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Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease.

E. Bron, S. Klein, J. Papma, L. Jiskoot, V. Venkatraghavan, J. Linders, P. Aalten, P. Deyn, G. Biessels, J. Claassen, H. Middelkoop, M. Smits, W. Niessen, J. van Swieten, W. van der Flier, I. Ramakers, and A. van der Lugt. CoRR, (2020)

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Christian Bron

Jan Bron

Michael Bron

Bernhard Bron

Vladimir Bron

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Projection-Wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis.X. Liu, B. Li, E. Bron, W. Niessen, E. Wolvius, and G. Roshchupkin. MICCAI (5), volume 12905 of Lecture Notes in Computer Science, page 814-823. Springer, (2021)Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset.B. Li, M. de Groot, M. Vernooij, M. Ikram, W. Niessen, and E. Bron. MLMI@MICCAI, volume 11046 of Lecture Notes in Computer Science, page 205-213. Springer, (2018)Learning unbiased group-wise registration (LUGR) and joint segmentation: evaluation on longitudinal diffusion MRI.B. Li, W. Niessen, S. Klein, M. Ikram, M. Vernooij, and E. Bron. Medical Imaging: Image Processing, volume 11596 of SPIE Proceedings, SPIE, (2021)Analyzing the effect of APOE on Alzheimer's disease progression using an event-based model for stratified populations.V. Venkatraghavan, S. Klein, L. Fani, L. Ham, H. Vrooman, M. Ikram, W. Niessen, and E. Bron. NeuroImage, (2021)A Hybrid Deep Learning Framework for Integrated Segmentation and Registration: Evaluation on Longitudinal White Matter Tract Changes.B. Li, W. Niessen, S. Klein, M. de Groot, M. Ikram, M. Vernooij, and E. Bron. MICCAI (3), volume 11766 of Lecture Notes in Computer Science, page 645-653. Springer, (2019)An Interpretable Machine Learning Model with Deep Learning-Based Imaging Biomarkers for Diagnosis of Alzheimer's Disease.W. Kang, B. Li, J. Papma, L. Jiskoot, P. Deyn, G. Biessels, J. Claassen, H. Middelkoop, W. van der Flier, I. Ramakers and 2 other author(s). ISIC/Care-AI/MedAGI/DeCaF@MICCAI, volume 14393 of Lecture Notes in Computer Science, page 69-78. Springer, (2023)A Discriminative Event Based Model for Alzheimer's Disease Progression Modeling.V. Venkatraghavan, E. Bron, W. Niessen, and S. Klein. IPMI, volume 10265 of Lecture Notes in Computer Science, page 121-133. Springer, (2017)Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration.B. Li, W. Niessen, S. Klein, M. de Groot, M. Ikram, M. Vernooij, and E. Bron. CoRR, (2020)Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021.C. Sudre, K. van Wijnen, F. Dubost, H. Adams, D. Atkinson, F. Barkhof, M. Birhanu, E. Bron, R. Camarasa, N. Chaturvedi and 39 other author(s). CoRR, (2022)AI-based association analysis for medical imaging using latent-space geometric confounder correction.X. Liu, B. Li, M. Vernooij, E. Wolvius, G. Roshchupkin, and E. Bron. CoRR, (2023)

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Disambiguation of "Bron, Esther E."

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Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease.

Please choose a person to relate this publication to

Christian Bron

Jan Bron

Michael Bron

Bernhard Bron

Vladimir Bron

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Bron, Esther E."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease.

Please choose a person to relate this publication to

Christian Bron

Jan Bron

Michael Bron

Bernhard Bron

Vladimir Bron

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
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APA
Chicago
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Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease.