Publications

All my publications, automatically synced from HAL.

Journal articles 41 documents

Unsupervised anomaly detection with deep generative models: an experimental analysis of model variability and mitigation strategies

M. Solal, P. André, N. Burgos

Journal of Medical Imaging, vol. 13, no. 04, pp. 1-22, SPIE Digital Library2026

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Multi-Domain Brain Vessel Segmentation Through Feature Disentanglement

F. Galati, D. Falcetta, R. Cortese, F. Prados, N. Burgos, M. Zuluaga

Journal of Machine Learning for Biomedical Imaging, vol. 3, no. September 2025, pp. 477-495, Melba editors2025

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Artificial intelligence in presymptomatic neurological diseases: Bridging normal variation and prodromal signatures

T. Soulier, N. Burgos, R. Hassanaly, M. Pitombeira, M. Solal, H. Roy, M. Hamzaoui, A. Yazdan-Panah, D. de Paula Faria, C. Louapre, B. Bodini, M. Bottlaender, N. Ayache, O. Colliot, B. Stankoff

Revue Neurologique, vol. 181, no. 9, pp. 944-950, Elsevier Masson2025

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Benchmarking 3D generative autoencoders for pseudo-healthy reconstruction of brain 18F-fluorodeoxyglucose positron emission tomography

R. Hassanaly, M. Solal, O. Colliot, N. Burgos

Journal of Medical Imaging, vol. 12, no. 5, pp. 054005, SPIE Digital Library2025

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Automatic quality control of brain 3D FLAIR MRIs for a clinical data warehouse

S. Loizillon, S. Bottani, A. Maire, S. Ströer, L. Chougar, D. Dormont, O. Colliot, N. Burgos

Medical Image Analysis, vol. 103, pp. 103617, Elsevier2025

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Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation

S. Loizillon, S. Bottani, S. Mabille, Y. Jacob, A. Maire, S. Ströer, D. Dormont, O. Colliot, N. Burgos

Journal of Machine Learning for Biomedical Imaging, vol. 2, no. June 2024, pp. 888-915, Melba editors2024

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Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI

S. Bottani, E. Thibeau-Sutre, A. Maire, S. Ströer, D. Dormont, O. Colliot, N. Burgos

BMC Medical Imaging, vol. 24, no. 1, pp. 67, BioMed Central2024

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Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET

R. Hassanaly, C. Brianceau, M. Solal, O. Colliot, N. Burgos

Journal of Machine Learning for Biomedical Imaging, vol. 2, pp. 611, Melba editors2024

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Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data

S. Loizillon, S. Bottani, A. Maire, S. Ströer, D. Dormont, O. Colliot, N. Burgos

Medical Image Analysis, vol. 93, pp. 103073, Elsevier2024

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Evaluation of MRI-based machine learning approaches for computer-aided diagnosis of dementia in a clinical data warehouse

S. Bottani, N. Burgos, A. Maire, D. Saracino, S. Stroër, D. Dormont, O. Colliot

Medical Image Analysis, vol. 89, pp. 102903, Elsevier2023

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Operationalizing the centiloid scale for [18 F]florbetapir PET studies on PET/MRI

W. Coath, M. Modat, M.-J. Cardoso, P. Markiewicz, C. Lane, T. Parker, A. Keshavan, S. Buchanan, S. Keuss, M. Harris, N. Burgos, J. Dickson, A. Barnes, D. Thomas, D. Beasley, I. Malone, A. Wong, K. Erlandsson, B. Thomas, M. Schöll, S. Ourselin, M. Richards, N. Fox, J. Schott, D. Cash

Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, vol. 15, no. 2, Wiley2023

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ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing

E. Thibeau-Sutre, M. Diaz, R. Hassanaly, A. Routier, D. Dormont, O. Colliot, N. Burgos

Computer Methods and Programs in Biomedicine, vol. 220, pp. 106818, Elsevier2022

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Pilot Study of Repeated Blood-Brain Barrier Disruption in Patients with Mild Alzheimer's Disease with an Implantable Ultrasound Device

S. Epelbaum, N. Burgos, M. Canney, D. Matthews, M. Houot, M. Santin, C. Desseaux, G. Bouchoux, S. Stroer, C. Martin, M.-O. Habert, M. Levy, A. Bah, K. Martin, B. Delatour, M. Riche, B. Dubois, L. Belin, A. Carpentier

Alzheimer's Research and Therapy, vol. 14, no. 40, BioMed Central2022

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Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse

S. Bottani, N. Burgos, A. Maire, A. Wild, S. Ströer, D. Dormont, O. Colliot

Medical Image Analysis, vol. 75, Elsevier2022

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Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

C. Chadebec, E. Thibeau-Sutre, N. Burgos, S. Allassonnière

IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers2022

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Clinica: an open source software platform for reproducible clinical neuroscience studies

A. Routier, N. Burgos, M. Diaz, M. Bacci, S. Bottani, O. El-Rifai, S. Fontanella, P. Gori, J. Guillon, A. Guyot, R. Hassanaly, T. Jacquemont, P. Lu, A. Marcoux, T. Moreau, J. Samper-González, M. Teichmann, E. Thibeau-Sutre, G. Vaillant, J. Wen, A. Wild, M.-O. Habert, S. Durrleman, O. Colliot

Frontiers in Neuroinformatics, vol. 15, pp. 689675, Frontiers Media2021

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AD Course Map charts Alzheimer’s disease progression

