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Level‐set techniques for microwave medical imaging
Author(s) -
Irishitalia,
Dorn Oliver,
Moscoso Miguel
Publication year - 2007
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200700053
Subject(s) - microwave imaging , a priori and a posteriori , breast cancer , microwave , regularization (linguistics) , curse of dimensionality , computer science , inverse problem , pixel , set (abstract data type) , permittivity , dielectric , artificial intelligence , pattern recognition (psychology) , mathematics , physics , medicine , cancer , mathematical analysis , optoelectronics , telecommunications , philosophy , epistemology , programming language
Microwave tomographic imaging is showing significant promise as a new technique for the early detection of breast cancer. Its physical basis is the contrast between the dielectric properties of the healthy breast tissue and the malignant tumors at microwave frequencies. We propose and analyze a novel shape‐reconstruction technique for the early detection of breast cancer from microwave data which is based on a level‐set technique. The advantages of this method compared to more traditional pixel‐based approaches are well‐defined boundaries and the incorporation of an intrinsic regularization in form of a‐priori assumptions about the general anatomical structure of breast that reduces the dimensionality of the inverse problem and thereby stabilizes the reconstruction. Our goal is not only to detect the tumors but to simultaneously determine their approximate locations, sizes and permittivity values. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)