Hervé Lombaert

Canada Research Chair

Prof – Research Scientist
ETS Montreal – Inria Sophia-Antipolis

(Currently in Eastern Time)

Hiring: (2) PhD, (1) Postdoc

Several topics in Medical Image Analysis:
➤ Geometry / Uncertainty / Probability / Learning-based algorithms

[ more at: https://hlombaert.etsmtl.ca/jobs.php ]

Short Bio

Associate Professor (2017 —) @ ETS Montreal,
working on Geometric Data Analysis in Medical Imaging.

Starting Research Scientist (2015 —) @ Inria,
working on Shape & Image Analysis in Medical Imaging.

Postdoc Fellow (2013-2015) @ Inria–Microsoft Research,
working on Statistical Learning in Medical Imaging, with N. Ayache & A. Criminisi.

Postdoc Fellow (2012-2013) @ McGill University,
working on Shapes in Medical Imaging, with K. Siddiqi.

Ph.D. (2012) @ Polytechnique Montréal – Siemens – Inria,
working on the Variability of Complex Anatomical Structures,
with F. Cheriet, L. Grady, H. Delingette & N. Ayache.

External Profiles: Google Scholar

(Pronounciation: Lom-bart)

Research Topics

Spectral Graph Theory	Shape Analysis	Geometric Learning	Medical Image Analysis
Riemannian Geometry	Cardiac	Neuro	Diffusion Imaging

Publications

[ Google Scholar ]

Journal Articles

[Highlight] Active Learning for Medical Image Segmentation with Stochastic Batches. In MedIA, 2023. Gaillochet, M.; Desrosiers, C. and Lombaert, H.
Learning Joint Surface Reconstruction and Segmentation, from Brain Images to Cortical Surface Parcellation. In MedIA, 2023. Gopinath, K.; Desrosiers, C. and Lombaert, H.
Source-free Domain Adaptation for Image Segmentation. In MedIA, 2022. Bateson, M.; Kervadec, H.; Dolz, J.; Lombaert, H. and Ben Ayed, I.
Attention-based Dynamic Subspace Learners for Medical Image Analysis. In IEEE Journal of Biomedical and Health Informatics (JBHI), 2022. Adiga, S.; Dolz, J. and Lombaert, H.
Little W-Net: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models. In Nature Scientific Reports, 2022. Galdran, A.; Anjos, A.; Dolz, J.; Chakor, H.; Lombaert, H. and Ben Ayed, I.
Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging. In Frontiers in Neuroimaging, 2022. Anctil-Robitaille, B.; Théberge, A.; Jodoin, P-M.; Descoteaux, M.; Desrosiers, C. and Lombaert, H.
Real-time simulation of viscoelastic tissue behavior with physics-guided deep learning. In CMIG, 2022. Karami, M.; Lombaert, H. and Rivest-Henault, D.
Realistic Image Normalization for Multi-Domain Segmentation. In Medical Image Analysis (MedIA), 2021. Delisle, P-L.; Anctil-Robitaille, B.; Desrosiers, C. and Lombaert, H.
Constrained Domain Adaptation for Image Segmentation. In IEEE Transactions on Medical Imaging (TMI), 2021. Bateson, M.; Dolz, J.; Kervadec, H.; Lombaert, H. and Ben Ayed, I.
[Highlight] Learnable Pooling in Graph Convolutional Networks for Brain Surface Analysis. In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2020. Gopinath, K.; Desrosiers, C. and Lombaert, H.
Non-uniform Label Smoothing for Diabetic Retinopathy Grading from Retinal Fundus Images with Deep Neural Networks. In TVST, 2020. Gadran, A.; Chelbi, J.; Dolz, J.; Lombaert, H.; Ben Ayed, I. and Chakor, H.
[Highlight] Graph Convolutions on Spectral Embeddings for Cortical Surface Parcellation. In Medical Image Analysis (MedIA), 2019. Gopinath, K.; Desrosiers, C. and Lombaert, H.
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation. In IEEE Transactions on Medical Imaging (TMI), 2018. Dolz, J.; Gopinath, K.; Yuan, J.; Lombaert, H.; Desrosiers, C. and Ben Ayed, I.
Spectral Shape Analysis of Human Torsos: Application to the Evaluation of Scoliosis Surgery Outcome. In IEEE Journal of Biomedical and Health Informatics (JBHI), 2017. Ahmad, O.; Lombaert, H.; Parent, S.; Labelle, H.; Dansereau, J. and Cheriet, F.
Cortical Folding of the Preterm Brain: A Longitudinal Analysis of Extremely Preterm Born Neonates using Spectral Matching. In Brain and Behavior, 2016. Orasanu, E.; Melbourne, A.; Cardoso, J.; Lombaert, H.; Robertson, N.; Kendall, G.; Marlow, N. and Ourselin, S.
Statistical Shape Analysis of Subcortical Structures using Spectral Matching. In Computerized Medical Imaging and Graphics (CMIG), 2016. Shakeri, M.; Lombaert, H.; Datta, A.; Oser, N.; Letourneau-Guillon, L.; Vincent Lapiere, L.; Martin, F.; Malfait, D.; Tucholka, A.; Lippe, S. and Kadoury, S.
[Highlight] Spectral Log-Demons - Diffeomorphic Image Registration with Very Large Deformations. In International Journal of Computer Vision (IJCV), 107 (3), 2014. Lombaert, H.; Grady, L.; Pennec, X.; Ayache, N. and Cheriet, F.
FOCUSR: Feature Oriented Correspondence using Spectral Regularization - A Method for Precise Surface Matching. In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 35 (9), 2013. Lombaert, H.; Grady, L.; Polimeni, J. R. and Cheriet, F.
FQRNT Etudiant Etoile
Best Paper Award Human Atlas of the Cardiac Fiber Architecture: Study on a Healthy Population. In IEEE Transactions on Medical Imaging (TMI), 31 (7), 2012. Lombaert, H.; Peyrat, J-M.; Croisille, P.; Rapacchi, S.; Fanton, L.; Cheriet, F.; Clarysse, P.; Magnin, I.; Delingette, H. and Ayache, N.

Top-Conference Articles & More

Note: Top Conferences, such as MICCAI,IPMI or ICCV,ECCV, have lower acceptance rates than many top journals.

Acceptance Rate: 30% Trust your neighbours: Penalty-based constraints for model calibration. In MICCAI, 2023. Murugesan, B.; Adiga, S.; Liu, B.; Lombaert, H.; Ben Ayed, I. and Dolz, J.
Oral Presentation GeoLS: Geodesic Label Smoothing for Image Segmentation. In MIDL, 2023. Adiga, S.; Dolz, J. and Lombaert, H.
TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation. In MICCAI DALI, 2022. Gaillochet, M.; Desrosiers, C. and Lombaert, H.
Acceptance Rate: 30% Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation. In MICCAI, 2022. Adiga, S.; Dolz, J. and Lombaert, H.
Acceptance Rate: 30% Test-Time Adaptation with Shape Moments for Image Segmentation. In MICCAI, 2022. Bateson, M.; Lombaert, H. and Ben Ayed, I.
Acceptance Rate: 30% Oral Presentation 3D Shape Representation via Spectral Coordinates on Medial Manifolds. In CVPR, 2022. Rezanejad, M.; Kohdadad, M.; Mahyar, H.; Lombaert, H.; Gruninger, M.; Walther, B. and Siddiqi, K.
Attention-based Dynamic Subspace Learners. In Medical Imaging with Deep Learning (MIDL), 2022. Adiga, S.; Dolz, J. and Lombaert, H.
Source-Free Domain Adaptation for Image Segmentation. In Medical Imaging with Deep Learning (MIDL), 2022. Bateson, M.; Kervadec, H.; Dolz, J.; Lombaert, H. and Ben Ayed, I.
Acceptance Rate: 30% Oral Presentation SegRecon: Learning Joint Brain Surface Reconstruction and Segmentation from Images. In MICCAI, 2021. Gopinath, K.; Desrosiers, C. and Lombaert, H.
Acceptance Rate: 30% Oral Presentation Source-Relaxed Domain Adaptation for Image Segmentation. In MICCAI, 2020. Bateson, M.; Kervadec, H.; Dolz, J.; Lombaert, H. and Ben Ayed, I.
Acceptance Rate: 30% Oral Presentation Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images. In MICCAI, 2020. Galdran, A.; Dolz, J.; Chakor, H.; Lombaert, H. and Ben Ayed, I.
Oral Presentation Manifold-Aware CycleGAN for High-Resolution Structural-to-DTI Synthesis. In MICCAI-CDMRI, 2020. Anctil-Robitaille, B.; Desrosiers, C. and Lombaert, H.
Oral Presentation
Best Paper Runnerup Graph Domain Adaptation for Alignment-Invariant Brain Surface Segmentation. In MICCAI-GRAIL, 2020. Gopinath, K.; Desrosiers, C. and Lombaert, H.
Oral Presentation Adversarial Normalization for Multi Domain Image Segmentation. In ISBI, 2020. Delisle, P-L.; Anctil-Robitaille, B.; Desrosiers, C. and Lombaert, H.
Oral Presentation Spectral Graph Transformer Networks for Brain Surface Parcellation. In ISBI, 2020. Gopinath, K.; He, R.; Desrosiers, C. and Lombaert, H.
Acceptance Rate: 30% Constrained Domain Adaptation for Segmentation. In MICCAI, 2019. Bateson, M.; Kervadec, H.; Dolz, J.; Lombaert, H. and Ben Ayed, I.
Acceptance Rate: 30% Oral Presentation Adaptive Graph Convolution Pooling for Brain Surface Analysis. In IPMI, 2019. Gopinath, K.; Desrosiers, C. and Lombaert, H.
Cortical Parcellation via Spectral Graph Convolutions. In MIDL, 2019. Gopinath, K.; Desrosiers, C. and Lombaert, H.
Brain Tumor Segmentation using Topological Loss in Convolutional Networks. In MIDL, 2019. Reddy, C.; Gopinath, K. and Lombaert, H.
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation. In MIDL, 2019. Dolz, J.; Gopinath, K.; Yuan, J.; Lombaert, H.; Desrosiers, C. and Ben Ayed, I.
Acceptance Rate: 21% Oral Presentation Graph Convolutions on Spectral Embeddings: Learning of Cortical Surface Data. In MED-NeurIPS/NIPS, 2018. Gopinath, K.; Desrosiers, C. and Lombaert, H.
Spectral Learning of Surface Data: Ideas from Medical Imaging. In MED-NeurIPS/NIPS, 2017. Lombaert, H.; Criminisi, A. and Ayache, N.
Acceptance Rate: 30% Longitudinal Analysis of the Preterm Cortex using Multi-Modal Spectral Matching. In Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016. Orasanu, E.; Bazin, P-L.; Melbourne, A.; Lorenzi, M.; Lombaert, H.; Robertson, N.; Kendall, G.; Weiskopf, N.; Marlow, N. and Ourselin, S.
Oral Presentation
ISMRM Summa Cum Laude (Top 5%) Mapping Longitudinal White Matter Changes in Extremely Preterm Born Infants. In International Society for Magnetic Resonance in Medicine (ISMRM), 2016. Orasanu, E.; Melbourne, A.; Modat, M.; Lorenzi, M.; Lombaert, H.; Eaton-Rosen, Z.; Robertson, N.; Kendall, G.; Marlow, N. and Ourselin, S.
Oral Presentation Deep Spectral-Based Shape Features for Alzheimer's Disease Classification. In MICCAI SESAMI, 2016. Shakeri, M.; Lombaert, H.; Tripathi, S. and Kadoury, S.
Oral Presentation Longitudinal Scoliotic Trunk Analysis via Spectral Representation and Statistical Analysis. In MICCAI SESAMI, 2016. Ahmad, O.; Lombaert, H.; Parent, S.; Labelle, H.; Dansereau, J. and Cheriet, F.
Acceptance Rate: 30% [Highlight] [video] Spectral Forests: Learning of Surface Data, Application to Cortical Parcellation. In Medical Image Computing and Computer Assisted Intervention (MICCAI), 2015. Lombaert, H.; Criminisi, A. and Ayache, N.
Acceptance Rate: ~25% [Highlight] Brain Transfer: Spectral Analysis of Cortical Surfaces and Functional Maps. In Information Processing and Medical Imaging (IPMI), 2015. Lombaert, H.; Arcaro, M. and Ayache, N.
Brain Transfer for the Analysis of Cortical Data. In Society for Neuroscience (SfN), 2015. Lombaert, H.; Arcaro, M.; Kastner, S. and Ayache, N.
Oral Presentation Tensor Spectral Matching of Diffusion Weighted Images. In MICCAI SAMI, 2015. Orasanu, E.; Melbourne, A.; Modat, M.; Lorenzi, M.; Lombaert, H.; Eaton-Rosen, Z.; Robertson, N.; Kendall, G.; Marlow, N. and Ourselin, S.
Oral Presentation Myocardial Infarct Localization using Neighborhood Approximation Forests. In MICCAI STACOM, 2015. Bleton, H.; Margeta, J.; Lombaert, H.; Delingette, H. and Ayache, N.
Oral Presentation Propagation of Myocardial Fibre Architecture Uncertainty on Electromechanical Model Parameter Estimation: A Case Study. In Functional Imaging and Modeling of the Heart (FIMH), 2015. Mollero, R.; Neumann, D.; Rohe, M-M.; Datar, M.; Lombaert, H.; Ayache, N.; Comaniciu, D.; Ecabert, O.; Chinali, M.; Rinelli, G.; Pennec, X.; Sermesant, M. and Mansi, T.
Oral Presentation Classification of Alzheimer's Disease using Discriminant Manifolds of Hippocampus Shapes. In ICML Workshop in Medical Imaging (ICML-ML-Medim), 2015. Shakeri, M.; Lombaert, H. and Kadoury, S.
Acceptance Rate: 30% [Highlight] Laplacian Forests: Semantic Image Segmentation by Guided Bagging. In Medical Computing and Computer Assisted Intervention (MICCAI), 2014. Lombaert, H.; Zikic, D.; Criminisi, A. and Ayache, N.
Acceptance Rate: 30% Multi-Atlas Spectral PatchMatch: Application to Cardiac Image Segmentation. In Medical Computing and Computer Assisted Intervention (MICCAI), 2014. Shi, W.; Lombaert, H.; Bai, W.; Ledig, C.; Zhuang, X.; Simoes Monteiro de Marvao, A.; Dawes, T.; O'Regan, D. and Rueckert, D.
Oral Presentation Prefrontal Cortical Folding of the Preterm Brain: A Longitudinal Analysis of Preterm-born Neonates. In MICCAI STIA, 2014. Orasanu, E.; Melbourne, A.; Lombaert, H.; Cardoso, M. J.; Johnsen, S. F.; Kendall, G. S; Robertson, N. J; Marlow, N. and Ourselin, S.
Oral Presentation Groupwise Shape Analysis of the Hippocampus using Spectral Matching. In SPIE Medical Imaging, 2014. Shakeri, M.; Lombaert, H.; Lippe, S. and Kadoury, S.
Acceptance Rate: 32% Joint Statistics on Cardiac Shape and Fiber Architecture. In Medical Computing and Computer Assisted Intervention (MICCAI), 2013. Lombaert, H. and Peyrat, J-M.
