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Prof talks about new way of detecting breast cancer tomorrow

Until recently, x-ray mammography was the only practical procedure for the detection of breast cancer, but there may be a better way. Professor Amir Asif, chair of York’s Department of Computer Science & Engineering, will discuss it at the next York eHealth Alliance Lecture Series.

The talk, “Time Reversal Array Imaging Algorithms: Application to Breast Cancer Detection”, will take place tomorrow, from 3 to 4pm at 3033 Computer Science & Engineering Building, Keele campus.

Left: Amir Asif

Breast cancer is the second leading cause of cancer death after lung cancer among women, but diagnostic mammography frequently generates many abnormal findings leading to additional, costly imaging procedures and biopsies. Asif will discuss a different backscatter imaging paradigm based on time-reversal signal processing that uses multipath propagation to its advantage for breast cancer detection.

With the introduction of time reversal, Asif says he believes for the first time there is analytical proof of the phenomena of super resolution focusing observed with time reversal. He will discuss time-reversal imaging algorithms used for detecting and accurately estimating the location of targets in a high-scattering environment with strong clutters.

The time-reversal beam-forming imager is applied for detecting and locating early-stage breast cancer tumours from MRI data, says Asif. He will present initial results based on the finite difference, time domain 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-the-art signal processing estimation algorithms they have tested.

Asif received MSc and PhD degrees in electrical and computer engineering from Carnegie Mellon University (CMU) in Pittsburgh, Penn. He was formerly on the faculty of CMU, and the Technical University of British Columbia (now part of Simon Fraser University) in Vancouver.

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. He is also co-author of the textbook, Continuous and Discrete Time Signals and Systems (Cambridge University Press, 2007).

Republished courtesy of YFile– York University’s daily e-bulletin.