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Federated Learning for Brain Tumor Segmentation Using MRI and Transformers.

, , , , , , , , и . BrainLes@MICCAI (2), том 12963 из Lecture Notes in Computer Science, стр. 444-454. Springer, (2021)

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Joseph A Bracken

Joseph A Bracken

R. A. A. Bowler

°Ake °Akerström

Mohamed A A Anndif

 

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Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation., , , , , , , и . BrainLes@MICCAI (2), том 11993 из Lecture Notes in Computer Science, стр. 148-157. Springer, (2019)A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain., , , , , , , , и . ICMLA (1), стр. 203-208. IEEE, (2012)Relational learning helps in three-way classification of Alzheimer patients from structural magnetic resonance images of the brain, , , , , , , , и . Int. J. Machine Learning & Cybernetics, 5 (5): 659--669 (2014)Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players., , , , , , , , , и 2 other автор(ы). Medical Imaging: Computer-Aided Diagnosis, том 10575 из SPIE Proceedings, стр. 105750F. SPIE, (2018)Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networks., , , , , , , , , и 2 other автор(ы). Medical Imaging: Computer-Aided Diagnosis, том 10575 из SPIE Proceedings, стр. 105750E. SPIE, (2018)Precentral gyrus discrepancy in electronic versions of the Talairach atlas., , и . NeuroImage, 21 (1): 450-455 (2004)Federated Learning for Brain Tumor Segmentation Using MRI and Transformers., , , , , , , , и . BrainLes@MICCAI (2), том 12963 из Lecture Notes in Computer Science, стр. 444-454. Springer, (2021)Changes in resting state MRI networks from a single season of football distinguishes controls, low, and high head impact exposure., , , , , , , , , и 1 other автор(ы). ISBI, стр. 464-467. IEEE, (2017)Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks., , , , , , , , , и 1 other автор(ы). DLMIA/ML-CDS@MICCAI, том 10553 из Lecture Notes in Computer Science, стр. 151-159. Springer, (2017)Determining the Optimal Number of MEG Trials: A Machine Learning and Speech Decoding Perspective., , , , , и . BI, том 11309 из Lecture Notes in Computer Science, стр. 163-172. Springer, (2018)