Applying a 4D [¹¹C]Raclopride Template to Automated Binding Potential Estimation in HRRT Brain PET. In Nuclear Science Symposium & Medical Imaging Conference (NSS/MIC), 2013. Novosad, P.; Bieth, M.; Lombaert, H.; Siddiqi, K. and and Reader, A.
Acceptance Rate: 32% Atlas Construction for Dynamic (4D) PET using Diffeomorphic Transformations. In Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013. Bieth, M.; Lombaert, H.; Reader, A. and Siddiqi, K.
Acceptance Rate: 32% Cardiac Fiber Inpainting using Maurer-Cartan Forms. In Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013. Piuze, E.; Lombaert, H.; Sporring, J. and Siddiqi, K.
Acceptance Rate: ~25% Oral Presentation
Erbsmann Prize
Best Paper Award Diffeomorphic Spectral Matching of Cortical Surfaces. In Information Processing and Medical Imaging (IPMI), 2013. Lombaert, H.; Sporring, J. and Siddiqi, K.
Atlases of Cardiac Fiber Differential Structure. In Functional Imaging and Modeling of the Heart (FIMH), 2013. Piuze, E.; Lombaert, H.; Sporring, J.; Strijkers, G.; Bakermans, A. and Siddiqi, K.
Oral Presentation
Best Paper Award Groupwise Spectral Log-Demons Framework for Atlas Construction. In MICCAI Workshop on Medical Computer Vision (MICCAI MCV), 2012. Lombaert, H.; Grady, L.; Pennec, X.; Peyrat, J-M.; Ayache, N. and Cheriet, F.
Acceptance Rate: 25% Spectral Demons - Image Registration via Global Spectral Correspondence. In European Conference in Computer Vision (ECCV), 2012. Lombaert, H.; Grady, L.; Pennec, X.; Ayache, N. and Cheriet, F.
Simultaneous Image Denoising and Registration using Graph Cuts. In Information Science, Signal Processing and Applications (ISSPA), 2012. Lombaert, H. and Cheriet, F.
Oral Presentation Variability of the Human Cardiac Laminar Structure. In MICCAI STACOM, 2011. Lombaert, H.; Peyrat, J-M.; Fanton, L.; Cheriet, F.; Delingette, H.; Ayache, N.; Clarysse, P.; Magnin, I. and Croisille, P.
Statistical Atlas of Human Cardiac Fibers: Comparison with Abnormal Hearts. In MICCAI STACOM, 2011. Lombaert, H.; Peyrat, J-M.; Fanton, L.; Cheriet, F.; Delingette, H.; Ayache, N.; Clarysse, P.; Magnin, I. and Croisille, P.
Acceptance Rate: 28% Fast Brain Matching with Spectral Correspondence. In Information Processing and Medical Imaging (IPMI), 2011. Lombaert, H.; Grady, L.; Polimeni, J. R. and Cheriet, F.
Oral Presentation
Best Paper Award Statistical Analysis of the Human Cardiac Fiber Architecture from DT-MRI. In Functional Imaging and Modeling of the Heart (FIMH), 2011. Lombaert, H.; Peyrat, J-M.; Croisille, P.; Rapacchi, S.; Fanton, L.; Clarysse, P.; Delingette, H. and Ayache, N.
Oral Presentation Human Statistical Atlas of Cardiac Fiber Architecture from DT-MRI. In International Society for Magnetic Resonance in Medicine (ISMRM), 2011. Lombaert, H.; Peyrat, J-M.; Rapacchi, S.; Fanton, L.; Delingette, H.; Ayache, N. and Croisille, P.
Fast 4D segmentation of large datasets using graph cuts. In SPIE Medical Imaging, 2011. Lombaert, H.; Sun, Y. and Cheriet, F.
Geodesic Thin Plate Splines for Image Segmentation. In IEEE International Conference on Pattern Recognition (ICPR), 2010. Lombaert, H. and Cheriet, F.
Spatio-Temporal Segmentation of the Heartin 4D MRI Images using Graph Cuts with Motion Cues. In Intenational Symposium in Biomedical Imaging (ISBI), 2010. Lombaert, H. and Cheriet, F.
Acceptance Rate: 44% Oral Presentation Landmark-based Non-rigid Registration via Graph Cuts. In International Conference on Image Analysis and Recognition (ICIAR), 2007. Lombaert, H.; Sun, Y. and Cheriet, F.
Acceptance Rate: 19% A Multilevel Banded Graph Cuts Method for Fast Image Segmentation. In IEEE International Conference in Computer Vision (ICCV), 2005. Lombaert, H.; Sun, Y.; Grady, L. and Xu, C.

