Ninon Burgos

131
Documents
Affiliations actuelles
  • Algorithms, models and methods for images and signals of the human brain = Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain [ICM Paris] (ARAMIS)
  • Institut du Cerveau = Paris Brain Institute (ICM)
Identifiants chercheurs

Présentation

Publications

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Publications

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

T. Soulier , Ninon Burgos , Ravi Hassanaly , M. Pitombeira , Maëlys Solal et al.

Revue Neurologique, 2025, 181 (9), pp.944-950. ⟨10.1016/j.neurol.2025.07.011⟩

Article dans une revue hal-05378338v1
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Benchmarking 3D generative autoencoders for pseudo-healthy reconstruction of brain 18F-fluorodeoxyglucose positron emission tomography

Ravi Hassanaly , Maëlys Solal , Olivier Colliot , Ninon Burgos

Journal of Medical Imaging, 2025, 12 (5), pp.054005. ⟨10.1117/1.JMI.12.5.054005⟩

Article dans une revue hal-04445378v2
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Automatic quality control of brain 3D FLAIR MRIs for a clinical data warehouse

Sophie Loizillon , Simona Bottani , Aurélien Maire , Sebastian Ströer , Lydia Chougar et al.

Medical Image Analysis, 2025, 103, pp.103617. ⟨10.1016/j.media.2025.103617⟩

Article dans une revue hal-05059257v1
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Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI

Simona Bottani , Elina Thibeau-Sutre , Aurélien Maire , Sebastian Ströer , Didier Dormont et al.

BMC Medical Imaging, 2024, 24 (1), pp.67. ⟨10.1186/s12880-024-01242-3⟩

Article dans une revue hal-03497645v2
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Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data

Sophie Loizillon , Simona Bottani , Aurélien Maire , Sebastian Ströer , Didier Dormont et al.

Medical Image Analysis, 2024, 93, pp.103073. ⟨10.1016/j.media.2023.103073⟩

Article dans une revue hal-03910451v2
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Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET

Ravi Hassanaly , Camille Brianceau , Maëlys Solal , Olivier Colliot , Ninon Burgos

Journal of Machine Learning for Biomedical Imaging, 2024, Special Issue for Generative Models, 2, pp.611. ⟨10.59275/j.melba.2024-b87a⟩

Article dans une revue hal-04315738v2
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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

Sophie Loizillon , Simona Bottani , Stéphane Mabille , Yannick Jacob , Aurélien Maire et al.

Journal of Machine Learning for Biomedical Imaging, 2024, 2 (June 2024), pp.888-915. ⟨10.59275/j.melba.2024-7fgd⟩

Article dans une revue hal-04623223v1
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Evaluation of MRI-based machine learning approaches for computer-aided diagnosis of dementia in a clinical data warehouse

Simona Bottani , Ninon Burgos , Aurélien Maire , Dario Saracino , Sebastian Stroër et al.

Medical Image Analysis, 2023, 89, pp.102903. ⟨10.1016/j.media.2023.102903⟩

Article dans une revue hal-03656136v2
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Operationalizing the centiloid scale for [18 F]florbetapir PET studies on PET/MRI

William Coath , Marc Modat , M. Jorge Cardoso , Pawel Markiewicz , Christopher Lane et al.

Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 2023, 15 (2), ⟨10.1002/dad2.12434⟩

Article dans une revue hal-04099627v1
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Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder

Clément Chadebec , Elina Thibeau-Sutre , Ninon Burgos , Stéphanie Allassonnière

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, ⟨10.1109/TPAMI.2022.3185773⟩

Article dans une revue hal-03214093v1
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ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing

Elina Thibeau-Sutre , Mauricio Diaz , Ravi Hassanaly , Alexandre M Routier , Didier Dormont et al.

Computer Methods and Programs in Biomedicine, 2022, 220, pp.106818. ⟨10.1016/j.cmpb.2022.106818⟩

Article dans une revue hal-03351976v2
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Pilot Study of Repeated Blood-Brain Barrier Disruption in Patients with Mild Alzheimer's Disease with an Implantable Ultrasound Device

Stephane Epelbaum , Ninon Burgos , Michael Canney , Dawn Matthews , Marion Houot et al.

Alzheimer's Research and Therapy, 2022, 14 (40), ⟨10.1186/s13195-022-00981-1⟩

Article dans une revue hal-03484130v1
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Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse

Simona Bottani , Ninon Burgos , Aurélien Maire , Adam Wild , Sébastian Ströer et al.

Medical Image Analysis, 2022, 75, ⟨10.1016/j.media.2021.102219⟩

Article dans une revue hal-03154792v4
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Anomaly detection for the individual analysis of brain PET images

Ninon Burgos , Jorge M. Cardoso , Jorge Samper-González , Marie-Odile Habert , Stanley Durrleman​ et al.

Journal of Medical Imaging, 2021, 8 (02), pp.024003. ⟨10.1117/1.JMI.8.2.024003⟩

Article dans une revue hal-03193306v1
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Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer's disease

Junhao Wen , Jorge Samper-González , Simona Bottani , Alexandre Routier , Ninon Burgos et al.

