Discrete Fourier Transform Techniques to Improve Diagnosis Accuracy in Biomedical Applications

Date
2018-01-08
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Transforming acquired data in time or space is necessary for many applications, due to practical constraints on time-domain sampling at high data rates or the requirement for algorithms to process frequency-domain data during the image reconstruction procedure. Therefore, the discrete Fourier transform (DFT) plays an important role in many fields for preprocessing, reconstruction or data analysis stages of algorithms. The hardware or physical constraints also necessitate acquisition of limited length raw data which results in DFT-imposed distortions after data processing for which low pass filters are considered as general solution. Through this thesis, fundamental DFT properties are investigated and an optimization method is introduced to take advantage of these properties. This method is a potential alternative to low pass filters which impose resolution loss to processed data. The formalized method is examined and validated using preliminary observer metrics for two magnetic resonance imaging reconstruction approaches and a microwave imaging technique.
Description
Keywords
Citation
Adipour, P. (2018). Discrete Fourier Transform Techniques to Improve Diagnosis Accuracy in Biomedical Applications (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.