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ORCIDEnzo Ferrante
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- affiliation: CONICET-UNL, Santa Fe, Argentina
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2020 – today
- 2024
[j15]Rodrigo Bonazzola
, Enzo Ferrante, Nishant Ravikumar, Yan Xia, Bernard D. Keavney, Sven Plein, Tanveer F. Syeda-Mahmood, Alejandro F. Frangi:
Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology. Nat. Mac. Intell. 6(3): 291-306 (2024)- [j14]Lucas Mansilla, Estanislao Claucich, Rodrigo Echeveste, Diego H. Milone, Enzo Ferrante:
Demographically-Informed Prediction Discrepancy Index: Early Warnings of Demographic Biases for Unlabeled Populations. Trans. Mach. Learn. Res. 2024 (2024) - [c28]Nicolás Gaggion, Enzo Ferrante, Beatriz Paniagua, Jared Vicory:
Fitting Skeletal Models via Graph-Based Learning. ISBI 2024: 1-4 - [c27]Amine Sadikine, Bogdan Badic, Enzo Ferrante, Vincent Noblet, Pascal Ballet, Dimitris Visvikis, Pierre-Henri Conze:
Deep Vessel Segmentation with Joint Multi-Prior Encoding. ISBI 2024: 1-5 - [e6]Lisa M. Koch, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris, Dong Yang:
Domain Adaptation and Representation Transfer - 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. Lecture Notes in Computer Science 14293, Springer 2024, ISBN 978-3-031-45856-9 [contents] - [i40]Dovile Juodelyte, Yucheng Lu, Amelia Jiménez-Sánchez, Sabrina Bottazzi, Enzo Ferrante, Veronika Cheplygina:
Source Matters: Source Dataset Impact on Model Robustness in Medical Imaging. CoRR abs/2403.04484 (2024) - [i39]Cynthia Maldonado García, Rodrigo Bonazzola, Enzo Ferrante, Thomas H. Julian, Panagiotis I Sergouniotis, Nishant Ravikumar, Alejandro F. Frangi:
Predicting risk of cardiovascular disease using retinal OCT imaging. CoRR abs/2403.18873 (2024) - [i38]Josefina Catoni, Enzo Ferrante, Diego H. Milone, Rodrigo Echeveste:
Uncertainty in latent representations of variational autoencoders optimized for visual tasks. CoRR abs/2404.15390 (2024) - [i37]Badr-Eddine Marani, Mohamed Hanini, Nihitha Malayarukil, Stergios Christodoulidis, Maria Vakalopoulou, Enzo Ferrante:
ViG-Bias: Visually Grounded Bias Discovery and Mitigation. CoRR abs/2407.01996 (2024) - [i36]Enzo Ferrante, Rodrigo Echeveste:
Open Challenges on Fairness of Artificial Intelligence in Medical Imaging Applications. CoRR abs/2407.16953 (2024) - 2023
- [j13]Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante:
Improving Anatomical Plausibility in Medical Image Segmentation via Hybrid Graph Neural Networks: Applications to Chest X-Ray Analysis. IEEE Trans. Medical Imaging 42(2): 546-556 (2023) - [c26]María Agustina Ricci Lara, Candelaria Mosquera, Enzo Ferrante, Rodrigo Echeveste:
Towards Unraveling Calibration Biases in Medical Image Analysis. CLIP/FAIMI/EPIMI@MICCAI 2023: 132-141 - [c25]Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Unsupervised Bias Discovery in Medical Image Segmentation. CLIP/FAIMI/EPIMI@MICCAI 2023: 266-275 - [c24]Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante:
Multi-Center Anatomical Segmentation with Heterogeneous Labels Via Landmark-Based Models. ISBI 2023: 1-5 - [c23]Agostina J. Larrazabal, César Martínez, Jose Dolz, Enzo Ferrante:
Maximum Entropy on Erroneous Predictions: Improving Model Calibration for Medical Image Segmentation. MICCAI (3) 2023: 273-283 - [e5]Stefan Wesarg, Esther Puyol-Antón, John S. H. Baxter, Marius Erdt, Klaus Drechsler, Cristina Oyarzun Laura, Moti Freiman, Yufei Chen, Islem Rekik, Roy Eagleson, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Daniel Moyer, Eike Petersen:
Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging - 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023 Vancouver, BC, Canada, October 8 and October 12, 2023 Proceedings. Lecture Notes in Computer Science 14242, Springer 2023, ISBN 978-3-031-45248-2 [contents] - [i35]Rodrigo Bonazzola, Enzo Ferrante, Nishant Ravikumar, Yan Xia, Bernard D. Keavney, Sven Plein, Tanveer F. Syeda-Mahmood, Alejandro F. Frangi:
Unsupervised ensemble-based phenotyping helps enhance the discoverability of genes related to heart morphology. CoRR abs/2301.02916 (2023) - [i34]Eike Petersen, Enzo Ferrante, Melanie Ganz, Aasa Feragen:
Are demographically invariant models and representations in medical imaging fair? CoRR abs/2305.01397 (2023) - [i33]María Agustina Ricci Lara, Candelaria Mosquera, Enzo Ferrante, Rodrigo Echeveste:
Towards unraveling calibration biases in medical image analysis. CoRR abs/2305.05101 (2023) - [i32]Nicolás Gaggion, Candelaria Mosquera, Lucas Mansilla, Martina Aineseder, Diego H. Milone, Enzo Ferrante:
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images. CoRR abs/2307.03293 (2023) - [i31]Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Unsupervised bias discovery in medical image segmentation. CoRR abs/2309.00451 (2023) - [i30]Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F. Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R. Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard Ohene Botwe, Bishesh Khanal, Brigit Beger, Carol C. Wu, Celia Cintas, Curtis P. Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I. Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A. González, Folkert W. Asselbergs, Fred W. Prior, Gabriel P. Krestin, Gary S. Collins, Geletaw Sahle Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C. Woodruff, Hugo J. W. L. Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James S. Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W. Gichoya, Julia A. Schnabel, et al.:
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. CoRR abs/2309.12325 (2023) - [i29]Nicolás Gaggion, Benjamin A. Matheson, Yan Xia, Rodrigo Bonazzola, Nishant Ravikumar, Zeike A. Taylor, Diego H. Milone, Alejandro F. Frangi, Enzo Ferrante:
Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI. CoRR abs/2311.13706 (2023) - 2022
- [e4]Alessa Hering, Julia A. Schnabel, Miaomiao Zhang, Enzo Ferrante, Mattias P. Heinrich, Daniel Rueckert:
Biomedical Image Registration - 10th International Workshop, WBIR 2022, Munich, Germany, July 10-12, 2022, Proceedings. Lecture Notes in Computer Science 13386, Springer 2022, ISBN 978-3-031-11202-7 [contents] - [i28]Sean I. Young, Adrian V. Dalca, Enzo Ferrante, Polina Golland, Bruce Fischl, Juan Eugenio Iglesias:
SUD: Supervision by Denoising for Medical Image Segmentation. CoRR abs/2202.02952 (2022) - [i27]Nicolás Gaggion, Lucas Mansilla, Candelaria Mosquera, Diego H. Milone, Enzo Ferrante:
Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis. CoRR abs/2203.10977 (2022) - [i26]Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone, Enzo Ferrante:
