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 - TY - CHAP A1 - Gómez, Pedro A. A1 - Sperl, Jonathan I. A1 - Sprenger, Tim A1 - Metzler-Baddeley, Claudia A1 - Jones, Derek K. A1 - Saemann, Philipp A1 - Czisch, Michael A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. ED - Handels, Heinz ED - Deserno, Thomas M. ED - Meinzer, Hans-Peter ED - Tolxdorff, Thomas T1 - Joint Reconstruction of Multi-Contrast MRI for Multiple Sclerosis Lesion Segmentation T2 - Bildverarbeitung für die Medizin 2015, Algorithmen – Systeme – Anwendungen, Proceedings des Workshops vom 15. bis 17. März 2015 in Lübeck UR - https://doi.org/10.1007/978-3-662-46224-9_28 Y1 - 2015 UR - https://doi.org/10.1007/978-3-662-46224-9_28 SN - 978-3-662-46224-9 SN - 978-3-662-46223-2 N1 - Die vollständige Angabe der Autorinnen und Autoren findet sich im PDF. SP - 155 EP - 160 PB - Springer Vieweg CY - Berlin 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 - Gómez Damián, Pedro A. A1 - Sperl, Jonathan I. A1 - Janich, Martin A. A1 - Khegai, Oleksandr A1 - Wiesinger, Florian A1 - Glaser, Steffen J. A1 - Haase, Axel A1 - Schwaiger, Markus A1 - Schulte, Rolf F. A1 - Menzel, Marion Irene T1 - Multisite Kinetic Modeling of 13C Metabolic MR Using [1-13C]Pyruvate JF - Radiology Research and Practice N2 - Hyperpolarized13C imaging allows real-timein vivomeasurements of metabolite levels. Quantification of metabolite conversion between [1-13C]pyruvate and downstream metabolites [1-13C]alanine, [1-13C]lactate, and [13C]bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multisite, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multisite model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multisite model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues. UR - https://doi.org/10.1155/2014/871619 Y1 - 2014 UR - https://doi.org/10.1155/2014/871619 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-41646 SN - 2090-195X VL - 2014 PB - Hindawi CY - New York ER - TY - CHAP A1 - Golkov, Vladimir A1 - Sperl, Jonathan I. A1 - Menzel, Marion Irene A1 - Sprenger, Tim A1 - Tan, Ek Tsoon A1 - Marinelli, Luca A1 - Hardy, Christopher J. A1 - Haase, Axel A1 - Cremers, Daniel ED - O'Donnell, Lauren ED - Nedjati-Gilan, Gemma ED - Rathi, Yogesh ED - Reisert, Marco ED - Schneider, Torben T1 - Joint Super-Resolution Using Only One Anisotropic Low-Resolution Image per q-Space Coordinate T2 - Computational Diffusion MRI, MICCAI Workshop, Boston, MA, USA, September 2014 UR - https://doi.org/10.1007/978-3-319-11182-7_16 Y1 - 2014 UR - https://doi.org/10.1007/978-3-319-11182-7_16 SN - 978-3-319-11182-7 SN - 978-3-319-11181-0 SP - 181 EP - 191 PB - Springer CY - Cham ER - TY - CHAP A1 - Ulas, Cagdas A1 - Gómez, Pedro A. A1 - Krahmer, Felix A1 - Sperl, Jonathan I. A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. ED - Zuluaga, Maria A. ED - Bhatia, Kanwal ED - Kainz, Bernhard ED - Moghari, Mehdi H. ED - Pace, Danielle F. T1 - Robust Reconstruction of Accelerated Perfusion MRI Using Local and Nonlocal Constraints T2 - Reconstruction, Segmentation, and Analysis of Medical Images, First International Workshops, RAMBO 2016 and HVSMR 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers UR - https://doi.org/10.1007/978-3-319-52280-7_4 Y1 - 2017 UR - https://doi.org/10.1007/978-3-319-52280-7_4 SN - 978-3-319-52280-7 SN - 978-3-319-52279-1 SP - 37 EP - 47 PB - Springer CY - Cham ER - TY - CHAP A1 - Gómez, Pedro A. A1 - Ulas, Cagdas A1 - Sperl, Jonathan I. A1 - Sprenger, Tim A1 - Molina-Romero, Miguel A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. ED - Wu, Guorong ED - Coupé, Pierrick ED - Zhan, Yiqiang ED - Munsell, Brent ED - Rueckert, Daniel T1 - Learning a Spatiotemporal Dictionary for Magnetic Resonance Fingerprinting with Compressed Sensing T2 - Patch-Based Techniques in Medical Imaging, First