XIX Sympozjum Srodowiskowe PTZE - materialy.pdf

XIX Sympozjum Srodowiskowe PTZE - materialy.pdf XIX Sympozjum Srodowiskowe PTZE - materialy.pdf

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XIX Sympozjum PTZE, Worliny 2009 Slices are connected to 3D volume, Fig.2-a. Volume is meshed by Delaney triangulation algorithm. Supported are first and second order elements. The achieved list of elements is imported in ANSYS, Fig.2-b. Tissue electromagnetic material properties are applied for every element in the list. a) (b) 4D models contain a time sequence of 3D models (Fig.3). All models in the sequence have common mesh which is deformed for each time step object shape. Fig. 3. 4D model time sequence Implementation 116 Fig. 2. Reconstructed volume The developed method and software tool was effectively applied for part of cardiac muscle reconstruction. Achieved models are suitable for electromagnetic field distribution calculations with FEM. References [1] R. Hartley. Projective Reconstruction and Invariants from Multiple Images. IEEE PAMI Vol. 16, No. 10, 1994, pp. 1036-1041. [2] T. McInerney, D. Terzopoulos. Deformable models in medical image analysis: a survey, Medical Image Analysis. 1996 [3] D. Pham, C. Xu, J. Prince, Current Methods in Medical Image Segmentation, Annu. Rev. Biomed. Eng. 2000. Vol. 2, 315–37 [4] I. Marinova, Modelling, Simulation and Visualization of Electromagnetic Interaction in Human Body, Ashikaga, Japan, June 2000 [5] I. Marinova, V. Mateev. Virtual Dynamic Visualization of Field Distributions in Human Body. International Symposium on Electrical Apparatus and Technologies – SIELA 2005, Proceedings, Vol. 2, 2-3 June 2005, Plovdiv, Bulgaria.

XIX Sympozjum PTZE, Worliny 2009 INVERSE APPROACH FOR RECONSTRUCTION OF CURRENT DENSITY VECTORS Iliana Marinova, Valentin Mateev Technical University of Sofia, Department of Electrical Apparatus, 1156 Sofia, 8 Kliment Ohridski St., Bulgaria, e-mail: iliana@tu-sofia.bg, vmateev@tu-sofia.bg Abstract In this paper we apply an inverse approach for 3D current sources reconstruction using measured magnetic field data. The reconstruction approach is based on the 3D Green’s function of Poisson and Helmholtz equations. The developed approach was effectively applied for current source distribution reconstruction of coil in linear nonmagnetic media. Introduction Current source distributions in biological structures are extremely important for medical diagnosis and therapy treatments in various applications. Magneto CardioGraphy (MCG) and Magneto EncephaloGraphy (MEG) process measured magnetic field data outside the human body, near the chest or head, for inside current imaging used for medical diagnoses. In magnetic stimulation therapy applications, current pulses are supplied to the coil to produce a strong magnetic field to stimulate nerve fibres. Magnetic stimulation occurs as result of the current flow and the accompanying electric field induced in the tissue by an externally applied magnetic field. Determination of magnetic field and current distributions in the tissue in order to generate prescribed stimulation effect is an inverse source problem. The current density distribution is basic part in coil design optimisation and electromagnetic systems syntheses. In this paper we apply an inverse approach for 3D current sources reconstruction using measured magnetic field data. The reconstruction approach uses 3D Green’s function. The magnetic fields are measured in a surface mesh over the tested object region. These data are used for field source reconstruction in inaccessible for direct measurements region. The developed reconstruction approach is effectively applied for current source distribution reconstruction of a circular coil in linear non-magnetic media. Inverse approach The magnetic field distribution can be described through the Green’s (1, 2) functions of Poisson(3) and Helmholtz(4) equations for magnetic vector potential(MVP) and complex MVP. [1, 4, 5] 117

<strong>XIX</strong> <strong>Sympozjum</strong> <strong>PTZE</strong>, Worliny 2009<br />

Slices are connected to 3D volume, Fig.2-a. Volume is meshed by Delaney triangulation<br />

algorithm. Supported are first and second order elements. The achieved list of elements is<br />

imported in ANSYS, Fig.2-b.<br />

Tissue electromagnetic material properties are applied for every element in the list.<br />

a) (b)<br />

4D models contain a time<br />

sequence of 3D models (Fig.3).<br />

All models in the sequence have<br />

common mesh which is deformed<br />

for each time step object shape.<br />

Fig. 3. 4D model time sequence<br />

Implementation<br />

116<br />

Fig. 2. Reconstructed volume<br />

The developed method and software tool was effectively applied for part of cardiac muscle<br />

reconstruction. Achieved models are suitable for electromagnetic field distribution<br />

calculations with FEM.<br />

References<br />

[1] R. Hartley. Projective Reconstruction and Invariants from Multiple Images. IEEE PAMI Vol.<br />

16, No. 10, 1994, pp. 1036-1041.<br />

[2] T. McInerney, D. Terzopoulos. Deformable models in medical image analysis: a survey,<br />

Medical Image Analysis. 1996<br />

[3] D. Pham, C. Xu, J. Prince, Current Methods in Medical Image Segmentation, Annu. Rev.<br />

Biomed. Eng. 2000. Vol. 2, 315–37<br />

[4] I. Marinova, Modelling, Simulation and Visualization of Electromagnetic Interaction in<br />

Human Body, Ashikaga, Japan, June 2000<br />

[5] I. Marinova, V. Mateev. Virtual Dynamic Visualization of Field Distributions in Human<br />

Body. International Symposium on Electrical Apparatus and Technologies – SIELA 2005,<br />

Proceedings, Vol. 2, 2-3 June 2005, Plovdiv, Bulgaria.

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