Speaker:
Professor Michael Unser
Biomedical Imaging Group
École Polytechnique Fédérale de Lausanne
Switzerland
Chair:
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Abstract: Our purpose in this talk is
to advocate the use of wavelets for advanced bioimaging. We
start with a short tutorial on wavelet bases, emphasizing the
fact that they provide a concise multiresolution representation
of images and that they can be computed most efficiently. We
then discuss a simple—but remarkably effective—image denoising
procedure that essentially amounts to discarding small wavelet
coefficients (soft-thresholding); we show that this type of
algorithm is the solution of a variational problem that promotes
“sparse” solutions. We believe that the underlying principle of
wavelet regularization is a powerful concept that can be used
advantageously in a variety of inverse image-reconstruction
problems, including MRI and computed tomography. |
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We illustrate our point by presenting a novel wavelet-based
deconvolution algorithm for 3D fluorescence microscopy, as well
as some preliminary results for dynamic PET reconstruction. We
will also discuss wavelet techniques for the analysis of
functional MRI data and optical microscopy (extended depth of
field).. |
Biography:
Michael Unser is Professor and Director of EPFL's Biomedical
Imaging Group, Lausanne, Switzerland. His main research area is
biomedical image processing. He has a strong interest in sampling
theories, multiresolution algorithms, wavelets, and the use of splines
for image processing. He has published over 150 journal papers on
those topics, and is one of ISI’s Highly Cited authors in Engineering
(http://isihighlycited.com).
From 1985 to 1997, he was with the Biomedical Engineering and
Instrumentation Program, National Institutes of Health, Bethesda USA,
conducting research on bioimaging and heading the Image Processing
Group.
Dr. Unser is a fellow of the IEEE and the recipient of three Best
Paper Awards from the IEEE Signal Processing Society. He was recently
elected to the Swiss Academy of Engineering Sciences.
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