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121 documents

Articles dans une revue36 documents

  • Sophie Loizillon, Simona Bottani, Stéphane Mabille, Yannick Jacob, Aurélien Maire, et al.. Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation. Journal of Machine Learning for Biomedical Imaging, 2024, 2 (June 2024), pp.888-915. ⟨10.59275/j.melba.2024-7fgd⟩. ⟨hal-04623223⟩
  • Sophie Loizillon, Simona Bottani, Aurélien Maire, Sebastian Ströer, Didier Dormont, et al.. Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data. Medical Image Analysis, 2024, 93, pp.103073. ⟨10.1016/j.media.2023.103073⟩. ⟨hal-03910451v2⟩
  • Simona Bottani, Elina Thibeau-Sutre, Aurélien Maire, Sebastian Ströer, Didier Dormont, et al.. Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI. BMC Medical Imaging, 2024, 24 (1), pp.67. ⟨10.1186/s12880-024-01242-3⟩. ⟨hal-03497645v2⟩
  • Ravi Hassanaly, Camille Brianceau, Maëlys Solal, Olivier Colliot, Ninon Burgos. Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET. Journal of Machine Learning for Biomedical Imaging, 2024, Special Issue for Generative Models, 2, pp.611. ⟨10.59275/j.melba.2024-b87a⟩. ⟨hal-04315738v2⟩
  • Simona Bottani, Ninon Burgos, Aurélien Maire, Dario Saracino, Sebastian Stroer, et al.. Evaluation of MRI-based machine learning approaches for computer-aided diagnosis of dementia in a clinical data warehouse. Medical Image Analysis, 2023, 89, pp.102903. ⟨hal-03656136v2⟩
  • William Coath, Marc Modat, M. Jorge Cardoso, Pawel Markiewicz, Christopher Lane, et al.. Operationalizing the centiloid scale for [18 F]florbetapir PET studies on PET/MRI. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 2023, 15 (2), ⟨10.1002/dad2.12434⟩. ⟨hal-04099627⟩
  • Clément Chadebec, Elina Thibeau-Sutre, Ninon Burgos, Stéphanie Allassonnière. Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, ⟨10.1109/TPAMI.2022.3185773⟩. ⟨hal-03214093⟩
  • Elina Thibeau-Sutre, Mauricio Diaz, Ravi Hassanaly, Alexandre M Routier, Didier Dormont, et al.. ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing. Computer Methods and Programs in Biomedicine, 2022, 220, pp.106818. ⟨10.1016/j.cmpb.2022.106818⟩. ⟨hal-03351976v2⟩
  • Stephane Epelbaum, Ninon Burgos, Michael Canney, Dawn Matthews, Marion Houot, et al.. Pilot Study of Repeated Blood-Brain Barrier Disruption in Patients with Mild Alzheimer's Disease with an Implantable Ultrasound Device. Alzheimer's Research and Therapy, 2022, 14 (40), ⟨10.1186/s13195-022-00981-1⟩. ⟨hal-03484130⟩
  • Simona Bottani, Ninon Burgos, Aurélien Maire, Adam Wild, Sébastian Ströer, et al.. Automatic quality control of brain T1-weighted magnetic resonance images for a clinical data warehouse. Medical Image Analysis, 2022, 75, ⟨10.1016/j.media.2021.102219⟩. ⟨hal-03154792v4⟩
  • Alexandre Routier, Ninon Burgos, Mauricio Diaz, Michael Bacci, Simona Bottani, et al.. Clinica: an open source software platform for reproducible clinical neuroscience studies. Frontiers in Neuroinformatics, 2021, 15, pp.689675. ⟨10.3389/fninf.2021.689675⟩. ⟨hal-02308126v4⟩
  • Igor Koval, Alexandre Bône, Maxime Louis, Thomas Lartigue, Simona Bottani, et al.. AD Course Map charts Alzheimer’s disease progression. Scientific Reports, 2021, 11 (1), ⟨10.1038/s41598-021-87434-1⟩. ⟨hal-01964821v3⟩
  • Ninon Burgos, Jorge M. Cardoso, Jorge Samper-González, Marie-Odile Habert, Stanley Durrleman​, et al.. Anomaly detection for the individual analysis of brain PET images. Journal of Medical Imaging, 2021, 8 (02), pp.024003. ⟨10.1117/1.JMI.8.2.024003⟩. ⟨hal-03193306⟩
  • Ninon Burgos, Simona Bottani, Johann Faouzi, Elina Thibeau-Sutre, Olivier Colliot. Deep learning for brain disorders: from data processing to disease treatment. Briefings in Bioinformatics, 2021, 22 (2), pp.1560-1576. ⟨10.1093/bib/bbaa310⟩. ⟨hal-03070554⟩
  • Manon Ansart, Stéphane Epelbaum, Giulia Bassignana, Alexandre Bône, Simona Bottani, et al.. Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic, Quantitative and Critical Review. Medical Image Analysis, 2021, 67, pp.101848. ⟨10.1016/j.media.2020.101848⟩. ⟨hal-02337815v2⟩
  • Junhao Wen, Jorge Samper-González, Simona Bottani, Alexandre Routier, Ninon Burgos, et al.. Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimer's disease. Neuroinformatics, 2021, 19 (1), pp.57-78. ⟨10.1007/s12021-020-09469-5⟩. ⟨hal-02566361v2⟩
  • Baptiste Couvy-Duchesne, Johann Faouzi, Benoît Martin, Elina Thibeau-Sutre, Adam Wild, et al.. 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. Frontiers in Psychiatry, 2020, 11, ⟨10.3389/fpsyt.2020.593336⟩. ⟨hal-03136463⟩
  • Junhao Wen, Elina Thibeau-Sutre, Mauricio Diaz-Melo, Jorge Samper-González, Alexandre Routier, et al.. Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation. Medical Image Analysis, 2020, 63, pp.101694. ⟨10.1016/j.media.2020.101694⟩. ⟨hal-02562504v2⟩
