Disease Markers

Disease Markers / 2002 / Article
Special Issue

Functional Imaging of Early Markers of Disease

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Volume 18 |Article ID 108741 | https://doi.org/10.1155/2002/108741

Paul Sajda, Andrew Laine, Yehoshua Zeevi, "Multi-Resolution and Wavelet Representations for Identifying Signatures of Disease", Disease Markers, vol. 18, Article ID 108741, 25 pages, 2002. https://doi.org/10.1155/2002/108741

Multi-Resolution and Wavelet Representations for Identifying Signatures of Disease

Received17 Nov 2003
Accepted17 Nov 2003

Abstract

Identifying physiological and anatomical signatures of disease in signals and images is one of the fundamental challenges in biomedical engineering. The challenge is most apparent given that such signatures must be identified in spite of tremendous inter and intra-subject variability and noise. Crucial for uncovering these signatures has been the development of methods that exploit general statistical properties of natural signals. The signal processing and applied mathematics communities have developed, in recent years, signal representations which take advantage of Gabor-type and wavelet-type functions that localize signal energy in a joint time-frequency and/or space-frequency domain. These techniques can be expressed as multi-resolution transformations, of which perhaps the best known is the wavelet transform. In this paper we review wavelets, and other related multi-resolution transforms, within the context of identifying signatures for disease. These transforms construct a general representation of signals which can be used in detection, diagnosis and treatment monitoring. We present several examples where these transforms are applied to biomedical signal and imaging processing. These include computer-aided diagnosis in mammography, real-time mosaicking of ophthalmic slit-lamp imagery, characterization of heart disease via ultrasound, predicting epileptic seizures and signature analysis of the electroencephalogram, and reconstruction of positron emission tomography data.

Copyright © 2002 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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