Journal Articles

• Generalizable Spinal Cord Multiple Sclerosis Lesion Segmentation Across MRI Contrasts, Protocols, and Centers. In Multiple Sclerosis Journal, 2026. Benveniste, P-L.; +52 co-authors,; Lombaert, H. and Cohen-Adad, J.
• Prompt learning with bounding box constraints for medical image segmentation. In IEEE Transactions on Biomedical Engineering (TBME), 2025. Gaillochet, M.; Noori, M.; Dastani, S.; Desrosiers, C. and Lombaert, H.
• Neighbor-Aware Calibration of Segmentation Networks with Penalty-Based Constraints. In Medical Image Analysis (MedIA), 2025. Murugesan, B.; Adiga, S.; Liu, B.; Lombaert, H.; Ben Ayed, I. and Dolz, J.
• GeoLS: an Intensity-based, Geodesic Soft Labeling for Image Segmentation. In Melba, 2024. Adiga, S.; Dolz, J. and Lombaert, H.
• Anatomically-aware Uncertainty for Semi-supervised Image Segmentation. In Medical Image Analysis (MedIA), 2023. Adiga, S.; Dolz, J. and Lombaert, H.
• [Highlight] Active Learning for Medical Image Segmentation with Stochastic Batches. In Medical Image Analysis (MedIA), 2023. Gaillochet, M.; Desrosiers, C. and Lombaert, H.
• Learning Joint Surface Reconstruction and Segmentation, from Brain Images to Cortical Surface Parcellation. In Medical Image Analysis (MedIA), 2023. Gopinath, K.; Desrosiers, C. and Lombaert, H.
• Source-free Domain Adaptation for Image Segmentation. In Medical Image Analysis (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 Computerized Medical Imaging and Graphics (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. Galdran, 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

• Acceptance Rate: <30% Oral Presentation ToothForge: Automatic Dental Shape Generation using Synchronized Spectral Embeddings. In IPMI, 2025. Kubik, T.; Guibault, F.; Spanel, M. and Lombaert, H.
• Acceptance Rate: <30% TRUST: Test-Time Refinement using Uncertainty-Guided SSM Traverses. In NeurIPS, 2025. Dastani, S.; Bahri, A.; Hakim, G. A. V.; Yazdanpanah, M.; Noori, M.; Osowiechi, D.; Barbeau, S.; Ben Ayed, I.; Lombaert, H. and Desrosiers, C.
• Acceptance Rate: <30% Oral Presentation Variational Visible Layers: A Practical Framework for Uncertainty Estimation. In MICCAI, 2025. Abboud, Z.; Lombaert, H. and Kadoury, S.
• Best Paper Award Anatomically-Focused Patches for Lightweight and Explainable Knee OA Grading. In MICCAI ShapeMI, 2025. Chang, T-E. and Lombaert, H.
• Oral Presentation Reinforcing the generalizability of spinal cord multiple sclerosis lesion segmentation models. In ESMRMB, 2025. Benveniste, P-L.; more, 45; Lombaert, H. and Cohen-Adad, J.
• Investigations on the mitigation of 'noisy labels' for the automatic segmentation. In ECTRIMS, 2025. Benveniste, P-L.; more, 45; Lombaert, H. and Cohen-Adad, J.
• Acceptance Rate: <30% Spectral State Space Model for Rotation-Invariant Visual Representation Learning. In CVPR, 2025. Dastani, S.; Bahri, A.; Yazdanpanah, M.; Noori, M.; Osowiechi, D.; Vargas-Hakim, G. A.; Beizaee, F.; Cheraghalikhani, M.; Mondal, A. K.; Lombaert, H. and Desrosiers, C.
• Acceptance Rate: <30% Sparse Bayesian Networks: Efficient Uncertainty Quantification in Medical Image Analysis. In MICCAI, 2024. Abboud, Z.; Lombaert, H. and Kadoury, S.
• Sparse Partial Bayesian Networks: Efficient Uncertainty Quantification in Medical Image Analysis. In WIML@NeurIPS, 2024. Abboud, Z.; Lombaert, H. and Kadoury, S.
• Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision. In MICCAI MedAGI, 2024. Gaillochet, M.; Desrosiers, C. and Lombaert, H.
• 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

• Canada's Gov General Gold Medal Learning with Uncertainty in Medical Image Segmentation. Ph.D. Thesis, Ecole de Technologie Superieure, 2024. Adiga, S.
• Domain Adaptation with Missing Data. Ph.D. Thesis, Ecole de Technologie Superieure, 2023. Bateson, M.
• Best Thesis Award
  Canada's Gov General Gold Medal Geometrical Learning of Brain Surface Data. Ph.D. Thesis, Ecole de Technologie Superieure, 2021. Gopinath, K.
• Best Thesis Award 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, Published Dec. 1, 2011, Ussed Feb. 24, 2015. Grady, L.; Lombaert, H. J.; Polimeni, J. R. and Cheriet, F.
• Method and apparatus for interactive 4-dimensional (4D) virtual endoscopy. US Patent No 8007437, 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 7889227, 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 8913830, Application No 11/313,102, Filled Dec. 20, 2005, Published Jul. 20, 2006, Issued Dec. 16 2014. Sun, Y.; Lombaert, H.; Grady, L. and Xu, C.
• Multilevel Image Segmentation. Chinese Provisional Application. Sun, Y.; Lombaert, H.; Grady, L. and Xu, C.

Books

• 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.