Multi-center anatomical segmentation with heterogeneous labels via landmark-based models. CoRR abs/2211.07395 (2022) - 2021
- [j12]Wufeng Xue, Jiahui Li, Zhiqiang Hu, Eric Kerfoot, James R. Clough, Ilkay Öksüz, Hao Xu, Vicente Grau, Fumin Guo, Matthew Ng, Xiang Li, Quanzheng Li, Lihong Liu, Jin Ma, Elias Grinias, Georgios Tziritas, Wenjun Yan, Angélica Atehortúa, Mireille Garreau, Yeonggul Jang, Alejandro Debus, Enzo Ferrante, Guanyu Yang, Tiancong Hua, Shuo Li:
Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data. IEEE J. Biomed. Health Informatics 25(9): 3541-3553 (2021) - [j11]Jianning Li, Pedro Pimentel, Angelika Szengel, Moritz Ehlke, Hans Lamecker, Stefan Zachow, Laura Jovani Estacio Cerquin, Christian Doenitz, Heiko Ramm, Haochen Shi, Xiaojun Chen, Franco Matzkin, Virginia F. J. Newcombe, Enzo Ferrante, Yuan Jin, David G. Ellis, Michele R. Aizenberg, Oldrich Kodym, Michal Spanel, Adam Herout, James G. Mainprize, Zachary Fishman, Michael R. Hardisty, Amirhossein Bayat, Suprosanna Shit, Bomin Wang, Zhi Liu, Matthias Eder, Antonio Pepe, Christina Gsaxner, Victor Alves, Ulrike Zefferer, Gord von Campe, Karin Pistracher, Ute Schäfer, Dieter Schmalstieg, Bjoern H. Menze, Ben Glocker, Jan Egger:
AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design. IEEE Trans. Medical Imaging 40(9): 2329-2342 (2021) - [c22]Lucas Mansilla, Rodrigo Echeveste, Diego H. Milone, Enzo Ferrante:
Domain Generalization via Gradient Surgery. ICCV 2021: 6610-6618 - [c21]Agostina J. Larrazabal, César Ernesto Martínez, Jose Dolz, Enzo Ferrante:
Orthogonal Ensemble Networks for Biomedical Image Segmentation. MICCAI (3) 2021: 594-603 - [c20]Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Hybrid Graph Convolutional Neural Networks for Landmark-Based Anatomical Segmentation. MICCAI (1) 2021: 600-610 - [c19]Rodrigo Bonazzola, Nishant Ravikumar, Rahman Attar, Enzo Ferrante, Tanveer F. Syeda-Mahmood, Alejandro F. Frangi:
Image-Derived Phenotype Extraction for Genetic Discovery via Unsupervised Deep Learning in CMR Images. MICCAI (5) 2021: 699-708 - [i25]Agostina J. Larrazabal, César Ernesto Martínez, Jose Dolz, Enzo Ferrante:
Orthogonal Ensemble Networks for Biomedical Image Segmentation. CoRR abs/2105.10827 (2021) - [i24]Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Hybrid graph convolutional neural networks for landmark-based anatomical segmentation. CoRR abs/2106.09832 (2021) - [i23]Lucas Mansilla, Rodrigo Echeveste, Diego H. Milone, Enzo Ferrante:
Domain Generalization via Gradient Surgery. CoRR abs/2108.01621 (2021) - [i22]Agostina J. Larrazabal, César Ernesto Martínez, José Dolz, Enzo Ferrante:
Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation. CoRR abs/2112.12218 (2021) - [i21]Candelaria Mosquera, Luciana Ferrer, Diego H. Milone, Daniel R. Luna, Enzo Ferrante:
Understanding the impact of class imbalance on the performance of chest x-ray image classifiers. CoRR abs/2112.12843 (2021) - 2020
- [j10]Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Learning deformable registration of medical images with anatomical constraints. Neural Networks 124: 269-279 (2020) - [j9]Agostina J. Larrazabal, César Ernesto Martínez, Ben Glocker, Enzo Ferrante:
Post-DAE: Anatomically Plausible Segmentation via Post-Processing With Denoising Autoencoders. IEEE Trans. Medical Imaging 39(12): 3813-3820 (2020) - [c18]Franco Matzkin, Virginia F. J. Newcombe, Ben Glocker, Enzo Ferrante:
Cranial Implant Design via Virtual Craniectomy with Shape Priors. AutoImplant@MICCAI 2020: 37-46 - [c17]Franco Matzkin, Virginia F. J. Newcombe, Susan Stevenson, Aneesh Khetani, Tom Newman, Richard Digby, Andrew Stevens, Ben Glocker, Enzo Ferrante:
Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy. MICCAI (2) 2020: 390-399 - [e3]Carole H. Sudre, Hamid Fehri, Tal Arbel, Christian F. Baumgartner, Adrian V. Dalca, Ryutaro Tanno, Koen Van Leemput, William M. Wells III, Aristeidis Sotiras, Bartlomiej W. Papiez, Enzo Ferrante, Sarah Parisot:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis - Second International Workshop, UNSURE 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings. Lecture Notes in Computer Science 12443, Springer 2020, ISBN 978-3-030-60364-9 [contents] - [i20]Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Learning Deformable Registration of Medical Images with Anatomical Constraints. CoRR abs/2001.07183 (2020) - [i19]Agostina J. Larrazabal, César Ernesto Martínez, Ben Glocker, Enzo Ferrante:
Post-DAE: Anatomically Plausible Segmentation via Post-Processing with Denoising Autoencoders. CoRR abs/2006.13791 (2020) - [i18]Franco Matzkin, Virginia F. J. Newcombe, Susan Stevenson, Aneesh Khetani, Tom Newman, Richard Digby, Andrew Stevens, Ben Glocker, Enzo Ferrante:
Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy. CoRR abs/2007.03817 (2020) - [i17]Julian Alberto Palladino, Diego Fernández Slezak, Enzo Ferrante:
Unsupervised Domain Adaptation via CycleGAN for White Matter Hyperintensity Segmentation in Multicenter MR Images. CoRR abs/2009.04985 (2020) - [i16]Franco Matzkin, Virginia F. J. Newcombe, Ben Glocker, Enzo Ferrante:
Cranial Implant Design via Virtual Craniectomy with Shape Priors. CoRR abs/2009.13704 (2020)
2010 – 2019
- 2019
- [j8]Enzo Ferrante, Puneet Kumar Dokania, Rafael Marini, Nikos Paragios:
Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration. IEEE J. Biomed. Health Informatics 23(4): 1374-1384 (2019) - [c16]Miguel Monteiro, Konstantinos Kamnitsas, Enzo Ferrante, Francois Mathieu, Steven McDonagh, Sam Cook, Susan Stevenson, Tilak Das, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jonathan P. Coles, Daniel Rueckert, David K. Menon, Virginia F. J. Newcombe, Ben Glocker:
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation. BrainLes@MICCAI (1) 2019: 13-22 - [c15]Agostina J. Larrazabal, César Ernesto Martínez, Enzo Ferrante:
Anatomical Priors for Image Segmentation via Post-processing with Denoising Autoencoders. MICCAI (6) 2019: 585-593 - [c14]Nicolas Roulet, Diego Fernández Slezak, Enzo Ferrante:
Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets. MIDL 2019: 401-413 - [i15]Nicolas Roulet, Diego Fernández Slezak, Enzo Ferrante:
Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets. CoRR abs/1903.03445 (2019) - [i14]Agostina J. Larrazabal, César Ernesto Martínez, Enzo Ferrante:
Anatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders. CoRR abs/1906.02343 (2019) - 2018
- [j7]Enzo Ferrante, Nikos Paragios:
Graph-Based Slice-to-Volume Deformable Registration. Int. J. Comput. Vis. 126(1): 36-58 (2018) - [j6]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer's disease. Medical Image Anal. 48: 117-130 (2018) - [j5]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Metric learning with spectral graph convolutions on brain connectivity networks. NeuroImage 169: 431-442 (2018) - [j4]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation. IEEE Trans. Medical Imaging 37(2): 384-395 (2018) - [c13]Juan J. Cerrolaza, Matthew Sinclair, Yuanwei Li, Alberto Gómez, Enzo Ferrante, Jacqueline Matthew, Chandni Gupta, Caroline L. Knight, Daniel Rueckert:
Deep learning with ultrasound physics for fetal skull segmentation. ISBI 2018: 564-567 - [c12]Enzo Ferrante, Ozan Oktay, Ben Glocker, Diego H. Milone:
On the Adaptability of Unsupervised CNN-Based Deformable Image Registration to Unseen Image Domains. MLMI@MICCAI 2018: 294-302 - [c11]Alejandro Debus, Enzo Ferrante:
Left Ventricle Quantification Through Spatio-Temporal CNNs. STACOM@MICCAI 2018: 466-475 - [e2]Danail Stoyanov, Zeike Taylor, Enzo Ferrante, Adrian V. Dalca, Anne L. Martel, Lena Maier-Hein, Sarah Parisot, Aristeidis Sotiras, Bartlomiej W. Papiez, Mert R. Sabuncu, Li Shen:
Graphs in Biomedical Image Analysis - and - Integrating Medical Imaging and Non-Imaging Modalities - Second International Workshop, GRAIL 2018 - and - First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. Lecture Notes in Computer Science 11044, Springer 2018, ISBN 978-3-030-00688-4 [contents] - [i13]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew Lee, Ricardo Guerrero, Ben Glocker, Daniel Rueckert:
Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease. CoRR abs/1806.01738 (2018) - [i12]Alejandro Debus, Enzo Ferrante:
Left ventricle quantification through spatio-temporal CNNs. CoRR abs/1808.07967 (2018) - [i11]Enzo Ferrante, Puneet Kumar Dokania, Rafael Marini, Nikos Paragios:
Weakly-Supervised Learning of Metric Aggregations for Deformable Image Registration. CoRR abs/1809.09004 (2018) - 2017
- [j3]Enzo Ferrante, Nikos Paragios:
Slice-to-volume medical image registration: A survey. Medical Image Anal. 39: 101-123 (2017) - [c10]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-Based Disease Prediction. MICCAI (3) 2017: 177-185 - [c9]Enzo Ferrante, Puneet Kumar Dokania, Rafael Marini, Nikos Paragios:
Deformable Registration Through Learning of Context-Specific Metric Aggregation. MLMI@MICCAI 2017: 256-265 - [c8]Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. BrainLes@MICCAI 2017: 450-462 - [c7]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks. MICCAI (1) 2017: 469-477 - [e1]M. Jorge Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec, Adrian V. Dalca, Sarah Parisot, Sarang C. Joshi, Nematollah Kayhan Batmanghelich, Aristeidis Sotiras, Mads Nielsen, Mert R. Sabuncu, Tom Fletcher, Li Shen, Stanley Durrleman, Stefan Sommer:
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings. Lecture Notes in Computer Science 10551, Springer 2017, ISBN 978-3-319-67674-6 [contents] - [i10]Enzo Ferrante, Nikos Paragios:
Slice-to-volume medical image registration: a survey. CoRR abs/1702.01636 (2017) - [i9]Sofia Ira Ktena, Sarah Parisot, Enzo Ferrante, Martin Rajchl, Matthew C. H. Lee, Ben Glocker, Daniel Rueckert:
Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks. CoRR abs/1703.02161 (2017) - [i8]Sarah Parisot, Sofia Ira Ktena, Enzo Ferrante, Matthew C. H. Lee, Ricardo Guerrero Moreno, Ben Glocker, Daniel Rueckert:
Spectral Graph Convolutions for Population-based Disease Prediction. CoRR abs/1703.03020 (2017) - [i7]José Ignacio Orlando, Hugo Luis Manterola, Enzo Ferrante, Federico Ariel:
