breathing virtual patients often need 4D image data acquisitions as a prerequisite. Here, first
a population-based breathing virtual patient 4D atlas is built and second the requirement of
a dose-relevant or expensive acquisition of a 4D CT or MRI data set for a new patient can be
mitigated by warping the mean atlas motion. The breakthrough contribution of this work is
the construction and reuse of population-based, learned 4D motion models.