A Near-Infrared-Based Magnetic Induction Tomography Solution to Improve the Image Reconstruction Accuracy in Opaque Environments

In this paper, we propose a new magnetic induction tomography (MIT) system which uses, in addition to the set of magnetic coils, some infrared launch-detector fibers surrounding the cross-sectional image plane. The system is used to reconstruct the interior conductivity distribution of the body and to enhance the accuracy of images obtained by a single MIT. A constrained Landweber algorithm is proposed for image reconstruction. It uses both the boundary data obtained from the coils, and the foreground-background fractions at some neighboring elements of the mesh obtained using the infrared fibers. The effectiveness of the proposed method is demonstrated by numerical data generated for some circular phantoms. Comparisons, in terms of several metrics, between the reconstructed images obtained using the new method and a conventional MIT based on Landweber reconstruction clearly show the outperformance of the method.

[1]  Wuliang Yin,et al.  Sensitivity Formulation Including Velocity Effects for Electromagnetic Induction Systems , 2010, IEEE transactions on magnetics.

[2]  H. Griffiths Magnetic induction tomography , 2001 .

[3]  Hermann Scharfetter,et al.  Numerical solution of the general 3D eddy current problem for magnetic induction tomography (spectroscopy). , 2003, Physiological measurement.

[4]  Andy Adler,et al.  Enhancing Impedance Imaging Through Multimodal Tomography , 2011, IEEE Transactions on Biomedical Engineering.

[5]  Hamid Dehghani,et al.  Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction. , 2009, Communications in numerical methods in engineering.

[6]  Hongbin Wang,et al.  Implementation of Generalized Back Projection Algorithm in 3-D EIT , 2011, IEEE Transactions on Magnetics.

[7]  M. Schweiger,et al.  Diffuse optical tomography with spectral constraints and wavelength optimization. , 2005, Applied optics.

[8]  Manuchehr Soleimani,et al.  Nonlinear image reconstruction for electrical capacitance tomography using experimental data , 2005 .

[9]  C H Igney,et al.  A measurement system and image reconstruction in magnetic induction tomography. , 2008, Physiological measurement.

[10]  B. Pogue,et al.  Spectrally constrained chromophore and scattering near-infrared tomography provides quantitative and robust reconstruction. , 2005, Applied optics.

[11]  R. Merwa,et al.  Numerical simulation of the eddy current problem in magnetic induction tomography for biomedical applications by edge elements , 2004, IEEE Transactions on Magnetics.

[12]  William R B Lionheart,et al.  GREIT: a unified approach to 2D linear EIT reconstruction of lung images , 2009, Physiological measurement.

[13]  Patricia Brunner,et al.  Solution of the inverse problem of magnetic induction tomography (MIT) , 2005, Physiological measurement.

[14]  Per Christian Hansen,et al.  Regularization methods for large-scale problems , 1993 .

[15]  E. M. Freeman,et al.  A method of computing the sensitivity of electromagnetic quantities to changes in materials and sources , 1994 .

[16]  A. J. Peyton,et al.  A state of the art review of electromagnetic tomography. , 2003 .