Development, characterization and application of the s-transform to medical imaging
Date
2008
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Abstract
The S-transform (ST) is a relatively new technique, first proposed in 1996 and applied to problems in geophysics. The properties and applications of the transform, and its relationship to existing techniques have not been fully explored. Though some applications, particularly in medical signal and image processing, have shown promise, the high computational requirements of the algorithm have hampered research and application of the ST. In this thesis the computational requirements of the ST are addressed and a promising image processing technique using the transform is characterized, validated and applied to several biomedical imaging problems. Two approaches to speeding up the ST are explored: (1) a parallel ST algorithm is introduced, which allows the ST calculation to take advantage of modern multi-processor hardware and computing clusters and (2) a fast ST algorithm is formulated, which dramatically reduces the computational requirements of the transform. Additionally, a general description of time-frequency transforms is presented, which clearly demonstrates the similarities and differences between the ST and both the wavelet and Fourier families of transforms. Extending this theoretical relationship, a technique that uses the ST to detect and quantify image texture is compared to an equivalent procedure based on the Fourier transform, and validated using a purpose built magnetic resonance phantom. The ST texture analysis technique is then applied to several examples of medical image analysis problems. One of these potential applications, detection of an important genetic marker in brain tumours, is explored in depth with a clinical study of 54 patients.
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Bibliography: p. 164-175
Some pages are in colour.
Some pages are in colour.
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Citation
Brown, R. A. (2008). Development, characterization and application of the s-transform to medical imaging (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/1611