The 10th IASTED International Conference on
Visualization, Imaging, and Image Processing
July 3 – 5, 2012
Time Reversal Array Imaging Algorithms: Application to Breast Cancer Detection
Breast cancer is the second leading cause of cancer death after lung cancer among women. For years, X-ray mammography was the only practical procedure for detection of breast cancer. However, diagnostic mammography frequently generates many abnormal findings leading to additional, costly imaging procedures and biopsies. This is especially true for young women, who present a higher ratio of dense to fatty tissues in their breast, limiting the effectiveness of X-ray mammography in such cases. More recently, backscatter imaging techniques (based on the seminal work by Fear and Stoica) using low-intensity electromagnetic radiation have been introduced. Malignant breast tumours have electrical properties that are significantly different from those of healthy breast tissues. For example, the cancerous tumour produces a stronger backscattered electromagnetic energy return as compared to the reflections from the normal tissues. However, unlike X-rays, which are non-diffractive and travel in straight lines, electromagnetic microwave propagation in breast tissues is characterized by refraction and multipath effects, i.e., the backscattered cancer signature signal reaches the detector by two or more paths. As a result, standard signal processing algorithms do not perform well due to multipath propagation and cannot accurately identify nor locate cancer tumours with sufficiently fine resolution.
The presentation discusses a different backscatter imaging paradigm based on time reversal signal processing that uses multipath propagation to its advantage for breast cancer detection. After introducing time reversal, we prove analytically, we believe for the first time, the phenomena of super resolution focusing observed with time reversal. TR imaging algorithms used for detecting and accurately estimating the location of targets in a high scattering environment with strong clutters are then discussed. The time reversal beamforming imager is applied for detecting and locating early stage breast cancer tumours from MRI data. We present initial results based on the finite difference, time domain (FDTD) electromagnetic model and illustrate that the proposed detector estimates the locations of breast cancer tumours with a higher accuracy than some of the current state of art signal processing estimation algorithms tested by us.
Biography of the Keynote Speaker
Amir Asif works in the area of statistical signal processing and communications. His current projects include error-resilient, scalable video compression; time-reversal, array imaging detection; genomic signal processing; and sparse, block-banded matrix technologies. He has authored over 100 technical contributions, including invited ones, published in international journals and conference proceedings, and a textbook "Continuous and Discrete Time Signals and Systems" published by the Cambridge Press. Dr. Asif has been a Technical Associate Editor for the IEEE SIGNAL PROCESSING LETTERS (2002-2006, 2009-date) . He has organized two IEEE conferences on signal processing theory and applications and served on the technical committees of several international conferences. He has received several distinguishing awards including several teaching accolades and
Sr. Asif received the M.Sc. and Ph.D. degrees in electrical and computer engineering from Carnegie Mellon University (CMU), Pittsburgh, PA. He is an Associate Professor of computer science and engineering at York University, Toronto, ON, Canada. Prior to this, he was on the faculty of CMU and the Technical University of British Columbia (now part of the Simon Fraser University), Vancouver, BC, Canada, where he was an Assistant/Associate Professor. He is a member of the Professional Engineering Society of Ontario and a senior member of the IEEE Signal Processing Society.