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moco:用于钙成像的快速运动校正

moco: Fast Motion Correction for Calcium Imaging.

作者信息

Dubbs Alexander, Guevara James, Yuste Rafael

机构信息

Departments of Mathematics and CSE, University of Michigan Ann Arbor, MI, USA.

Neurotechnology Center, Department of Biological Sciences, Columbia University New York, NY, USA.

出版信息

Front Neuroinform. 2016 Feb 16;10:6. doi: 10.3389/fninf.2016.00006. eCollection 2016.

Abstract

Motion correction is the first step in a pipeline of algorithms to analyze calcium imaging videos and extract biologically relevant information, for example the network structure of the neurons therein. Fast motion correction is especially critical for closed-loop activity triggered stimulation experiments, where accurate detection and targeting of specific cells in necessary. We introduce a novel motion-correction algorithm which uses a Fourier-transform approach, and a combination of judicious downsampling and the accelerated computation of many L 2 norms using dynamic programming and two-dimensional, fft-accelerated convolutions, to enhance its efficiency. Its accuracy is comparable to that of established community-used algorithms, and it is more stable to large translational motions. It is programmed in Java and is compatible with ImageJ.

摘要

运动校正是分析钙成像视频并提取生物学相关信息(例如其中神经元的网络结构)的一系列算法中的第一步。快速运动校正对于闭环活动触发刺激实验尤为关键,在这类实验中,准确检测和定位特定细胞是必要的。我们引入了一种新颖的运动校正算法,该算法使用傅里叶变换方法,结合明智的下采样以及使用动态规划和二维快速傅里叶变换加速卷积对多个L2范数进行加速计算,以提高其效率。其准确性与已被广泛使用的社区算法相当,并且对大的平移运动更稳定。它用Java编写,并且与ImageJ兼容。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f791/4754735/01f0b3974005/fninf-10-00006-g0001.jpg

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