Neuroinformatics, 2021, 19 (1), pp.57-78. ⟨10.1007/s12021-020-09469-5⟩

Article dans une revue hal-02566361v2
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Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic, Quantitative and Critical Review

Manon Ansart , Stéphane Epelbaum , Giulia Bassignana , Alexandre Bône , Simona Bottani et al.

Medical Image Analysis, 2021, 67, pp.101848. ⟨10.1016/j.media.2020.101848⟩

Article dans une revue hal-02337815v2
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Clinica: an open source software platform for reproducible clinical neuroscience studies

Alexandre Routier , Ninon Burgos , Mauricio Diaz , Michael Bacci , Simona Bottani et al.

Frontiers in Neuroinformatics, 2021, 15, pp.689675. ⟨10.3389/fninf.2021.689675⟩

Article dans une revue hal-02308126v4
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AD Course Map charts Alzheimer’s disease progression

Igor Koval , Alexandre Bône , Maxime Louis , Thomas Lartigue , Simona Bottani et al.

Scientific Reports, 2021, 11 (1), ⟨10.1038/s41598-021-87434-1⟩

Article dans une revue hal-01964821v3
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Deep learning for brain disorders: from data processing to disease treatment

Ninon Burgos , Simona Bottani , Johann Faouzi , Elina Thibeau-Sutre , Olivier Colliot

Briefings in Bioinformatics, 2021, 22 (2), pp.1560-1576. ⟨10.1093/bib/bbaa310⟩

Article dans une revue hal-03070554v1
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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

Baptiste Couvy-Duchesne , Johann Faouzi , Benoît Martin , Elina Thibeau-Sutre , Adam Wild et al.

Frontiers in Psychiatry, 2020, 11, ⟨10.3389/fpsyt.2020.593336⟩

Article dans une revue hal-03136463v1
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Machine learning for classification and prediction of brain diseases: recent advances and upcoming challenges

Ninon Burgos , Olivier Colliot

Current Opinion in Neurology, 2020, 33 (4), pp.439-450. ⟨10.1097/WCO.0000000000000838⟩

Article dans une revue hal-02902586v1
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Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation

Junhao Wen , Elina Thibeau-Sutre , Mauricio Diaz-Melo , Jorge Samper-González , Alexandre Routier et al.

Medical Image Analysis, 2020, 63, pp.101694. ⟨10.1016/j.media.2020.101694⟩

Article dans une revue hal-02562504v2
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Tribute to Anne Bertrand (1978–2018): Neuroradiologist, scientist, teacher and friend

Didier Dormont , Noam Ben-Eliezer , Ninon Burgos , Olivier Colliot , Fabrizio de Vico Fallani et al.

Journal de Neuroradiologie / Journal of Neuroradiology, 2019, 46 (2), pp.155-159. ⟨10.1016/j.neurad.2019.01.001⟩

Article dans une revue hal-02265305v1
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Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

Jorge Samper-González , Ninon Burgos , Simona Bottani , Sabrina Fontanella , Pascal Lu et al.

NeuroImage, 2018, 183, pp.504-521. ⟨10.1016/j.neuroimage.2018.08.042⟩

Article dans une revue hal-01858384v2
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Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region

Jennifer Petra Kieselmann , Cornelis Philippus Kamerling , Ninon Burgos , Martin J. Menten , Clifton David Fuller et al.

Physics in Medicine and Biology, 2018, 63 (14), ⟨10.1088/1361-6560/aacb65⟩

Article dans une revue hal-01827187v1
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Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region

Hossein Arabi , Jason Dowling , Ninon Burgos , Xiao Han , Peter Greer et al.

Medical Physics : The international journal of medical physics research and practice, 2018, ⟨10.1002/mp.13187⟩

Article dans une revue hal-01890646v1
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An Automated Pipeline for the Analysis of PET Data on the Cortical Surface

Arnaud Marcoux , Ninon Burgos , Anne Bertrand , Marc Teichmann , Alexandre Routier et al.

Frontiers in Neuroinformatics, 2018, 12, ⟨10.3389/fninf.2018.00094⟩

Article dans une revue hal-01950933v1
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Reduced acquisition time PET pharmacokinetic modelling using simultaneous ASL–MRI: proof of concept

Catherine Scott , Jieqing Jiao , Andrew Melbourne , Ninon Burgos , David Cash et al.

Journal of Cerebral Blood Flow and Metabolism, 2018, ⟨10.1177/0271678X18797343⟩

Article dans une revue hal-01871983v1

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

F. Guerreiro , Ninon Burgos , A. Dunlop , K. Wong , I. Petkar et al.

Physica Medica European Journal of Medical Physics, 2017, 35, pp.7--17. ⟨10.1016/j.ejmp.2017.02.017⟩

Article dans une revue hal-01827195v1

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

Claes N. Ladefoged , Ian Law , Udunna Anazodo , Keith St. Lawrence , David Izquierdo-Garcia et al.

NeuroImage, 2017, 147, pp.346--359. ⟨10.1016/j.neuroimage.2016.12.010⟩

Article dans une revue hal-01827196v1

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

Christopher A. Lane , Thomas D. Parker , Dave M. Cash , Kirsty Macpherson , Elizabeth Donnachie et al.

