Open AccessReal-time GPU-based 3D Deconvolution
Author(s) -
Marc A. Bruce,
Manish J. Butte
Publication year - 2013
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.21.004766
Subject(s) - deconvolution , computer science , software , focus (optics) , computer graphics (images) , graphics , computer vision , microscopy , image processing , blind deconvolution , autofocus , optics , artificial intelligence , computational science , image (mathematics) , algorithm , physics , programming language
Confocal microscopy is an oft-used technique in biology. Deconvolution of 3D images reduces blurring from out-of-focus light and enables quantitative analyses, but existing software for deconvolution is slow and expensive. We present a parallelized software method that runs within ImageJ and deconvolves 3D images ~100 times faster than conventional software (few seconds per image) by running on a low-cost graphics processor board (GPU). We demonstrate the utility of this software by analyzing microclusters of T cell receptors in the immunological synapse of a CD4 + T cell and dendritic cell. This software provides a low-cost and rapid way to improve the accuracy of 3D microscopic images obtained by any method.