Parameter and Structure Indentification in Optical Tomography
Lead Research Organisation:
University College London
Department Name: Computer Science
Abstract
Optical tomography is a non-invasive imaging technique for imaging the optical properties of biological tissue, particularly the peripheral muscle, breast and the brain. Optical tomography utilizes a set of optodes placed on the surface of the tissue to deliver an input signal. A second set of optodes at different locations detect exiting photons which have propagated through the biological tissue. The distribution of photons in these boundary measurements is used to reconstruct images of internal optical absorption and scattering coefficient distributions.The resulting images support a wide range of clinical applications. These include (i) non-invasive detection of breast tumours; (ii) functional imaging of muscle and brain activities; (iii) estimation of cerebral oxygenation and haemodynamics; (iv) measurements of cytochrome oxidase and mitochondrial energetics; (v) investigation of oxidative metabolism in muscle; (vi) measurements of tissue viability in transplantationof organs; and (vii) detection of abnormalities in joints of arthritic patients.Optical tomography is faster and cheaper than alternative imaging methods. The hardware is compact, allowing use in clinical settings where other imaging modalities are impractical. However, despite these advantages, optical tomography is not yet widely used. One of the major barriers to widespread acceptance is that the image reconstruction methods are slow and inaccurate. We consider three basic problems that are at the root of this block to progress :1. Accurate modelling methods for light propagation in tissue are too slow to be used repeatedly in solving the imaging problem.2. Optical measurements are noisy and limited in number which makes the imaging problem intrinsically inaccurate.3. Identification of clinically significant objects in the reconstructed images involves processing of noisy images even though the number or tyoe of object being sought is small.We will tackle these problems with three strategies :1. The use of model reduction techniques that allow the use of relatively inaccurate (but fast )models provided that the resultant errors are correctly handled2. The use of prior knowledge in a rigorous way using statistical techniques3. The direct reconstruction of clinical objects from the data, missing out the potentially unstable step of making the images.We will undertake a rigorous development and evaluation of these methods, including validation on experimental data. Developed software will be released on the internet.
Organisations
Publications
Arridge S
(2013)
Preconditioning of complex symmetric linear systems with applications in optical tomography
in Applied Numerical Mathematics
Soloviev VY
(2011)
Förster resonance energy transfer imaging in vivo with approximated radiative transfer equation.
in Applied optics
Farina A
(2017)
Time-Domain Functional Diffuse Optical Tomography System Based on Fiber-Free Silicon Photomultipliers
in Applied Sciences
Mora A
(2015)
Towards next-generation time-domain diffuse optics for extreme depth penetration and sensitivity
in Biomedical Optics Express
Tarvainen T
(2010)
Corrections to linear methods for diffuse optical tomography using approximation error modelling.
in Biomedical optics express
Tarvainen Tanja
(2010)
Corrections to linear methods for diffuse optical tomography using approximation error modelling
in BIOMEDICAL OPTICS EXPRESS
Correia T
(2011)
Split operator method for fluorescence diffuse optical tomography using anisotropic diffusion regularisation with prior anatomical information.
in Biomedical optics express
Soloviev VY
(2011)
Optical Tomography in weakly scattering media in the presence of highly scattering inclusions.
in Biomedical optics express
Elisee J
(2011)
Diffuse optical cortical mapping using the boundary element method.
in Biomedical optics express
Brigadoi S
(2015)
Evaluating real-time image reconstruction in diffuse optical tomography using physiologically realistic test data.
in Biomedical optics express
Mozumder M
(2013)
Compensation of optode sensitivity and position errors in diffuse optical tomography using the approximation error approach.
in Biomedical optics express
McGinty J
(2011)
In vivo fluorescence lifetime tomography of a FRET probe expressed in mouse.
in Biomedical optics express
Soloviev VY
(2010)
Fluorescence lifetime optical tomography with Discontinuous Galerkin discretisation scheme.
in Biomedical optics express
Elisee JP
(2010)
Combination of boundary element method and finite element method in diffuse optical tomography.
in IEEE transactions on bio-medical engineering
Somayajula S
(2011)
PET image reconstruction using information theoretic anatomical priors.
in IEEE transactions on medical imaging
Jones G
(2017)
Bayesian Estimation of Intrinsic Tissue Oxygenation and Perfusion From RGB Images.
in IEEE transactions on medical imaging
Schweiger M
(2016)
Basis mapping methods for forward and inverse problems
in International Journal for Numerical Methods in Engineering
Mohan P
(2010)
Discontinuous Galerkin method for the forward modelling in optical diffusion tomography
in International Journal for Numerical Methods in Engineering
Kolehmainen V
(2011)
MARGINALIZATION OF UNINTERESTING DISTRIBUTED PARAMETERS IN INVERSE PROBLEMS?APPLICATION TO DIFFUSE OPTICAL TOMOGRAPHY
in International Journal for Uncertainty Quantification
Schweiger M
(2011)
GPU-Accelerated Finite Element Method for Modelling Light Transport in Diffuse Optical Tomography.
in International journal of biomedical imaging
Arridge S
(2014)
Iterated preconditioned LSQR method for inverse problems on unstructured grids
in Inverse Problems
Arridge S
(2018)
Variational Gaussian approximation for Poisson data
in Inverse Problems
Mozumder M
(2015)
Nonlinear approach to difference imaging in diffuse optical tomography
in Journal of Biomedical Optics
Schweiger M
(2014)
The Toast++ software suite for forward and inverse modeling in optical tomography.
in Journal of biomedical optics
Abascal JF
(2012)
Influence of absorption and scattering on the quantification of fluorescence diffuse optical tomography using normalized data.
