共聚焦图像衍射模糊引入的基因表达数据误差估计

E. Myasnikova, S. Surkova, M. Samsonova, J. Reinitz
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引用次数: 4

摘要

共聚焦扫描显微镜是获取单细胞分辨率下基因表达数据的最常用方法。共聚焦图像的质量非常高,这使得从中提取高精度的定量信息成为可能。然而,由于可能的实验误差,数据的准确性受到限制。在这项研究中,我们提出了一种估计和校正共聚焦图像衍射散射引起的数据误差的算法。该方法基于Richardson-Lucy (RL)反卷积算法。改进了RL算法,以提供从具有锐利边缘的物体的模糊图像中读取的数据的更高精度。我们使用了{\it果蝇}胚胎的分割基因表达数据集作为测试案例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Errors in Gene Expression Data Introduced by Diffractive Blurring of Confocal Images
The confocal scanning microscopy is the most common method for acquisition of gene expression data at a resolution of a single cell. Confocal images are of very high quality that makes it possible to extract high-precision quantitative information from them. However the accuracy of the data is limited due to possible experimental errors. In this study we propose an algorithm for estimation and correction of errors in the data caused by diffractive scattering of confocal images. The method is based on the Richardson-Lucy (RL) deconvolution algorithm. The RL algorithm is modified to provide the higher accuracy of data read off from blurred images of objects with sharp edges. We have used the dataset on segmentation gene expression in {\it Drosophila} embryo as a test case.
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