Rhesus monkey brain imaging through intact skull with thermoacoustic tomography

Two-dimensional microwave-induced thermoacoustic tomography (TAT) is applied to imaging the Rhesus monkey brain through the intact skull. To reduce the wavefront distortion caused by the skull, only the low-frequency components of the thermoacoustic signals (< 1 MHz) are used to reconstruct the TAT images. The methods of signal processing and image reconstruction are validated by imaging a lamb kidney. The resolution of the system is found to be 4 mm when we image a 1-month-old monkey head containing inserted needles. We also image the coronal and axial sections of a 7-month-old monkey head. Brain features that are 3 cm deep in the head are imaged clearly. Our results demonstrate that TAT has potential for use in portable, cost-effective imagers for pediatric brains

Application of time reversal to thermoacoustic tomography

Reconstruction for thermoacoustic tomography in an arbitrary detection geometry is proposed by time-reversing the measured field back to the time when the thermoacoustic sources are excited. Time reversal of the field can be implemented efficiently by applying the delay-and-sum algorithm. The theoretical conclusions are supported by a numerical simulation of three-dimensional thermoacoustic tomography

Effects of acoustic heterogeneity on the breast thermoacoustic tomography

The effects of wavefront distortions induced by acoustic heterogeneities in breast thermoacoustic tomography (TAT) are studied. First, amplitude distortions are shown to be insignificant for different scales of acoustic heterogeneities. Next, the effects of phase distortions (errors in time-of-flight) in our numerical studies are investigated, and the spreads of point sources and boundaries caused by the phase distortions are studied. After that, a demonstration showing that the blurring of images can be compensated for by using the distribution of acoustic velocity in the tissues in the reconstructions is presented. Last, the differences in the effects of acoustic heterogeneity and the generation of speckles in breast TAT and breast ultrasound imaging are discussed

Effects of acoustic heterogeneity in breast thermoacoustic tomography

The effects of wavefront distortions induced by acoustic heterogeneities in breast thermoacoustic tomography (TAT) are studied. Amplitude distortions are shown to be insignificant for different scales of acoustic heterogeneities. For wavelength-scale, or smaller, heterogeneities, amplitude distortion of the wavefront is minor as a result of diffraction when the detectors are placed in the far field of the heterogeneities. For larger-scale heterogeneities at the parenchyma wall, by using a ray approach (geometric optics), we show that no refraction-induced multipath interference occurs and, consequently, that no severe amplitude distortion, such as is found in ultrasound tomography, exists. Next, we consider the effects of phase distortions (errors in time-of-flight) in our numerical studies. The numerical results on the spreads of point sources and boundaries caused by the phase distortions are in good agreement with the proposed formula. After that, we demonstrate that the blurring of images can be compensated for by using the distribution of acoustic velocity in the tissues in the reconstructions. The effects of the errors in the acoustical velocities on this compensation also are investigated. An approach to implement the compensation using only TAT data is proposed. Lastly, the differences in the effects of acoustic heterogeneity and the generation of speckles in breast TAT and breast ultrasound imaging are discussed

Limited view thermoacoustic tomography

Truncated conjugate gradient method was applied to study the limited view problem in thermoacoustic tomography, and the results were compared with those of modified backprojection method, which is the backprojection of the first order time derivative of acoustic signals. Our numerical simulations showed that there is complete data for a stable and perfect reconstruction in a 2-D π-view problem, where the least angle acquired by the detection curve is π when viewed from the imaged region of interest. On the contrary, in a problem where the view is less than π, data is incomplete, and artifacts and quantitative errors were obvious in the reconstructed images. It was pointed out that the result after one iteration in truncated conjugate gradient method is equivalent to that of modified backprojection, which can restore the high frequency information of imaged objects. The low frequency information can be recovered significantly in the next ten iterations of truncated conjugate gradient method

Time Reversal and Its Application to Tomography with Diffracting Sources

An exact time-domain method is proposed to time reverse a transient scalar wave using only the field measured on an arbitrary closed surface enclosing the initial source. Under certain conditions, a time-reversed field can be approximated by retransmitting the measured signals in a reversed temporal order. Exact reconstruction for three-dimensional broadband diffraction tomography (a linearized inverse scattering problem) is proposed by time-reversing the measured field back to the time when each secondary source is excited. The algorithm is verified by a numerical simulation. Extension to the case using Green’s function in a heterogeneous medium is discussed

Signal processing in microwave-induced thermoacoustic tomography

Microwave-induced thermoacoustic tomography was explored to image biological tissues. Short microwave pulses irradiated tissues to generate acoustic waves by thermoelastic expansion. The microwave-induced thermoacoustic waves were detected with a focused ultrasonic transducer to obtain two-dimensional tomographic images of biological tissues. The dependence of the axial and the lateral resolutions on the spectra of the signals was studied. A self-adaptive filter was applied to the temporal piezoelectric signals from the transducer to increase the weight of the high-frequency components, which improved the lateral resolution, and to broaden the spectrum of the signal, which enhanced the axial resolution

Time-domain reconstruction algorithms and numerical simulations for thermoacoustic tomography in various geometries

In this paper, we present time-domain reconstruction algorithms for the thermoacoustic imaging of biological tissues. The algorithm for a spherical measurement configuration has recently been reported in another paper. Here, we extend the reconstruction algorithms to planar and cylindrical measurement configurations. First, we generalize the rigorous reconstruction formulas by employing Green's function technique. Then, in order to detect small (compared with the measurement geometry) but deeply buried objects, we can simplify the formulas when two practical conditions exist: 1) that the high-frequency components of the thermoacoustic signals contribute more to the spatial resolution than the low-frequency ones, and 2) that the detecting distances between the thermoacoustic sources and the detecting transducers are much greater than the wavelengths of the high-frequency thermoacoustic signals (i.e., those that are useful for imaging). The simplified formulas are computed with temporal back projections and coherent summations over spherical surfaces using certain spatial weighting factors. We refer to these reconstruction formulas as modified back projections. Numerical results are given to illustrate the validity of these algorithms

Exact frequency-domain reconstruction for thermoacoustic tomography. I. Planar geometry

We report an exact and fast Fourier-domain reconstruction algorithm for thermoacoustic tomography in a planar configuration assuming thermal confinement and constant acoustic speed. The effects of the finite size of the detector and the finite length of the excitation pulse are explicitly included in the reconstruction algorithm. The algorithm is numerically and experimentally verified. We also demonstrate that the blurring caused by the finite size of the detector surface is the primary limiting factor on the resolution and that it can be compensated for by deconvolution