  • Ninon Burgos, Olivier Colliot. Machine learning for classification and prediction of brain diseases: recent advances and upcoming challenges. Current Opinion in Neurology, 2020, 33 (4), pp.439-450. ⟨10.1097/WCO.0000000000000838⟩. ⟨hal-02902586⟩
  • Didier Dormont, Noam Ben-Eliezer, Ninon Burgos, Olivier Colliot, Fabrizio de Vico Fallani, et al.. Tribute to Anne Bertrand (1978–2018): Neuroradiologist, scientist, teacher and friend. Journal de Neuroradiologie / Journal of Neuroradiology, 2019, 46 (2), pp.155-159. ⟨10.1016/j.neurad.2019.01.001⟩. ⟨hal-02265305⟩
  • Arnaud Marcoux, Ninon Burgos, Anne Bertrand, Marc Teichmann, Alexandre Routier, et al.. An Automated Pipeline for the Analysis of PET Data on the Cortical Surface. Frontiers in Neuroinformatics, 2018, 12, ⟨10.3389/fninf.2018.00094⟩. ⟨hal-01950933⟩
  • Jorge Samper-González, Ninon Burgos, Simona Bottani, Sabrina Fontanella, Pascal Lu, et al.. Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data. NeuroImage, 2018, 183, pp.504-521. ⟨10.1016/j.neuroimage.2018.08.042⟩. ⟨hal-01858384v2⟩
  • Catherine Scott, Jieqing Jiao, Andrew Melbourne, Ninon Burgos, David Cash, et al.. Reduced acquisition time PET pharmacokinetic modelling using simultaneous ASL–MRI: proof of concept. Journal of Cerebral Blood Flow and Metabolism, 2018, ⟨10.1177/0271678X18797343⟩. ⟨hal-01871983⟩
  • Hossein Arabi, Jason Dowling, Ninon Burgos, Xiao Han, Peter Greer, et al.. Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region. Medical Physics, 2018, ⟨10.1002/mp.13187⟩. ⟨hal-01890646⟩
  • Jennifer Petra Kieselmann, Cornelis Philippus Kamerling, Ninon Burgos, Martin J. Menten, Clifton David Fuller, et al.. Geometric and dosimetric evaluations of atlas-based segmentation methods of MR images in the head and neck region. Physics in Medicine and Biology, 2018, 63 (14), ⟨10.1088/1361-6560/aacb65⟩. ⟨hal-01827187⟩
  • Ninon Burgos, Filipa Guerreiro, M Mcclelland, Benoît Presles, M Modat, et al.. Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning. Physics in Medicine and Biology, 2017, 62 (11), pp.4237 - 4253. ⟨10.1088/1361-6560/aa66bf⟩. ⟨hal-01556656⟩
  • Christopher A. Lane, Thomas D. Parker, Dave M. Cash, Kirsty Macpherson, Elizabeth Donnachie, et al.. Study protocol: Insight 46 – a neuroscience sub-study of the MRC National Survey of Health and Development. BMC Neurology, 2017, 17, pp.75. ⟨10.1186/s12883-017-0846-x⟩. ⟨hal-01827191⟩
  • F. Guerreiro, Ninon Burgos, A. Dunlop, K. Wong, I. Petkar, et al.. Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning. Physica Medica European Journal of Medical Physics, 2017, 35, pp.7--17. ⟨10.1016/j.ejmp.2017.02.017⟩. ⟨hal-01827195⟩
  • Claes N. Ladefoged, Ian Law, Udunna Anazodo, Keith St. Lawrence, David Izquierdo-Garcia, et al.. A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients. NeuroImage, 2017, 147, pp.346--359. ⟨10.1016/j.neuroimage.2016.12.010⟩. ⟨hal-01827196⟩
  • J. Jiao, A. Bousse, K. Thielemans, Ninon Burgos, P. S. J. Weston, et al.. Direct parametric reconstruction with joint motion estimation/correction for dynamic brain PET data. IEEE Transactions on Medical Imaging, 2017, 36 (1), pp.203--213. ⟨10.1109/TMI.2016.2594150⟩. ⟨hal-01827197⟩
  • Tetsuro Sekine, Ninon Burgos, Geoffrey Warnock, Martin Huellner, Alfred Buck, et al.. 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. Journal of Nuclear Medicine, 2016, 57 (8), pp.1258--1264. ⟨10.2967/jnumed.115.169045⟩. ⟨hal-01827202⟩
  • Philip S. J. Weston, Ross W. Paterson, Marc Modat, Ninon Burgos, Manuel J. Cardoso, et al.. Using florbetapir positron emission tomography to explore cerebrospinal fluid cut points and gray zones in small sample sizes. Alzheimer's & Dementia : the Journal of the Alzheimer's Association, 2015, 1 (4), pp.440--446. ⟨10.1016/j.dadm.2015.10.001⟩. ⟨hal-01827214⟩
  • Maria A. Zuluaga, Ninon Burgos, Alex F. Mendelson, Andrew M. Taylor, Sébastien Ourselin. Voxelwise atlas rating for computer assisted diagnosis: Application to congenital heart diseases of the great arteries. Medical Image Analysis, 2015, 26 (1), pp.185--194. ⟨10.1016/j.media.2015.09.001⟩. ⟨hal-01827215⟩
  • Martin Kochan, Pankaj Daga, Ninon Burgos, Mark White, Jorge M. Cardoso, et al.. Simulated field maps for susceptibility artefact correction in interventional MRI. International Journal of Computer Assisted Radiology and Surgery, 2015, 10 (9), pp.1405--1416. ⟨10.1007/s11548-015-1253-7⟩. ⟨hal-01827211⟩
  • Ninon Burgos, Jorge M. Cardoso, Kris Thielemans, Marc Modat, John Dickson, et al.. Multi-contrast attenuation map synthesis for PET/MR scanners: assessment on FDG and Florbetapir PET tracers. European Journal of Nuclear Medicine and Molecular Imaging, 2015, 42 (9), pp.1447--1458. ⟨10.1007/s00259-015-3082-x⟩. ⟨hal-01827213⟩
  • Ninon Burgos, M. J. Cardoso, K. Thielemans, M. Modat, S. Pedemonte, et al.. Attenuation correction synthesis for hybrid PET-MR scanners: Application to brain studies. IEEE Transactions on Medical Imaging, 2014, 33 (12), pp.2332--2341. ⟨10.1109/TMI.2014.2340135⟩. ⟨hal-01827217⟩