BMC Neurology, 2017, 17, pp.75. ⟨10.1186/s12883-017-0846-x⟩

Article dans une revue hal-01827191v1

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

J. Jiao , A. Bousse , K. Thielemans , Ninon Burgos , P. S. J. Weston et al.

IEEE Transactions on Medical Imaging, 2017, 36 (1), pp.203--213. ⟨10.1109/TMI.2016.2594150⟩

Article dans une revue hal-01827197v1

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

Ninon Burgos , Filipa Guerreiro , M Mcclelland , Benoît Presles , M Modat et al.

Physics in Medicine and Biology, 2017, 62 (11), pp.4237 - 4253. ⟨10.1088/1361-6560/aa66bf⟩

Article dans une revue hal-01556656v1

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

Tetsuro Sekine , Ninon Burgos , Geoffrey Warnock , Martin Huellner , Alfred Buck et al.

Journal of Nuclear Medicine, 2016, 57 (8), pp.1258--1264. ⟨10.2967/jnumed.115.169045⟩

Article dans une revue hal-01827202v1

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

Maria A. Zuluaga , Ninon Burgos , Alex F. Mendelson , Andrew M. Taylor , Sébastien Ourselin

Medical Image Analysis, 2015, 26 (1), pp.185--194. ⟨10.1016/j.media.2015.09.001⟩

Article dans une revue hal-01827215v1

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

Ninon Burgos , Jorge M. Cardoso , Kris Thielemans , Marc Modat , John Dickson et al.

European Journal of Nuclear Medicine and Molecular Imaging, 2015, 42 (9), pp.1447--1458. ⟨10.1007/s00259-015-3082-x⟩

Article dans une revue hal-01827213v1

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

Philip S. J. Weston , Ross W. Paterson , Marc Modat , Ninon Burgos , Manuel J. Cardoso et al.

Alzheimer's & Dementia : the Journal of the Alzheimer's Association, 2015, 1 (4), pp.440--446. ⟨10.1016/j.dadm.2015.10.001⟩

Article dans une revue hal-01827214v1

Simulated field maps for susceptibility artefact correction in interventional MRI

Martin Kochan , Pankaj Daga , Ninon Burgos , Mark White , Jorge M. Cardoso et al.

International Journal of Computer Assisted Radiology and Surgery, 2015, 10 (9), pp.1405--1416. ⟨10.1007/s11548-015-1253-7⟩

Article dans une revue hal-01827211v1

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

Ninon Burgos , M. J. Cardoso , K. Thielemans , M. Modat , S. Pedemonte et al.

IEEE Transactions on Medical Imaging, 2014, 33 (12), pp.2332--2341. ⟨10.1109/TMI.2014.2340135⟩

Article dans une revue hal-01827217v1
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Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection

Agathe Senellart , Maëlys Solal , Stéphanie Allassonnière , Ninon Burgos

ISBI 2026 - International Symposium on Biomedical Imaging, Apr 2026, London, United Kingdom

Communication dans un congrès hal-05423947v2
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Unsupervised anomaly detection using Bayesian flow networks: application to brain FDG pet in the context of Alzheimer’s disease

Hugues Roy , Reuben Dorent , Ninon Burgos

DGM4MICCAI 2025 - Deep Generative Models, Sep 2025, Daejong, South Korea. pp.254-264, ⟨10.1007/978-3-032-05472-2_25⟩

Communication dans un congrès hal-05322316v1
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Comparing Longitudinal Preprocessing Pipelines for Brain Volume Consistency in T1-Weighted MRI Test-Retest Scans

Matthieu Joulot , Olivier Colliot , Ninon Burgos

SPIE Medical Imaging 2026, Feb 2026, Vancouver, Canada

Communication dans un congrès hal-05349492v1
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Étude de la qualité des IRM T1 et FLAIR de routine clinique au sein d'un entrepôt de données de santé de l'AP-HP

Manon Heffernan , Sophie Loizillon , Olivier Colliot , Ninon Burgos

IABM 2026 - Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale, Mar 2026, Lyon, France

Communication dans un congrès hal-05483191v1
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Assessing the Efficacy of Artefact Synthesis and Transfer Learning for Quality Control in Clinical 3D FLAIR Brain MRI

Manon Heffernan , Sophie Loizillon , Sebastian Ströer , Lydia Chougar , Didier Dormont et al.

SPIE Medical Imaging 2026, Feb 2026, Vancouver, Canada

Communication dans un congrès hal-05444176v2
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Unsupervised anomaly detection in brain FDG PET with deep generative models: An experimental analysis of model variability and mitigation strategies

Maëlys Solal , Pascaline André , Ninon Burgos

SPIE Medical Imaging 2026, Feb 2026, Vancouver, Canada

Communication dans un congrès hal-05340039v2
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Simulation d'artefacts pour le contrôle automatique de la qualité d'IRM cérébrales FLAIR en routine clinique

Manon Heffernan , Sophie Loizillon , Yannick Jacob , Aurélien Maire , Lydia Chougar et al.

Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale (IABM 2025), Mar 2025, Nice, France

Communication dans un congrès hal-05088701v1
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Exploitation de la variabilité de la population contrôle pour la détection d'anomalies non supervisée par apprentissage profond en imagerie cérébrale FDG PET

Maëlys Solal , Ravi Hassanaly , Ninon Burgos

IABM 2024 - Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale, Mar 2024, Grenoble, France

Communication dans un congrès hal-05443392v1
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Clinica, an open-source software to facilitate neuroimaging studies

Matthieu Joulot , Nicolas Gensollen , Ghislain Vaillant , Ninon Burgos , Olivier Colliot

Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale (IABM), Mar 2024, Grenoble, France

Communication dans un congrès hal-04653352v1
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Leveraging noise and contrast simulation for the automatic quality control of routine clinical T1-weighted brain MRI

Sophie Loizillon , Stéphane Mabille , Simona Bottani , Yannick Jacob , Aurélien Maire et al.

SPIE Medical Imaging 2024: Image Processing, Feb 2024, San Diego (CA), United States. ⟨10.1117/12.3005781⟩

Communication dans un congrès hal-04674029v1
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Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET

Maëlys Solal , Ravi Hassanaly , Ninon Burgos

SPIE Medical Imaging, Feb 2024, San Diego, United States. ⟨10.1117/12.2691683⟩

Communication dans un congrès hal-04291561v2
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Evaluation of pseudo-healthy reconstruction for anomaly detection in brain FDG PET

Ravi Hassanaly , Camille Brianceau , Maëlys Solal , Olivier Colliot , Ninon Burgos

MIDL 2024 - Medical Imaging with Deep Learning, Jul 2024, Paris, France

Communication dans un congrès hal-05444841v1
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Confidence intervals uncovered: Are we ready for real-world medical imaging AI?

Evangelia Christodoulou , Annika Reinke , Rola Houhou , Piotr Kalinowski , Selen Erkan et al.

MICCAI 2024 - 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2024, Marrakech, Morocco. pp.124-132, ⟨10.1007/978-3-031-72117-5_12⟩

Communication dans un congrès hal-04715638v1
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The intriguing effect of frequency disentangled learning on medical image segmentation

Guanghui Fu , Gabriel Jiménez , Sophie Loizillon , Lydia Chougar , Didier Dormont et al.

Medical Imaging 2024, Feb 2024, San Diego, CA, United States. pp.49, ⟨10.1117/12.2692286⟩

Communication dans un congrès hal-04654627v1
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Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networks

Théodore Soulier , Mariem Hamzaoui , Milena Sales Pitombeira , Daniele De Paula Faria , Arya Yazdan-Panah et al.

SPIE Medical Imaging, Feb 2024, San Diego, United States. ⟨10.1117/12.3004975⟩

Communication dans un congrès hal-04362506v1
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Detecting Brain Anomalies in Clinical Routine with the β-VAE: Feasibility Study on Age-Related White Matter Hyperintensities

Sophie Loizillon , Yannick Jacob , Aurelien Maire , Didier Dormont , Olivier Colliot et al.

Medical Imaging with Deep Learning - MIDL 2024, Jul 2024, Paris, France

Communication dans un congrès hal-04674025v1
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Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learning

Ravi Hassanaly , Camille Brianceau , Mauricio Diaz , Sophie Loizillon , Elina Thibeau-Sutre et al.

SPIE Medical Imaging, Feb 2024, San Diego, United States. pp.519-524, ⟨10.1117/12.3006039⟩

Communication dans un congrès hal-04419141v1
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From Nipype to Pydra: a Clinica story

Ghislain Vaillant , Nicolas Gensollen , Matthieu Joulot , Omar El-Rifai , Mauricio Diaz et al.

OHBM 2023 - Annual meeting of the Organization for Human Brain Mapping, Jul 2023, Montreal, Canada

Communication dans un congrès hal-04278898v1
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Unsupervised anomaly detection in 3D brain FDG PET: A benchmark of 17 VAE-based approaches

Ravi Hassanaly , Camille Brianceau , Olivier Colliot , Ninon Burgos

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

Communication dans un congrès hal-04185304v1
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Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse

Sophie Loizillon , Olivier Colliot , Lydia Chougar , Sebastian Stroer , Yannick Jacob et al.

DART 2023 - 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, Oct 2023, Vancouver (BC), Canada. pp.84-93, ⟨10.1007/978-3-031-45857-6_9⟩

Communication dans un congrès hal-04273997v1
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A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation

Francesco Galati , Daniele Falcetta , Rosa Cortese , Barbara Casolla , Ferran Prados et al.

BMVC 2023, 34th British Machine Vision Conference, Nov 2023, Aberdeen, United Kingdom

Communication dans un congrès hal-04195756v2
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How can data augmentation improve attribution maps for disease subtype explainability?

Elina Thibeau-Sutre , Jelmer M Wolterink , Olivier Colliot , Ninon Burgos

SPIE Medical Imaging, Feb 2023, San Diego, United States

Communication dans un congrès hal-03966737v1
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Simulation-based evaluation framework for deep learning unsupervised anomaly detection on brain FDG PET

Ravi Hassanaly , Simona Bottani , Benoît Sauty , Olivier Colliot , Ninon Burgos

SPIE Medical Imaging, Feb 2023, San Diego, United States

Communication dans un congrès hal-03835015v2
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Transfer learning from synthetic to routine clinical data for motion artefact detection in brain T1-weighted MRI

Sophie Loizillon , Simona Bottani , Aurélien Maire , Sebastian Stroer , Didier Dormont et al.

