VNeAT (Voxel-wise Neuroimaging Analysis Toolbox)

VNeAT (Voxel-wise Neuroimaging Analysis Toolbox) is a command-line toolbox written in Python that provides the tools to analyze the linear and nonlinear dynamics of a particular tissue and study the statistical significance of such dynamics at the voxel level.

Authors

Institutions

Image and Video Processing Group, Universitat Politècnica de Catalunya

Pasqual Maragall Foundation

Publication

This work has been accepted at the NIPS 2016 Workshop on Machine Learning for Health.

The workshop paper is available on arXiv, and the associated poster is available here.

In order to cite this work please use the following BibTeX code:

@article{Puch_2016_NIPS4H,
   author = {{Puch}, S. and {Aduriz}, A. and {Casamitjana}, A. and {Vilaplana}, V. and 
	{Petrone}, P. and {Operto}, G. and {Cacciaglia}, R. and {Skouras}, S. and 
	{Falcon}, C. and {Molinuevo}, J.~L. and {Domingo Gispert}, J.
	},
    title = "{Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling}",
    journal = {ArXiv e-prints},
    archivePrefix = "arXiv",
    eprint = {1612.00667},
    primaryClass = "stat.ML",
    year = 2016,
    month = dec
}