Fast shared boosting: Application to large-scale visual concept detection. - Hervé Le Borgne; Nicolas Honnorat (CBMI, 2010)

Robust guidewire segmentation through boosting, clustering and linear programming. - Nicolas Honnorat; Régis Vaillant; Nikos Paragios (ISBI, 2010)

Guide-Wire Extraction through Perceptual Organization of Local Segments in Fluoroscopic Images. - Nicolas Honnorat; Régis Vaillant; Nikos Paragios (MICCAI (3), 2010)

Curvilinear structures extraction in cluttered bioimaging data with discrete optimization methods. - Nicolas Honnorat; Régis Vaillant; James S. Duncan; Nikos Paragios (ISBI, 2011)

Graph-Based Geometric-Iconic Guide-Wire Tracking. - Nicolas Honnorat; Régis Vaillant; Nikos Paragios (MICCAI (1), 2011)

Graph-based guide-wire segmentation through fusion of contrast-enhanced and fluoroscopic images. - Nicolas Honnorat; Régis Vaillant; Nikos Paragios (ISBI, 2012)

Fast shared boosting for large-scale concept detection. - Hervé Le Borgne; Nicolas Honnorat (Multim. Tools Appl., 2012)

A Graph-Based Brain Parcellation Method Extracting Sparse Networks. - Nicolas Honnorat; Harini Eavani; Theodore D. Satterthwaite; Christos Davatzikos (PRNI, 2013)

GraSP: Geodesic Graph-based Segmentation with Shape Priors for the functional parcellation of the cortex. - Nicolas Honnorat; Harini Eavani; Theodore D. Satterthwaite; Raquel E. Gur; Ruben C. Gur; Christos Davatzikos (NeuroImage, 2015)

CHIMERA: Clustering of Heterogeneous Disease Effects via Distribution Matching of Imaging Patterns. - Aoyan Dong; Nicolas Honnorat; Bilwaj Gaonkar; Christos Davatzikos (IEEE Trans. Medical Imaging, 2016)

Riccati-Regularized Precision Matrices for Neuroimaging. - Nicolas Honnorat; Christos Davatzikos (IPMI, 2017)

Subject-Specific Structural Parcellations Based on Randomized AB-divergences. - Nicolas Honnorat; Drew Parker; Birkan Tunç; Christos Davatzikos; Ragini Verma (MICCAI (1), 2017)

Sparse Hierachical Extrapolated Parametric Methods for Cortical Data Analysis. - Nicolas Honnorat; Christos Davatzikos (CoRR, 2017)

GPU accelerated extraction of sparse Granger causality patterns. - Dushyant Sahoo; Nicolas Honnorat; Christos Davatzikos (ISBI, 2018)

Extrapolated nonnegative decompositions for the analysis of functional connectivity. - Nicolas Honnorat; Christos Davatzikos (Image Processing, 2018)

High resolution robust and smooth precision matrices to capture functional connectivity. - Nicolas Honnorat; Christos Davatzikos (Image Processing, 2018)

Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis. - Qingyu Zhao; Nicolas Honnorat; Ehsan Adeli 001; Adolf Pfefferbaum; Edith V. Sullivan; Kilian M. Pohl (IPMI, 2019)

Covariance Shrinkage for Dynamic Functional Connectivity. - Nicolas Honnorat; Ehsan Adeli 001; Qingyu Zhao; Adolf Pfefferbaum; Edith V. Sullivan; Kilian M. Pohl (CNI@MICCAI, 2019)

Variational AutoEncoder for Regression: Application to Brain Aging Analysis. - Qingyu Zhao; Ehsan Adeli 001; Nicolas Honnorat; Tuo Leng; Kilian M. Pohl (MICCAI (2), 2019)

Regularized topological data analysis for extraction of coherent brain regions. - Ishaan Batta; Nicolas Honnorat; Christos Davatzikos (Image Processing, 2019)

Sparse low-dimensional causal modeling for the analysis of brain function. - Dushyant Sahoo; Nicolas Honnorat; Christos Davatzikos (Image Processing, 2019)

Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis. - Qingyu Zhao; Nicolas Honnorat; Ehsan Adeli 001; Kilian M. Pohl (CoRR, 2019)

Deep Parametric Mixtures for Modeling the Functional Connectome. - Nicolas Honnorat; Adolf Pfefferbaum; Edith V. Sullivan; Kilian M. Pohl (PRIME@MICCAI, 2020)

Covariance shrinkage can assess and improve functional connectomes. - Nicolas Honnorat; Mohamad Habes (NeuroImage, 2022)

Deep Attention Assisted Multi-resolution Networks for the Segmentation of White Matter Hyperintensities in Postmortem MRI Scans. - Anoop Benet Nirmala; Tanweer Rashid; Elyas Fadaee; Nicolas Honnorat; Karl Li; Sokratis Charisis; Di Wang; Aishwarya Vemula; Jinqi Li; Peter Fox 002; Timothy E. Richardson; Jamie M. Walker; et al. (MLCN@MICCAI, 2023)

Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies. - Di Wang; Nicolas Honnorat; Peter T. Fox; Kerstin Ritter; Simon B. Eickhoff; Sudha Seshadri; Mohamad Habes (NeuroImage, 2023)

Riemannian frameworks for the harmonization of resting-state functional MRI scans. - Nicolas Honnorat; Sudha Seshadri; Ron Killiany; John Blangero; David C. Glahn; Peter T. Fox; Mohamad Habes (Medical Image Anal., 2024)