title: Multiple-fiber reconstruction algorithms for diffusion MRI.
abstract: This chapter reviews multiple-fiber reconstruction algorithms for diffusion magnetic resonance imaging (MRI) and provides some initial comparative results for two such algorithms, q-ball imaging and PASMRI, on data from a typical clinical diffusion MRI acquisition. The chapter highlights the problems with standard approaches, such as diffusion-tensor MRI, to motivate a recent set of alternative approaches. The review concentrates on the software implementation of the new techniques. Results of the preliminary comparison show that PASMRI recovers the principal directions of simple test functions more consistently than q-ball imaging and produces qualitatively better results on the test data set. Further simulations suggest that a moderate increase in data quality allows q-ball, which is much faster to run, to recover directions with consistency comparable to that of PASMRI on the test data.
authors.affiliation: Department of Computer Science, University College London, Gower Street, London WC1E 6BT, United Kingdom. d.alexander@cs.ucl.ac.uk
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Alexander
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009413:Nerve Fibers, Myelinated / Q000502:physiology / Q000648:ultrastructure; D009434:Neural Pathways / Q000033:anatomy & histology / Q000502:physiology; D012984:Software