Communications dans un congrès66 documents

  • Evangelia Christodoulou, Annika Reinke, Rola Houhou, Piotr Kalinowski, Selen Erkan, et al.. Confidence intervals uncovered: Are we ready for real-world medical imaging AI?. MICCAI 2024 - Medical Image Computing and Computer-Assisted Intervention, Oct 2024, Marrakech, Morocco. ⟨hal-04715638⟩
  • Sophie Loizillon, Yannick Jacob, Aurelien Maire, Didier Dormont, Olivier Colliot, et al.. Detecting Brain Anomalies in Clinical Routine with the β-VAE: Feasibility Study on Age-Related White Matter Hyperintensities. Medical Imaging with Deep Learning - MIDL 2024, Jul 2024, Paris, France. ⟨hal-04674025⟩
  • Matthieu Joulot, Nicolas Gensollen, Ghislain Vaillant, Ninon Burgos, Olivier Colliot. Clinica, an open-source software to facilitate neuroimaging studies. Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale (IABM), Mar 2024, Grenoble, France. ⟨hal-04653352⟩
  • Guanghui Fu, Gabriel Jiménez, Sophie Loizillon, Lydia Chougar, Didier Dormont, et al.. The intriguing effect of frequency disentangled learning on medical image segmentation. Medical Imaging 2024, Feb 2024, San Diego, CA, United States. pp.49, ⟨10.1117/12.2692286⟩. ⟨hal-04654627⟩
  • Sophie Loizillon, Stéphane Mabille, Simona Bottani, Yannick Jacob, Aurélien Maire, et al.. Leveraging noise and contrast simulation for the automatic quality control of routine clinical T1-weighted brain MRI. SPIE Medical Imaging 2024: Image Processing, Feb 2024, San Diego (CA), United States. ⟨hal-04674029⟩
  • Maëlys Solal, Ravi Hassanaly, Ninon Burgos. Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET. SPIE Medical Imaging, Feb 2024, San Diego (California), United States. ⟨hal-04291561v2⟩
  • Théodore Soulier, Mariem Hamzaoui, Milena Sales Pitombeira, Daniele De Paula Faria, Arya Yazdan-Panah, et al.. Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networks. SPIE Medical Imaging, Feb 2024, San Diego, United States. ⟨hal-04362506⟩
  • Ravi Hassanaly, Camille Brianceau, Mauricio Diaz, Sophie Loizillon, Elina Thibeau-Sutre, et al.. Recent advances in the open-source ClinicaDL software for reproducible neuroimaging with deep learning. SPIE Medical Imaging, Feb 2024, San Diego, United States. ⟨hal-04419141⟩
  • Francesco Galati, Daniele Falcetta, Rosa Cortese, Barbara Casolla, Ferran Prados, et al.. A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation. BMVC 2023, 34th British Machine Vision Conference, Nov 2023, Aberdeen, United Kingdom. ⟨hal-04195756v2⟩
  • Ravi Hassanaly, Camille Brianceau, Olivier Colliot, Ninon Burgos. Unsupervised anomaly detection in 3D brain FDG PET: A benchmark of 17 VAE-based approaches. Deep Generative Models workshop at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Oct 2023, Vancouver, Canada. ⟨hal-04185304⟩
  • Sophie Loizillon, Olivier Colliot, Lydia Chougar, Sebastian Stroer, Yannick Jacob, et al.. Semi-supervised Domain Adaptation for Automatic Quality Control of FLAIR MRIs in a Clinical Data Warehouse. 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⟩. ⟨hal-04273997⟩
  • Ghislain Vaillant, Nicolas Gensollen, Matthieu Joulot, Omar El-Rifai, Mauricio Diaz, et al.. From Nipype to Pydra: a Clinica story. OHBM 2023 - Annual meeting of the Organization for Human Brain Mapping, Jul 2023, Montreal, Canada. ⟨hal-04278898⟩
  • Ravi Hassanaly, Simona Bottani, Benoît Sauty, Olivier Colliot, Ninon Burgos. Simulation-based evaluation framework for deep learning unsupervised anomaly detection on brain FDG PET. SPIE Medical Imaging, Feb 2023, San Diego, United States. ⟨hal-03835015v2⟩
  • Elina Thibeau-Sutre, Jelmer M Wolterink, Olivier Colliot, Ninon Burgos. How can data augmentation improve attribution maps for disease subtype explainability?. SPIE Medical Imaging, Feb 2023, San Diego, United States. ⟨hal-03966737⟩
  • Sophie Loizillon, Simona Bottani, Aurélien Maire, Sebastian Stroer, Didier Dormont, et al.. Transfer learning from synthetic to routine clinical data for motion artefact detection in brain T1-weighted MRI. SPIE Medical Imaging 2023: Image Processing, Feb 2023, San Diego, United States. ⟨hal-03831746v2⟩
  • Elina Thibeau-Sutre, Mauricio Diaz, Ravi Hassanaly, Olivier Colliot, Ninon Burgos. ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing. OHBM 2022 - Annual meeting of the Organization for Human Brain Mapping, Jun 2022, Glasgow, United Kingdom. ⟨hal-04279014⟩
  • Omar El Rifai, Mauricio Diaz Melo, Ravi Hassanaly, Matthieu Joulot, Alexandre M Routier, et al.. Advances in the Clinica software platform for clinical neuroimaging studies. OHBM 2022 - Annual meeting of the Organization for Human Brain Mapping, Jun 2022, Glasgow, United Kingdom. ⟨hal-03728243⟩
  • Elina Thibeau-Sutre, Baptiste Couvy-Duchesne, Didier Dormont, Olivier Colliot, Ninon Burgos. MRI field strength predicts Alzheimer's disease: a case example of bias in the ADNI data set. ISBI 2022 - International Symposium on Biomedical Imaging, Mar 2022, Kolkata, India. ⟨10.1109/ISBI52829.2022.9761504⟩. ⟨hal-03542213⟩
  • Simona Bottani, Elina Thibeau-Sutre, Aurélien Maire, Sebastian Ströer, Didier Dormont, et al.. Homogenization of brain MRI from a clinical data warehouse using contrast-enhanced to non-contrast-enhanced image translation with U-Net derived models. SPIE Medical Imaging 2022: Image Processing, Feb 2022, San Diego, United States. pp.576-582, ⟨10.1117/12.2608565⟩. ⟨hal-03478798⟩
  • Omar El-Rifai, Mauricio Diaz Melo, Ravi Hassanaly, Matthieu Joulot, Alexandre M Routier, et al.. Clinica: an open-source software platform for reproducible clinical neuroscience studies. MRI Together 2021 - A global workshop on Open Science and Reproducible MR Research, Dec 2021, Online, France. ⟨hal-03513920⟩
  • Alexandre Routier, Arnaud Marcoux, Mauricio Diaz Melo, Jorge Samper-González, Adam Wild, et al.. New longitudinal and deep learning pipelines in the Clinica software platform. OHBM 2020 - Annual meeting of the Organization for Human Brain Mapping, Jun 2020, Montreal / Virtual, Canada. ⟨hal-02549242⟩
  • Elina Thibeau-Sutre, Olivier Colliot, Didier Dormont, Ninon Burgos. Visualization approach to assess the robustness of neural networks for medical image classification. SPIE Medical Imaging 2020, Feb 2020, Houston, United States. ⟨10.1117/12.2548952⟩. ⟨hal-02370532v3⟩
  • Junhao Wen​, Elina Thibeau--Sutre​, Jorge Samper-González​, Alexandre M Routier, Simona Bottani​, et al.. How serious is data leakage in deep learning studies on Alzheimer's disease classification?. 2019 OHBM Annual meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy. ⟨hal-02105133v2⟩
  • Igor Koval, Arnaud Marcoux, Ninon Burgos, Stéphanie Allassonnière, Olivier Colliot, et al.. Deciphering the progression of PET alterations using surface-based spatiotemporal modeling. OHBM 2019 - Annual meeting of the Organization for Human Brain Mapping, Jun 2019, Rome, Italy. ⟨hal-02134909⟩
  • Junhao Wen​, Jorge Samper-González​, Alexandre M Routier, Simona Bottani​, Stanley Durrleman​, et al.. Beware of feature selection bias! Example on Alzheimer's disease classification from diffusion MRI. 2019 OHBM Annual Meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy. ⟨hal-02105134v2⟩
  • Jorge Samper-Gonzalez, Ninon Burgos, Simona Bottani, Marie-Odile Habert, Theodoros Evgeniou, et al.. Predicting progression to Alzheimer’s disease from clinical and imaging data: a reproducible study. OHBM 2019 - Organization for Human Brain Mapping Annual Meeting 2019, Jun 2019, Rome, Italy. ⟨hal-02142315⟩
  • Alexandre Routier, Arnaud Marcoux, Mauricio Diaz Melo, Jérémy Guillon, Jorge Samper-González, et al.. New advances in the Clinica software platform for clinical neuroimaging studies. OHBM 2019 - Annual Meeting on Organization for Human Brain Mapping, Jun 2019, Roma, Italy. ⟨10.1016/j.neuroimage.2011.09.015⟩. ⟨hal-02132147v2⟩