SPIE Medical Imaging 2023: Image Processing, Feb 2023, San Diego, United States

Communication dans un congrès hal-03831746v2
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Advances in the Clinica software platform for clinical neuroimaging studies

Omar El Rifai , Mauricio Diaz Melo , Ravi Hassanaly , Matthieu Joulot , Alexandre M Routier et al.

OHBM 2022 - Annual meeting of the Organization for Human Brain Mapping, Jun 2022, Glasgow, United Kingdom

Communication dans un congrès hal-03728243v1
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ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing

Elina Thibeau-Sutre , Mauricio Diaz , Ravi Hassanaly , Olivier Colliot , Ninon Burgos

OHBM 2022 - Annual meeting of the Organization for Human Brain Mapping, Jun 2022, Glasgow, United Kingdom

Communication dans un congrès hal-04279014v1
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MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data set

Elina Thibeau-Sutre , Baptiste Couvy-Duchesne , Didier Dormont , Olivier Colliot , Ninon Burgos

ISBI 2022 - International Symposium on Biomedical Imaging, Mar 2022, Kolkata, India. ⟨10.1109/ISBI52829.2022.9761504⟩

Communication dans un congrès hal-03542213v1
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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

Simona Bottani , Elina Thibeau-Sutre , Aurélien Maire , Sebastian Ströer , Didier Dormont et al.

SPIE Medical Imaging 2022: Image Processing, Feb 2022, San Diego, United States. pp.576-582, ⟨10.1117/12.2608565⟩

Communication dans un congrès hal-03478798v1
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Clinica: an open-source software platform for reproducible clinical neuroscience studies

Omar El-Rifai , Mauricio Diaz Melo , Ravi Hassanaly , Matthieu Joulot , Alexandre M Routier et al.

MRI Together 2021 - A global workshop on Open Science and Reproducible MR Research, Dec 2021, Online, France

Communication dans un congrès hal-03513920v1
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New longitudinal and deep learning pipelines in the Clinica software platform

Alexandre Routier , Arnaud Marcoux , Mauricio Diaz Melo , Jorge Samper-González , Adam Wild et al.

OHBM 2020 - Annual meeting of the Organization for Human Brain Mapping, Jun 2020, Montreal / Virtual, Canada

Communication dans un congrès hal-02549242v1
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Visualization approach to assess the robustness of neural networks for medical image classification

Elina Thibeau-Sutre , Olivier Colliot , Didier Dormont , Ninon Burgos

SPIE Medical Imaging 2020, Feb 2020, Houston, United States. ⟨10.1117/12.2548952⟩

Communication dans un congrès hal-02370532v3
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How serious is data leakage in deep learning studies on Alzheimer’s disease classification?

Junhao Wen , Elina Thibeau-Sutre , Jorge Samper-Gonzalez , Alexandre M Routier , Simona Bottani et al.

Organization for Human Brain Mapping (OHBM), Jun 2019, Roma, Italy

Communication dans un congrès hal-03365742v1
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Deciphering the progression of PET alterations using surface-based spatiotemporal modeling

Igor Koval , Arnaud Marcoux , Ninon Burgos , Stéphanie Allassonnière , Olivier Colliot et al.

OHBM 2019 - Annual meeting of the Organization for Human Brain Mapping, Jun 2019, Rome, Italy

Communication dans un congrès hal-02134909v1
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Beware of feature selection bias! Example on Alzheimer's disease classification from diffusion MRI

Junhao Wen​ , Jorge Samper-González​ , Alexandre M Routier , Simona Bottani​ , Stanley Durrleman​ et al.

2019 OHBM Annual Meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy

Communication dans un congrès hal-02105134v2
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How serious is data leakage in deep learning studies on Alzheimer's disease classification?

Junhao Wen​ , Elina Thibeau--Sutre​ , Jorge Samper-González​ , Alexandre M Routier , Simona Bottani​ et al.

2019 OHBM Annual meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy

Communication dans un congrès hal-02105133v2
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New advances in the Clinica software platform for clinical neuroimaging studies

Alexandre Routier , Arnaud Marcoux , Mauricio Diaz Melo , Jérémy Guillon , Jorge Samper-González et al.

OHBM 2019 - Annual Meeting on Organization for Human Brain Mapping, Jun 2019, Roma, Italy. ⟨10.1016/j.neuroimage.2011.09.015⟩

Communication dans un congrès hal-02132147v2
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Predicting progression to Alzheimer’s disease from clinical and imaging data: a reproducible study

Jorge Samper-Gonzalez , Ninon Burgos , Simona Bottani , Marie-Odile Habert , Theodoros Evgeniou et al.

OHBM 2019 - Organization for Human Brain Mapping Annual Meeting 2019, Jun 2019, Rome, Italy

Communication dans un congrès hal-02142315v1
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Prediction of future cognitive scores and dementia onset in Mild Cognitive Impairment patients

Manon Ansart , Ninon Burgos , Olivier Colliot , Didier Dormont , Stanley Durrleman

OHBM 2019 - Organization for Human Brain Mapping Conference, Jun 2019, Rome, Italy

Communication dans un congrès hal-02098427v2
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Reproducible evaluation of methods for predicting progression to Alzheimer's disease from clinical and neuroimaging data

Jorge Samper-Gonzalez , Ninon Burgos , Simona Bottani , Marie-Odile Habert , Theodoros Evgeniou et al.

