title: High-fidelity meshes from tissue samples for diffusion MRI simulations.
abstract: This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.
authors.affiliation: Centre for Medical Image Computing, Department of Computer Science, University College London, UK. E.Panagiotaki@cs.ucl.ac.uk
authors.forename: Eleftheria
authors.initials: E
authors.lastname: Panagiotaki
authors.forename: Matt G
authors.initials: MG
authors.lastname: Hall
authors.forename: Hui
authors.initials: H
authors.lastname: Zhang
authors.forename: Bernard
authors.initials: B
authors.lastname: Siow
authors.forename: Mark F
authors.initials: MF
authors.lastname: Lythgoe
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Alexander
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D020342:Finite Element Analysis; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008953:Models, Anatomic; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity