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.
Highlights
Multidimensional microscopic image data sets (Figure 1) are widely used in modern biology studies, especially in screening various phenotypic data
We briefly introduce the basic concepts and methods of 3D microscopic image visualization and analysis, which are the two core components for a number of bioimage informatics applications
The essential visualization and analysis methods introduced here can be applied to a wide range of data, including many of those not explicitly discussed
Summary
Multidimensional microscopic image data sets (Figure 1) are widely used in modern biology studies, especially in screening various phenotypic data. ImageJ [13] (a newer variant bears the name Fiji), a popular tool to visualize and analyze microscopic images, uses mainly the z-section display to visualize 3D images, various additional ImageJ modules or plugins were developed to render 3D views. Maximal (or minimal) intensity projection (MIP or mIP) and alpha-value blended views (Table 1) are two main types of methods to display 3D data.
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