Microwave Imaging for Breast Cancer Detection Amir H. Golnabi Thayer School of Engineering at Dartmouth College, NH 1st Annual IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems 16 – 20 January 2011, Phoenix, Az, USA
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Microwave Imaging for Breast Cancer Detection and Therapy Monitoring
This work was presented at the first Annual IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS) held as part of the IEEE Radio and Wireless Symposium 2011, in Phoenix, AZ.
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Microwave Imaging for Breast Cancer Detection
Amir H. Golnabi Thayer School of Engineering at Dartmouth
College, NH
1st Annual IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems
16 – 20 January 2011, Phoenix, Az, USA
• Breast Cancer:
– 32% of all cancers in women, ~40,460 deaths
annually (ACS)
– Most commonly diagnosed cancer
– Second cause of cancer death in women, after
lung cancer
• Patients’ long term survival: tumor detection at its
• Extension of the 2D reconstruction algorithm:– Iterative regularized Gauss-Newton algorithm using the
dual-mesh approach…• What is different?
– 3D volumetric regions– Size of forward field and parameter modeling problems– More measurement data → more reconstruction parameters– Significant increase in computational time and effort
• How to approach?– MATLAB interface– MEX-Files– Parallel Computing
• Using microwave imaging for breast cancer detection and therapy monitoring• 2D and 3D simulation and phantom experiments• Non-uniform complex geometry• Small-size inclusion
• Clinical patient data: size of the tumor decreased significantly during the course of treatment
• Microwave imaging has the potential to become an alternative and/or supplementary technique for breast cancer detection and therapy monitoring.
6. Future direction
• Improving the reconstruction algorithms • Recover more accurate dielectric property
distributions • Detect even smaller tumors
• Using 3D reconstruction algorithm for patient data • more detailed and accurate images
• Combining 3D microwave imaging and MR
Acknowledgement
• MIS group at Thayer School of Engineering
Matt Pallone, Tian Zhou, Neil Epstein
This work was sponsored by NIH/NCI grant # P01-CA080139
Prof. Paul Meaney Prof. Keith PaulsenShireen Geimer