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Considerable attention from the international scientific community is currently focused on the wide ranging applications of wavelets. For the first time, the field's leading experts have come together to produce a complete guide to wavelet transform applications in medicine and biology. Wavelets in Medicine and Biology provides accessible, detailed, and comprehensive guidelines for all those interested in learning about wavelets and their applications to biomedical problems.
Considerable attention from the international scientific community
is currently focused on the wide ranging applications of wavelets.
For the first time, the field's leading experts have come together
to produce a complete guide to wavelet transform applications in
medicine and biology. Wavelets in Medicine and Biology provides
accessible, detailed, and comprehensive guidelines for all those
interested in learning about wavelets and their applications to
biomedical problems.
Biomedical imaging is a vast and diverse field. There are a
plethora of imaging devices using light, X-rays, sound waves,
magnetic fields, electrons, or protons, to measure structures
ranging from nano to macroscale. In many cases, computer software
is needed to turn the signals collected by the hardware into a
meaningful image. These computer algorithms are similarly diverse
and numerous.This survey presents a wide swath of biomedical image
reconstruction algorithms under a single framework. It is a
coherent, yet brief survey of some six decades of research. The
underpinning theory of the techniques are described and practical
considerations for designing reconstruction algorithms for use in
biomedical systems form the central theme of each chapter. The
unifying framework deployed throughout the monograph models imaging
modalities as combinations of a small set of building blocks, which
identify connections between modalities. Thus, the user can quickly
port ideas and computer code from one to the next. Furthermore,
reconstruction algorithms can treat the imaging model as a black.
box, meaning that one algorithm can work for many modalities. This
provides a pragmatic approach to designing effective reconstruction
algorithms.This monograph is written in a tutorial style that
concisely introduces students, researchers and practitioners to the
development and design of effective biomedical image reconstruction
algorithms.
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