205 research outputs found
Quantitative photoacoustic imaging in radiative transport regime
The objective of quantitative photoacoustic tomography (QPAT) is to
reconstruct optical and thermodynamic properties of heterogeneous media from
data of absorbed energy distribution inside the media. There have been
extensive theoretical and computational studies on the inverse problem in QPAT,
however, mostly in the diffusive regime. We present in this work some numerical
reconstruction algorithms for multi-source QPAT in the radiative transport
regime with energy data collected at either single or multiple wavelengths. We
show that when the medium to be probed is non-scattering, explicit
reconstruction schemes can be derived to reconstruct the absorption and the
Gruneisen coefficients. When data at multiple wavelengths are utilized, we can
reconstruct simultaneously the absorption, scattering and Gruneisen
coefficients. We show by numerical simulations that the reconstructions are
stable.Comment: 40 pages, 13 figure
Computational Inverse Problems
Inverse problem typically deal with the identification of unknown quantities from indirect measurements and appear in many areas in technology, medicine, biology, finance, and econometrics. The computational solution of such problems is a very active, interdisciplinary field with close connections to optimization, control theory, differential equations, asymptotic analysis, statistics, and probability. The focus of this workshop was on hybrid methods, model reduction, regularization in Banach spaces, and statistical approaches
Innovative boundary integral and hybrid methods for diffuse optical imaging
Diffuse Optical Imaging (DOI), the study of the propagation of Near Infra-Red (NIR) light in
biological media, is an emerging method in medical imaging. Its state-of-the-art is non-invasive,
versatile and reasonably inexpensive.
In Diffuse Optical Tomography (DOT), the adaptation of numerical methods such as the
Finite Element Method (FEM) and, more recently the Boundary Element Method (BEM), has
allowed the treatment of complex problems, even for in vivo functional three-dimensional imaging.
This work is the first attempt to combine these two methods in DOT.
The BEM-FEM is designed to tackle layered turbid media problems. It focuses on the region
of interest by restraining the reconstruction to it. All other regions are treated as piecewise-constant
in a surface-integral approach. We validated the model in concentric spheres and found
that it compared well with an analytical result. We then performed functional imaging of the
neonate’s motor cortex in vivo, in a reconstruction restricted to the brain, both with FEM and
BEM-FEM.
Another use of the BEM in DOI is also outlined. NIR Spectroscopy (NIRS) devices are
particularly used in brain monitoring and Diffuse Optical Cortical Mapping (DOCM). Unfortunately,
they are very often accompanied by rudimentary analysis of the data and the 3D appreciation
of the problem is missed. The BEM DOCM developed in the current work represents an
improvement, especially since a topographical representation of a motor activation in the cortex
is clearly reconstructed in vivo.
In the interest of computational speed an acceleration technique for the BEM has been
developed. The Fast Multipole Method (FMM), which is based on the decomposition of Green’s
function on a basis of Bessel and Hankel functions, eases the evaluation of the BEM matrix,
along with a faster calculation of the solutions
The superiorization method with restarted perturbations for split minimization problems with an application to radiotherapy treatment planning
In this paper we study the split minimization problem that consists of two constrained minimization problems in two separate spaces that are connected via a linear operator that maps one space into the other. To handle the data of such a problem we develop a superiorization approach that can reach a feasible point with reduced (not necessarily minimal) objective function values. The superiorization methodology is based on interlacing the iterative steps of two separate and independent iterative processes by perturbing the iterates of one process according to the steps dictated by the other process. We include in our developed method two novel elements. The first one is the permission to restart the perturbations in the superiorized algorithm which results in a significant acceleration and increases the computational efficiency. The second element is the ability to independently superiorize subvectors. This caters to the needs of real-world applications, as demonstrated here for a problem in intensity-modulated radiation therapy treatment planning.The work of Yair Censor was supported by the ISF-NSFC joint research plan Grant Number 2874/19. Francisco Aragón and David Torregrosa were partially supported by the Ministry of Science, Innovation and Universities of Spain and the European Regional Development Fund (ERDF) of the European Commission, Grant PGC2018-097960-B-C22, and the Generalitat Valenciana (AICO/2021/165). David Torregrosa was supported by MINECO and European Social Fund (PRE2019-090751) under the program “Ayudas para contratos predoctorales para la formación de doctores” 2019
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Fast Radiative-Transfer-Equation-Based Image Reconstruction Algorithms for Non-Contact Diffuse Optical Tomography Systems
It is well known that the radiative transfer equation (RTE) is the most accurate deterministic light propagation model employed in diffuse optical tomography (DOT). RTE-based algorithms provide more accurate tomographic results than codes that rely on the diffusion equation (DE), which is an approximation to the RTE, in scattering dominant media. However, RTE based DOT (RTE-DOT) has limited utility in practice due to its high computational cost and lack of support for general non-contact imaging systems. In this dissertation, I developed fast reconstruction algorithms for RTE-based DOT (RTE-DOT), which consists of three independent components: an efficient linear solver for forward problems, an improved optimization solver for inverse problem, and the first light propagation model in free space that fully considers the angular dependency, which can provide a suitable measurement operator for RTE-DOT. This algorithm is validated and evaluated with numerical experiments and clinical data. According to these studies, the novel reconstruction algorithm is up to 30 times faster than traditional reconstruction techniques, while achieving comparable reconstruction accuracy
Multiplexed fluorescence diffuse optical tomography
Fluorescence tomography (FT) is an emerging non-invasive in vivo molecular imaging modality that aims at quantification and three-dimensional (3D) localization of fluorescent tagged inclusions, such as cancer lesions and drug molecules, buried deep in human and animal subjects. Depth-resolved 3D reconstruction of fluorescent inclusions distributed over the volume of optically turbid biological tissue using the diffuse fluorescent photons detected on the skin poses a highly ill-conditioned problem, as depth information must be extracted from boundary data. Due to this ill-posed nature of FT reconstructions, noise and errors in the data can severely impair the accuracy of the 3D reconstructions. Consequently, improvements in the signal-to-noise ratio (SNR) of the data significantly enhance the quality of the FT reconstructions. Furthermore, enhancing the SNR of the FT data can greatly contribute to the speed of FT scans. The pivotal factor in the SNR of the FT data is the power of the radiation illuminating the subject and exciting the administered fluorescent agents. In existing single-point illumination FT systems, the illumination power level is limited by the skin maximum radiation exposure levels. In this research, a multiplexed architecture governed by the Hadamard transform was conceptualized, developed, and experimentally implemented for orders-of-magnitude enhancement of the SNR and the robustness of FT reconstructions. The multiplexed FT system allows for Hadamard-coded multi-point illumination of the subject while maintaining the maximal information content of the FT data. The significant improvements offered by the multiplexed FT system were validated by numerical and experimental studies carried out using a custom-built multiplexed FT system developed exclusively in this work. The studies indicate that Hadamard multiplexing offers significantly enhanced robustness in reconstructing deep fluorescent inclusions from low-SNR FT data.Ph.D
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