DEPARTMENT OF MATHEMATICAL & STATISTICAL
UNIVERSITY OF ALBERTA
MATHEMATICAL BIOLOGY SEMINAR
MONDAY DECEMBER 1, 2003.
Dr. Hongmei Zhu
Departments of Radiology and
University of Calgary, and
Seaman Family MR Research Centre
Foothills Medical Centre, Calgary
Biomedical signals are typically finite duration, dynamic and non-stationary processes whose frequency characteristics vary over time or space. This often requires algorithms capable of locally analyzing and processing signals. The recently developed S-transform (ST) combines the time-frequency representation of the Gabor transform with the multi-scale analysis of the wavelet transforms. Applying this transform to a temporal signal reveals information on what and when frequency events occur. In addition, its multi-scale analysis allows more accurate detection of subtle signal changes while interpretation in a time-frequency domain is easy to understand. Based on the ST, a series of adaptive time-frequency analysis techniques can be derived, which may provide valuable information for disease diagnosis and treatment. In this talk, we overview the theory of the ST and illustrate its usefulness in de-noising and analyzing magnetic resonance imaging data.
This work is done in collaboration with Dr. J Ross Mitchell.