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Parallel CGLS technique for solving large scale EIT inverse problem

Parallel CGLS technique for solving large scale EIT inverse problem. Presenter: Chuan Li Yang Dept of Electronic and Electrical Engineering. Contents. Introduction Hardware Mathematical model Method for solving large scale EIT Conclusion and Future improvement. Introduction.

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Parallel CGLS technique for solving large scale EIT inverse problem

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  1. Parallel CGLS technique for solving large scale EIT inverse problem Presenter: Chuan Li Yang Dept of Electronic and Electrical Engineering

  2. Contents • Introduction • Hardware • Mathematical model • Method for solving large scale EIT • Conclusion and Future improvement

  3. Introduction • What is EIT (electrical impedance tomography )? • An imaging technique in which an image of the conductivity or permittivity of part of the body is inferred from surface electrical measurements.

  4. Control Computer Multiplexer switching pattern Excitation Multiplexer 1 National Instrument Data Acquisition Card Sink EIT Phantom Multiplexer 2 Measurement 1 Measurement 2 How does it work? Includes: Control computer, DAQ unit, multiplexers and phantom. EIT hardware ( sensors)

  5. Phantom design 3D 4x4 plane array sensor 2D 32 electrodes phantom 32 channel square fabric sensor 3D 32 electrodes phantom (2x 16)

  6. How does it work? Measurement Patterns

  7. Mathematical model Forward problem • Inverse problem • One of the most typical regularization schemes is Tikhonov regularization.

  8. When EIT problem becomes large scale What is large scale mean? More than 128 electrodes. Require large space to store the Jacobian matrix.

  9. Method introduced Sparse matrix with parallel CGLS reconstruction • Sparse Jacobian thresholding ( Memory and time save) • Block-wise parallel CGLS (Multiple CPUs) ( Further time save)

  10. Block-wise matrix • The matrix J can be divided in to blocks • can be expressed as the sum of all blocks,

  11. Results on speed

  12. Simulation for 128 electrodes

  13. Experimental images(32 electrodes)

  14. Conclusion and future improvement • We have introduced the basics of electrical impedance tomography. • A PC is now efficient enough to produce satisfying results for large scale EIT system while using the developed software. • This program will be utilized by HPC in the future.

  15. Acknowledgement • Thanks to my supervisor Dr. M Soleimani for his guidance and consistently support of my project.

  16. Thank you! Questions?

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