  • Manon Ansart, Ninon Burgos, Olivier Colliot, Didier Dormont, Stanley Durrleman. Prediction of future cognitive scores and dementia onset in Mild Cognitive Impairment patients. OHBM 2019 - Organization for Human Brain Mapping Conference, Jun 2019, Rome, Italy. ⟨hal-02098427v2⟩
  • Jorge Samper-Gonzalez, Ninon Burgos, Simona Bottani, Marie-Odile Habert, Theodoros Evgeniou, et al.. Reproducible evaluation of methods for predicting progression to Alzheimer's disease from clinical and neuroimaging data. SPIE Medical Imaging 2019, Feb 2019, San Diego, United States. ⟨10.1117/12.2512430⟩. ⟨hal-02025880v2⟩
  • Junhao Wen, Jorge Samper-Gonzalez, Simona Bottani, Alexandre Routier, Ninon Burgos, et al.. Using diffusion MRI for classification and prediction of Alzheimer's Disease: a reproducible study. AAIC 2018 - Alzheimer's Association International Conference, Jul 2018, Chicago, United States. ⟨hal-01758167v2⟩
  • Jorge Samper-Gonzalez, Simona Bottani, Ninon Burgos, Sabrina Fontanella, Pascal Lu, et al.. Reproducible evaluation of Alzheimer's Disease classification from MRI and PET data. Annual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore. ⟨hal-01761666⟩
  • Junhao Wen, Jorge Samper-Gonzalez, Simona Bottani, Alexandre Routier, Ninon Burgos, et al.. Comparison of DTI Features for the Classification of Alzheimer's Disease: A Reproducible Study. OHBM 2018 - Organization for Human Brain Mapping Annual Meeting, Jun 2018, Singapour, Singapore. ⟨hal-01758206v3⟩
  • Alexandre Routier, Jérémy Guillon, Ninon Burgos, Jorge Samper-Gonzalez, Junhao Wen, et al.. Clinica: an open source software platform for reproducible clinical neuroscience studies. Annual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapore, Singapore. ⟨hal-01760658⟩
  • Arnaud Marcoux, Ninon Burgos, Anne Bertrand, Alexandre Routier, Junhao Wen, et al.. A pipeline for the analysis of 18F-FDG PET data on the cortical surface and its evaluation on ADNI. Annual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore. ⟨hal-01757646⟩
  • Jorge Samper-Gonzalez, Ninon Burgos, Simona Bottani, Marie-Odile Habert, Theodoros Evgeniou, et al.. Three simple ideas for predicting progression to Alzheimer's disease. 8th International Workshop on Pattern Recognition in Neuroimaging, Jun 2018, Singapour, Singapore. ⟨hal-01891996⟩
  • Ninon Burgos, Jorge Samper-González, Anne Bertrand, Marie-Odile Habert, Sébastien Ourselin, et al.. Diagnosis of Alzheimer’s Disease Through Identification of Abnormality Patterns in FDG PET Data. 30th Annual Congress of the European Association of Nuclear Medicine (EANM), Oct 2017, Vienna, Austria. pp.253 - 254, ⟨10.1007/s00259-017-3822-1⟩. ⟨hal-01632509⟩
  • Jorge Samper-Gonzalez, Ninon Burgos, Sabrina Fontanella, Hugo Bertin, Marie-Odile Habert, et al.. Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease. Machine Learning in Medical Imaging 2017, Sep 2017, Quebec City, Canada. pp.8. ⟨hal-01578479⟩
  • Ninon Burgos, Jorge Samper-González, Anne Bertrand, Marie-Odile Habert, Sébastien Ourselin, et al.. Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality Patterns. Computational Methods for Molecular Imaging - [MICCAI 2017 Satellite Workshop], Sep 2017, Quebec City, Canada. ⟨hal-01567343⟩
  • Jonathan M. Schott, David M. Cash, Christopher A. Lane, Thomas Parker, Ninon Burgos, et al.. Exploring the population prevalence of β-amyloid burden: An analysis of 250 individuals born in mainland Britain in the same week in 1946. AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P1088--P1089, ⟨10.1016/j.jalz.2017.06.1563⟩. ⟨hal-01827189⟩
  • Ninon Burgos, Jorge Samper-González, Jorge M. Cardoso, Stanley Durrleman, Sébastien Ourselin, et al.. Early Diagnosis of Alzheimer’s Disease Using Subject-Specific Models of FDG-PET Data. AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.1-2, ⟨10.1016/j.jalz.2017.06.1618⟩. ⟨hal-01621383⟩
