title: Geometric metamorphosis.
abstract: Standard image registration methods do not account for changes in image appearance. Hence, metamorphosis approaches have been developed which jointly estimate a space deformation and a change in image appearance to construct a spatio-temporal trajectory smoothly transforming a source to a target image. For standard metamorphosis, geometric changes are not explicitly modeled. We propose a geometric metamorphosis formulation, which explains changes in image appearance by a global deformation, a deformation of a geometric model, and an image composition model. This work is motivated by the clinical challenge of predicting the long-term effects of traumatic brain injuries based on time-series images. This work is also applicable to the quantification of tumor progression (e.g., estimating its infiltrating and displacing components) and predicting chronic blood perfusion changes after stroke. We demonstrate the utility of the method using simulated data as well as scans from a clinical traumatic brain injury patient.
authors: University of North Carolina (UNC), Chapel Hill NC 27599-3175, USA.
authors: Marc
authors: M
authors: Niethammer
authors: Gabriel L
authors: GL
authors: Hart
authors: Danielle F
authors: DF
authors: Pace
authors: Paul M
authors: PM
authors: Vespa
authors: Andrei
authors: A
authors: Irimia
authors: John D
authors: JD
authors: Van Horn
authors: Stephen R
authors: SR
authors: Aylward
mesh_terms: D000465:Algorithms; D001930:Brain Injuries / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods; D003952:Diagnostic Imaging / Q000379:methods*; D018450:Disease Progression; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D015233:Models, Statistical; D008962:Models, Theoretical; D009369:Neoplasms / Q000473:pathology*; D010477:Perfusion; D012984:Software; D020521:Stroke / Q000473:pathology