In this work BoneMRI is presented, a deep learning approach aiming at visualisation of radiodensity contrast by learning a mapping from MRI to CT data from 25 patients. Normal as well as pathological osseous structures in the cervical spine were clearly depicted. Quantitatively, radiodensity contrast similarity and high geometrical accuracy of vertebral dimensions was demonstrated. As BoneMRI is a 3D method it facilitates multiplanar reformatting in any desired direction. As such, BoneMRI is a promising tool for efficient morphological assessment of osseous structures without the need for ionizing radiation, simultaneously providing soft tissue contrasts in a single examination.