VNeAT (Voxel-wise Neuroimaging Analysis Toolbox)

Resource Type Date
Software 2017-06-29


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.



Name Position / Role
Santi Puch Giner Author
Asier Aduriz Berasategi Author
Adrià Casamitjana Díaz Contributor
Verónica Vilaplana Besler Advisor (UPC)
Juan Domingo Gispert Advisor (PMF)Institutions


Image and Video Processing Group, Universitat Politècnica de Catalunya

Pasqual Maragall Foundation



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:

   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


People involved

Veronica Vilaplana Associate Professor
Adrià Casamitjana PhD Candidate