| Multiscale brain MRI super-resolution using deep 3D convolutional networks CH Pham, C Tor-Díez, H Meunier, N Bednarek, R Fablet, N Passat, ... Computerized Medical Imaging and Graphics 77, 101647, 2019 | 395 | 2019 |
| A non-local fuzzy segmentation method: application to brain MRI B Caldairou, N Passat, PA Habas, C Studholme, F Rousseau Pattern Recognition 44 (9), 1916-1927, 2011 | 158 | 2011 |
| Spatio-temporal reasoning for the classification of satellite image time series F Petitjean, C Kurtz, N Passat, P Gançarski Pattern Recognition Letters 33 (13), 1805-1815, 2012 | 121 | 2012 |
| Extraction of complex patterns from multiresolution remote sensing images: A hierarchical top-down methodology C Kurtz, N Passat, P Gancarski, A Puissant Pattern Recognition 45 (2), 685-706, 2012 | 115 | 2012 |
| Magnetic resonance angiography: From anatomical knowledge modeling to vessel segmentation N Passat, C Ronse, J Baruthio, JP Armspach, C Maillot Medical image analysis 10 (2), 259-274, 2006 | 104 | 2006 |
| Region‐growing segmentation of brain vessels: An atlas‐based automatic approach N Passat, C Ronse, J Baruthio, JP Armspach, C Maillot, C Jahn Journal of Magnetic Resonance Imaging: An Official Journal of the …, 2005 | 97 | 2005 |
| Hierarchical extraction of landslides from multiresolution remotely sensed optical images C Kurtz, A Stumpf, JP Malet, P Gançarski, A Puissant, N Passat ISPRS Journal of Photogrammetry and Remote Sensing 87, 122-136, 2014 | 88 | 2014 |
| Filtering and segmentation of 3D angiographic data: Advances based on mathematical morphology A Dufour, O Tankyevych, B Naegel, H Talbot, C Ronse, J Baruthio, ... Medical image analysis 17 (2), 147-164, 2013 | 87 | 2013 |
| Grey-level hit-or-miss transforms—part I: unified theory B Naegel, N Passat, C Ronse Pattern Recognition 40 (2), 635-647, 2007 | 83 | 2007 |
| SegSRGAN: Super-resolution and segmentation using generative adversarial networks—Application to neonatal brain MRI Q Delannoy, CH Pham, C Cazorla, C Tor-Díez, G Dollé, H Meunier, ... Computers in Biology and Medicine 120, 103755, 2020 | 79 | 2020 |
| Curvilinear structure analysis by ranking the orientation responses of path operators O Merveille, H Talbot, L Najman, N Passat IEEE transactions on pattern analysis and machine intelligence 40 (2), 304-317, 2017 | 77 | 2017 |
| 3D segmentation of coronary arteries based on advanced mathematical morphology techniques B Bouraoui, C Ronse, J Baruthio, N Passat, P Germain Computerized medical imaging and graphics 34 (5), 377-387, 2010 | 75 | 2010 |
| Interactive segmentation based on component-trees N Passat, B Naegel, F Rousseau, M Koob, JL Dietemann Pattern Recognition 44 (10-11), 2539-2554, 2011 | 55 | 2011 |
| Fully automatic 3D segmentation of coronary arteries based on mathematical morphology B Bouraoui, C Ronse, J Baruthio, N Passat, P Germain 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to …, 2008 | 54 | 2008 |
| Grey-level hit-or-miss transforms—Part II: Application to angiographic image processing B Naegel, N Passat, C Ronse Pattern Recognition 40 (2), 648-658, 2007 | 50 | 2007 |
| Automated 3D lymphoma lesion segmentation from PET/CT characteristics E Grossiord, H Talbot, N Passat, M Meignan, L Najman 2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017 | 48 | 2017 |
| Unsupervised quantification of under-and over-segmentation for object-based remote sensing image analysis A Troya-Galvis, P Gançarski, N Passat, L Berti-Equille IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2015 | 48 | 2015 |
| Vesselness filters: A survey with benchmarks applied to liver imaging J Lamy, O Merveille, B Kerautret, N Passat, A Vacavant 2020 25th international conference on pattern recognition (ICPR), 3528-3535, 2021 | 46 | 2021 |
| Segmentation using vector-attribute filters: methodology and application to dermatological imaging B Naegel, N Passat, N Boch, M Kocher International Symposium on Mathematical Morphology (ISMM) 1, 239-250, 2007 | 43 | 2007 |
| Component-trees and multivalued images: Structural properties N Passat, B Naegel Journal of Mathematical Imaging and Vision 49, 37-50, 2014 | 42 | 2014 |
Hugues TalbotCentraleSupelec Université Paris-SaclayVerified email at centralesupelec.fr