I. Koval, A. Bône, M. Louis, T. Lartigue, S. Bottani, A. Marcoux, J. Samper-González, N. Burgos, B. Charlier, A. Bertrand, S. Epelbaum, O. Colliot, S. Allassonnière, S. Durrleman

Scientific Reports, vol. 11, no. 1, pp. 8020, Nature Publishing Group2021

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Anomaly detection for the individual analysis of brain PET images

N. Burgos, J. Cardoso, J. Samper-González, M.-O. Habert, S. Durrleman, S. Ourselin, O. Colliot

Journal of Medical Imaging, vol. 8, no. 02, pp. 024003, SPIE Digital Library2021

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Deep learning for brain disorders: from data processing to disease treatment

N. Burgos, S. Bottani, J. Faouzi, E. Thibeau-Sutre, O. Colliot

Briefings in Bioinformatics, vol. 22, no. 2, pp. 1560-1576, Oxford University Press (OUP)2021

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Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic, Quantitative and Critical Review

M. Ansart, S. Epelbaum, G. Bassignana, A. Bône, S. Bottani, T. Cattai, R. Couronné, J. Faouzi, I. Koval, M. Louis, E. Thibeau-Sutre, J. Wen, A. Wild, N. Burgos, D. Dormont, O. Colliot, S. Durrleman

Medical Image Analysis, vol. 67, pp. 101848, Elsevier2021

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Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer's disease

J. Wen, J. Samper-González, S. Bottani, A. Routier, N. Burgos, T. Jacquemont, S. Fontanella, S. Durrleman, S. Epelbaum, A. Bertrand, O. Colliot

Neuroinformatics, vol. 19, no. 1, pp. 57-78, Springer2021

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Ensemble Learning of Convolutional Neural Network, Support Vector Machine, and Best Linear Unbiased Predictor for Brain Age Prediction: ARAMIS Contribution to the Predictive Analytics Competition 2019 Challenge

B. Couvy-Duchesne, J. Faouzi, B. Martin, E. Thibeau-Sutre, A. Wild, M. Ansart, S. Durrleman, D. Dormont, N. Burgos, O. Colliot

Frontiers in Psychiatry, vol. 11, Frontiers2020

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Machine learning for classification and prediction of brain diseases: recent advances and upcoming challenges

N. Burgos, O. Colliot

Current Opinion in Neurology, vol. 33, no. 4, pp. 439-450, Lippincott, Williams & Wilkins2020

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Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation

J. Wen, E. Thibeau-Sutre, M. Diaz-Melo, J. Samper-González, A. Routier, S. Bottani, D. Dormont, S. Durrleman, N. Burgos, O. Colliot

Medical Image Analysis, vol. 63, pp. 101694, Elsevier2020

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Tribute to Anne Bertrand (1978–2018): Neuroradiologist, scientist, teacher and friend

D. Dormont, N. Ben-Eliezer, N. Burgos, O. Colliot, F. de Vico Fallani, M. Dhenain, S. Durrleman, S. Epelbaum, M.-O. Habert, I. Le Ber, J.-F. Méder, Y. Menu, C. Oppenheim, Y. Wadghiri

Journal de Neuroradiologie / Journal of Neuroradiology, vol. 46, no. 2, pp. 155-159, Elsevier Masson2019

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Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

J. Samper-González, N. Burgos, S. Bottani, S. Fontanella, P. Lu, A. Marcoux, A. Routier, J. Guillon, M. Bacci, J. Wen, A. Bertrand, H. Bertin, M.-O. Habert, S. Durrleman, T. Evgeniou, O. Colliot

NeuroImage, vol. 183, pp. 504-521, Elsevier2018

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An Automated Pipeline for the Analysis of PET Data on the Cortical Surface

A. Marcoux, N. Burgos, A. Bertrand, M. Teichmann, A. Routier, J. Wen, J. Samper-Gonzalez, S. Bottani, S. Durrleman, M.-O. Habert, O. Colliot

Frontiers in Neuroinformatics, vol. 12, Frontiers Media2018

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Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region

H. Arabi, J. Dowling, N. Burgos, X. Han, P. Greer, N. Koutsouvelis, H. Zaidi

Medical Physics, American Association of Physicists in Medicine2018

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Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region

J.-P. Kieselmann, C.-P. Kamerling, N. Burgos, M.-J. Menten, C.-D. Fuller, S. Nill, J. Cardoso, U. Oelfke

Physics in Medicine and Biology, vol. 63, no. 14, IOP Publishing2018

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Reduced acquisition time PET pharmacokinetic modelling using simultaneous ASL–MRI: proof of concept

C. Scott, J. Jiao, A. Melbourne, N. Burgos, D. Cash, E. de Vita, P. Markiewicz, A. O'Connor, D. Thomas, P.-S. Weston, J. Schott, B. Hutton, S. Ourselin

Journal of Cerebral Blood Flow and Metabolism, Nature Publishing Group2018

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Direct parametric reconstruction with joint motion estimation/correction for dynamic brain PET data

J. Jiao, A. Bousse, K. Thielemans, N. Burgos, P.-S.-J. Weston, J.-M. Schott, D. Atkinson, S.-R. Arridge, B.-F. Hutton, P. Markiewicz, S. Ourselin

IEEE Transactions on Medical Imaging, vol. 36, no. 1, pp. 203--213, Institute of Electrical and Electronics Engineers2017

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A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients

C.-N. Ladefoged, I. Law, U. Anazodo, K. St. Lawrence, D. Izquierdo-Garcia, C. Catana, N. Burgos, J. Cardoso, S. Ourselin, B. Hutton, I. Mérida, N. Costes, A. Hammers, D. Benoit, S. Holm, M. Juttukonda, H. An, J. Cabello, M. Lukas, S. Nekolla, S. Ziegler, M. Fenchel, B. Jakoby, M.-E. Casey, T. Benzinger, L. Højgaard, A.-E. Hansen, F.-L. Andersen

NeuroImage, vol. 147, pp. 346--359, Elsevier2017

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Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning

F. Guerreiro, N. Burgos, A. Dunlop, K. Wong, I. Petkar, C. Nutting, K. Harrington, S. Bhide, K. Newbold, D. Dearnaley, N.-M. Desouza, V.-A. Morgan, J. Mcclelland, S. Nill, M.-J. Cardoso, S. Ourselin, U. Oelfke, A.-C. Knopf

Physica Medica European Journal of Medical Physics, vol. 35, pp. 7--17, Elsevier2017

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Study protocol: Insight 46 – a neuroscience sub-study of the MRC National Survey of Health and Development

C.-A. Lane, T.-D. Parker, D.-M. Cash, K. Macpherson, E. Donnachie, H. Murray-Smith, A. Barnes, S. Barker, D.-G. Beasley, J. Bras, D. Brown, N. Burgos, M. Byford, M. Jorge Cardoso, A. Carvalho, J. Collins, E. de Vita, J.-C. Dickson, N. Epie, M. Espak, S.-M.-D. Henley, C. Hoskote, M. Hutel, J. Klimova, I.-B. Malone, P. Markiewicz, A. Melbourne, M. Modat, A. Schrag, S. Shah, N. Sharma, C.-H. Sudre, D.-L. Thomas, A. Wong, H. Zhang, J. Hardy, H. Zetterberg, S. Ourselin, S.-J. Crutch, D. Kuh, M. Richards, N.-C. Fox, J.-M. Schott

BMC Neurology, vol. 17, pp. 75, BioMed Central2017

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Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning

N. Burgos, F. Guerreiro, M. Mcclelland, B. Presles, M. Modat, S. Nill, D. Dearnaley, N. Desouza, U. Oelfke, A.-C. Knopf, S. Ourselin, M. Jorge Cardoso

Physics in Medicine and Biology, vol. 62, no. 11, pp. 4237 - 4253, IOP Publishing2017

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Multi atlas-based attenuation correction for brain FDG- PET imaging using a TOF-PET/MR scanner: Comparison with clinical single atlas- and CT-based attenuation correction

T. Sekine, N. Burgos, G. Warnock, M. Huellner, A. Buck, E.-E.-G.-W.-T. Voert, J. Cardoso, B.-F. Hutton, S. Ourselin, P. Veit-Haibach, G. Delso

Journal of Nuclear Medicine, vol. 57, no. 8, pp. 1258--1264, Society of Nuclear Medicine2016

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Voxelwise atlas rating for computer assisted diagnosis: Application to congenital heart diseases of the great arteries

M. Zuluaga, N. Burgos, A.-F. Mendelson, A.-M. Taylor, S. Ourselin

Medical Image Analysis, vol. 26, no. 1, pp. 185--194, Elsevier2015

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Using florbetapir positron emission tomography to explore cerebrospinal fluid cut points and gray zones in small sample sizes

P.-S.-J. Weston, R.-W. Paterson, M. Modat, N. Burgos, M.-J. Cardoso, N. Magdalinou, M. Lehmann, J.-C. Dickson, A. Barnes, J.-B. Bomanji, I. Kayani, D.-M. Cash, S. Ourselin, J. Toombs, M.-P. Lunn, C.-J. Mummery, J.-D. Warren, M.-N. Rossor, N.-C. Fox, H. Zetterberg, J.-M. Schott

Alzheimer's & Dementia : the Journal of the Alzheimer's Association, vol. 1, no. 4, pp. 440--446, Alzheimer's Association / Wiley2015

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Multi-contrast attenuation map synthesis for PET/MR scanners: assessment on FDG and Florbetapir PET tracers

N. Burgos, J. Cardoso, K. Thielemans, M. Modat, J. Dickson, J.-M. Schott, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

European Journal of Nuclear Medicine and Molecular Imaging, vol. 42, no. 9, pp. 1447--1458, Springer Verlag (Germany) [1976-....]2015

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Simulated field maps for susceptibility artefact correction in interventional MRI

M. Kochan, P. Daga, N. Burgos, M. White, J. Cardoso, L. Mancini, G.-P. Winston, A.-W. Mcevoy, J. Thornton, T. Yousry, J.-S. Duncan, D. Stoyanov, S. Ourselin

International Journal of Computer Assisted Radiology and Surgery, vol. 10, no. 9, pp. 1405--1416, Springer Verlag2015

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Attenuation correction synthesis for hybrid PET-MR scanners: Application to brain studies

N. Burgos, M.-J. Cardoso, K. Thielemans, M. Modat, S. Pedemonte, J. Dickson, A. Barnes, R. Ahmed, C.-J. Mahoney, J.-M. Schott, J.-S. Duncan, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

IEEE Transactions on Medical Imaging, vol. 33, no. 12, pp. 2332--2341, Institute of Electrical and Electronics Engineers2014