Arabidopsis roots segmentation based on morphological operations and CRFs. CoRR abs/1704.07793 (2017) - [i6]Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias P. Heinrich, Wenjia Bai, Jose Caballero, Ricardo Guerrero, Stuart A. Cook, Antonio de Marvao, Timothy Dawes, Declan P. O'Regan, Bernhard Kainz, Ben Glocker, Daniel Rueckert:
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation. CoRR abs/1705.08302 (2017) - [i5]Enzo Ferrante, Puneet Kumar Dokania, Rafael Marini, Nikos Paragios:
Deformable Registration through Learning of Context-Specific Metric Aggregation. CoRR abs/1707.06263 (2017) - [i4]Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante, Steven G. McDonagh, Matthew Sinclair, Nick Pawlowski, Martin Rajchl, Matthew C. H. Lee, Bernhard Kainz, Daniel Rueckert, Ben Glocker:
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation. CoRR abs/1711.01468 (2017) - 2016
- [b1]Enzo Ferrante:
Graph-based deformable registration : slice-to-volume mapping and context specific methods. (Recalage déformable à base de graphes : mise en correspondance coupe-vers-volume et méthodes contextuelles). University of Paris-Saclay, France, 2016 - [j2]Nikos Paragios, Enzo Ferrante, Ben Glocker, Nikos Komodakis, Sarah Parisot, Evangelia I. Zacharaki:
(Hyper)-graphical models in biomedical image analysis. Medical Image Anal. 33: 102-106 (2016) - [c6]Mahsa Shakeri, Stavros Tsogkas, Enzo Ferrante, Sarah Lippé, Samuel Kadoury, Nikos Paragios, Iasonas Kokkinos:
Sub-cortical brain structure segmentation using F-CNN'S. ISBI 2016: 269-272 - [c5]Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya V. Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker:
DeepMedic for Brain Tumor Segmentation. BrainLes@MICCAI 2016: 138-149 - [c4]Roque Porchetto, Franco Stramana, Nikos Paragios, Enzo Ferrante:
Rigid Slice-To-Volume Medical Image Registration Through Markov Random Fields. MCV/BAMBI@MICCAI 2016: 172-185 - [c3]Mahsa Shakeri, Enzo Ferrante, Stavros Tsogkas, Sarah Lippé, Samuel Kadoury, Iasonas Kokkinos, Nikos Paragios:
Prior-Based Coregistration and Cosegmentation. MICCAI (2) 2016: 529-537 - [i3]Mahsa Shakeri, Stavros Tsogkas, Enzo Ferrante, Sarah Lippé, Samuel Kadoury, Nikos Paragios, Iasonas Kokkinos:
Sub-cortical brain structure segmentation using F-CNN's. CoRR abs/1602.02130 (2016) - [i2]Mahsa Shakeri, Enzo Ferrante, Stavros Tsogkas, Sarah Lippé, Samuel Kadoury, Iasonas Kokkinos, Nikos Paragios:
Prior-based Coregistration and Cosegmentation. CoRR abs/1607.06787 (2016) - [i1]Roque Porchetto, Franco Stramana, Nikos Paragios, Enzo Ferrante:
Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields. CoRR abs/1608.05562 (2016) - 2015
- [j1]Enzo Ferrante, Vivien Fecamp, Nikos Paragios:
Slice-to-volume deformable registration: efficient one-shot consensus between plane selection and in-plane deformation. Int. J. Comput. Assist. Radiol. Surg. 10(6): 791-800 (2015) - [c2]Enzo Ferrante, Vivien Fecamp, Nikos Paragios:
Implicit planar and in-plane deformable mapping in medical images through high order graphs. ISBI 2015: 721-724 - 2013
- [c1]Enzo Ferrante, Nikos Paragios:
Non-rigid 2D-3D Medical Image Registration Using Markov Random Fields. MICCAI (3) 2013: 163-170
Coauthor Index
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