TY - JOUR A1 - Molina-Romero, Miguel A1 - Gómez, Pedro A. A1 - Sperl, Jonathan I. A1 - Czisch, Michael A1 - Sämann, Philipp G. A1 - Jones, Derek K. A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. T1 - A diffusion model-free framework with echo time dependence for free-water elimination and brain tissue microstructure characterization JF - Magnetic Resonance in Medicine N2 - Purpose The compartmental nature of brain tissue microstructure is typically studied by diffusion MRI, MR relaxometry or their correlation. Diffusion MRI relies on signal representations or biophysical models, while MR relaxometry and correlation studies are based on regularized inverse Laplace transforms (ILTs). Here we introduce a general framework for characterizing microstructure that does not depend on diffusion modeling and replaces ill-posed ILTs with blind source separation (BSS). This framework yields proton density, relaxation times, volume fractions, and signal disentanglement, allowing for separation of the free-water component. Theory and Methods Diffusion experiments repeated for several different echo times, contain entangled diffusion and relaxation compartmental information. These can be disentangled by BSS using a physically constrained nonnegative matrix factorization. Results Computer simulations, phantom studies, together with repeatability and reproducibility experiments demonstrated that BSS is capable of estimating proton density, compartmental volume fractions and transversal relaxations. In vivo results proved its potential to correct for free-water contamination and to estimate tissue parameters. Conclusion Formulation of the diffusion-relaxation dependence as a BSS problem introduces a new framework for studying microstructure compartmentalization, and a novel tool for free-water elimination. UR - https://doi.org/10.1002/mrm.27181 KW - blind source separation KW - brain microstructure KW - diffusion MRI KW - free-water elimination KW - MR relaxometry KW - non-negative matrix factorization Y1 - 2018 UR - https://doi.org/10.1002/mrm.27181 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-28210 SN - 1522-2594 VL - 80 IS - 5 SP - 2155 EP - 2172 PB - Wiley CY - Hoboken ER - TY - CHAP A1 - Golkov, Vladimir A1 - Sprenger, Tim A1 - Sperl, Jonathan I. A1 - Menzel, Marion Irene A1 - Czisch, Michael A1 - Sämann, Philipp G. A1 - Cremers, Daniel T1 - Model-free novelty-based diffusion MRI T2 - 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI) UR - https://doi.org/10.1109/ISBI.2016.7493489 Y1 - 2016 UR - https://doi.org/10.1109/ISBI.2016.7493489 SN - 978-1-4799-2349-6 SP - 1233 EP - 1236 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Golkov, Vladimir A1 - Dosovitskiy, Alexey A1 - Sperl, Jonathan I. A1 - Menzel, Marion Irene A1 - Czisch, Michael A1 - Sämann, Philipp G. A1 - Brox, Thomas A1 - Cremers, Daniel T1 - q-Space Deep Learning: Twelve-Fold Shorter and Model-Free Diffusion MRI Scans JF - IEEE Transactions on Medical Imaging UR - https://doi.org/10.1109/TMI.2016.2551324 Y1 - 2016 UR - https://doi.org/10.1109/TMI.2016.2551324 SN - 1558-254X SN - 0278-0062 VL - 35 IS - 5 SP - 1344 EP - 1351 PB - IEEE CY - New York ER - TY - JOUR A1 - Sprenger, Tim A1 - Sperl, Jonathan I. A1 - Fernandez, Brice A1 - Golkov, Vladimir A1 - Eidner, Ines A1 - Sämann, Philipp G. A1 - Czisch, Michael A1 - Tan, Ek Tsoon A1 - Hardy, Christopher J. A1 - Marinelli, Luca A1 - Haase, Axel A1 - Menzel, Marion Irene T1 - Bias and precision analysis of diffusional kurtosis imaging for different acquisition schemes JF - Magnetic Resonance in Medicine UR - https://doi.org/10.1002/mrm.26008 Y1 - 2016 UR - https://doi.org/10.1002/mrm.26008 SN - 1522-2594 SN - 0740-3194 VL - 76 IS - 6 SP - 1684 EP - 1696 PB - Wiley CY - Hoboken ER - TY - CHAP A1 - Golkov, Vladimir A1 - Dosovitskiy, Alexey A1 - Sämann, Philipp G. A1 - Sperl, Jonathan I. A1 - Sprenger, Tim A1 - Czisch, Michael A1 - Menzel, Marion Irene A1 - Gómez, Pedro A. A1 - Haase, Axel A1 - Brox, Thomas A1 - Cremers, Daniel ED - Navab, Nassir ED - Hornegger, Joachim ED - Wells, William M. ED - Frangi, Alejandro F. T1 - q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans T2 - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, 18th International Conference, Munich, Germany, October 5–9, 2015, Proceedings, Part I UR - https://doi.org/10.1007/978-3-319-24553-9_5 Y1 - 2015 UR - https://doi.org/10.1007/978-3-319-24553-9_5 SN - 978-3-319-24553-9 SN - 978-3-319-24552-2 SP - 37 EP - 44 PB - Springer CY - Cham ER -