title: NiftyFit: a Software Package for Multi-parametric Model-Fitting of 4D Magnetic Resonance Imaging Data.
abstract: Multi-modal, multi-parametric Magnetic Resonance (MR) Imaging is becoming an increasingly sophisticated tool for neuroimaging. The relationships between parameters estimated from different individual MR modalities have the potential to transform our understanding of brain function, structure, development and disease. This article describes a new software package for such multi-contrast Magnetic Resonance Imaging that provides a unified model-fitting framework. We describe model-fitting functionality for Arterial Spin Labeled MRI, T1 Relaxometry, T2 relaxometry and Diffusion Weighted imaging, providing command line documentation to generate the figures in the manuscript. Software and data (using the nifti file format) used in this article are simultaneously provided for download. We also present some extended applications of the joint model fitting framework applied to diffusion weighted imaging and T2 relaxometry, in order to both improve parameter estimation in these models and generate new parameters that link different MR modalities. NiftyFit is intended as a clear and open-source educational release so that the user may adapt and develop their own functionality as they require.
authors.affiliation: Centre for Medical Image Computing, University College London, London, UK. a.melbourne@ucl.ac.uk.
authors.forename: Andrew
authors.initials: A
authors.lastname: Melbourne
authors.affiliation: Centre for Medical Image Computing, University College London, London, UK.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Toussaint
authors.affiliation: Centre for Medical Image Computing, University College London, London, UK.
authors.forename: David
authors.initials: D
authors.lastname: Owen
authors.affiliation: Centre for Medical Image Computing, University College London, London, UK.
authors.forename: Ivor
authors.initials: I
authors.lastname: Simpson
authors.affiliation: Centre for Medical Image Computing, University College London, London, UK.
authors.forename: Thanasis
authors.initials: T
authors.lastname: Anthopoulos
authors.affiliation: Academic Neuroradiological Unit, UCL Institute of Neurology, London, UK.
authors.forename: Enrico
authors.initials: E
authors.lastname: De Vita
authors.affiliation: Medical Physics, University College Hospital, London, UK.
authors.forename: David
authors.initials: D
authors.lastname: Atkinson
authors.affiliation: Centre for Medical Image Computing, University College London, London, UK.
authors.forename: Sebastien
authors.initials: S
authors.lastname: Ourselin
mesh_terms: D001921:Brain / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods*; D038524:Diffusion Magnetic Resonance Imaging; D056324:Diffusion Tensor Imaging; D006801:Humans; D008279:Magnetic Resonance Imaging; D064847:Multimodal Imaging; D012984:Software
keywords: Cerebral blood flow; Diffusion; MRI; Relaxometry; g-ratio