Shape-constrained deformable brain segmentation: Methods and quantitative validation.

MRI-guided neuro interventions require rapid, accurate, and reproducible segmentation of anatomical brain structures for identification of targets during surgical procedures and post-surgical evaluation of intervention efficiency. Segmentation algorithms must be validated and cleared for clinical use. This work introduces a methodology for shape-constrained deformable brain segmentation, describes the quantitative validation used for its clinical clearance, and presents a comparison with manual expert segmentation and FreeSurfer, an open source software for neuroimaging data analysis.

Patient-Specific Sensor Registration for Electrical Source Imaging Using a Deformable Head Model.

Objective: Electrical source imaging of brain activity is most accurate when using individualized bioelectric head models. Constructing these models requires identifying electrode positions on the scalp surface. Current methods such as photogrammetry involve significant user interaction that limits integration in clinical workflows.

Measuring topology from dynamics by obtaining the Chern number from a linking number.

Integer-valued topological indices, characterizing nonlocal properties of quantum states of matter, are known to directly predict robust physical properties of equilibrium systems. The Chern number, e.g.

Observation of Topological Bloch-State Defects and Their Merging Transition.

Topological defects in Bloch bands, such as Dirac points in graphene, and their resulting Berry phases play an important role for the electronic dynamics in solid state crystals. Such defects can arise in systems with a two-atomic basis due to the momentum-dependent coupling of the two sublattice states, which gives rise to a pseudospin texture. The topological defects appear as vortices in the azimuthal phase of this pseudospin texture.