Theses

Domain Adaptation with Missing Data. Ph.D. Thesis, Ecole de Technologie Superieure, 2023. Bateson, M.
Best Thesis Award
(ETS Montreal) Geometrical Learning of Brain Surface Data. Ph.D. Thesis, Ecole de Technologie Superieure, 2021. Gopinath, K.
Best Thesis Award
(ETS Montreal) Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging. Master's Thesis, Ecole de Technologie Superieure, 2021. Anctil-Robitaille, B.
Realistic Image Normalization for Multi-Domain Segmentation. Master's Thesis, Ecole de Technologie Superieure, 2021. Delisle, P-L.
Best Thesis Award
(Computer Engineering) Atlas Construction for Measuring the Variability of Complex Anatomical Structures. Ph.D. Thesis, Ecole Polytechnique, 2012. Lombaert, H.
Fusion of Multimodal Cardiac Image Sequences. Thesis Proposal, Ecole Polytechnique, 2007. Lombaert, H.

Patents

Fast 4D Segmentation of Large Datasets Using Graph Cuts. US Patent No 8131075, Application No 11/927,777, Filled Oct. 30, 2007, Issued Mar. 6, 2012. Sun, Y.; Lombaert, H. J. and Cheriet, F.
Methods and Systems for Fast Automatic Brain Matching via Spectral Correspondence. US Patent No 8965077, Application No 13/107,002, Filled May 13, 2011, Issued Dec. 1, 2011. Grady, L.; Lombaert, H. J.; Polimeni, J. R. and Cheriet, F.
Method and apparatus for interactive 4-dimensional (4D) virtual endoscopy. US Patent No US8007437, Application No 11/874,975, Filled Oct. 19, 2007, Issued Aug. 30, 2011. Lombaert, H. J.; Sauer, F.; Sun, Y. and Xu, C.
Intuitive User Interface for Endoscopic View Visualization. US Patent No 20070061726, Application No 11/227,807, Filled Sep. 15, 2005, Issued Feb. 15, 2011. Rahn, N.; Xu, C.; Sun, Y.; Baker, S.; John, M. and Lombaert, H.
Multilevel Image Segmentation. US Patent No 20060159342, Application No 11/313,102, Filled Dec. 20, 2005, Issued Jul. 20, 2006. Sun, Y.; Lombaert, H.; Grady, L. and Xu, C.
Multilevel Image Segmentation. Chinese Provisional Application. Sun, Y.; Lombaert, H.; Grady, L. and Xu, C.
Multilevel Image Segmentation. 2005P00855IN, Indian Provisional Application. Sun, Y.; Lombaert, H.; Grady, L. and Xu, C.
Ultrasound Frame Compensation and Compounding. Patent Pending.
A System and Method for Finding Accurate Pointwise Correspondences between Images. Patent Pending.

