Visualization and analysis of 3D microscopic images

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.

Figure 1. Examples of 3D microscopic images.

(a) A confocal image of kinetochores (EGFP labeled) and chromosomes (histone-mCherry labeled) used in studying the first meiotic division in mouse oocytes . (b) A confocal image of the first larval stage of C. elegans . Gray: DAPI labeled nuclei; yellow: myo3:EGFP. (c) A confocal image of an adult fruit fly brain . Gray: NC82 labeled neuropil; green: ato-GAL4 (courtesy of Julie Simpson). (d) A serial section electron microscopic image of mouse visual cortex . (e) A digital scanned laser light sheet fluorescence microscopic image of a Medaka juvenile . Green: acetylated tubulin immuno-staining of the developing brain and spinal cord.

Figure 2. Vaa3D visualization of 4D and 5D microscopic images, as well as associated 3D surface objects, of different model animals.

(a) The hierarchical (multi-scale) 3D visualization of a fluorescent confocal image of fruit fly (Drosophila melanogaster) brain using both global and local 3D viewers. In the global viewer, different brain compartments rendered using surface meshes (in different colors) are overlaid on top of the 3D volume of a fruit fly brain. When an image is very large, the global viewer can serve for navigation purpose. A user can quickly define any 3D local region of interest and display it in a local 3D viewer using full resolution. In this example, the brain voxels can be rendered in a different color from the global viewer, while the user can optionally display other surface objects, such as the single 3D-reconstructed neuron (yellow). (b) 5D visualization of a series of multi-color 3D image stacks of C. elegans (courtesy of Rex Kerr). Different 3D viewing angles can be adjusted in real-time in Vaa3D, with which the user can freely change the displayed time point (bottom).

Figure 3. 3D image visualization and analysis for measuring single-cell gene expression of C. elegans.

(a) Tri-view display of a confocal image of C. elegans (L1 stage). Green: DAPI staining (pseudo-colored); red: myo3:GFP labeled muscle cells. (b) Tri-view display of the 3D watershed segmented nuclei of (a). The co-localized image objects are indicated by crosses (white). (c) A spreadsheet display of 3D measured gene expression of various cells. All sub-figures are produced using VANO , a 3D annotation tool.

Figure 4. 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 . Pseudo colors are used to distinguish different tracts. The width of each tract equals its spatial divergence.