A novel 3D wavelet-based filter for visualizing features in noisy biological data.
Summary We have developed a three-dimensional (3D) wavelet-based filter for visualizing structural features in volumetric data. The only variable parameter is a characteristic linear size of the feature of interest. The filtered output contains only those regions that are correlated with the characteristic size, thus de-noising the image. We demonstrate the use of the filter by applying it to 3D data from a variety of electron microscopy samples, including low-contrast vitreous ice cryogenic preparations, as well as 3D optical microscopy specimens.
Moss
W C
WC
Lawrence Livermore National Laboratory, CA 94550, USA. wmoss@llnl.gov
Haase
S
S
Lyle
J M
JM
Agard
D A
DA
Sedat
J W
JW
D000818:Animals; D002502:Centrioles / Q000648:ultrastructure; D020285:Cryoelectron Microscopy / Q000379:methods; D005057:Eukaryotic Cells / Q000648:ultrastructure; D005374:Filtration; D008433:Mathematics; D008853:Microscopy / Q000379:methods*; D008870:Microtubules / Q000648:ultrastructure; D014054:Tomography / Q000379:methods; D014404:Tubulin / Q000648:ultrastructure
D014404:Tubulin