Books

MELBA Journal, MIDL 2020 Special Issue. MELBA, 2020. de Bruijne, M.; Arbel, T.; Ben Ayed, I. and Lombaert, H.
Proceedings of Medical Imaging with Deep Learning: MIDL 2020. PMLR, 2020. (Equal Contributors),; Arbel, T.; Ben Ayed, I.; de Bruijne, M.; Descoteaux, M.; Lombaert, H. and Pal, C.
Compendium of Medical Imaging with Deep Learning: MIDL 2020, Short Paper Tracks. arXiv Compendium, 2020. (Equal Contributors),; Arbel, T.; Ben Ayed, I.; de Bruijne, M.; Descoteaux, M.; Lombaert, H. and Pal, C.
Proceedings of the MICCAI Workshop on Shape in Medical Imaging. Springer, Lecture Notes on Computer Science, volume 12474, 2020. (Equal Contributors),; Reuter, M.; Wachinger, C.; Lombaert, H.; Paniagua, B.; Goksel, O. and Rekik, I.
Proceedings of the MICCAI Workshop on Shape in Medical Imaging. Springer, Lecture Notes on Computer Science, volume 11167, 2018. (Equal Contributors),; Reuter, M.; Wachinger, C.; Lombaert, H.; Paniagua, B.; Luthi, M. and Egger, B.
Proceedings of the First MICCAI Workshop on Spectral and Shape Analysis in Medical Imaging. Springer, Lecture Notes on Computer Science, volume 10126, 2016. (Equal Contributors),; Reuter, M.; Wachinger, C. and Lombaert, H.
Proceedings of the First ICML Workshop on Machine Learning Meets Medical Imaging. Springer, Lecture Notes on Computer Science, volume 9487, 2015. (Equal Contributors),; Bhatia, K. and Lombaert, H.

Awards

Publication Awards

Erbsmann Prize at IPMI, 2013 One of the highest recognition in medical image analysis
FQRNT Étudiant-Chercheur Étoile Award, 2013 Chosen among 205 candidates in the province of Quebec
Best Thesis Award, 2012 From the Computer Engineering department at Polytechnique
Best Paper Award at MICCAI-MCV, 2012 Major workshop in medical computer vision
Best Paper Award at FIMH, 2011 Major conference in cardiac image processing

Grants & Fellowship Awards

Canada Research Chair, Tier II 948 CRC hair holders (Top 3.5%) among all 25,643 Early Career Profs in Canada
NSERC Postdoctoral Fellowship Ranked 1^st in Canada among all postdoctoral applicantsont
FQRNT Postdoctoral Fellowship Ranked 2^nd among all postdoctoral applicants in the province of Quebec
NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS-D) Chosen among the highest-caliber candidates in Canada
FQRNT Doctoral Scholarship Ranked 8^th among all doctoral applicants in the province of Quebec

Teaching Awards & Others

Best Lab Teacher, Gala Meritas Polytechnique, 2002 Chosen among all disciplines of the core curriculum
First prize Computer Graphics Image Contest, Polytechnique, 2001

Funding

(5 years) Canada Research Chair
(5 years) NSERC Discovery Grant
(2 years) FRQNT New Academics
(2 years) NSERC Postdoctoral Fellowship
(2 years) FQRNT Postdoctoral Fellowship
(2 years) NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS-D)
(2 years) Siemens Scholarship
(2 years) Ecole Polytechnique / LIV4D Student Financial Aid
(3 months) Siemens Stipend
(10 months) INRIA / Egide Stipend
(6 months) NSERC Michael Smith (CGS-MSFSS)
(1 week) IAPR Travel Grant
(1 week) IPMI Travel Grant