Design of compactly supported wavelet to match singularities in medical images

Carrson Fung*, Pengcheng Shi


研究成果: Conference article同行評審

4 引文 斯高帕斯(Scopus)


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.

頁(從 - 到)358-369
期刊Proceedings of SPIE - The International Society for Optical Engineering
出版狀態Published - 1 12月 2002
事件Applications of Digital Image Processing XXV - Seattle, WA, United States
持續時間: 8 7月 200210 7月 2002


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