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International conferences with full-length peer-reviewed proceedings 35 documents

Unsupervised Brain Anomaly Detection as a Bayesian Inverse Problem with Diffusion Prior

H. Roy, R. Dorent, N. Burgos

In MICCAI 2026 - Medical Image Computing and Computer Assisted Intervention2026

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Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection

A. Senellart, M. Solal, S. Allassonnière, N. Burgos

In ISBI 2026 - International Symposium on Biomedical Imaging, pp. 1-5, IEEE2026

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Unsupervised anomaly detection in brain FDG PET with deep generative models: An experimental analysis of model variability and mitigation strategies

M. Solal, A. Pascaline, N. Burgos

In SPIE Medical Imaging 2026, pp. 6, SPIE2026

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Assessing the Efficacy of Artefact Synthesis and Transfer Learning for Quality Control in Clinical 3D FLAIR Brain MRI

M. Heffernan, S. Loizillon, S. Ströer, L. Chougar, D. Dormont, O. Colliot, N. Burgos

In SPIE Medical Imaging 2026, pp. 9, SPIE2026

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Comparing Longitudinal Preprocessing Pipelines for Brain Volume Consistency in T1-Weighted MRI Test-Retest Scans

M. Joulot, O. Colliot, N. Burgos

In SPIE Medical Imaging 2026, pp. 51, SPIE2026

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Unsupervised anomaly detection using Bayesian flow networks: application to brain FDG pet in the context of Alzheimer’s disease

H. Roy, R. Dorent, N. Burgos

In DGM4MICCAI 2025 - Deep Generative Models, pp. 254-264, Springer Nature Switzerland2026

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Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET

M. Solal, R. Hassanaly, N. Burgos

In SPIE Medical Imaging, SPIE2024

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Evaluation of pseudo-healthy reconstruction for anomaly detection in brain FDG PET

R. Hassanaly, C. Brianceau, M. Solal, O. Colliot, N. Burgos

In MIDL 2024 - Medical Imaging with Deep Learning2024

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Confidence intervals uncovered: Are we ready for real-world medical imaging AI?

E. Christodoulou, A. Reinke, R. Houhou, P. Kalinowski, S. Erkan, C. Sudre, N. Burgos, S. Boutaj, S. Loizillon, M. Solal, N. Rieke, V. Cheplygina, M. Antonelli, L. Mayer, M. Tizabi, M.-J. Cardoso, A. Simpson, P. Jäger, A. Kopp-Schneider, G. Varoquaux, O. Colliot, L. Maier-Hein

In MICCAI 2024 - 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 124-132, Springer Nature Switzerland2024

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Leveraging noise and contrast simulation for the automatic quality control of routine clinical T1-weighted brain MRI

S. Loizillon, S. Mabille, S. Bottani, Y. Jacob, A. Maire, S. Ströer, D. Dormont, O. Colliot, N. Burgos

In SPIE Medical Imaging 2024: Image Processing, pp. 129261A, SPIE2024

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Detecting Brain Anomalies in Clinical Routine with the β-VAE: Feasibility Study on Age-Related White Matter Hyperintensities

S. Loizillon, Y. Jacob, A. Maire, D. Dormont, O. Colliot, N. Burgos

In Medical Imaging with Deep Learning - MIDL 20242024

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The intriguing effect of frequency disentangled learning on medical image segmentation

G. Fu, G. Jiménez, S. Loizillon, L. Chougar, D. Dormont, R. Valabrègue, N. Burgos, S. Lehéricy, D. Racoceanu, O. Colliot

In Medical Imaging 2024, pp. 49, SPIE2024

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Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learning

R. Hassanaly, C. Brianceau, M. Diaz, S. Loizillon, E. Thibeau-Sutre, N. Cassereau, O. Colliot, N. Burgos

In SPIE Medical Imaging, pp. 519-524, SPIE2024

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Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networks

T. Soulier, M. Hamzaoui, M. Sales Pitombeira, D. De Paula Faria, A. Yazdan-Panah, M. Tonietto, C. Leroy, M. Bottlaender, B. Bodini, N. Burgos, N. Ayache, O. Colliot, B. Stankoff

In SPIE Medical Imaging, SPIE2024

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Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse

S. Loizillon, O. Colliot, L. Chougar, S. Stroer, Y. Jacob, A. Maire, D. Dormont, N. Burgos

In DART 2023 - 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, pp. 84-93, Springer Nature Switzerland2023

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A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation

F. Galati, D. Falcetta, R. Cortese, B. Casolla, F. Prados, N. Burgos, M.-A. Zuluaga

In BMVC 2023, 34th British Machine Vision Conference2023

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Simulation-based evaluation framework for deep learning unsupervised anomaly detection on brain FDG PET

R. Hassanaly, S. Bottani, B. Sauty, O. Colliot, N. Burgos

In SPIE Medical Imaging2023

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How can data augmentation improve attribution maps for disease subtype explainability?

