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实时多视图反卷积

Real-time multi-view deconvolution.

作者信息

Schmid Benjamin, Huisken Jan

机构信息

Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.

出版信息

Bioinformatics. 2015 Oct 15;31(20):3398-400. doi: 10.1093/bioinformatics/btv387. Epub 2015 Jun 25.

Abstract

UNLABELLED

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.

AVAILABILITY AND IMPLEMENTATION

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'.

CONTACT

bschmid@mpi-cbg.de or huisken@mpi-cbg.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

未标注

在光片显微镜中,通过从不同方向获取并融合样本的多个视图,整体图像内容和分辨率得以提高。最新的多视图(MV)反卷积可在三维空间中同时融合和解卷积图像,但处理时间是采集时间的数倍,这构成了成像流程中的瓶颈。在此,我们表明,通过在图形处理单元(GPU)的大规模并行架构上单独处理横截面平面,最终可以实时实现三维MV反卷积。我们的近似方法在旋转轴位于成像平面的典型情况下是有效的。

可用性与实现

源代码和二进制文件可在github(https://github.com/bene51/)上获取,原生代码在“gpu_deconvolution”仓库下,实现Fiji插件的Java包装器在“SPIM_Reconstruction_Cuda”下。

联系方式

bschmid@mpi-cbg.dehuisken@mpi-cbg.de

补充信息

补充数据可在《生物信息学》在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28c1/4595906/007deef06a9b/btv387f1p.jpg

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