SPIE Medical Imaging 2019, Feb 2019, San Diego, United States. ⟨10.1117/12.2512430⟩

Communication dans un congrès hal-02025880v2
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Three simple ideas for predicting progression to Alzheimer's disease

Jorge Samper-Gonzalez , Ninon Burgos , Simona Bottani , Marie-Odile Habert , Theodoros Evgeniou et al.

8th International Workshop on Pattern Recognition in Neuroimaging, Jun 2018, Singapour, Singapore

Communication dans un congrès hal-01891996v1
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Clinica: an open source software platform for reproducible clinical neuroscience studies

Alexandre Routier , Jérémy Guillon , Ninon Burgos , Jorge Samper-Gonzalez , Junhao Wen et al.

Annual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapore, Singapore

Communication dans un congrès hal-01760658v1
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Reproducible evaluation of Alzheimer's Disease classification from MRI and PET data

Jorge Samper-Gonzalez , Simona Bottani , Ninon Burgos , Sabrina Fontanella , Pascal Lu et al.

Annual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore

Communication dans un congrès hal-01761666v1
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Using diffusion MRI for classification and prediction of Alzheimer's Disease: a reproducible study

Junhao Wen , Jorge Samper-Gonzalez , Simona Bottani , Alexandre Routier , Ninon Burgos et al.

AAIC 2018 - Alzheimer's Association International Conference, Jul 2018, Chicago, United States

Communication dans un congrès hal-01758167v2
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Comparison of DTI Features for the Classification of Alzheimer's Disease: A Reproducible Study

Junhao Wen , Jorge Samper-Gonzalez , Simona Bottani , Alexandre Routier , Ninon Burgos et al.

OHBM 2018 - Organization for Human Brain Mapping Annual Meeting, Jun 2018, Singapour, Singapore

Communication dans un congrès hal-01758206v3
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A pipeline for the analysis of 18F-FDG PET data on the cortical surface and its evaluation on ADNI

Arnaud Marcoux , Ninon Burgos , Anne Bertrand , Alexandre Routier , Junhao Wen et al.

Annual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore

Communication dans un congrès hal-01757646v1

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

David M. Cash , Ninon Burgos , Marc Modat , John Dickson , Daniel Beasley et al.

AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P12--P13, ⟨10.1016/j.jalz.2017.06.2276⟩

Communication dans un congrès hal-01827194v1

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

Sarah-Naomi James , Thomas Parker , Christopher A. Lane , David M. Cash , Andrew Wong et al.

AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P212, ⟨10.1016/j.jalz.2017.07.086⟩

Communication dans un congrès hal-01827192v1
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Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns

Ninon Burgos , Jorge Samper-González , Anne Bertrand , Marie-Odile Habert , Sébastien Ourselin et al.

Computational Methods for Molecular Imaging - [MICCAI 2017 Satellite Workshop], Sep 2017, Quebec City, Canada

Communication dans un congrès hal-01567343v1

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

Catherine J. Scott , Jieqing Jiao , Jorge M. Cardoso , Andrew Melbourne , Enrico de Vita et al.

Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017, 2017, Québec, Canada. pp.737--744, ⟨10.1007/978-3-319-66185-8_83⟩

Communication dans un congrès hal-01827190v1

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

Thomas Parker , David M. Cash , Christopher A. Lane , Heidi Murray-Smith , Andrew Wong et al.

AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P1464--P1465, ⟨10.1016/j.jalz.2017.07.534⟩

Communication dans un congrès istex hal-01827188v1

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 , Ninon Burgos , M. J. Menten , S. Nill et al.

MR in RT symposium, Jun 2017, Sydney, Australia

Communication dans un congrès hal-01827193v1

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

Jonathan M. Schott , David M. Cash , Christopher A. Lane , Thomas Parker , Ninon Burgos et al.

AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P1088--P1089, ⟨10.1016/j.jalz.2017.06.1563⟩

Communication dans un congrès hal-01827189v1
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Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease

Jorge Samper-Gonzalez , Ninon Burgos , Sabrina Fontanella , Hugo Bertin , Marie-Odile Habert et al.

Machine Learning in Medical Imaging 2017, Sep 2017, Quebec City, Canada. pp.8

Communication dans un congrès hal-01578479v1
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Early Diagnosis of Alzheimer’s Disease Using Subject-Specific Models of FDG-PET Data

Ninon Burgos , Jorge Samper-González , Jorge M. Cardoso , Stanley Durrleman , Sébastien Ourselin et al.

AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.1-2, ⟨10.1016/j.jalz.2017.06.1618⟩

Communication dans un congrès hal-01621383v1
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Diagnosis of Alzheimer’s Disease Through Identification of Abnormality Patterns in FDG PET Data

Ninon Burgos , Jorge Samper-González , Anne Bertrand , Marie-Odile Habert , Sébastien Ourselin et al.

