Mathematical Modelling of Optical Coherence Tomography

In this chapter a general mathematical model of Optical Coherence Tomography (OCT) is presented on the basis of the electromagnetic theory. OCT produces high resolution images of the inner structure of biological tissues. Images are obtained by measuring the time delay and the intensity of the backscattered light from the sample considering also the coherence properties of light. The scattering problem is considered for a weakly scattering medium located far enough from the detector. The inverse problem is to reconstruct the susceptibility of the medium given the measurements for different positions of the mirror. Different approaches are addressed depending on the different assumptions made about the optical properties of the sample. This procedure is applied to a full field OCT system and an extension to standard (time and frequency domain) OCT is briefly presented.Comment: 28 pages, 5 figures, book chapte

Image reconstruction of low conductivity material distribution using magnetic induction tomography

Magnetic induction tomography (MIT) is a non-invasive, soft field imaging modality that has the potential to map the electrical conductivity (σ) distribution inside an object under investigation. In MIT, a number of exciter and receiver coils are distributed around the periphery of the object. A primary magnetic field is emitted by each exciter, and interacts with the object. This induces eddy currents in the object, which in turn create a secondary field. This latter is coupled to the receiver coils and voltages are induced. An image reconstruction algorithm is then used to infer the conductivity map of the object. In this thesis, the application of MIT for volumetric imaging of objects with low conductivity materials (< 5 Sm-1) and dimensions < 1 m is investigated. In particular, two low conductivity applications are approached: imaging cerebral stroke and imaging the saline water in multiphase flows. In low conductivity applications, the measured signals are small and the spatial sensitivity is critically compromised making the associated inverse problem severely non-linear and ill-posed.The main contribution from this study is to investigate three non-linear optimisation techniques for solving the MIT inverse problem. The first two methods, namely regularised Levenberg Marquardt method and trust region Powell's Dog Leg method, employ damping and trust region strategies respectively. The third method is a modification of the Gauss Newton method and utilises a damping regularisation technique. An optimisation in the convergence and stability of the inverse solution was observed with these methods compared to standard Gauss Newton method. For such non linear treatment, re-evaluation of the forward problem is also required. The forward problem is solved numerically using the impedance method and a weakly coupled field approximation is employed to reduce the computation time and memory requirements. For treating the ill-posedness, different regularisation methods are investigated. Results show that the subspace regularisation technique is suitable for absolute imaging of the stroke in a real head model with synthetic data. Tikhonov based smoothing and edge preserving regularisation methods also produced successful results from simulations of oil/water. However, in a practical setup, still large geometrical and positioning noise causes a major problem and only difference imaging was viable to achieve a reasonable reconstruction.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Image reconstruction of low conductivity material distribution using magnetic induction tomography

Magnetic induction tomography (MIT) is a non-invasive, soft field imaging modality that has the potential to map the electrical conductivity (σ) distribution inside an object under investigation. In MIT, a number of exciter and receiver coils are distributed around the periphery of the object. A primary magnetic field is emitted by each exciter, and interacts with the object. This induces eddy currents in the object, which in turn create a secondary field. This latter is coupled to the receiver coils and voltages are induced. An image reconstruction algorithm is then used to infer the conductivity map of the object. In this thesis, the application of MIT for volumetric imaging of objects with low conductivity materials (< 5 Sm-1) and dimensions < 1 m is investigated. In particular, two low conductivity applications are approached: imaging cerebral stroke and imaging the saline water in multiphase flows. In low conductivity applications, the measured signals are small and the spatial sensitivity is critically compromised making the associated inverse problem severely non-linear and ill-posed.The main contribution from this study is to investigate three non-linear optimisation techniques for solving the MIT inverse problem. The first two methods, namely regularised Levenberg Marquardt method and trust region Powell's Dog Leg method, employ damping and trust region strategies respectively. The third method is a modification of the Gauss Newton method and utilises a damping regularisation technique. An optimisation in the convergence and stability of the inverse solution was observed with these methods compared to standard Gauss Newton method. For such non linear treatment, re-evaluation of the forward problem is also required. The forward problem is solved numerically using the impedance method and a weakly coupled field approximation is employed to reduce the computation time and memory requirements. For treating the ill-posedness, different regularisation methods are investigated. Results show that the subspace regularisation technique is suitable for absolute imaging of the stroke in a real head model with synthetic data. Tikhonov based smoothing and edge preserving regularisation methods also produced successful results from simulations of oil/water. However, in a practical setup, still large geometrical and positioning noise causes a major problem and only difference imaging was viable to achieve a reasonable reconstruction.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

The opportunity of magnetic induction tomography modality in breast cancer detection

The needs for non-invasive technique in breast cancer detection could enhance and preserve the future of medical field in Malaysia as well as countries around the world. Breast cancer has become the main concern nowadays not only for women but for man as well. In overall, the risk of women getting breast cancer is higher than man due to the denser tissue of breast in women compare to man. Beside the unawareness for the disease, the reason which contributes to this increasing number of breast cancer reported is also due to the limitations arising from modalities such as MRI, Mammography, ultrasound and other modalities. An alternative to current technologies should be improved for early detection and treatment which causes no physical harm to patients if possible. Thus, non-invasive and better technology in detecting breast cancer is very much needed in the current market. This paper will be discussing the insights of Magnetic Induction Tomography techniques in breast cancer detection

Noninvasive Conductivity and Temperature Sensing using Magnetic Induction Spectroscopy Imaging

The work presents a perspective in evaluating electromagnetic tomography reconstruction through a spectral eddy current imaging arrangement. Embarking from an established analytical basis, the spectroscopic relation of a metallic conductive body to its physical properties is revealed via multifrequency mutual impedance measurement. Characteristics are evident, from either modeling or experiment, on certain frequency ranges that discriminate the object's circumstances. Both the amplitude ratio and phase-contrast image spectrum show information on the conductivity and structure of a target considered pivotal for industrial applications. Two test cases are reported: liquid metal structure determination and contactless temperature evaluation of a remote/hidden medium/object. Using eddy current-based spectroscopic imaging data and appropriate calibration, this work, for the first time, demonstrates a novel thermal mapping system. This is a wireless and inductive-based temperature mapping device that can have great potential applications where none of the existing thermal measuring devices could work noninvasively. <br/