  • Thomas Parker, David M. Cash, Christopher A. Lane, Heidi Murray-Smith, Andrew Wong, et al.. Brain volume, cerebral β-amyloid deposition, and ageing: A study of over 200 individuals born in the same week in 1946. AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P1464--P1465, ⟨10.1016/j.jalz.2017.07.534⟩. ⟨hal-01827188⟩
  • Sarah-Naomi James, Thomas Parker, Christopher A. Lane, David M. Cash, Andrew Wong, et al.. Midlife affective symptoms are associated with lower brain volumes in later life: Evidence from a prospective UK birth cohort. AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P212, ⟨10.1016/j.jalz.2017.07.086⟩. ⟨hal-01827192⟩
  • David M. Cash, Ninon Burgos, Marc Modat, John Dickson, Daniel Beasley, et al.. A comparison of techniques for quantifying amyloid burden on a combined PET/MR scanner. AAIC 2017 - Alzheimer's Association International Conference, Jul 2017, London, United Kingdom. pp.P12--P13, ⟨10.1016/j.jalz.2017.06.2276⟩. ⟨hal-01827194⟩
  • J. P Kieselmann, C. P. Kamerling, Ninon Burgos, M. J. Menten, S. Nill, et al.. Geometric and Dosimetric Evaluation of Three Atlas-based Segmentation Methods for Head and Neck Cancer Patients on MR Images. MR in RT symposium, Jun 2017, Sydney, Australia. ⟨hal-01827193⟩
  • Catherine J. Scott, Jieqing Jiao, Jorge M. Cardoso, Andrew Melbourne, Enrico de Vita, et al.. Short acquisition time PET quantification using MRI-based pharmacokinetic parameter synthesis. Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017, 2017, Québec, Canada. pp.737--744, ⟨10.1007/978-3-319-66185-8_83⟩. ⟨hal-01827190⟩
  • Claes N. Ladefoged, Ian Law, Udunna Anazodo, David Izquierdo-Garcia, Ninon Burgos, et al.. A multi-method, multi-center study of PET/MRI brain attenuation correction on a large cohort of [18F]- FDG patients: ready for clinical implementation. RSNA 216 – Annual Meeting of the Radiological Society of North America, Nov 2016, Chicago, United States. ⟨hal-01827203⟩
  • Ninon Burgos, Filipa Guerreiro, Jamie Mcclelland, Simeon Nill, David Dearnaley, et al.. Joint segmentation and CT synthesis for MRI-only radiotherapy treatment planning. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, Oct 2016, Athens, Greece. pp.547--555, ⟨10.1007/978-3-319-46723-8_63⟩. ⟨hal-01827201⟩
  • Claes N. Ladefoged, Ian Law, Udunna Anazodo, Keith St. Lawrence, David Izquierdo-Garcia, et al.. A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients. IEEE Nuclear Science Symposium and Medical Imaging Conference – IEEE NSS/MIC 2016, Oct 2016, Strasbourg, France. ⟨hal-01827199⟩
  • Ninon Burgos, Jorge M. Cardoso, Filipa Guerreiro, Jamie Mcclelland, Antje-Christin Knopf, et al.. Simultaneous organ-at-risk segmentation and CT synthesis in the pelvic region for MRI-only radiotherapy treatment planning. International Conference on the use of Computers in Radiation Therapy – ICCR 2016, Jun 2016, London, United Kingdom. ⟨hal-01827204⟩
  • F. Prados Carrasco, M. J. Cardoso, Ninon Burgos, C. A. M. Wheeler-Kingshott, S. Ourselin. NiftyWeb: web based platform for image processing on the cloud. Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine – ISMRM 2016, May 2016, Singapore, Singapore. ⟨hal-01827198⟩
  • Tetsuro Sekine, Ninon Burgos, Geoffrey Warnock, Martin Huellner, Alfred Buck, et al.. 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. Scientific Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine – ISMRM 2016, May 2016, Singapore, Singapore. ⟨hal-01827200⟩
  • Ninon Burgos, Jorge M. Cardoso, Filipa Guerreiro, Jamie Mcclelland, Antje-Christin Knopf, et al.. CT synthesis in the head & neck and pelvic regions for radiotherapy treatment planning. IPEM Workshop on MRI Guided Radiotherapy, Mar 2016, Sheffield, United Kingdom. ⟨hal-01827224⟩
  • Ninon Burgos, Jorge M. Cardoso, Filipa Guerreiro, Catarina Veiga, Marc Modat, et al.. Robust CT synthesis for radiotherapy planning: Application to the head & neck region. Medical Image Computing and Computer-Assisted Intervention − MICCAI 2015, Oct 2015, Munich, Germany. pp.476--484, ⟨10.1007/978-3-319-24571-3_57⟩. ⟨hal-01827209⟩
