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| Content Provider | Springer Nature Link |
|---|---|
| Author | Melbourne, Andrew Toussaint, Nicolas Owen, David Simpson, Ivor Anthopoulos, Thanasis Vita, Enrico Atkinson, David Ourselin, Sebastien |
| Copyright Year | 2016 |
| 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. |
| Starting Page | 319 |
| Ending Page | 337 |
| Page Count | 19 |
| File Format | |
| ISSN | 15392791 |
| Journal | Neuroinformatics |
| Volume Number | 14 |
| Issue Number | 3 |
| e-ISSN | 15590089 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2016-03-14 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | MRI Relaxometry Diffusion Cerebral blood flow g-ratio Neurosciences Bioinformatics Computational Biology/Bioinformatics Computer Application in Life Sciences Neurology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Neuroscience Information Systems Software |
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