A prototype time-domain fluorescence diffusion optical tomography (FDOT) system using near-infrared light is
presented. The system employs two pulsed light sources, 32 source fibers and 32 detection channels, working separately
for acquiring the temporal distribution of the photon flux on the tissue surface. The light sources are provided by low
power picosecond pulsed diode lasers at wavelengths of 780 nm and 830 nm, and a 1×32-fiber-optic-switch sequentially
directs light sources to the object surface through 32 source fibers. The light signals re-emitted from the object are
collected by 32 detection fibers connected to four 8×1 fiber-optic-switch and then routed to four time-resolved
measuring channels, each of which consists of a collimator, a filter wheel, a photomultiplier tube (PMT)
photon-counting head and a time-correlated single photon counting (TCSPC) channel. The performance and efficacy of
the designed multi-channel PMT-TCSPC system are assessed by reconstructing the fluorescent yield and lifetime
images of a solid phantom.
In this paper we apply the shape-based approach to diffuse optical tomography (DOT) reconstruction,
which aims to simultaneously recover the smooth boundaries of the tissue regions and the constant
coefficients within them. An advantage of shape-based solutions is the reduction of the unknown
parameters, which is especially important for nonlinear ill-posed inverse problems. We introduce a
Fourier series representation of the closed region boundaries and a boundary element method (BEM)
for the forward model. For inverse problem the Levenberg-Marquardt optimization process is
implemented here. The performance of the proposed method is evaluated by simulations at different
noise levels and phantom experiment which is embedded a single cylinder target. We can get
reasonable reconstruction from both Gauss noise and real noise in the experimental study. The results
illuminate that the methodology is very promising and of global convergence, the boundaries and the
optical coefficients can both be recovered with good accuracy from the noisy measurements.
Time-domain optical mammography has attracted many attentions since it can diagnose early breast cancer by efficiently
reconstructing optical parameter. However, the currently available image reconstruction algorithms for time-domain
optical mammography are badly influenced by different Jacobian magnitudes of absorption coefficient and reduced
scattering coefficient. To improve image quality, we proposed an efficient Jacobian scaling method with a relative data
type based on generalized pulse spectrum technique. Our simulated and experimental reconstructions show that this
Jacobian scaling method can efficiently enhancing the quality of reconstructed image.
It is generally believed that the inverse problem in diffuse optical tomography (DOT) is highly ill-posed and its solution
is always under-determined and sensitive to noise, which is the main problem in the application of DOT. In this paper,
we propose a method on image reconstruction for time-domain diffuse optical tomography based on panel detection and
Finite-Difference Method, and introduce an approach to reduce the number of unknown parameters in the reconstruction
process. We propose a multi-level scheme to reduce the number of unknowns by parameterizing the spatial distribution
of optical properties via wavelet transform and then reconstruct the coefficients of this transform. Compared with previous
traditional uni-level full spatial domain algorithm, this method can efficiently improve the reconstruction quality.
Numerical simulations show that wavelet-based multi-level inversion is superior to the uni-level algebraic reconstruction technique.
Breast diffuse optical tomography is now highly expected as a potential routine inspection means for the high specificity
and safety. Many efforts have been put to overcome its intrinsic adversities, such as low spatial resolution and
quantitativeness. In this study, we propose a technique for enhancing image reconstruction of time-domain breast diffuse
optical tomography (DOT). The technique uses finite-element-method (FEM) solution to the Laplace-transformed
diffusion equation as the forward model, and an inverse model of Newton-Raphson iterative scheme. Through a target
location that is provided by the preliminary image that is reconstructed using global optode arrangement or other
techniques, we can obtain a more accurate image reconstruction by relocating all the optodes within the targeted region.
The simulative experiments show that the performance of reconstructed image is evidently improved by the aid of the
optodes relocation strategy.
Near infrared diffusion optical tomography (DOT) is one of promising tools for breast tumor detection because of its
noninvasiveness and potential portability. In this paper, we propose an image reconstruction method for time-domain
breast diffuse optical tomography, which offers simultaneous recovery of the absorption and scattering coefficients.
Under the panel-compression detection mode, we propose a forward model based on the finite-difference solution to the
diffusion equation, and furthermore develop an inverse model within a framework of the Newton-Raphson linearization
and the generalized pulse spectrum technique. The proposed methodology is validated by experiments on a
specifically-designed solid slab phantom containing two
deeply-located absorption and scattering contrasting cylinders,
using our multi-channel time-correlated single-photon-counting system.
The investigations on the optical mammography have attracted many clinical attentions, since the conventional X-ray mammography has shown some deficiencies in sensitivity, specificity, security and comfortableness. In this study, we propose an image reconstruction technique of time-domain diffuse optical tomography (DOT) for the optical mammography in the first place. This technique uses the finite-element method (FEM) solution to the Laplace-transformed coupled diffusion equations as the forward model, and develops an inverse model based on a Newton-Raphson scheme. On the basis of the preliminary reconstructed image of this technique, we also present an efficient Jacobian reduction method by the aid of image segmentation to obtain a more accurate image reconstruction. The simulative experiments reveal that the performance of reconstructed image by the aid of the image segmentation makes a notable improvement on the conventional algorithm in breast phantom image.
We present our preliminary results on two-dimensional (2-D) optical tomographic imaging of hemodynamic changes of two preterm infant brains in different ventilation settings conditions. The investigations use the established two-wavelength, 16-channel time-correlated single photon counting system for the detection, and the generalized pulse spectrum technique based algorithm for the image reconstruction. The experiments demonstrate that two-dimensional diffuse optical tomography may be a potent and relatively simple way of investigating the functions and neural development of infant brains in the perinatal period.
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