E. Thibeau-Sutre, J. Wolterink, O. Colliot, N. Burgos

In SPIE Medical Imaging, SPIE2023

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Transfer learning from synthetic to routine clinical data for motion artefact detection in brain T1-weighted MRI

S. Loizillon, S. Bottani, A. Maire, S. Stroer, D. Dormont, O. Colliot, N. Burgos

In SPIE Medical Imaging 2023: Image Processing2023

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MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data set

E. Thibeau-Sutre, B. Couvy-Duchesne, D. Dormont, O. Colliot, N. Burgos

In ISBI 2022 - International Symposium on Biomedical Imaging2022

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Homogenization of brain MRI from a clinical data warehouse using contrast-enhanced to non-contrast-enhanced image translation with U-Net derived models

S. Bottani, E. Thibeau-Sutre, A. Maire, S. Ströer, D. Dormont, O. Colliot, N. Burgos

In SPIE Medical Imaging 2022: Image Processing, pp. 576-582, SPIE2022

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Visualization approach to assess the robustness of neural networks for medical image classification

E. Thibeau-Sutre, O. Colliot, D. Dormont, N. Burgos

In SPIE Medical Imaging 20202020

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Reproducible evaluation of methods for predicting progression to Alzheimer's disease from clinical and neuroimaging data

J. Samper-Gonzalez, N. Burgos, S. Bottani, M.-O. Habert, T. Evgeniou, S. Epelbaum, O. Colliot

In SPIE Medical Imaging 20192019

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Short acquisition time PET quantification using MRI-based pharmacokinetic parameter synthesis

C.-J. Scott, J. Jiao, J. Cardoso, A. Melbourne, E. de Vita, D.-L. Thomas, N. Burgos, P. Markiewicz, J.-M. Schott, B.-F. Hutton, S. Ourselin

In Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017, pp. 737--744, Springer2017

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Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease

J. Samper-Gonzalez, N. Burgos, S. Fontanella, H. Bertin, M.-O. Habert, S. Durrleman, T. Evgeniou, O. Colliot

In Machine Learning in Medical Imaging 2017, pp. 82017

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Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns

N. Burgos, J. Samper-González, A. Bertrand, M.-O. Habert, S. Ourselin, S. Durrleman, J. Cardoso, O. Colliot

In Computational Methods for Molecular Imaging - [MICCAI 2017 Satellite Workshop]2017

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Joint segmentation and CT synthesis for MRI-only radiotherapy treatment planning

N. Burgos, F. Guerreiro, J. Mcclelland, S. Nill, D. Dearnaley, N. Desouza, U. Oelfke, A.-C. Knopf, S. Ourselin, J. Cardoso

In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, pp. 547--555, Springer2016

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Multi-atlas synthesis for computer assisted diagnosis: Application to cardiovascular diseases

M.-A. Zuluaga, N. Burgos, A.-M. Taylor, S. Ourselin

In IEEE International Symposium on Biomedical Imaging – IEEE ISBI 2015, pp. 290--2932015

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Detail-preserving PET reconstruction with sparse image representation and anatomical priors

J. Jiao, P. Markiewicz, N. Burgos, D. Atkinson, B. Hutton, S. Arridge, S. Ourselin

In Information Processing in Medical Imaging – IPMI 2015, pp. 540--551, Springer2015

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Robust CT synthesis for radiotherapy planning: Application to the head & neck region

N. Burgos, J. Cardoso, F. Guerreiro, C. Veiga, M. Modat, J. Mcclelland, A.-C. Knopf, S. Punwani, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

In Medical Image Computing and Computer-Assisted Intervention − MICCAI 2015, pp. 476--484, Springer2015

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Subject-specific models for the analysis of pathological FDG PET data

N. Burgos, J. Cardoso, A.-F. Mendelson, J.-M. Schott, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

In Medical Image Computing and Computer-Assisted Intervention − MICCAI 2015, pp. 651--658, Springer2015

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Simulated field maps: Toward improved susceptibility artefact correction in interventional MRI

M. Kochan, P. Daga, N. Burgos, M. White, J. Cardoso, L. Mancini, G.-P. Winston, A.-W. Mcevoy, J. Thornton, T. Yousry, J.-S. Duncan, D. Stoyanov, S. Ourselin

In Information Processing in Computer-Assisted Interventions – IPCAI 2014, pp. 226--235, Springer2014

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Effect of scatter correction when comparing attenuation maps: Application to brain PET/MR

N. Burgos, K. Thielemans, M.-J. Cardoso, P. Markiewicz, J. Jiao, J. Dickson, J.-S. Duncan, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

In IEEE Nuclear Science Symposium and Medical Imaging Conference – IEEE NSS/MIC 2014, pp. 1--52014

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Joint parametric reconstruction and motion correction framework for dynamic PET data

J. Jiao, A. Bousse, K. Thielemans, P. Markiewicz, N. Burgos, D. Atkinson, S. Arridge, B.-F. Hutton, S. Ourselin

In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, pp. 114-121, Springer2014

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Attenuation correction synthesis for hybrid PET-MR scanners

N. Burgos, M.-J. Cardoso, M. Modat, S. Pedemonte, J. Dickson, A. Barnes, J.-S. Duncan, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, pp. 147--154, Springer2013

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International conference abstracts 46 documents

Beyond Tool Development: Building the Nipoppy Pipeline Store, Ecosystem and Community

M. Dugré, M. Wang, N. Bhagwat, J.-K. Pfarr, A. Macdonald, E. d'Angremont, A. Dai, M. Danyluik, R. Gau, A. Ismaili, A. Jahanpour, N. Jahanshad, A. Joubert, M. Joulot, M. Laansma, S. Mansour, B. Mcpherson, G. Mohammadalinejad, S. Prasad, D. Roper, J. Sanz-Robinson, J. Scarsbrook, A. Stewart, T. Tan, M. Torabi, J. Tu, S. Urchs, E. van Heese, L. Waller, G. Devenyi, M.-M. Chakravarty, S. Bollmann, P. M. Thompson, Y. van der Werf, E. Dickie, N. Burgos, Y. Halchenko, J.-B. Poline

