As the imaging technology and the understanding of neurological disease improve, a solid understanding of neu-roanatomy has become increasingly relevant. Neuroanatomy teaching includes the practice of cadaveric dissectionand neuroanatomy atlases consisting of images of a brain with its labeled structures. However, the natural inter-individual neuroanatomical variability cannot be taken into account. This work addresses the individual grossneuroanatomy atlas that could enrich medical students’ experiences with various individual variations in anatomi-cal landmarks and their spatial relationships. We propose to deform the CerebrA cortical atlas into the individualanatomical magnetic resonance imaging data to increase students’ opportunity to contact normal neuroanatomicalvariations in the early stages of studies. Besides, we include interactive queries on the labels/names of neu-roanatomical structures from an individual neuroanatomical atlas in a 3D space. An implementation on top ofSimpleITK library and VMTK-Neuro software is presented. We generated a series of surface and internal neu-roanatomy maps from 16 test volumes to attest to the potential of the proposed technique in brain labeling. Forthe age group between 10 to 75, there is evidence that the superficial cortical labeling is accurate with the visualassessment of the degree of concordance between the neuroanatomical and label boundaries.
Is it possible to assess the best mitral valve repair in the individual patient? Preliminary results of a finite element study from magnetic resonance imaging data