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Expansion Methods

  • Habib Ammari
  • Hyeonbae Kang

Abstract

The aim of this chapter is to review recent developments in the mathematical and numerical modeling of anomaly detection and multi-physics biomedical imaging. Expansion methods are designed for anomaly detection. They provide robust and accurate reconstruction of the location and of some geometric features of the anomalies, even with moderately noisy data. Asymptotic analysis of the measured data in terms of the size of the unknown anomalies plays a key role in characterizing all the information about the anomaly that can be stably reconstructed from the measured data. In multi-physics imaging approaches, different physical types of waves are combined into one tomographic process to alleviate deficiencies of each separate type of waves, while combining their strengths. Muti-physics systems are capable of high-resolution and high-contrast imaging. Asymptotic analysis plays a key role in multi-physics modalities as well.

Keywords

Electrical Impedance Tomography Anomaly Detection Location Search Algorithm Polarization Tensor Magnetic Resonance Elastography 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Habib Ammari
  • Hyeonbae Kang

There are no affiliations available

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