Ninon Burgos
28
Documents
Identifiants chercheurs
- ninon-burgos
- 0000-0002-4668-2006
- Google Scholar : https://scholar.google.co.uk/citations?user=lHuYSU0AAAAJ&hl=en
- IdRef : 25099884X
- ResearcherId : U-3404-2018
Présentation
[Ninon Burgos](https://ninonburgos.com/) is a CNRS researcher at the [Paris Brain Institute](http://icm-institute.org/) in the [ARAMIS Lab](http://www.aramislab.fr/). She completed her PhD at University College London in the [Centre for Medical Image Computing](http://www.ucl.ac.uk/medical-image-computing). She received an MSc in Biomedical Engineering from Imperial College London and an Engineering degree from a French Graduate School in Electrical Engineering and Computer Science (ENSEA). Her research currently focuses on the development of computational imaging tools to improve the understanding and diagnosis of neurological diseases.
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Advances in the Clinica software platform for clinical neuroimaging studiesOHBM 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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Clinica: an open-source software platform for reproducible clinical neuroscience studiesMRI 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 platformOHBM 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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New advances in the Clinica software platform for clinical neuroimaging studiesOHBM 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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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
Communication dans un congrès
hal-02105133v2
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Beware of feature selection bias! Example on Alzheimer's disease classification from diffusion MRI2019 OHBM Annual Meeting - Organization for Human Brain Mapping, Jun 2019, Rome, Italy
Communication dans un congrès
hal-02105134v2
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Deciphering the progression of PET alterations using surface-based spatiotemporal modelingOHBM 2019 - Annual meeting of the Organization for Human Brain Mapping, Jun 2019, Rome, Italy
Communication dans un congrès
hal-02134909v1
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Prediction of future cognitive scores and dementia onset in Mild Cognitive Impairment patientsOHBM 2019 - Organization for Human Brain Mapping Conference, Jun 2019, Rome, Italy
Communication dans un congrès
hal-02098427v2
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Using diffusion MRI for classification and prediction of Alzheimer's Disease: a reproducible studyAAIC 2018 - Alzheimer's Association International Conference, Jul 2018, Chicago, United States
Communication dans un congrès
hal-01758167v2
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Reproducible evaluation of Alzheimer's Disease classification from MRI and PET dataAnnual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore
Communication dans un congrès
hal-01761666v1
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Comparison of DTI Features for the Classification of Alzheimer's Disease: A Reproducible StudyOHBM 2018 - Organization for Human Brain Mapping Annual Meeting, Jun 2018, Singapour, Singapore
Communication dans un congrès
hal-01758206v3
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Clinica: an open source software platform for reproducible clinical neuroscience studiesAnnual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapore, Singapore
Communication dans un congrès
hal-01760658v1
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A pipeline for the analysis of 18F-FDG PET data on the cortical surface and its evaluation on ADNIAnnual meeting of the Organization for Human Brain Mapping - OHBM 2018, Jun 2018, Singapour, Singapore
Communication dans un congrès
hal-01757646v1
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Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's DiseaseMachine 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 DataAAIC 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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Individual Analysis of Molecular Brain Imaging Data Through Automatic Identification of Abnormality PatternsComputational Methods for Molecular Imaging - [MICCAI 2017 Satellite Workshop], Sep 2017, Quebec City, Canada
Communication dans un congrès
hal-01567343v1
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Diagnosis of Alzheimer’s Disease Through Identification of Abnormality Patterns in FDG PET Data30th 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
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How serious is data leakage in deep learning studies on Alzheimer’s disease classification?Organization for Human Brain Mapping (OHBM), Jun 2019, Roma, Italy
Poster de conférence
hal-03365742v1
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