FMRIB Software Library. FSL is a comprehensive library of analysis tools for FMRI, MRI and DTI brain imaging data. It runs on Apple and PCs (both Linux, and Windows via a Virtual Machine), and is very easy to install. Most of the tools can be run both from the command line and as GUIs (”point-and-click” graphical user interfaces). To quote the relevant references for FSL tools you should look in the individual tools’ manual pages, and also please reference one or more of the FSL overview papers: 1. M.W. Woolrich, S. Jbabdi, B. Patenaude, M. Chappell, S. Makni, T. Behrens, C. Beckmann, M. Jenkinson, S.M. Smith. Bayesian analysis of neuroimaging data in FSL. NeuroImage, 45:S173-86, 2009. 2. S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady, and P.M. Matthews. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(S1):208-19, 2004. 3. M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, S.M. Smith. FSL. NeuroImage, 62:782-90, 2012

References in zbMATH (referenced in 45 articles )

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  1. Jensen, Henrik G.; Lauze, François; Darkner, Sune: Information-theoretic registration with explicit reorientation of diffusion-weighted images (2022)
  2. Xing, Xin; Xie, Rui; Zhong, Wenxuan: Model-based sparse coding beyond Gaussian independent model (2022)
  3. Cardona Jiménez, Johnatan; de B. Pereira, Carlos A.: Assessing dynamic effects on a Bayesian matrix-variate dynamic linear model: an application to task-based fMRI data analysis (2021)
  4. Feng, Long; Bi, Xuan; Zhang, Heping: Brain regions identified as being associated with verbal reasoning through the use of imaging regression via internal variation (2021)
  5. Martin Ondrus, Emily Olds, Ivor Cribben: Factorized Binary Search: change point detection in the network structure of multivariate high-dimensional time series (2021) arXiv
  6. Sakhanenko, Lyudmila; DeLaura, Michael; Zhu, David C.: Nonparametric model for a tensor field based on high angular resolution diffusion imaging (HARDI) (2021)
  7. Zhao, Yi; Caffo, Brian; Luo, Xi: Principal regression for high dimensional covariance matrices (2021)
  8. Conte, Martina; Gerardo-Giorda, Luca; Groppi, Maria: Glioma invasion and its interplay with nervous tissue and therapy: a multiscale model (2020)
  9. Maugis, P.-A. G.; Olhede, S. C.; Priebe, C. E.; Wolfe, P. J.: Testing for equivalence of network distribution using subgraph counts (2020)
  10. Pinheiro, G. R.; Carmo, D. S.; Yasuda, C.; Lotufo, R. A.; Rittner, L.: Convolutional neural network on DTI data for sub-cortical brain structure segmentation (2020)
  11. Pizzolato, Marco; Palombo, Marco; Bonet-Carne, Elisenda; Tax, Chantal M. W.; Grussu, Francesco; Ianus, Andrada; et al.: Acquiring and predicting multidimensional diffusion (MUDI) data: an open challenge (2020)
  12. Spencer, Daniel; Guhaniyogi, Rajarshi; Prado, Raquel: Joint Bayesian estimation of voxel activation and inter-regional connectivity in fMRI experiments (2020)
  13. Weninger, Leon; Koppers, Simon; Na, Chuh-Hyoun; Juetten, Kerstin; Merhof, Dorit: Free-water correction in diffusion MRI: a reliable and robust learning approach (2020)
  14. Yoder, Jordan; Chen, Li; Pao, Henry; Bridgeford, Eric; Levin, Keith; Fishkind, Donniell E.; Priebe, Carey; Lyzinski, Vince: Vertex nomination: the canonical sampling and the extended spectral nomination schemes (2020)
  15. Li, Kan; Luo, Sheng: Bayesian functional joint models for multivariate longitudinal and time-to-event data (2019)
  16. Polzehl, Jörg; Tabelow, Karsten: Magnetic resonance brain imaging. Modeling and data analysis using R (2019)
  17. Zhang, Fengqing; Gou, Jiangtao: Control of false positive rates in clusterwise fMRI inferences (2019)
  18. Andrew Beers; James Brown; Ken Chang; Katharina Hoebel; Elizabeth Gerstner; Bruce Rosen; Jayashree Kalpathy-Cramer: DeepNeuro: an open-source deep learning toolbox for neuroimaging (2018) arXiv
  19. Banerjee, Abhirup; Maji, Pradipta: Spatially constrained Student’s (t)-distribution based mixture model for robust image segmentation (2018)
  20. Macdonald, Jan; Ruthotto, Lars: Improved susceptibility artifact correction of echo-planar MRI using the alternating direction method of multipliers (2018)

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