Parallel deconvolution of large 3D images obtained by confocal laser scanning microscopy.
Various deconvolution algorithms are often used for restoration of digital images. Image deconvolution is especially needed for the correction of three-dimensional images obtained by confocal laser scanning microscopy. Such images suffer from distortions, particularly in the Z dimension. As a result, reliable automatic segmentation of these images may be difficult or even impossible. Effective deconvolution algorithms are memory-intensive and time-consuming. In this work, we propose a parallel version of the well-known Richardson-Lucy deconvolution algorithm developed for a system with distributed memory and implemented with the use of Message Passing Interface (MPI). It enables significantly more rapid deconvolution of two-dimensional and three-dimensional images by efficiently splitting the computation across multiple computers. The implementation of this algorithm can be used on professional clusters provided by computing centers as well as on simple networks of ordinary PC machines.
Pawliczek
Piotr
P
Department of Computer Science, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, AGH University of Science and Technology, Kraków. piotr@pawliczek.net.pl
Romanowska-Pawliczek
Anna
A
Soltys
Zbigniew
Z
D000465:Algorithms; D000818:Animals; D001921:Brain / Q000166:cytology*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007150:Immunohistochemistry; D018613:Microscopy, Confocal / Q000379:methods*; D008962:Models, Theoretical; D009457:Neuroglia / Q000737:chemistry* / Q000166:cytology*; D051381:Rats