Diffusion Imaging for the Reconstruction of Neural Pathways
Motivation
Diffusion imaging (based on magnetic resonance imaging) can be used to obtain information about the course of neuronal pathways. Neuronal pathways are important structures in the brain that are associated with integrative functions, e.g., motor or sensory. In neurosurgery, diffusion imaging is of great value, because in case of pathological changes (tumor) during brain surgery, the neural pathways must not be injured in order to avoid neurological deficits.
However, reconstruction of neuronal structures from DT-MRI data is not trivial due to the complexity of the diffusion information available. Our research in this area focuses on the application of deep learning for diffusion imaging, in particular harmonization between different scanners, reconstruction of the signal using compressed sensing, and tracking and clustering of neural pathways as reliably as possible.
Theses
New theses are regularly advertised in the area of Diffusion Imaging. In addition to the general overview, there are also numerous topics that have not yet been advertised, which will be gladly presented in a personal conversation.
Leon Weninger, Mushawar Ahmad and Dorit Merhof From supervised to unsupervised harmonization of diffusion MRI acquisitions In: IEEE International Symposium on Biomedical Imaging (ISBI)
2022
Leon Weninger, Jarek Ecke, Na, Chuh-Hyoun Na, Kerstin Jütten and Dorit Merhof Diffusion MRI Specific Pretraining by Self-Supervision on an Auxiliary Dataset In: Bildverarbeitung fuer die Medizin (BVM)
2021
Kerstin Jütten, Leon Weninger, Verena Mainz, Siegfried Gauggel, Ferdinand Binkofski, Martin Wiesmann, Dorit Merhof, Hans Clusmann, Chuh-Hyoun Na Dissociation of structural and functional connectomic coherence in glioma patients In: Scientific Reports 11 (16790)
2021
Leon Weninger, Maxim Drobjazko, Na, Chuh-Hyoun Na, Kerstin Jütten and Dorit Merhof Autoencoder-based quality assessment for synthetic diffusion-MRI data In: Bildverarbeitung fuer die Medizin (BVM)
2020
Leon Weninger, Chuh-Hyoun Na, Kerstin Jütten, Dorit Merhof Analyzing the effects of free water modeling by deep learning on diffusion MRI structural connectivity estimates in glioma patients In: PLOS ONE 15 (9)
2019
Leon Weninger, Simon Koppers, Chuh-Hyoun Na, Kerstin Juetten and Dorit Merhof Free-Water Correction in Diffusion MRI: A Reliable and Robust Learning Approach In: MICCAI Workshop on Computational Diffusion MRI (CDMRI)
2019
Chantal MW Tax, Francesco Grussu, Enrico Kaden, Lipeng Ning, Umesh Rudrapatna, John Evans, Samuel St-Jean, Alexander Leemans, Simon Koppers, Dorit Merhof, others Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms In: NeuroImage
2018
Simon Koppers, Luke Bloy, Jeffrey I. Berman, Chantal M.W. Tax, J. Christopher Edgar and Dorit Merhof Spherical Harmonic Residual Network for Diffusion Signal Harmonization In: MICCAI Workshop on Computational Diffusion MRI (CDMRI)
2017
Simon Koppers, Matthias Friedrichs and Dorit Merhof Reconstruction of Diffusion Anisotropies using 3D Deep Convolutional Neural Networks in Diffusion Imaging In: Modeling, Analysis, and Visualization of Anisotropy
2017
Simon Koppers, Christoph Haarburger, J. Christopher Edgar and Dorit Merhof Reliable Estimation of the Number of Compartments in Diffusion MRI In: Bildverarbeitung für die Medizin (BVM)
2016
Simon Koppers, Christoph Haarburger and Dorit Merhof Diffusion MRI Signal Augmentation - From Single Shell to Multi Shell with Deep Learning In: MICCAI Workshop on Computational Diffusion MRI (CDMRI)
2016
Simon Koppers and Dorit Merhof Direct Estimation of Fiber Orientations using Deep Learning in Diffusion Imaging In: MICCAI Workshop on Machine Learning in Medical Imaging (MLMI)
2016
Simon Koppers and Dorit Merhof Qualitative Comparison of Reconstruction Algorithms for Diffusion Imaging In: Visualization of the Brain and its Pathologies – Technical and Neurosurgical Aspects
2016
Simon Koppers, Christoph Hebisch and Dorit Merhof A Feature Selection Framework for White Matter Fiber Clustering Based on Normalized Cuts In: Bildverarbeitung für die Medizin (BVM)
2015
Simon Koppers, Thomas Schultz and Dorit Merhof Spherical Ridgelets for Multi-Diffusion-Tensor Refinement - Concept and Evaluation In: Bildverarbeitung für die Medizin (BVM)
2013
Daniela Kuhnt, Miriam H.A. Bauer, Jens Sommer, Dorit Merhof and Christopher Nimsky Optic Radiation Fiber Tractography in Glioma Patients Based on High Angular Resolution Diffusion Imaging with Compressed Sensing Compared with Diffusion Tensor Imaging - Initial Experience In: PLoS ONE 8 (7)
2013
Daniela Kuhnt, Miriam H. Bauer, Jan Egger, Mirco Richter, Tina Kapur, Jens Sommer, Dorit Merhof and Christopher Nimsky Fiber Tractography Based on Diffusion Tensor Imaging Compared with High-Angular-Resolution Diffusion Imaging with Compressed Sensing: Initial Experience In: Neurosurgery 72 (Suppl 1)
2013
Mirco Richter, Amir Zolal, Oliver Ganslandt, Michael Buchfelder, Christopher Nimsky, Dorit Merhof Evaluation of diffusion-tensor imaging-based global search and tractography for tumor surgery close to the language system. In: PLOS ONE 8 (1)
2007
Dorit Merhof, Grzegorz Soza, Andreas Stadlbauer, Günther Greiner, Christopher Nimsky Correction of susceptibility artifacts in diffusion tensor data using non-linear registration
In: Medical Image Analysis 11 (6)
2006
Dorit Merhof, Markus Sonntag, Frank Enders, Christopher Nimsky, Peter Hastreiter, Günther Greiner Hybrid Visualization for White Matter Tracts using Triangle Strips and Point Sprites
In: IEEE Transactions on Visualization and Computer Graphics 12 (5)
2006
Dorit Merhof, Mirco Richter, Frank Enders, Peter Hastreiter, Oliver Ganslandt, Michael Buchfelder, Christopher Nimsky, Günther Greiner Fast and Accurate Connectivity Analysis between Functional Regions based on DT-MRI
In: Medical Image Computing and Computer Assisted Intervention (MICCAI)
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