In OHBM 2026 - Annual Meeting of the Organization for Human Brain Mapping2026

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Latent maximum-a-posteriori approach to improve pseudo-healthy reconstruction quality

M. Solal, A. Senellart, N. Burgos, S. Allassonnière

In OHBM 2026 - Annual meeting of the Organization for Human Brain Mapping2026

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Pseudo-healthy FDG PET synthesis: Revisiting a registration and fusion approach with deep learning

M. Krause, H. Roy, N. Burgos

In OHBM 2026 - Annual Meeting Organization for Human Brain Mapping2026

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Benchmarking skull-stripping methods for integration in Clinica

A. Joubert, M. Joulot, N. Gensollen, N. Burgos

In OHBM 2026 - Organization for Human Brain Mapping2026

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Integrating Clinica into Nipoppy to Facilitate Reproducible Large-Scale Neuroimaging Studies

A. Joubert, A. Ismaili, M. Dugré, M. Wang, N. Bhagwat, J.-B. Poline, N. Burgos

In OHBM 2026 - Organization for Human Brain Mapping2026

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Comparing Volumetric Consistency of Longitudinal Preprocessing: A Multi-Cohort Test-Retest Study

M. Joulot, O. Colliot, N. Burgos

In OHBM 2026 - Annual meeting of the Organization for Human Brain Mapping2026

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ClinicaDL v2: an open-source Python library for reproducible deep learning in neuroimaging

T. de Varax, C. Brianceau, R. Hassanaly, M. Heffernan, H. Roy, M. Solal, N. Burgos

In OHBM 2026 - Annual meeting of the Organization for Human Brain Mapping2026

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Study of the quality of clinical routine T1w and FLAIR brain MRI scans in a clinical data warehouse

M. Heffernan, S. Loizillon, O. Colliot, N. Burgos

In OHBM 2026 - Annual Meeting Organization for Human Brain Mapping2026

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From Nipype to Pydra: a Clinica story

G. Vaillant, N. Gensollen, M. Joulot, O. El-Rifai, M. Diaz, O. Colliot, N. Burgos

In OHBM 2023 - Annual meeting of the Organization for Human Brain Mapping2023

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Unsupervised anomaly detection in 3D brain FDG PET: A benchmark of 17 VAE-based approaches

R. Hassanaly, C. Brianceau, O. Colliot, N. Burgos

In Deep Generative Models workshop at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023)2023

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ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing

E. Thibeau-Sutre, M. Diaz, R. Hassanaly, O. Colliot, N. Burgos

In OHBM 2022 - Annual meeting of the Organization for Human Brain Mapping2022

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Advances in the Clinica software platform for clinical neuroimaging studies

O. Rifai, M. Diaz Melo, R. Hassanaly, M. Joulot, A. Routier, E. Thibeau-Sutre, G. Vaillant, S. Durrleman, N. Burgos, O. Colliot

In OHBM 2022 - Annual meeting of the Organization for Human Brain Mapping2022

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Clinica: an open-source software platform for reproducible clinical neuroscience studies

O. El-Rifai, M. Diaz Melo, R. Hassanaly, M. Joulot, A. Routier, E. Thibeau-Sutre, G. Vaillant, S. Durrleman, N. Burgos, O. Colliot

In MRI Together 2021 - A global workshop on Open Science and Reproducible MR Research2021

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New longitudinal and deep learning pipelines in the Clinica software platform

A. Routier, A. Marcoux, M. Diaz Melo, J. Samper-González, A. Wild, A. Guyot, J. Wen, E. Thibeau-Sutre, S. Bottani, S. Durrleman, N. Burgos, O. Colliot

In OHBM 2020 - Annual meeting of the Organization for Human Brain Mapping2020

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How serious is data leakage in deep learning studies on Alzheimer’s disease classification?

J. Wen, E. Thibeau-Sutre, J. Samper-Gonzalez, A. Routier, S. Bottani, D. Dormont, S. Durrleman, O. Colliot, N. Burgos

In Organization for Human Brain Mapping (OHBM)2019

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Beware of feature selection bias! Example on Alzheimer's disease classification from diffusion MRI

J. Wen, J. Samper-González, A. Routier, S. Bottani, S. Durrleman, N. Burgos, O. Colliot

In 2019 OHBM Annual Meeting - Organization for Human Brain Mapping2019

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New advances in the Clinica software platform for clinical neuroimaging studies

A. Routier, A. Marcoux, M. Diaz Melo, J. Guillon, J. Samper-González, J. Wen, S. Bottani, A. Guyot, E. Thibeau-Sutre, M. Teichmann, M.-O. Habert, S. Durrleman, N. Burgos, O. Colliot

In OHBM 2019 - Annual Meeting on Organization for Human Brain Mapping2019

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Prediction of future cognitive scores and dementia onset in Mild Cognitive Impairment patients

M. Ansart, N. Burgos, O. Colliot, D. Dormont, S. Durrleman

In OHBM 2019 - Organization for Human Brain Mapping Conference2019

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Predicting progression to Alzheimer’s disease from clinical and imaging data: a reproducible study

J. Samper-Gonzalez, N. Burgos, S. Bottani, M.-O. Habert, T. Evgeniou, S. Epelbaum, O. Colliot

In OHBM 2019 - Organization for Human Brain Mapping Annual Meeting 20192019

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How serious is data leakage in deep learning studies on Alzheimer's disease classification?

