title: Computational cardiac anatomy using MRI.
abstract: Ventricular geometry and fiber orientation may undergo global or local remodeling in cardiac disease. However, there are as yet no mathematical and computational methods for quantifying variation of geometry and fiber orientation or the nature of their remodeling in disease. Toward this goal, a landmark and image intensity-based large deformation diffeomorphic metric mapping (LDDMM) method to transform heart geometry into common coordinates for quantification of shape and form was developed. Two automated landmark placement methods for modeling tissue deformations expected in different cardiac pathologies are presented. The transformations, computed using the combined use of landmarks and image intensities, yields high-registration accuracy of heart anatomies even in the presence of significant variation of cardiac shape and form. Once heart anatomies have been registered, properties of tissue geometry and cardiac fiber orientation in corresponding regions of different hearts may be quantified.
authors.affiliation: Center for Imaging Science, The Whitaker Biomedical Engineering Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
authors.forename: Mirza Faisal
authors.initials: MF
authors.lastname: Beg
authors.forename: Patrick A
authors.initials: PA
authors.lastname: Helm
authors.forename: Elliot
authors.initials: E
authors.lastname: McVeigh
authors.forename: Michael I
authors.initials: MI
authors.lastname: Miller
authors.forename: Raimond L
authors.initials: RL
authors.lastname: Winslow
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D004285:Dogs; D006321:Heart / Q000033:anatomy & histology*; D006331:Heart Diseases / Q000473:pathology; D007091:Image Processing, Computer-Assisted; D008297:Male; D008962:Models, Theoretical; D012016:Reference Values