  • J. C. Dickson, K. Erlandsson, M. Lehmann, M. Modat, Ninon Burgos, et al.. Partial Volume Correction of Amyvid and FDG PET data using the discrete iterative Yang technique. Annual Congress of the European Association of Nuclear Medicine – EANM 2015, Oct 2015, Hamburg, Germany. pp.S69, ⟨10.1007/s00259-015-3198-z⟩. ⟨hal-01827205⟩
  • Ninon Burgos, Jorge M. Cardoso, Alex F. Mendelson, Jonathan M. Schott, David Atkinson, et al.. Subject-specific models for the analysis of pathological FDG PET data. Medical Image Computing and Computer-Assisted Intervention − MICCAI 2015, Oct 2015, Munich, Germany. pp.651--658, ⟨10.1007/978-3-319-24571-3_78⟩. ⟨hal-01827208⟩
  • F. Guerreiro, J. Mcclelland, Ninon Burgos, M. J. Cardoso, A. Dunlop, et al.. Evaluation of different approaches to obtain synthetic CT images for a MRI-only radiotherapy workflow. MR in RT symposium, Jun 2015, Lund, Sweden. ⟨hal-01827206⟩
  • Jieqing Jiao, Pawel Markiewicz, Ninon Burgos, David Atkinson, Brian Hutton, et al.. Detail-preserving PET reconstruction with sparse image representation and anatomical priors. 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⟩. ⟨hal-01827210⟩
  • Ana Mota, Vesna Cuplov, Jonathan Schott, Brian Hutton, Kris Thielemans, et al.. Establishment of an open database of realistic simulated data for evaluation of partial volume correction techniques in brain PET/MR. Conference on PET/MR and SPECT/MR – PSMR 2015, May 2015, Elba, Italy. pp.A44, ⟨10.1186/2197-7364-2-S1-A44⟩. ⟨hal-01827207⟩
  • Ninon Burgos, Jorge M. Cardoso, Marc Modat, Shonit Punwani, David Atkinson, et al.. CT synthesis in the head & neck region for PET/MR attenuation correction: an iterative multi-atlas approach. Conference on PET/MR and SPECT/MR – PSMR 2015, May 2015, Elba, Italy. pp.A31, ⟨10.1186/2197-7364-2-S1-A31⟩. ⟨hal-01827212⟩
  • M. A. Zuluaga, Ninon Burgos, A. M. Taylor, S. Ourselin. Multi-atlas synthesis for computer assisted diagnosis: Application to cardiovascular diseases. IEEE International Symposium on Biomedical Imaging – IEEE ISBI 2015, Apr 2015, New-York, United States. pp.290--293, ⟨10.1109/ISBI.2015.7163870⟩. ⟨hal-01827216⟩
  • Ninon Burgos, K. Thielemans, M. J. Cardoso, P. Markiewicz, J. Jiao, et al.. Effect of scatter correction when comparing attenuation maps: Application to brain PET/MR. 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⟩. ⟨hal-01827220⟩
  • Jieqing Jiao, Alexandre Bousse, Kris Thielemans, Pawel Markiewicz, Ninon Burgos, et al.. Joint parametric reconstruction and motion correction framework for dynamic PET data. 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⟩. ⟨hal-01827218⟩
  • Martin Kochan, Pankaj Daga, Ninon Burgos, Mark White, Jorge M. Cardoso, et al.. Simulated field maps: Toward improved susceptibility artefact correction in interventional MRI. Information Processing in Computer-Assisted Interventions – IPCAI 2014, Jun 2014, Fukuoka, Japan. pp.226--235, ⟨10.1007/978-3-319-07521-1_24⟩. ⟨hal-01827221⟩
  • Ninon Burgos, Jorge M. Cardoso, Kris Thielemans, John S. Duncan, David Atkinson, et al.. Attenuation correction synthesis for hybrid PET-MR scanners: validation for brain study applications. Conference on PET/MR and SPECT/MR – PSMR 2014, May 2014, Kos, Greece. pp.A52, ⟨10.1186/2197-7364-1-S1-A52⟩. ⟨hal-01827222⟩
  • Pawel Markiewicz, Kris Thielemans, Ninon Burgos, Richard Manber, Jieqing Jiao, et al.. Image reconstruction of mMR PET data using the open source software STIR. Conference on PET/MR and SPECT/MR – PSMR 2014, May 2014, Kos, Greece. pp.A44, ⟨10.1186/2197-7364-1-S1-A44⟩. ⟨hal-01827219⟩
  • Ninon Burgos, Manuel Jorge Cardoso, Marc Modat, Stefano Pedemonte, John Dickson, et al.. Attenuation correction synthesis for hybrid PET-MR scanners. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, Sep 2013, Nagoya, Japan. pp.147--154, ⟨10.1007/978-3-642-40811-3_19⟩. ⟨hal-01827223⟩

