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Compendium Paper information and status T.E.
Merryman and J. Kovačević, “An adaptive multirate algorithm
for acquisition of fluorescence microscopy data sets”, IEEE Trans.
Image Proc., special issue on Molecular and Cellular Bioimaging, September
2005. vol. 14, no. 9, September 2005, pp. 1246-1253. [pdf] Abstract We present
an algorithm for efficient acquisition of fluorescence microscopy data sets,
a problem not addressed until now in the literature. We do this as part of a
larger system for protein classification based on their subcellular location
patterns, and thus strive to maintain the achieved level of classification
accuracy as much as possible. This problem is similar to image compression
but unique due to additional restrictions, namely causality; we have access
only to the information that has been scanned up to that point. While we do
want to acquire fewer samples with as low distortion as possible to achieve
compression, our goal is to do so while affecting the overall classification
accuracy as little as possible. We achieve this by using an adaptive multiresolution
scanning scheme which samples the regions of the image area that hold the
most pertinent information. Our results show that we can achieve significant
compression which we can then use to increase either time of space resolution
of our data set, all while minimally affecting the classification accuracy of
the entire system. Data 2D and 3D HeLa data sets
available from MurphyLab. Code The zipped archive contains
the readme file as well as the code to generate all the figures and tables in
the paper. [download] Pseudo-code NA Proofs NA List of tested configurations NA For more information or to
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