2D slices are a simple method of extracting two dimensional data (suitable for displaying on a graphical workstation) from a three dimensional data set. The method is simple -- a plane through the data set is specified (it may be orthogonal, that is, parallel to an axis of the data set, or arbitrarily oriented) and the data points at the intersection of this plane and data set are displayed on the plane. The plane may be displayed orthogonally on the screen or more commonly in its actual orientation in the 3D space.
Slices overcome in a simple fashion the inability to see an entire cube of data at once. They are often an extremely good way to get a first impression of a data set, and an animation which steps through all the slice planes is also very useful.
Slices are applicable to density data, such as the lobster's CT/MRI scan, as they correspond back to physical space -- the density one would find taking a thin slice of the lobster. As such, it is easy for a human to interpret the visual image of the slice. However, while it is easy to understand what the slice is, caution must be exercised when attempting to understand how the different slices relate. Simply stepping through the slices is reasonable, but often requires a good deal of concentration to comprehend what is seen. Sometimes switching the slice to be perpendicular to its current position helps to show the context of the original slice.
The logical extension to this is to have more than one slice, each mutually perpendicular. This provides the desired context, and each slice supports the others in the user's comprehension of the data set. The major downside to this method is that it is often easy for the slices to obscure one another, which limits the amount of the slices that can be easily observed1.