Biomedical signal processing using a new class of wavelets

Zhuoer Shi; DeSheng Zhang; Haixiang Wang; Donald J. Kouri; David K. Hoffman

doi:10.1117/12.381705

5 April 2000 Biomedical signal processing using a new class of wavelets

Zhuoer Shi, DeSheng Zhang, Haixiang Wang, Donald J. Kouri, David K. Hoffman

Proceedings Volume 4056, Wavelet Applications VII; (2000) https://doi.org/10.1117/12.381705
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

We design a new compactly-supported interpolating wavelet- distributed approximating functional (DAF) wavelet for biomedical signal/image processing. DAF class is a smooth, continuous interpolating function system which is symmetric and fast-decaying. DAF neural networks are designed for time varying electrocardiogram signal filtering. The neural nets use the Hermite-DAF as the basis function and implement a 3- layer structure. DAF wavelets and the corresponding subband filters are constructed for image processing. Edge- enhancement normalization and device-adapted visual group normalization algorithms are presented which sharpen the desired image features without prior knowledge of the spatial characteristics of the images. We design a nonlinear multiscale gradient-stretch method for feature extraction of mammograms. A fractal technique is introduced to characterize microcalcifications in localized regions of breast tissue. We employ a DAF wavelet-based multiscale edge detection and Dijkstra fractal technique is introduced to characterize microcalcifications in localized regions of breast tissue. We employ a DAF wavelet-based multiscale edge detection and Dijkstra fractal technique to identify micro calcification regions, and use a stochastic thresholding method to detect the calcified spots. The combined perceptual techniques produce natural high-quality images based on the human vision system. The underlying technologies significantly facilitate the creation of generic signal processing and computer-aided diagnostic systems. The system is implemented in the JAVA language, which is cross-platform friendly and is facilitated for telemedicine application.

Citation Download Citation

Zhuoer Shi, DeSheng Zhang, Haixiang Wang, Donald J. Kouri, and David K. Hoffman "Biomedical signal processing using a new class of wavelets", Proc. SPIE 4056, Wavelet Applications VII, (5 April 2000); https://doi.org/10.1117/12.381705

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