in Journal of biomedical optics
Correia T
(2013)
Wavelet-based data and solution compression for efficient image reconstruction in fluorescence diffuse optical tomography.
in Journal of biomedical optics
Ducros N
(2013)
Fluorescence molecular tomography of an animal model using structured light rotating view acquisition
in Journal of Biomedical Optics
Lehtikangas O
(2015)
Finite element approximation of the radiative transport equation in a medium with piece-wise constant refractive index
in Journal of Computational Physics
Surya Mohan P
(2011)
Variable order spherical harmonic expansion scheme for the radiative transport equation using finite elements
in Journal of Computational Physics
Tarvainen T
(2011)
Image reconstruction in diffuse optical tomography using the coupled radiative transport-diffusion model
in Journal of Quantitative Spectroscopy and Radiative Transfer
Lehtikangas O
(2010)
Finite element approximation of the Fokker-Planck equation for diffuse optical tomography
in Journal of Quantitative Spectroscopy and Radiative Transfer
Mozumder M
(2014)
Compensation of modeling errors due to unknown domain boundary in diffuse optical tomography.
in Journal of the Optical Society of America. A, Optics, image science, and vision
Panagiotou C
(2009)
Information theoretic regularization in diffuse optical tomography.
in Journal of the Optical Society of America. A, Optics, image science, and vision
Kolehmainen V
(2009)
Approximation errors and model reduction in three-dimensional diffuse optical tomography.
in Journal of the Optical Society of America. A, Optics, image science, and vision
Bousse A
(2017)
Evaluation of a direct motion estimation/correction method in respiratory-gated PET/MRI with motion-adjusted attenuation.
in Medical physics
Abascal JF
(2011)
Fluorescence diffuse optical tomography using the split Bregman method.
in Medical physics
Ban HY
(2016)
Heterodyne frequency-domain multispectral diffuse optical tomography of breast cancer in the parallel-plane transmission geometry.
in Medical physics
Brigadoi S
(2014)
A 4D neonatal head model for diffuse optical imaging of pre-term to term infants.
in NeuroImage
Markiewicz PJ
(2018)
NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis.
in Neuroinformatics
Mora AD
(2015)
Fast silicon photomultiplier improves signal harvesting and reduces complexity in time-domain diffuse optics.
in Optics express
Zacharopoulos AD
(2009)
3D shape based reconstruction of experimental data in Diffuse Optical Tomography.
in Optics express
Husakov A
(2009)
Chirped multilayer hollow waveguides with broadband transmission.
in Optics express
Schweiger M
(2010)
3D level set reconstruction of model and experimental data in Diffuse Optical Tomography.
in Optics express
Zacharopoulos AD
(2009)
A matrix-free algorithm for multiple wavelength fluorescence tomography.
in Optics express
Correia T
(2013)
Quantitative fluorescence diffuse optical tomography in the presence of heterogeneities.
in Optics letters
Farina A
(2017)
Multiple-view diffuse optical tomography system based on time-domain compressive measurements.
in Optics letters
Arridge SR
(2011)
Methods in diffuse optical imaging.
in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Wang P
(2014)
Radiative transfer equation for media with spatially varying refractive index
in Physical Review A
Soloviev VY
(2011)
Angularly selective mesoscopic tomography.
in Physical review. E, Statistical, nonlinear, and soft matter physics
Hiltunen P
(2009)
A combined reconstruction-classification method for diffuse optical tomography.
in Physics in medicine and biology
Description | Imaging of functional and structural information in the brain is possible using infra red light. Sufficient signal is transmitted through the complete width of the head of newborn babies to localise functional activity for example in the motor cortex. Algorithmic methods developed allow solution of non-linear imaging problems in a few minutes on standard desktop computers. |
Exploitation Route | The results open the door to portable non-invasive imaging devices that can operate in a clinical environment. |
Sectors | Healthcare |
URL | http://www.ucl.ac.uk/medphys/research/borl |
Description | The methods and software developed are used in NeoLab at Addenbrookes Cambridge for monitoring of seizures in premature babies. |
First Year Of Impact | 2011 |
Sector | Healthcare |
Impact Types | Societal |
Description | Healthcare Engineering |
Amount | £874,937 (GBP) |
Funding ID | EP/J021318/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 10/2012 |
End | 03/2016 |
Title | TOAST++ |
Description | Toast++ is a software suite for image reconstruction in diffuse optical tomography (DOT). It contains a forward solver module using the finite element method for simulating the propagation of light in highly scattering, inhomogeneous biological tissues, such as the brain. The inverse solver module uses an iterative, model-based approach to reconstruct the unknown distributions of absorption and scattering coefficients in the volume of interest from boundary measurements of light transmission. Toast++ consists of a set of libraries written in C++ for sparse linear algebra, finite element computation, and nonlinear image reconstruction. Several command line applications for forward modelling and inverse solution are included. Users who need additional functionality can write their own applications and link to the core Toast++ libraries. In addition, Toast++ contains bindings for Matlab and Python. This provides a set of functions for accessing the Toast methods from within these scripting environments, without loss of performance. Using Toast++ from within Matlab or Python provides a user-friendly way for quickly adapting Toast to a specific reconstruction problem. It allows rapid prototyping, debugging and visualisation. The Toast++ sources are distributed with a GPL license. In addition to the sources, binary distributions for various computing platforms can be downloaded. Toast++ toolbox is being developed by Martin Schweiger and Simon Arridge at University College London. |
Type Of Technology | Software |
Year Produced | 2014 |
Open Source License? | Yes |
Impact | Is being widely used for functional Near Infra Red Spectroscopic Imaging Also used in small animal imaging including fluoresence lifetime imaging. |
URL | http://web4.cs.ucl.ac.uk/research/vis/toast/index.html |