205 research outputs found
Quantitative photoacoustic tomography with piecewise constant material parameters
The goal of quantitative photoacoustic tomography is to determine optical and
acoustical material properties from initial pressure maps as obtained, for
instance, from photoacoustic imaging. The most relevant parameters are
absorption, diffusion and Grueneisen coefficients, all of which can be
heterogeneous. Recent work by Bal and Ren shows that in general, unique
reconstruction of all three parameters is impossible, even if multiple
measurements of the initial pressure (corresponding to different laser
excitation directions at a single wavelength) are available.
Here, we propose a restriction to piecewise constant material parameters. We
show that in the diffusion approximation of light transfer, piecewise constant
absorption, diffusion and Gr\"uneisen coefficients can be recovered uniquely
from photoacoustic measurements at a single wavelength. In addition, we
implemented our ideas numerically and tested them on simulated
three-dimensional data
A variational method for quantitative photoacoustic tomography with piecewise constant coefficients
In this article, we consider the inverse problem of determining spatially
heterogeneous absorption and diffusion coefficients from a single measurement
of the absorbed energy (in the steady-state diffusion approximation of light
transfer). This problem, which is central in quantitative photoacoustic
tomography, is in general ill-posed since it admits an infinite number of
solution pairs. We show that when the coefficients are known to be piecewise
constant functions, a unique solution can be obtained. For the numerical
determination of the coefficients, we suggest a variational method based based
on an Ambrosio-Tortorelli-approximation of a Mumford-Shah-like functional,
which we implemented numerically and tested on simulated two-dimensional data
Visual Quality Enhancement in Optoacoustic Tomography using Active Contour Segmentation Priors
Segmentation of biomedical images is essential for studying and
characterizing anatomical structures, detection and evaluation of pathological
tissues. Segmentation has been further shown to enhance the reconstruction
performance in many tomographic imaging modalities by accounting for
heterogeneities of the excitation field and tissue properties in the imaged
region. This is particularly relevant in optoacoustic tomography, where
discontinuities in the optical and acoustic tissue properties, if not properly
accounted for, may result in deterioration of the imaging performance.
Efficient segmentation of optoacoustic images is often hampered by the
relatively low intrinsic contrast of large anatomical structures, which is
further impaired by the limited angular coverage of some commonly employed
tomographic imaging configurations. Herein, we analyze the performance of
active contour models for boundary segmentation in cross-sectional optoacoustic
tomography. The segmented mask is employed to construct a two compartment model
for the acoustic and optical parameters of the imaged tissues, which is
subsequently used to improve accuracy of the image reconstruction routines. The
performance of the suggested segmentation and modeling approach are showcased
in tissue-mimicking phantoms and small animal imaging experiments.Comment: Accepted for publication in IEEE Transactions on Medical Imagin
Asymptotic Expansions for Higher Order Elliptic Equations with an Application to Quantitative Photoacoustic Tomography
In this paper, we derive new asymptotic expansions for the solutions of
higher order elliptic equations in the presence of small inclusions. As a
byproduct, we derive a topological derivative based algorithm for the
reconstruction of piecewise smooth functions. This algorithm can be used for
edge detection in imaging, topological optimization, and for inverse problems,
such as Quantitative Photoacoustic Tomography, for which we demonstrate the
effectiveness of our asymptotic expansion method numerically
Quantitative photoacoustic tomography using illuminations from a single direction.
Quantitative photoacoustic tomography is an emerging imaging technique aimed at estimating optical parameters inside tissues from photoacoustic images, which are formed by combining optical information and ultrasonic propagation. This optical parameter estimation problem is ill-posed and needs to be approached within the framework of inverse problems. It has been shown that, in general, estimating the spatial distribution of more than one optical parameter is a nonunique problem unless more than one illumination pattern is used. Generally, this is overcome by illuminating the target from various directions. However, in some cases, for example when thick samples are investigated, illuminating the target from different directions may not be possible. In this work, the use of spatially modulated illumination patterns at one side of the target is investigated with simulations. The results show that the spatially modulated illumination patterns from a single direction could be used to provide multiple illuminations for quantitative photoacoustic tomography. Furthermore, the results show that the approach can be used to distinguish absorption and scattering inclusions located near the surface of the target. However, when compared to a full multidirection illumination setup, the approach cannot be used to image as deep inside tissues
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