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Visualization and analysis of 3D microscopic images.

Long F, Zhou J, Peng H - PLoS Comput. Biol. (2012)

Bottom Line: In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images.In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets.We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.

View Article: PubMed Central - PubMed

Affiliation: Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.

ABSTRACT
In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.

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A pipeline of image analysis and data mining tools for building the neuronal atlases of fruit fly brains.(a) A flowchart of the key steps in building a fruit fly brain atlas. (b) A 3D digital atlas of 269 stereotyped neurite tracts reconstructed from GAL4-label fruit fly brains [19]. Pseudo colors are used to distinguish different tracts. The width of each tract equals its spatial divergence.
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pcbi-1002519-g004: A pipeline of image analysis and data mining tools for building the neuronal atlases of fruit fly brains.(a) A flowchart of the key steps in building a fruit fly brain atlas. (b) A 3D digital atlas of 269 stereotyped neurite tracts reconstructed from GAL4-label fruit fly brains [19]. Pseudo colors are used to distinguish different tracts. The width of each tract equals its spatial divergence.

Mentions: Pipelining image analysis modules and other more sophisticated data analysis/mining modules is a powerful way to generate quantitative biology. One such pipeline is shown in Figure 4a, which illustrates the main steps to construct the first 3D map of spatially invariant neurite tracts of a brain. Confocal images of adult fruit fly brains are first registered in 3D using the BrainAligner system [19] (Figure 4a, Step 2), so that different populations of neurons labeled using a number of GAL4 lines can be aligned and compared within the same 3D coordinate system. Then, neurite tracts are segmented and traced in 3D (Figure 4a, Step 3). The neurite tracts reconstructed from the same GAL4 line have a clear correspondence. They are then annotated (Figure 4a, Step 4). A neuron/neurite comparison and mining module is then used to determine the spatial divergence of the corresponding neurite tracts (Figure 4a, Step 5), followed by a final mapping to the standard space of the 3D fly brain atlas (Figure 4a, Step 5). With this approach, it is possible to measure hundreds of stereotyped neurite tracts in a fruit fly's brain (Figure 4b). The same pipeline can be used to study other brain wiring-maps of neurons.


Visualization and analysis of 3D microscopic images.

Long F, Zhou J, Peng H - PLoS Comput. Biol. (2012)

A pipeline of image analysis and data mining tools for building the neuronal atlases of fruit fly brains.(a) A flowchart of the key steps in building a fruit fly brain atlas. (b) A 3D digital atlas of 269 stereotyped neurite tracts reconstructed from GAL4-label fruit fly brains [19]. Pseudo colors are used to distinguish different tracts. The width of each tract equals its spatial divergence.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3375219&req=5

pcbi-1002519-g004: A pipeline of image analysis and data mining tools for building the neuronal atlases of fruit fly brains.(a) A flowchart of the key steps in building a fruit fly brain atlas. (b) A 3D digital atlas of 269 stereotyped neurite tracts reconstructed from GAL4-label fruit fly brains [19]. Pseudo colors are used to distinguish different tracts. The width of each tract equals its spatial divergence.
Mentions: Pipelining image analysis modules and other more sophisticated data analysis/mining modules is a powerful way to generate quantitative biology. One such pipeline is shown in Figure 4a, which illustrates the main steps to construct the first 3D map of spatially invariant neurite tracts of a brain. Confocal images of adult fruit fly brains are first registered in 3D using the BrainAligner system [19] (Figure 4a, Step 2), so that different populations of neurons labeled using a number of GAL4 lines can be aligned and compared within the same 3D coordinate system. Then, neurite tracts are segmented and traced in 3D (Figure 4a, Step 3). The neurite tracts reconstructed from the same GAL4 line have a clear correspondence. They are then annotated (Figure 4a, Step 4). A neuron/neurite comparison and mining module is then used to determine the spatial divergence of the corresponding neurite tracts (Figure 4a, Step 5), followed by a final mapping to the standard space of the 3D fly brain atlas (Figure 4a, Step 5). With this approach, it is possible to measure hundreds of stereotyped neurite tracts in a fruit fly's brain (Figure 4b). The same pipeline can be used to study other brain wiring-maps of neurons.

Bottom Line: In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images.In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets.We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.

View Article: PubMed Central - PubMed

Affiliation: Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.

ABSTRACT
In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.

Show MeSH