein, we modify the model-based reconstruction methodology to incorporate statistically-based weighting in order to minimize these artefacts. The method is compared with another weighting procedure termed half-image reconstruction, yielding generally better results. The statistically-based weighting is subsequently verified experimentally, attaining quality improvement of the optoacoustic image reconstructions in the presence of acoustic mismatches in tissue phantoms and small animals ex-vivo.  [Read more…]

Fig. 5 Tomographic reconstructions of the zebrafish obtained with the IMMI algorithm (a)–(c), with the statistically-based weighted IMMI algorithm (d)–(f) and with the half-time weighted IMMI algorithm (g)–(i). The reconstructions are done by considering all the measuring locations in a full-view scenario (a), (d), (g), or for a limited-view case by taking measuring locations along an arc covering an angle of 270° (b), (e), (h) or 180° (c), (f), (i). For the limited-view case, the centre of the detection arc is located above the images. (j) and (k) show a comparison of the reconstructions obtained with the IMMI algorithm and the statistically-based IMMI algorithm for several slices. The area A is taken as the as the area inside the dashed circumferences and the weighting parameter ω = 1 for all cases.

X Luís Deán-Ben, Rui Ma, Amir Rosenthal, Vasilis Ntziachristos and Daniel Razansky,”Weighted model-based optoacoustic reconstruction in acoustic scattering media,” Physics in Medicine & Biology, Volume 58, Number 16 (2013)