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Nicolas Honnorat
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2020 – today
- 2024
- [j6]Nicolas Honnorat, Sudha Seshadri, Ron Killiany, John Blangero, David C. Glahn, Peter T. Fox, Mohamad Habes:
Riemannian frameworks for the harmonization of resting-state functional MRI scans. Medical Image Anal. 91: 103043 (2024) - 2023
- [j5]Di Wang, Nicolas Honnorat, Peter T. Fox, Kerstin Ritter, Simon B. Eickhoff, Sudha Seshadri, Mohamad Habes:
Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies. NeuroImage 269: 119929 (2023) - [c19]Anoop Benet Nirmala, Tanweer Rashid, Elyas Fadaee, Nicolas Honnorat, Karl Li, Sokratis Charisis, Di Wang, Aishwarya Vemula, Jinqi Li, Peter Fox, Timothy E. Richardson, Jamie M. Walker, Kevin Bieniek, Sudha Seshadri, Mohamad Habes:
Deep Attention Assisted Multi-resolution Networks for the Segmentation of White Matter Hyperintensities in Postmortem MRI Scans. MLCN@MICCAI 2023: 143-152 - 2022
- [j4]Nicolas Honnorat, Mohamad Habes:
Covariance shrinkage can assess and improve functional connectomes. NeuroImage 256: 119229 (2022) - [i4]Di Wang, Nicolas Honnorat, Peter T. Fox, Kerstin Ritter, Simon B. Eickhoff, Sudha Seshadri, Mohamad Habes:
Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies. CoRR abs/2207.11352 (2022) - 2020
- [c18]Nicolas Honnorat, Adolf Pfefferbaum, Edith V. Sullivan, Kilian M. Pohl:
Deep Parametric Mixtures for Modeling the Functional Connectome. PRIME@MICCAI 2020: 133-143
2010 – 2019
- 2019
- [c17]Qingyu Zhao, Nicolas Honnorat, Ehsan Adeli, Adolf Pfefferbaum, Edith V. Sullivan, Kilian M. Pohl:
Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis. IPMI 2019: 867-879 - [c16]Nicolas Honnorat, Ehsan Adeli, Qingyu Zhao, Adolf Pfefferbaum, Edith V. Sullivan, Kilian M. Pohl:
Covariance Shrinkage for Dynamic Functional Connectivity. CNI@MICCAI 2019: 32-41 - [c15]Qingyu Zhao, Ehsan Adeli, Nicolas Honnorat, Tuo Leng, Kilian M. Pohl:
Variational AutoEncoder for Regression: Application to Brain Aging Analysis. MICCAI (2) 2019: 823-831 - [c14]Ishaan Batta, Nicolas Honnorat, Christos Davatzikos:
Regularized topological data analysis for extraction of coherent brain regions. Medical Imaging: Image Processing 2019: 109490I - [c13]Dushyant Sahoo, Nicolas Honnorat, Christos Davatzikos:
Sparse low-dimensional causal modeling for the analysis of brain function. Medical Imaging: Image Processing 2019: 109492R - [i3]Qingyu Zhao, Nicolas Honnorat, Ehsan Adeli, Kilian M. Pohl:
Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis. CoRR abs/1902.03717 (2019) - [i2]Qingyu Zhao, Ehsan Adeli, Nicolas Honnorat, Tuo Leng, Kilian M. Pohl:
Variational AutoEncoder For Regression: Application to Brain Aging Analysis. CoRR abs/1904.05948 (2019) - 2018
- [c12]Dushyant Sahoo, Nicolas Honnorat, Christos Davatzikos:
GPU accelerated extraction of sparse Granger causality patterns. ISBI 2018: 604-607 - [c11]Nicolas Honnorat, Christos Davatzikos:
High resolution robust and smooth precision matrices to capture functional connectivity. Medical Imaging: Image Processing 2018: 105742B - [c10]Nicolas Honnorat, Christos Davatzikos:
Extrapolated nonnegative decompositions for the analysis of functional connectivity. Medical Imaging: Image Processing 2018: 1057410 - 2017
- [c9]Nicolas Honnorat, Christos Davatzikos:
Riccati-Regularized Precision Matrices for Neuroimaging. IPMI 2017: 275-286 - [c8]Nicolas Honnorat, Drew Parker, Birkan Tunç, Christos Davatzikos, Ragini Verma:
Subject-Specific Structural Parcellations Based on Randomized AB-divergences. MICCAI (1) 2017: 407-415 - [i1]Nicolas Honnorat, Christos Davatzikos:
Sparse Hierachical Extrapolated Parametric Methods for Cortical Data Analysis. CoRR abs/1704.08631 (2017) - 2016
- [j3]Aoyan Dong, Nicolas Honnorat, Bilwaj Gaonkar, Christos Davatzikos:
CHIMERA: Clustering of Heterogeneous Disease Effects via Distribution Matching of Imaging Patterns. IEEE Trans. Medical Imaging 35(2): 612-621 (2016) - 2015
- [j2]Nicolas Honnorat, Harini Eavani, Theodore D. Satterthwaite, Raquel E. Gur, Ruben C. Gur, Christos Davatzikos:
GraSP: Geodesic Graph-based Segmentation with Shape Priors for the functional parcellation of the cortex. NeuroImage 106: 207-221 (2015) - 2013
- [c7]Nicolas Honnorat, Harini Eavani, Theodore D. Satterthwaite, Christos Davatzikos:
A Graph-Based Brain Parcellation Method Extracting Sparse Networks. PRNI 2013: 157-160 - 2012
- [j1]Hervé Le Borgne, Nicolas Honnorat:
Fast shared boosting for large-scale concept detection. Multim. Tools Appl. 60(2): 389-402 (2012) - [c6]Nicolas Honnorat, Régis Vaillant, Nikos Paragios:
Graph-based guide-wire segmentation through fusion of contrast-enhanced and fluoroscopic images. ISBI 2012: 948-951 - 2011
- [c5]Nicolas Honnorat, Régis Vaillant, James S. Duncan, Nikos Paragios:
Curvilinear structures extraction in cluttered bioimaging data with discrete optimization methods. ISBI 2011: 1353-1357 - [c4]Nicolas Honnorat, Régis Vaillant, Nikos Paragios:
Graph-Based Geometric-Iconic Guide-Wire Tracking. MICCAI (1) 2011: 9-16 - 2010
- [c3]Hervé Le Borgne, Nicolas Honnorat:
Fast shared boosting: Application to large-scale visual concept detection. CBMI 2010: 1-6 - [c2]Nicolas Honnorat, Régis Vaillant, Nikos Paragios:
Robust guidewire segmentation through boosting, clustering and linear programming. ISBI 2010: 924-927 - [c1]Nicolas Honnorat, Régis Vaillant, Nikos Paragios:
Guide-Wire Extraction through Perceptual Organization of Local Segments in Fluoroscopic Images. MICCAI (3) 2010: 440-448
Coauthor Index
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