DocumentCode :
152408
Title :
Breast cancer imaging using microwave tomography with radar-derived prior information
Author :
Baran, Anastasia ; Kurrant, Doug ; Zakaria, A. ; Fear, Elise ; LoVetri, Joe
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Manitoba, Winnipeg, MB, Canada
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
259
Lastpage :
259
Abstract :
Summary form only given. Biomedical imaging at microwave frequencies has shown potential for breast cancer detection and monitoring. Current modalities suffer from significant underlying disadvantages. For example, mammography utilizes high-energy, ionizing radiation and is uncomfortable for patients, and breast MRI has a high false positive rate due to high sensitivity and low specificity. Microwave imaging is an inexpensive technique that uses low-power, non-ionizing radiation that is not harmful to patients. Two techniques that exploit microwave frequencies for breast imaging are microwave tomography (MWT) and radar-based imaging. These two techniques suffer from limitations in resolution of fine structures and accuracy of tissue dielectric properties.We present a novel algorithm that combines MWT with a radar-based region estimation technique, with a focus on breast cancer imaging. The region estimation method creates a patient-specific spatial map of the breast anatomy that includes skin, adipose and fibroglandular tissue regions, and contains the average dielectric properties over those regions (D. Kurrant and E. Fear, Inverse Prob., 2012). This map is incorporated into a finite element contrast source inversion (FEM-CSI) algorithm as prior information in the form of an inhomogeneous background (A. Zakaria, A. Baran, and J. LoVetri, Antennas Wireless Propag. Lett., 2012). This hybrid approach is able to reconstruct finer structural details of tissues within the breast, and estimates their dielectric properties more accurately than either technique used alone. Results from various numerical phantoms characterize this significant improvement in image quality. In addition to improvement of accuracy and resolution, the algorithm is able to produce reliable results within the 1GHz-4GHz frequency range, allowing us to take advantage of march-on-frequency techniques to further improve image quality and localize tumors. Simulations also produce reliable results using- several different immersion media that vary greatly in their real and imaginary permittivity values, providing more flexibility in the choice of immersion medium for clinical systems. Results from numerical breast phantoms using this hybrid technique will be presented and compared to traditional MWT methods.
Keywords :
cancer; finite element analysis; medical image processing; microwave imaging; permittivity; phantoms; skin; FEM-CSI algorithm; adipose tissue regions; breast anatomy; breast cancer imaging; breast phantoms; dielectric property; fibroglandular tissue regions; finite element contrast source inversion algorithm; frequency 1 GHz to 4 GHz; image quality; imaginary permittivity values; march-on-frequency techniques; microwave tomography; numerical phantoms; patient-specific spatial map; radar-based region estimation technique; radar-derived prior information; region estimation method; skin tissue regions; Breast cancer; Educational institutions; Microwave imaging; Microwave theory and techniques; Radar imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radio Science Meeting (Joint with AP-S Symposium), 2014 USNC-URSI
Conference_Location :
Memphis, TN
Type :
conf
DOI :
10.1109/USNC-URSI.2014.6955642
Filename :
6955642
Link To Document :
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