Mr. Carrson C. Fung Profile

Carrson C. Fung

at HKUST

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Proceedings Article | 21 November 2002 Paper

Design of compactly supported wavelet to match singularities in medical images

Carrson Fung, Pengcheng Shi

Proceedings Volume 4790, (2002) https://doi.org/10.1117/12.452348

KEYWORDS: Wavelets, Edge detection, Medical imaging, Algorithm development, Detection and tracking algorithms, Signal detection, Discrete wavelet transforms, Continuous wavelet transforms, Pattern recognition, Image processing

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Analysis and understanding of medical images has important clinical values for patient diagnosis and treatment, as well as technical implications for computer vision and pattern recognition. One of the most fundamental issues is the detection of object boundaries or singularities, which is often the basis for further processes such as organ/tissue recognition, image registration, motion analysis, measurement of anatomical and physiological parameters, etc. The focus of this work involved taking a correlation based approach toward edge detection, by exploiting some of desirable properties of wavelet analysis. This leads to the possibility of constructing a bank of detectors, consisting of multiple wavelet basis functions of different scales which are optimal for specific types of edges, in order to optimally detect all the edges in an image. Our work involved developing a set of wavelet functions which matches the shape of the ramp and pulse edges. The matching algorithm used focuses on matching the edges in the frequency domain. It was proven that this technique could create matching wavelets applicable at all scales. Results have shown that matching wavelets can be obtained for the pulse edge while the ramp edge requires another matching algorithm.

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