1. A method for automatic determination of perfusion in a magnetic resonance (MR) system, comprising the steps of: (a) generating multiple first MR data sets from a volume element of a subject over time using a perfusion-sensitive imaging sequence; (b) generating multiple second MR data sets of said volume element of said subject over time using a control MR imaging sequence; (c) obtaining a statistical analysis result by statistically analyzing said first MR data sets and said second MR data sets with at least one model function embodying at least one regressor, and selecting said at least one regressor from the group consisting of regressors representing breathing of the subject, regressors representing a heartbeat of the subject, regressors representing a physiological state of the subject, and regressors representing functional activity of the subject, and, using said statistical analysis result, determining perfusion in said volume element, as determined perfusion; (d) tracking quality of the determined perfusion in said volume element by also statistically analyzing said first MR data sets and said second MR data sets to obtain at least one further result, other than said statistical analysis result from which said perfusion is determined, selected from the group consisting of a reliability indicator for said determination of said perfusion of said volume element, information describing a contrast-to-noise ratio for an image point of said volume element, and information describing at least one characteristic of said subject that may produce an artifact in an image reconstructed from said first MR data sets and said second MR data sets and using said at least one further result to exclude at least a portion of at least one of said first and second MR data sets for which said at least one further result indicates a poor quality, to produce quality-tracked first and second MR data sets; and (e) continuously reconstructing MR images of said volume from said quality-tracked first MR data sets and said second MR data sets, and continuously updating said MR images with newly acquired multiple first MR data sets and multiple second MR data sets to which steps (c) and (d) are also applied.