Medical imaging tends to produce files with a large amount of
ancillary data (patient information, image information, acquisition
information, etc.). To organise this information in a useful fashion,
MINC uses variables to group together related attributes. The variable
itself may or may not contain useful data. For example, the variable
MIimage contains the image data and has attributes relevant to this
data. The variable
MIpatient has no relevant variable data, but
serves to group together all attributes describing the patient (name,
birthdate, etc.). This sort of variable is called a group variable.
Variables that correspond to dimensions are called dimension variables and describe the coordinate system corresponding to the dimension. An example is MIxspace -- both a dimension and a variable describing the x coordinate of other variables.
The NetCDF conventions allow for these dimension variables to specify
the coordinate at each point, but there is nothing to describe the
width of the sample at that point. MINC provides the convention of
dimension width variables, e.g.
MIxspace_width, to give this
Finally, it is possible to have attributes that vary over some of the
dimensions of the variable. For example, if we have a volume of image
data, varying over
MIzspace, we may want an attribute giving the maximum value of
the each image, varying over
MIzspace. To achieve this we use a
variable, called a variable attribute, pointed to by an attribute of
the image variable.
Thus MINC introduces a number of types of variables: group variables, dimension variables, dimension width variables and variable attributes.