Real-time multi-view deconvolution.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 26112291.
- Also identified by DOI 10.1093/bioinformatics/btv387 and PMC identifier 4595906.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
In light-sheet microscopy, overall image content and resolution are improved by acquiring and fusing multiple views of the sample from different directions. State-of-the-art multi-view (MV) deconvolution simultaneously fuses and deconvolves the images in 3D, but processing takes a multiple of the acquisition time and constitutes the bottleneck in the imaging pipeline. Here, we show that MV deconvolution in 3D can finally be achieved in real-time by processing cross-sectional planes individually on the massively parallel architecture of a graphics processing unit (GPU). Our approximation is valid in the typical case where the rotation axis lies in the imaging plane. Source code and binaries are available on github (https://github.com/bene51/), native code under the repository 'gpu_deconvolution', Java wrappers implementing Fiji plugins under 'SPIM_Reconstruction_Cuda'. bschmid@mpi-cbg.de or huisken@mpi-cbg.de Supplementary data are available at Bioinformatics online.
Medical subject headings
- Imaging, Three-Dimensional
- Microscopy