Rekonstruktion und Clustering neuronaler Bahnen

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.

Partners

External Funding

  • DFG Research Grant, “Novel Deep Learning Approaches for Analyzing Diffusion Imaging Data”, Project nr. 417063796
  • DFG IGRK 2150, “The Neuroscience of Modulating Aggression and Impulsivity in Psychopathology”, Project nr. 269953372

Contact


Publications

2022

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)