Diffuse photon propagation in multilayered geometries

Sikora, J.; Zacharopoulos, Athanasios; Douiri, Abdel; Schweiger, Martin; Horesh, Lior; Arridge, Simon; Ripoll, Jorge

doi:10.1088/0031-9155/51/3/003

Cited by 52 publications

(48 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Toast also contains a modeling module using the boundary element method (BEM), 20 which allows efficient simulation of piecewise constant parameter distributions. This scheme has been applied to shape reconstruction of internal boundaries of regions with piecewise constant optical parameter values.…”

Section: Alternative Numerical Modeling Schemesmentioning

confidence: 99%

The Toast++ software suite for forward and inverse modeling in optical tomography

2014

Self Cite

View full text Add to dashboard Cite

Abstract. We present the Toast++ open-source software environment for solving the forward and inverse problems in diffuse optical tomography (DOT). The software suite consists of a set of libraries to simulate near-infrared light propagation in highly scattering media with complex boundaries and heterogeneous internal parameter distribution, based on a finite-element solver. Steady-state, time-and frequency-domain data acquisition systems can be modeled. The forward solver is implemented in C++ and supports performance acceleration with parallelization for shared and distributed memory architectures, as well as graphics processing computation. Building on the numerical forward solver, Toast++ contains model-based iterative inverse solvers for reconstructing the volume distribution of absorption and scattering parameters from boundary measurements of light transmission. A range of regularization methods are provided, including the possibility of incorporating prior knowledge of internal structure. The user can link to the Toast++ libraries either directly to compile application programs for DOT, or make use of the included MATLAB and PYTHON bindings to generate script-based solutions. This approach allows rapid prototyping and provides a rich toolset in both environments for debugging, testing, and visualization. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

show abstract

Section: Alternative Numerical Modeling Schemesmentioning

confidence: 99%

The Toast++ software suite for forward and inverse modeling in optical tomography

2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…[30][31][32] The BEM was applied to the diffusion approximation under the assumption that the tissue being imaged contains homogeneous regions whose boundaries are known a priori (from MRI). 28,33 It reduces the dimensionality of the problem, requiring only surface rather than volume discretization in three dimension, which is significantly easier and more reliable to generate. Using this numerical model to solve the diffusion equation, unknown NIRS parameters can be reconstructed from boundary measurement of light amplitude and phase.…”

Section: Bem-based Multispectral Image Reconstructionmentioning

confidence: 99%

Image guided near-infrared spectroscopy of breast tissue in vivo using boundary element method

et al. 2010

View full text Add to dashboard Cite

Abstract. We demonstrate quantitative functional imaging using imageguided near-infrared spectroscopy (IG-NIRS) implemented with the boundary element method (BEM) for reconstructing 3-D optical property estimates in breast tissue in vivo. A multimodality MRI-NIR system was used to collect measurements of light reflectance from breast tissue. The BEM was used to model light propagation in 3-D based only on surface discretization in order to reconstruct quantitative values of total hemoglobin (HbT), oxygen saturation, water, and scatter. The technique was validated in experimental measurements from heterogeneous breast-shaped phantoms with known values and applied to a total of seven subjects comprising six healthy individuals and one participant with cancer imaged at two time points during neoadjuvant chemotherapy. Using experimental measurements from a heterogeneous breast phantom, BEM for IG-NIRS produced accurate values for HbT in the inclusion with a <3% error. Healthy breast tissues showed higher HbT and water in fibroglandular tissue than in adipose tissue. In a subject with cancer, the tumor showed higher HbT compared to the background. HbT in the tumor was reduced by 9 μM during treatment. We conclude that 3-D MRI-NIRS with BEM provides quantitative and functional characterization of breast tissue in vivo through measurement of hemoglobin content. The method provides potentially complementary information to DCE-MRI for tumor characterization. C 2010 Society of Photo-Optical Instrumentation Engineers.

show abstract

“…It is shown in [22,23] that applying a flow by a smooth vector field v(x) yields an infinitesimal response in this cost (58) that is given by…”

Section: Penalizing Volume or Area Of Shapementioning

confidence: 99%

Level Set Techniques For Structural Inversion In Medical Imaging

Dorn

Lesselier

2007

Deformable Models

View full text Add to dashboard Cite

Most biological bodies are structured in the sense that they contain quite well-defined interfaces between regions of different types of tissue or anatomical material. Extracting structural information from medical or biological images has been an important research topic for a long time. Recently, much attention has been devoted to quite novel techniques for the direct recovery of structural information from physically measured data. These techniques differ from more traditional image processing and image segmentation techniques by the fact that they try to recover structured images not from already given pixel or voxelbased reconstructions (obtained, e.g., using traditional medical inversion techniques), but directly from the given raw data. This has the advantage that the final result is guaranteed to satisfy the imposed criteria of data fitness as well as those of the given structural prior information. The 'level-set-technique' [1][2][3] plays an important role in many of these novel structural inversion approaches, due to its capability of modeling topological changes during the typically iterative inversion process. In this text we will provide a brief introduction into some techniques that have been developed recently for solving structural inverse problems using a level set technique.

show abstract

Diffuse photon propagation in multilayered geometries

Cited by 52 publications

References 57 publications

The Toast++ software suite for forward and inverse modeling in optical tomography

The Toast++ software suite for forward and inverse modeling in optical tomography

Image guided near-infrared spectroscopy of breast tissue in vivo using boundary element method

Level Set Techniques For Structural Inversion In Medical Imaging

Contact Info

Product

Resources

About