基于图形处理器（GPU）的实时三维反卷积
Real-time GPU-based 3D Deconvolution.
作者信息
Bruce Marc A, Butte Manish J
机构信息
Stanford Immunology, Stanford University, Stanford, California 94305, USA.
出版信息
Opt Express. 2013 Feb 25;21(4):4766-73. doi: 10.1364/OE.21.004766.
Abstract
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.
摘要
共聚焦显微镜是生物学中常用的技术。三维图像的去卷积减少了离焦光造成的模糊，并能进行定量分析，但现有的去卷积软件速度慢且成本高。我们提出了一种并行化软件方法，该方法在ImageJ中运行，通过在低成本图形处理器板（GPU）上运行，对三维图像进行去卷积的速度比传统软件快约100倍（每张图像只需几秒钟）。我们通过分析CD4 + T细胞和树突状细胞免疫突触中的T细胞受体微簇来证明该软件的实用性。该软件提供了一种低成本且快速的方法来提高通过任何方法获得的三维显微图像的准确性。
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