Daniel Güllmar
Affiliations: | Medical Physics Group | University Hospital Jena, Jena, Thüringen, Germany |
Area:
DTI, fMRI, EEGWebsite:
http://www.mrt.uni-jena.de/Daniel-Guellmar.16.0.htmlGoogle:
"Daniel Güllmar"Mean distance: 35622
Parents
Sign in to add mentor| Jürgen R. Reichenbach | grad student | 2002- | University Hospital Jena | |
| (Ph.D. supervisor) | ||||
| Jens Haueisen | grad student | 2002-2008 | University Hospital Jena | |
| (Ph.D. supervisor) | ||||
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Publications
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| Güllmar D, Hsu WC, Reichenbach JR. (2023) Predicting disease-related MRI patterns of multiple sclerosis through GAN-based image editing. Zeitschrift Fur Medizinische Physik |
| Sibgatulin R, Güllmar D, Deistung A, et al. (2022) Magnetic susceptibility anisotropy in normal appearing white matter in multiple sclerosis from single-orientation acquisition. Neuroimage. Clinical. 35: 103059 |
| Güllmar D, Jacobsen N, Deistung A, et al. (2022) Investigation of biases in convolutional neural networks for semantic segmentation using performance sensitivity analysis. Zeitschrift Fur Medizinische Physik |
| Sibgatulin R, Güllmar D, Deistung A, et al. (2021) In vivo assessment of anisotropy of apparent magnetic susceptibility in white matter from a single orientation acquisition. Neuroimage. 241: 118442 |
| Lopatina A, Ropele S, Sibgatulin R, et al. (2020) Investigation of Deep-Learning-Driven Identification of Multiple Sclerosis Patients Based on Susceptibility-Weighted Images Using Relevance Analysis. Frontiers in Neuroscience. 14: 609468 |
| de la Cruz F, Wagner G, Schumann A, et al. (2020) Interrelations between dopamine and serotonin producing sites and regions of the default mode network. Human Brain Mapping |
| Wolfram F, Güllmar D, Böttcher J, et al. (2019) Assessment of MR imaging during one-lung flooding in a large animal model. Magma (New York, N.Y.) |
| Hettwer W, Horstmann PF, Bischoff S, et al. (2019) Establishment and effects of allograft and synthetic bone graft substitute treatment of a critical size metaphyseal bone defect model in the sheep femur. Apmis : Acta Pathologica, Microbiologica, Et Immunologica Scandinavica. 127: 53-63 |
| Jacobsen N, Deistung A, Timmann D, et al. (2018) Analysis of intensity normalization for optimal segmentation performance of a fully convolutional neural network. Zeitschrift Fur Medizinische Physik |
| Schumann A, Köhler S, de la Cruz F, et al. (2018) The Use of Physiological Signals in Brainstem/Midbrain fMRI. Frontiers in Neuroscience. 12: 718 |