J. Wen, E. Thibeau--Sutre, J. Samper-González, A. Routier, S. Bottani, D. Dormont, S. Durrleman, O. Colliot, N. Burgos

In 2019 OHBM Annual meeting - Organization for Human Brain Mapping2019

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Deciphering the progression of PET alterations using surface-based spatiotemporal modeling

I. Koval, A. Marcoux, N. Burgos, S. Allassonnière, O. Colliot, S. Durrleman

In OHBM 2019 - Annual meeting of the Organization for Human Brain Mapping2019

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Comparison of DTI Features for the Classification of Alzheimer's Disease: A Reproducible Study

J. Wen, J. Samper-Gonzalez, S. Bottani, A. Routier, N. Burgos, T. Jacquemont, S. Fontanella, S. Durrleman, A. Bertrand, O. Colliot

In OHBM 2018 - Organization for Human Brain Mapping Annual Meeting2018

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Using diffusion MRI for classification and prediction of Alzheimer's Disease: a reproducible study

J. Wen, J. Samper-Gonzalez, S. Bottani, A. Routier, N. Burgos, T. Jacquemont, S. Fontanella, S. Durrleman, A. Bertrand, O. Colliot

In AAIC 2018 - Alzheimer's Association International Conference2018

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Three simple ideas for predicting progression to Alzheimer's disease

J. Samper-Gonzalez, N. Burgos, S. Bottani, M.-O. Habert, T. Evgeniou, S. Epelbaum, O. Colliot

In 8th International Workshop on Pattern Recognition in Neuroimaging2018

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Reproducible evaluation of Alzheimer's Disease classification from MRI and PET data

J. Samper-Gonzalez, S. Bottani, N. Burgos, S. Fontanella, P. Lu, A. Marcoux, A. Routier, J. Guillon, M. Bacci, J. Wen, A. Bertrand, H. Bertin, M.-O. Habert, S. Durrleman, T. Evgeniou, O. Colliot

In Annual meeting of the Organization for Human Brain Mapping - OHBM 20182018

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Clinica: an open source software platform for reproducible clinical neuroscience studies

A. Routier, J. Guillon, N. Burgos, J. Samper-Gonzalez, J. Wen, S. Fontanella, S. Bottani, T. Jacquemont, A. Marcoux, P. Gori, P. Lu, T. Moreau, M. Bacci, S. Durrleman, O. Colliot

In Annual meeting of the Organization for Human Brain Mapping - OHBM 20182018

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A pipeline for the analysis of 18F-FDG PET data on the cortical surface and its evaluation on ADNI

A. Marcoux, N. Burgos, A. Bertrand, A. Routier, J. Wen, J. Samper-Gonzalez, S. Bottani, S. Durrleman, M.-O. Habert, O. Colliot

In Annual meeting of the Organization for Human Brain Mapping - OHBM 20182018

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A comparison of techniques for quantifying amyloid burden on a combined PET/MR scanner

D.-M. Cash, N. Burgos, M. Modat, J. Dickson, D. Beasley, P. Markiewicz, C.-A. Lane, T. Parker, A. Barnes, D.-L. Thomas, J. Cardoso, I.-B. Malone, T. Veale, D. Wallon, J. Klimova, K. Erlandsson, A. Wong, M. Richards, N.-C. Fox, S. Ourselin, J.-M. Schott

In AAIC 2017 - Alzheimer's Association International Conference, pp. P12--P132017

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Geometric and Dosimetric Evaluation of Three Atlas-based Segmentation Methods for Head and Neck Cancer Patients on MR Images

J.-P. Kieselmann, C.-P. Kamerling, N. Burgos, M.-J. Menten, S. Nill, M.-J. Cardoso, U. Oelfke

In MR in RT symposium2017

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Midlife affective symptoms are associated with lower brain volumes in later life: Evidence from a prospective UK birth cohort

S.-N. James, T. Parker, C.-A. Lane, D.-M. Cash, A. Wong, A. Barnes, D. Beasley, N. Burgos, J. Cardoso, J. Dickson, J. Klimova, I.-B. Malone, M. Modat, D.-L. Thomas, D. Kuh, S. Ourselin, N.-C. Fox, J.-M. Schott, M. Richards

In AAIC 2017 - Alzheimer's Association International Conference, pp. P2122017

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Exploring the population prevalence of β-amyloid burden: An analysis of 250 individuals born in mainland Britain in the same week in 1946

J.-M. Schott, D.-M. Cash, C.-A. Lane, T. Parker, N. Burgos, M. Modat, D. Beasley, J. Dickson, A. Barnes, D.-L. Thomas, H. Murray-Smith, A. Wong, K. Macpherson, S.-N. James, J. Cardoso, I.-B. Malone, J. Klimova, P. Markiewicz, S.-J. Crutch, D. Kuh, S. Ourselin, M. Richards, N.-C. Fox

In AAIC 2017 - Alzheimer's Association International Conference, pp. P1088--P10892017

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Brain volume, cerebral β-amyloid deposition, and ageing: A study of over 200 individuals born in the same week in 1946

T. Parker, D.-M. Cash, C.-A. Lane, H. Murray-Smith, A. Wong, I.-B. Malone, N. Burgos, M. Modat, D. Beasley, J. Dickson, A. Barnes, D.-L. Thomas, J. Cardoso, J. Klimova, S. Ourselin, C. Frost, D. Kuh, M. Richards, N.-C. Fox, J.-M. Schott

