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Whole-Brain Connectivity in a Large Study of Huntington's Disease Gene Mutation Carriers and Healthy Controls.

F. Espinoza, J. Turner, V. Vergara, R. Miller, E. Mennigen, J. Liu, M. Misiura, J. Ciarochi, H. Johnson, J. Long, H. Bockholt, V. Magnotta, J. Paulsen, und V. Calhoun. Brain Connectivity, 8 (3): 166-178 (2018)

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L. Ahlgrimm

Eva Miller University of Stuttgart

Markus Miller University of Stuttgart

Lambert Theisen University of Stuttgart

Annika Liebgott

Automated reference-free assessment of MR image quality using an active learning approach: Comparison of Support Vector Machine versus Deep Neural Network classificationS. Gatidis, A. Liebgott, M. Schwartz, P. Martirosian, F. Schick, K. Nikolaou, B. Yang, und T. Küstner. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA, (April 2017)

Automated reference-free assessment of MR image quality using an active learning approach: Comparison of Support Vector Machine versus Deep Neural Network classificationS. Gatidis, A. Liebgott, M. Schwartz, P. Martirosian, F. Schick, K. Nikolaou, B. Yang, und T. Küstner. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA, (April 2017)An easy-to-use image labeling platform for automatic Magnetic Resonance Image Quality AssessmentT. Küstner, P. Wolf, M. Schwartz, A. Liebgott, F. Schick, S. Gatidis, und B. Yang. Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, (April 2017)Automated image quality assessment in whole-body MRIS. Gatidis, A. Liebgott, H. Schmidt, N. Schwenzer, P. Martirosian, K. Nikolaou, F. Schick, B. Yang, und T. Küstner. Proceedings of the Radiological Society of North America (RSNA), Chicago, USA, (November 2016)

Weitere Publikationen von Autoren mit dem selben Namen

Classification of schizophrenia and bipolar patients using static and time-varying resting-state FMRI brain connectivity.B. Rashid, M. Arbabshirani, E. Damaraju, R. Miller, M. Çetin, G. Pearlson, und V. Calhoun. ISBI, Seite 251-254. IEEE, (2015)Characterization of connectivity dynamics in intrinsic brain networks.V. Calhoun, M. Yaesoubi, B. Rashid, und R. Miller. GlobalSIP, Seite 831-834. IEEE, (2013)Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications.A. Hunter, B. Moore, M. Mudunuru, V. Chau, R. Miller, R. Tchoua, C. Nyshadham, S. Karra, D. O'Malley, E. Rougier und 2 andere Autor(en). CoRR, (2018)A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study.B. Rashid, J. Chen, I. Rashid, E. Damaraju, J. Liu, R. Miller, O. Agcaoglu, T. van Erp, K. Lim, J. Turner und 9 andere Autor(en). NeuroImage, (2019)Replicability of time-varying connectivity patterns in large resting state fMRI samples.A. Abrol, E. Damaraju, R. Miller, J. Stephen, E. Claus, A. Mayer, und V. Calhoun. NeuroImage, (2017)A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information Flow.R. Miller, V. Vergara, D. Keator, und V. Calhoun. IEEE Trans. Biomed. Engineering, 63 (12): 2525-2539 (2016)Higher dimensional fMRI connectivity dynamics show reduced dynamism in schizophrenia patients.R. Miller, M. Yaesoubi, V. Calhoun, und S. Gopal. PRNI, Seite 1-4. IEEE, (2014)Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study.H. Xie, V. Calhoun, J. Gonzalez-Castillo, E. Damaraju, R. Miller, P. Bandettini, und S. Mitra. NeuroImage, 180 (Part): 495-504 (2018)Mutually temporally independent connectivity patterns: A new framework to study the dynamics of brain connectivity at rest with application to explain group difference based on gender.M. Yaesoubi, R. Miller, und V. Calhoun. NeuroImage, (2015)Time-varying frequency modes of resting fMRI brain networks reveal significant gender differences.M. Yaesoubi, R. Miller, T. Adali, und V. Calhoun. ICASSP, Seite 6310-6314. IEEE, (2016)