PUMA

academical publication management
collect, organize, and share publications

( en | de )

 

Disambiguation of "Miller, Robyn L."

Author of the publication

copydeleteadd this publication to your clipboard
Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder.

, , , , , , , , , , , , , and . Brain Connect., 11 (10): 838-849 (2021)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

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 classification, , , , , , , and . 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 classification, , , , , , , and . 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 Assessment, , , , , , and . Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, (April 2017)Automated image quality assessment in whole-body MRI, , , , , , , , and . Proceedings of the Radiological Society of North America (RSNA), Chicago, USA, (November 2016)
 

Other publications of authors with the same name

Characterization of connectivity dynamics in intrinsic brain networks., , , and . GlobalSIP, page 831-834. IEEE, (2013)Classification of schizophrenia and bipolar patients using static and time-varying resting-state FMRI brain connectivity., , , , , , and . ISBI, page 251-254. IEEE, (2015)A Method for Intertemporal Functional-Domain Connectivity Analysis: Application to Schizophrenia Reveals Distorted Directional Information Flow., , , and . IEEE Trans. Biomed. Engineering, 63 (12): 2525-2539 (2016)A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study., , , , , , , , , and 9 other author(s). NeuroImage, (2019)Replicability of time-varying connectivity patterns in large resting state fMRI samples., , , , , , and . NeuroImage, (2017)Reduced-Order Modeling through Machine Learning Approaches for Brittle Fracture Applications., , , , , , , , , and 2 other author(s). CoRR, (2018)Higher dimensional fMRI connectivity dynamics show reduced dynamism in schizophrenia patients., , , and . PRNI, page 1-4. IEEE, (2014)Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study., , , , , , and . 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., , and . NeuroImage, (2015)Time-varying frequency modes of resting fMRI brain networks reveal significant gender differences., , , and . ICASSP, page 6310-6314. IEEE, (2016)