In AAIC 2017 - Alzheimer's Association International Conference, pp. P1464--P14652017

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Diagnosis of Alzheimer’s Disease Through Identification of Abnormality Patterns in FDG PET Data

N. Burgos, J. Samper-González, A. Bertrand, M.-O. Habert, S. Ourselin, S. Durrleman, J. Cardoso, O. Colliot

In 30th Annual Congress of the European Association of Nuclear Medicine (EANM), pp. 253 - 2542017

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Early Diagnosis of Alzheimer’s Disease Using Subject-Specific Models of FDG-PET Data

N. Burgos, J. Samper-González, J. Cardoso, S. Durrleman, S. Ourselin, O. Colliot

In AAIC 2017 - Alzheimer's Association International Conference, pp. 1-22017

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CT synthesis in the head & neck and pelvic regions for radiotherapy treatment planning

N. Burgos, J. Cardoso, F. Guerreiro, J. Mcclelland, A.-C. Knopf, S. Punwani, S. Ourselin

In IPEM Workshop on MRI Guided Radiotherapy2016

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Simultaneous organ-at-risk segmentation and CT synthesis in the pelvic region for MRI-only radiotherapy treatment planning

N. Burgos, J. Cardoso, F. Guerreiro, J. Mcclelland, A.-C. Knopf, S. Ourselin

In International Conference on the use of Computers in Radiation Therapy – ICCR 20162016

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A multi-method, multi-center study of PET/MRI brain attenuation correction on a large cohort of [18F]- FDG patients: ready for clinical implementation

C.-N. Ladefoged, I. Law, U. Anazodo, D. Izquierdo-Garcia, N. Burgos, I. Mérida, D. Benoit, M. Juttukonda, J. Cabello, M. Fenchel, B. Jakoby, L. Højgaard, A.-E. Hansen, F.-L. Andersen

In RSNA 216 – Annual Meeting of the Radiological Society of North America2016

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Multi atlas-based attenuation correction for brain FDG- PET imaging using a TOF-PET/MR scanner: Comparison with clinical single atlas- and CT-based attenuation correction

T. Sekine, N. Burgos, G. Warnock, M. Huellner, A. Buck, E.-E.-G.-W.-T. Voert, J. Cardoso, B.-F. Hutton, S. Ourselin, P. Veit-Haibach, G. Delso

In Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine – ISMRM 20162016

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A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients

C.-N. Ladefoged, I. Law, U. Anazodo, K. St. Lawrence, D. Izquierdo-Garcia, C. Catana, N. Burgos, J. Cardoso, B. Hutton, S. Ourselin, I. Mérida, N. Costes, A. Hammers, D. Benoit, S. Holm, M. Juttukonda, H. An, J. Cabello, M. Lukas, S. Nekolla, S. Ziegler, M. Fenchel, B. Jakoby, M.-E. Casey, T. Benzinger, L. Højgaard, A.-E. Hansen, F.-L. Andersen

In IEEE Nuclear Science Symposium and Medical Imaging Conference – IEEE NSS/MIC 20162016

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NiftyWeb: web based platform for image processing on the cloud

F. Prados Carrasco, M.-J. Cardoso, N. Burgos, C.-A.-M. Wheeler-Kingshott, S. Ourselin

In Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine – ISMRM 20162016

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CT synthesis in the head & neck region for PET/MR attenuation correction: an iterative multi-atlas approach

N. Burgos, J. Cardoso, M. Modat, S. Punwani, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

In Conference on PET/MR and SPECT/MR – PSMR 2015, pp. A312015

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Establishment of an open database of realistic simulated data for evaluation of partial volume correction techniques in brain PET/MR

A. Mota, V. Cuplov, J. Schott, B. Hutton, K. Thielemans, I. Drobnjak, J. Dickson, J. Bert, N. Burgos, J. Cardoso, M. Modat, S. Ourselin, K. Erlandsson

In Conference on PET/MR and SPECT/MR – PSMR 2015, pp. A442015

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Evaluation of different approaches to obtain synthetic CT images for a MRI-only radiotherapy workflow

F. Guerreiro, J. Mcclelland, N. Burgos, M.-J. Cardoso, A. Dunlop, K. Wong, S. Nill, U. Oelfke, A.-C. Knopf

In MR in RT symposium2015

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Partial Volume Correction of Amyvid and FDG PET data using the discrete iterative Yang technique

J.-C. Dickson, K. Erlandsson, M. Lehmann, M. Modat, N. Burgos, A. Groves, J. Schott

In Annual Congress of the European Association of Nuclear Medicine – EANM 2015, pp. S69, Springer2015

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Attenuation correction synthesis for hybrid PET-MR scanners: validation for brain study applications

N. Burgos, J. Cardoso, K. Thielemans, J.-S. Duncan, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

In Conference on PET/MR and SPECT/MR – PSMR 2014, pp. A522014

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Image reconstruction of mMR PET data using the open source software STIR

P. Markiewicz, K. Thielemans, N. Burgos, R. Manber, J. Jiao, A. Barnes, D. Atkinson, S.-R. Arridge, B.-F. Hutton, S. Ourselin

In Conference on PET/MR and SPECT/MR – PSMR 2014, pp. A442014

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National conference abstracts 13 documents