30th Annual Congress of the European Association of Nuclear Medicine (EANM), Oct 2017, Vienna, Austria. pp.253 - 254, ⟨10.1007/s00259-017-3822-1⟩

Communication dans un congrès hal-01632509v1

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

Tetsuro Sekine , Ninon Burgos , Geoffrey Warnock , Martin Huellner , Alfred Buck et al.

Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine – ISMRM 2016, May 2016, Singapore, Singapore

Communication dans un congrès hal-01827200v1

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

Ninon Burgos , Jorge M. Cardoso , Filipa Guerreiro , Jamie Mcclelland , Antje-Christin Knopf et al.

International Conference on the use of Computers in Radiation Therapy – ICCR 2016, Jun 2016, London, United Kingdom

Communication dans un congrès hal-01827204v1

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

Claes N. Ladefoged , Ian Law , Udunna Anazodo , Keith St. Lawrence , David Izquierdo-Garcia et al.

IEEE Nuclear Science Symposium and Medical Imaging Conference – IEEE NSS/MIC 2016, Oct 2016, Strasbourg, France

Communication dans un congrès hal-01827199v1

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

Ninon Burgos , Filipa Guerreiro , Jamie Mcclelland , Simeon Nill , David Dearnaley et al.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Oct 2016, Athens, Greece. pp.547--555, ⟨10.1007/978-3-319-46723-8_63⟩

Communication dans un congrès hal-01827201v1

NiftyWeb: web based platform for image processing on the cloud

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

Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine – ISMRM 2016, May 2016, Singapore, Singapore

Communication dans un congrès hal-01827198v1

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

Claes N. Ladefoged , Ian Law , Udunna Anazodo , David Izquierdo-Garcia , Ninon Burgos et al.

RSNA 216 – Annual Meeting of the Radiological Society of North America, Nov 2016, Chicago, United States

Communication dans un congrès hal-01827203v1

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

Ninon Burgos , Jorge M. Cardoso , Filipa Guerreiro , Jamie Mcclelland , Antje-Christin Knopf et al.

IPEM Workshop on MRI Guided Radiotherapy, Mar 2016, Sheffield, United Kingdom

Communication dans un congrès hal-01827224v1

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

J. C. Dickson , K. Erlandsson , M. Lehmann , M. Modat , Ninon Burgos et al.

Annual Congress of the European Association of Nuclear Medicine – EANM 2015, Oct 2015, Hamburg, Germany. pp.S69, ⟨10.1007/s00259-015-3198-z⟩

Communication dans un congrès hal-01827205v1

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

Ninon Burgos , Jorge M. Cardoso , Marc Modat , Shonit Punwani , David Atkinson et al.

Conference on PET/MR and SPECT/MR – PSMR 2015, May 2015, Elba, Italy. pp.A31, ⟨10.1186/2197-7364-2-S1-A31⟩

Communication dans un congrès hal-01827212v1
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Multi-atlas synthesis for computer assisted diagnosis: Application to cardiovascular diseases

M. A. Zuluaga , Ninon Burgos , A. M. Taylor , S. Ourselin

IEEE International Symposium on Biomedical Imaging – IEEE ISBI 2015, Apr 2015, New-York, United States. pp.290--293, ⟨10.1109/ISBI.2015.7163870⟩

Communication dans un congrès hal-01827216v1

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

Jieqing Jiao , Pawel Markiewicz , Ninon Burgos , David Atkinson , Brian Hutton et al.

Information Processing in Medical Imaging – IPMI 2015, Jun 2015, Isle of Skye, United Kingdom. pp.540--551, ⟨10.1007/978-3-319-19992-4_42⟩

Communication dans un congrès hal-01827210v1

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

Ninon Burgos , Jorge M. Cardoso , Filipa Guerreiro , Catarina Veiga , Marc Modat et al.

Medical Image Computing and Computer-Assisted Intervention − MICCAI 2015, Oct 2015, Munich, Germany. pp.476--484, ⟨10.1007/978-3-319-24571-3_57⟩

Communication dans un congrès hal-01827209v1

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

F. Guerreiro , J. Mcclelland , Ninon Burgos , M. J. Cardoso , A. Dunlop et al.

MR in RT symposium, Jun 2015, Lund, Sweden

Communication dans un congrès hal-01827206v1

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

Ana Mota , Vesna Cuplov , Jonathan Schott , Brian Hutton , Kris Thielemans et al.

Conference on PET/MR and SPECT/MR – PSMR 2015, May 2015, Elba, Italy. pp.A44, ⟨10.1186/2197-7364-2-S1-A44⟩

Communication dans un congrès hal-01827207v1

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

Ninon Burgos , Jorge M. Cardoso , Alex F. Mendelson , Jonathan M. Schott , David Atkinson et al.

Medical Image Computing and Computer-Assisted Intervention − MICCAI 2015, Oct 2015, Munich, Germany. pp.651--658, ⟨10.1007/978-3-319-24571-3_78⟩

Communication dans un congrès hal-01827208v1

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

Ninon Burgos , K. Thielemans , M. J. Cardoso , P. Markiewicz , J. Jiao et al.

