AFNI

AFNI: Software for Analysis and Visualization of Functional Magnetic Resonance Neuroimages. A package of computer programs for analysis and visualization of three-dimensional human brain functional magnetic resonance imaging (FMRI) results is described. The software can color overlay neural activation maps onto higher resolution anatomical scans. Slices in each cardinal plane can be viewed simultaneously. Manual placement of markers on anatomical landmarks allows transformation of anatomical and functional scans into stereotaxic (Talairach–Tournoux) coordinates. The techniques for automatically generating transformed functional data sets from manually labeled anatomical data sets are described. Facilities are provided for several types of statistical analyses of multiple 3D functional data sets. The programs are written in ANSI C and Motif 1.2 to run on Unix workstations.


References in zbMATH (referenced in 23 articles )

Showing results 1 to 20 of 23.
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  1. Martin Ondrus, Emily Olds, Ivor Cribben: Factorized Binary Search: change point detection in the network structure of multivariate high-dimensional time series (2021) arXiv
  2. Li, Yingjie; Zhang, Liangliang; Maiti, Tapabrata: High dimensional classification for spatially dependent data with application to neuroimaging (2020)
  3. Adrian, Daniel W.; Maitra, Ranjan; Rowe, Daniel B.: Complex-valued time series modeling for improved activation detection in fMRI studies (2018)
  4. 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
  5. Choi, Ji Yeh; Hwang, Heungsun; Timmerman, Marieke E.: Functional parallel factor analysis for functions of one- and two-dimensional arguments (2018)
  6. Frank, Lawrence R.; Galinsky, Vitaly L.: Dynamic multiscale modes of resting state brain activity detected by entropy field decomposition (2016)
  7. John Muschelli, Elizabeth Sweeney, Martin Lindquist, Ciprian Crainiceanu: fslr: Connecting the FSL Software with R (2015) not zbMATH
  8. Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying: Spectral properties of the temporal evolution of brain network structure (2015)
  9. Anderson, John R.; Fincham, Jon M.: Extending problem-solving procedures through reflection (2014) MathEduc
  10. Ruiz Vargas, E.; Mitchell, D. G. V.; Greening, S. G.; Wahl, L. M.: Topology of whole-brain functional MRI networks: improving the truncated scale-free model (2014)
  11. Wang, Xiao-Feng; Li, Yingxing: Bayesian inferences for beta semiparametric-mixed models to analyze longitudinal neuroimaging data (2014)
  12. Rasmussen, Peter M.; Hansen, Lars K.; Madsen, Kristoffer H.; Churchill, Nathan W.; Strother, Stephen C.: Model sparsity and brain pattern interpretation of classification models in neuroimaging (2012) ioport
  13. Karsten Tabelow; Brandon Whitcher: Special Volume on Magnetic Resonance Imaging in R (2011) not zbMATH
  14. Karsten Tabelow; Jörg Polzehl: Statistical Parametric Maps for Functional MRI Experiments in R: The Package fmri (2011) not zbMATH
  15. Marijke Welvaert; Joke Durnez; Beatrijs Moerkerke; Geert Berdoolaege; Yves Rosseel: neuRosim: An R Package for Generating fMRI Data (2011) not zbMATH
  16. Zhang, Chunming; Fan, Jianqing; Yu, Tao: Multiple testing via (\mathrmFDR_L) for large-scale imaging data (2011)
  17. Preusse, Franziska; van der Meer, Elke; Ullwer, Dorothea; Brucks, Martin; Krueger, Frank; Wartenburger, IsabellAl.: Long-term characteristics of analogical processing in high-school students with high fluid intelligence: an fMRI study (2010) MathEduc
  18. Vidal, Camille; Jedynak, Bruno: Learning to match: deriving optimal template-matching algorithms from probabilistic image models (2010) ioport
  19. Yan, Xiaodan: Dissociated emergent-response system and fine-processing system in human neural network and a heuristic neural architecture for autonomous humanoid robots (2010) ioport
  20. Zhang, Chunming: Statistical inference of minimum BD estimators and classifiers for varying-dimensional models (2010)

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Further publications can be found at: https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/published/citations.html#afni-software-package