Electromagnetic target recognition for lossy and dispersive dielectric objects: applications to breast tissue classification and tumor detection problem /

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2014

Author

Barut, Başak Işık

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The aim of this thesis is to understand the fundamental concepts behind two different electromagnetic target recognition (EMTR) techniques and to extend their applications to the problem of classifying lossy and dispersive objects embedded either in air or in another lossy and dispersive medium. The EMTR techniques, which use either Wigner Distribution-Principal Component Analysis (WD-PCA) approach or Multiple Signal Classification (MUSIC) Algorithm approach, are both based on the Singularity Expansion Method (SEM). They use wide-band scattered data in resonance region to extract object features which are related to complex natural resonance (CNR) frequencies. In this thesis, application of aforementioned techniques will be studied for two different but closely related problems. First, classification of different lossy and dispersive breast tissue samples will be demonstrated when they are embedded in air. Secondly, the problem of breast tumor detection will be illustrated where both the object (tumor) and the surrounding medium (breast tissue) are lossy and dispersive. The Cole-Cole parameters will be used to model realistic tumor tissues as well as realistic breast tissues having different fat (adipose) content. Difficulty of recognition of tumors embedded in different types of breast tissue will be investigated for different tumor sizes by designing proper target classifiers using both EMTR techniques.

Subject Keywords

Electromagnetism., Dielectrics., Tumors., Breast, Electromagnetism in medicine.

URI

http://etd.lib.metu.edu.tr/upload/12617475/index.pdf
https://hdl.handle.net/11511/23738

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

B. I. Barut, “Electromagnetic target recognition for lossy and dispersive dielectric objects: applications to breast tissue classification and tumor detection problem /,” M.S. - Master of Science, Middle East Technical University, 2014.