IEEE Nuclear Science Symposium and Medical Imaging Conference – IEEE NSS/MIC 2014, Nov 2014, Seattle, United States. pp.1--5, ⟨10.1109/NSSMIC.2014.7430775⟩

Communication dans un congrès hal-01827220v1

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

Ninon Burgos , Jorge M. Cardoso , Kris Thielemans , John S. Duncan , David Atkinson et al.

Conference on PET/MR and SPECT/MR – PSMR 2014, May 2014, Kos, Greece. pp.A52, ⟨10.1186/2197-7364-1-S1-A52⟩

Communication dans un congrès hal-01827222v1

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

Pawel Markiewicz , Kris Thielemans , Ninon Burgos , Richard Manber , Jieqing Jiao et al.

Conference on PET/MR and SPECT/MR – PSMR 2014, May 2014, Kos, Greece. pp.A44, ⟨10.1186/2197-7364-1-S1-A44⟩

Communication dans un congrès hal-01827219v1

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

Martin Kochan , Pankaj Daga , Ninon Burgos , Mark White , Jorge M. Cardoso et al.

Information Processing in Computer-Assisted Interventions – IPCAI 2014, Jun 2014, Fukuoka, Japan. pp.226--235, ⟨10.1007/978-3-319-07521-1_24⟩

Communication dans un congrès hal-01827221v1

Joint parametric reconstruction and motion correction framework for dynamic PET data

Jieqing Jiao , Alexandre Bousse , Kris Thielemans , Pawel Markiewicz , Ninon Burgos et al.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, Sep 2014, Boston, United States. pp.114-121, ⟨10.1007/978-3-319-10404-1_15⟩

Communication dans un congrès hal-01827218v1

Attenuation correction synthesis for hybrid PET-MR scanners

Ninon Burgos , Manuel Jorge Cardoso , Marc Modat , Stefano Pedemonte , John Dickson et al.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, Sep 2013, Nagoya, Japan. pp.147--154, ⟨10.1007/978-3-642-40811-3_19⟩

Communication dans un congrès istex hal-01827223v1

Biomedical Image Synthesis and Simulation

Ninon Burgos , David Svoboda

Ninon Burgos; David Svoboda. Elsevier, 2022, 978-0-12-824349-7. ⟨10.1016/C2020-0-01250-8⟩

Ouvrages hal-03721959v1
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Reproducibility in medical image computing: what is it and how is it assessed?

Olivier Colliot , Elina Thibeau-Sutre , Camille Brianceau , Ninon Burgos

Marco Lorenzi and Maria Zuluaga. Trustworthy AI in Medical Imaging, Elsevier, pp.177-204, 2024, MICCAI Book Series, Elsevier, ⟨10.1016/B978-0-44-323761-4.00018-3⟩

Chapitre d'ouvrage hal-04895884v1
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Neuroimaging in Machine Learning for Brain Disorders

Ninon Burgos

Olivier Colliot. Machine Learning for Brain Disorders, 197, Springer, pp.253-284, 2023, Neuromethods, ⟨10.1007/978-1-0716-3195-9_8⟩

Chapitre d'ouvrage hal-03814787v1
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Deep learning: basics and convolutional neural networks (CNN)

Maria Vakalopoulou , Stergios Christodoulidis , Ninon Burgos , Olivier Colliot , Vincent Lepetit

Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_3⟩

Chapitre d'ouvrage hal-03957224v2
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Reproducibility in machine learning for medical imaging

Olivier Colliot , Elina Thibeau-Sutre , Ninon Burgos

Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023

Chapitre d'ouvrage hal-03957240v2
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Interpretability of Machine Learning Methods Applied to Neuroimaging

Elina Thibeau-Sutre , Sasha Collin , Ninon Burgos , Olivier Colliot

Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_22⟩

Chapitre d'ouvrage hal-03615163v2
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Validation and evaluation metrics for medical and biomedical image synthesis

Tereza Nečasová , Ninon Burgos , David Svoboda

Biomedical Image Synthesis and Simulation, Elsevier, pp.573-600, 2022, 978-0-12-824349-7. ⟨10.1016/B978-0-12-824349-7.00032-3⟩

Chapitre d'ouvrage hal-03721947v1
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Future trends in medical and biomedical image synthesis

Ninon Burgos , Sotirios A Tsaftaris , David Svoboda

Ninon Burgos; David Svoboda. Biomedical Image Synthesis and Simulation, Elsevier, pp.643-645, 2022, 978-0-12-824349-7. ⟨10.1016/B978-0-12-824349-7.00034-7⟩

Chapitre d'ouvrage hal-03721950v1
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Medical image synthesis using segmentation and registration

Ninon Burgos

Biomedical Image Synthesis and Simulation, Elsevier, pp.55-77, 2022, 9780128243497. ⟨10.1016/B978-0-12-824349-7.00011-6⟩

Chapitre d'ouvrage hal-03721697v1
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Introduction to medical and biomedical image synthesis

David Svoboda , Ninon Burgos

Ninon Burgos; David Svoboda. Biomedical Image Synthesis and Simulation, Elsevier, pp.1-3, 2022, 978-0-12-824349-7. ⟨10.1016/B978-0-12-824349-7.00008-6⟩

Chapitre d'ouvrage hal-03721967v1