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一种用于测量和计数实验室微宇宙中生物的自动化图像分析系统。

An automated image analysis system to measure and count organisms in laboratory microcosms.

机构信息

CNRS/UPMC/ENS, Écologie et Évolution, UMR 7625, École Normale Supérieure, Paris, France.

出版信息

PLoS One. 2013 May 29;8(5):e64387. doi: 10.1371/journal.pone.0064387. Print 2013.

DOI:10.1371/journal.pone.0064387
PMID:23734199
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3667193/
Abstract
  1. Because of recent technological improvements in the way computer and digital camera perform, the potential use of imaging for contributing to the study of communities, populations or individuals in laboratory microcosms has risen enormously. However its limited use is due to difficulties in the automation of image analysis. 2. We present an accurate and flexible method of image analysis for detecting, counting and measuring moving particles on a fixed but heterogeneous substrate. This method has been specifically designed to follow individuals, or entire populations, in experimental laboratory microcosms. It can be used in other applications. 3. The method consists in comparing multiple pictures of the same experimental microcosm in order to generate an image of the fixed background. This background is then used to extract, measure and count the moving organisms, leaving out the fixed background and the motionless or dead individuals. 4. We provide different examples (springtails, ants, nematodes, daphnia) to show that this non intrusive method is efficient at detecting organisms under a wide variety of conditions even on faintly contrasted and heterogeneous substrates. 5. The repeatability and reliability of this method has been assessed using experimental populations of the Collembola Folsomia candida. 6. We present an ImageJ plugin to automate the analysis of digital pictures of laboratory microcosms. The plugin automates the successive steps of the analysis and recursively analyses multiple sets of images, rapidly producing measurements from a large number of replicated microcosms.
摘要
  1. 由于计算机和数码相机在性能上的技术进步,成像技术在实验室微宇宙中对群落、种群或个体进行研究的潜在用途大大增加。然而,由于图像分析自动化的困难,其应用仍然有限。

  2. 我们提出了一种准确而灵活的图像分析方法,用于检测、计数和测量固定但不均匀基质上的移动粒子。该方法专门用于跟踪实验实验室微宇宙中的个体或整个种群。它可以用于其他应用。

  3. 该方法包括比较同一实验微宇宙的多张图片,以生成固定背景的图像。然后,使用该背景提取、测量和计数移动生物,同时排除固定背景和静止或死亡的个体。

  4. 我们提供了不同的例子(跳虫、蚂蚁、线虫、水蚤),以表明这种非侵入性的方法在检测各种条件下的生物时非常有效,即使在对比度和不均匀性较差的基质上也是如此。

  5. 使用 Collembola Folsomia candida 的实验种群评估了该方法的可重复性和可靠性。

  6. 我们提出了一种用于自动化实验室微宇宙数字图像分析的 ImageJ 插件。该插件自动化了分析的连续步骤,并递归地分析多组图像,从大量重复的微宇宙中快速生成测量结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cae/3667193/ce6264a44d48/pone.0064387.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cae/3667193/ccf0d3346872/pone.0064387.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cae/3667193/ce6264a44d48/pone.0064387.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cae/3667193/ccf0d3346872/pone.0064387.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cae/3667193/ce6264a44d48/pone.0064387.g004.jpg

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