Real-time multi-view deconvolution
Quantitative Methods
2015-03-30 v1 Computer Vision and Pattern Recognition
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 employs the point spread functions (PSF) of the different views to simultaneously fuse and deconvolve 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 reslicing the acquired data and processing cross-sectional planes individually on the massively parallel architecture of a graphics processing unit (GPU).
Cite
@article{arxiv.1503.07998,
title = {Real-time multi-view deconvolution},
author = {Benjamin Schmid and Jan Huisken},
journal= {arXiv preprint arXiv:1503.07998},
year = {2015}
}
Comments
8 pages, 5 figures, submitted to Bioinformatics