Poster de conférence4 documents

  • Elina Thibeau-Sutre, Mauricio Diaz, Ravi Hassanaly, Alexandre M Routier, Didier Dormont, et al.. ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing. 3IA Doctoral Workshop, Nov 2021, Toulouse, France. ⟨hal-03423072v2⟩
  • Elina Thibeau-Sutre, Olivier Colliot, Didier Dormont, Ninon Burgos. Identification of unlabeled latent subtypes with saliency maps. ICM welcome days, Oct 2020, Paris (online), France. ⟨hal-03365788⟩
  • Elina Thibeau-Sutre, Olivier Colliot, Didier Dormont, Ninon Burgos. Visualization approach to assess the robustness of neural networks for medical image classification. ICM days 2019, Jan 2020, Louan, France. ⟨hal-03365775⟩
  • Junhao Wen, Elina Thibeau-Sutre, Jorge Samper-Gonzalez, Alexandre M Routier, Simona Bottani, et al.. How serious is data leakage in deep learning studies on Alzheimer’s disease classification?. Organization for Human Brain Mapping (OHBM), Jun 2019, Roma, Italy. ⟨hal-03365742⟩

Proceedings/Recueil des communications4 documents


Ouvrages (y compris édition critique et traduction)1 document


Chapitres d'ouvrage8 documents

  • Maria Vakalopoulou, Stergios Christodoulidis, Ninon Burgos, Olivier Colliot, Vincent Lepetit. Deep learning: basics and convolutional neural networks (CNN). Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_3⟩. ⟨hal-03957224v2⟩
  • Olivier Colliot, Elina Thibeau-Sutre, Ninon Burgos. Reproducibility in machine learning for medical imaging. Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023. ⟨hal-03957240v2⟩
  • Elina Thibeau-Sutre, Sasha Collin, Ninon Burgos, Olivier Colliot. Interpretability of Machine Learning Methods Applied to Neuroimaging. Olivier Colliot. Machine Learning for Brain Disorders, Springer, 2023, ⟨10.1007/978-1-0716-3195-9_22⟩. ⟨hal-03615163v2⟩
  • Ninon Burgos. Medical image synthesis using segmentation and registration. Biomedical Image Synthesis and Simulation, Elsevier, pp.55-77, 2022, 9780128243497. ⟨10.1016/B978-0-12-824349-7.00011-6⟩. ⟨hal-03721697⟩
  • David Svoboda, Ninon Burgos. Introduction to medical and biomedical image synthesis. 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⟩. ⟨hal-03721967⟩
  • Tereza Nečasová, Ninon Burgos, David Svoboda. Validation and evaluation metrics for medical and biomedical image synthesis. Biomedical Image Synthesis and Simulation, Elsevier, pp.573-600, 2022, 978-0-12-824349-7. ⟨10.1016/B978-0-12-824349-7.00032-3⟩. ⟨hal-03721947⟩
  • Ninon Burgos, Sotirios A Tsaftaris, David Svoboda. Future trends in medical and biomedical image synthesis. 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⟩. ⟨hal-03721950⟩
  • Ninon Burgos. Neuroimaging in Machine Learning for Brain Disorders. Olivier Colliot. Machine Learning for Brain Disorders, Springer, In press. ⟨hal-03814787⟩

Pré-publications, Documents de travail1 document

  • Ravi Hassanaly, Maëlys Solal, Olivier Colliot, Ninon Burgos. Pseudo-healthy image reconstruction with variational autoencoders for anomaly detection: A benchmark on 3D brain FDG PET. 2024. ⟨hal-04445378⟩

Habilitations à diriger des recherches1 document

  • Ninon Burgos. Individualised, interpretable and reproducible computer-aided diagnosis of dementia: towards application in clinical practice. Medical Imaging. Sorbonne Université, 2022. ⟨tel-03941953⟩

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