37 citations · 51 across the 7 of their papers we have counts for
8 papers
Automatic rating of incomplete hippocampal inversions evaluated across multiple cohorts
Lisa Hemforth, Baptiste Couvy-Duchesne, Kevin De Matos +34
Incomplete Hippocampal Inversion (IHI), sometimes called hippocampal malrotation, is an atypical anatomical pattern of the hippocampus found in about 20% of the general population.…
Self-supervised contrastive learning unveils cortical folding pattern linked to prematurity
Julien Laval, Aymeric Gaudin, Vincent Frouin +5
Brain folding patterns have been reported to carry clinically relevant information. The brain folds mainly during the last trimester of pregnancy, and the process might be durably…
A general multiblock method for structured variable selection
Tommy Löfstedt, Fouad Hadj-Selem, Vincent Guillemot +5
Regularised canonical correlation analysis was recently extended to more than two sets of variables by the multiblock method Regularised generalised canonical correlation analysis…
Structured Sparse Principal Components Analysis with the TV-Elastic Net penalty
Amicie de Pierrefeu, Tommy Löfstedt, Fouad Hadj-Selem +4
Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover dominant patterns of variability within a population. Despite its ability to repre…
Continuation of Nesterov's Smoothing for Regression with Structured Sparsity in High-Dimensional Neuroimaging
Fouad Hadj-Selem, Tommy Lofstedt, Elvis Dohmatob +4
Predictive models can be used on high-dimensional brain images for diagnosis of a clinical condition. Spatial regularization through structured sparsity offers new perspectives in…
Nonlinear functional mapping of the human brain
Nicholas Allgaier, Tobias Banaschewski, Gareth Barker +27
The field of neuroimaging has truly become data rich, and novel analytical methods capable of gleaning meaningful information from large stores of imaging data are in high demand.…
Predictive support recovery with TV-Elastic Net penalty and logistic regression: an application to structural MRI
Mathieu Dubois, Fouad Hadj-Selem, Tommy Lofstedt +4
The use of machine-learning in neuroimaging offers new perspectives in early diagnosis and prognosis of brain diseases. Although such multivariate methods can capture complex relat…
PyXNAT: XNAT in Python
Yannick Schwartz, Alexis Barbot, Benjamin Thyreau +5
As neuroimaging databases grow in size and complexity, the time researchers spend investigating and managing the data increases to the expense of data analysis. As a result, invest…