International Workshop, Patch-MI 2015, Held in Conjunction with MICCAI 2015 Munich, Germany, October 9, 2015 Revised Selected Papers UR - https://doi.org/10.1007/978-3-319-28194-0_14 Y1 - 2016 UR - https://doi.org/10.1007/978-3-319-28194-0_14 SN - 978-3-319-28194-0 SN - 978-3-319-28193-3 SP - 112 EP - 119 PB - Springer CY - Cham ER - TY - JOUR A1 - Tan, Ek Tsoon A1 - Marinelli, Luca A1 - Sperl, Jonathan I. A1 - Menzel, Marion Irene A1 - Hardy, Christopher J. T1 - Multi‐directional anisotropy from diffusion orientation distribution functions JF - Journal of Magnetic Resonance Imaging UR - https://doi.org/10.1002/jmri.24589 Y1 - 2014 UR - https://doi.org/10.1002/jmri.24589 SN - 1522-2586 SN - 1053-1807 VL - 41 IS - 3 SP - 841 EP - 850 PB - Wiley CY - New York ER - TY - CHAP A1 - Gómez, Pedro A. A1 - Molina-Romero, Miguel A1 - Ulas, Cagdas A1 - Bounincontri, Guido A1 - Sperl, Jonathan I. A1 - Jones, Derek K. A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. ED - Ourselin, Sebastien ED - Joskowicz, Leo ED - Sabuncu, Mert R. ED - Unal, Gozde ED - Wells, William M. T1 - Simultaneous Parameter Mapping, Modality Synthesis, and Anatomical Labeling of the Brain with MR Fingerprinting T2 - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016, 19th International Conference, Athens, Greece, October 17–21, 2016, Proceedings, Part III UR - https://doi.org/10.1007/978-3-319-46726-9_67 Y1 - 2016 UR - https://doi.org/10.1007/978-3-319-46726-9_67 SN - 978-3-319-46726-9 SN - 978-3-319-46725-2 SP - 579 EP - 586 PB - Springer CY - Cham ER - TY - JOUR A1 - Lacerda, Luis M. A1 - Sperl, Jonathan I. A1 - Menzel, Marion Irene A1 - Sprenger, Tim A1 - Barker, Gareth J. A1 - Dell'Acqua, Flavio T1 - Diffusion in realistic biophysical systems can lead to aliasing effects in diffusion spectrum imaging JF - Magnetic Resonance in Medicine N2 - Purpose Diffusion spectrum imaging (DSI) is an imaging technique that has been successfully applied to resolve white matter crossings in the human brain. However, its accuracy in complex microstructure environments has not been well characterized. Theory and Methods Here we have simulated different tissue configurations, sampling schemes, and processing steps to evaluate DSI performances' under realistic biophysical conditions. A novel approach to compute the orientation distribution function (ODF) has also been developed to include biophysical constraints, namely integration ranges compatible with axial fiber diffusivities. Results Performed simulations identified several DSI configurations that consistently show aliasing artifacts caused by fast diffusion components for both isotropic diffusion and fiber configurations. The proposed method for ODF computation showed some improvement in reducing such artifacts and improving the ability to resolve crossings, while keeping the quantitative nature of the ODF. Conclusion In this study, we identified an important limitation of current DSI implementations, specifically the presence of aliasing due to fast diffusion components like those from pathological tissues, which are not well characterized, and can lead to artifactual fiber reconstructions. To minimize this issue, a new way of computing the ODF was introduced, which removes most of these artifacts and offers improved angular resolution. UR - https://doi.org/10.1002/mrm.26080 Y1 - 2015 UR - https://doi.org/10.1002/mrm.26080 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-44426 SN - 1522-2594 SN - 0740-3194 VL - 76 IS - 6 SP - 1837 EP - 1847 PB - Wiley CY - Hoboken ER - 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 - JOUR A1 - Sprenger, Tim A1 - Sperl, Jonathan I. A1 - Fernandez, Brice A1 - Haase, Axel A1 - Menzel, Marion Irene T1 - Real valued diffusion‐weighted imaging using decorrelated phase filtering JF - Magnetic Resonance in Medicine UR - https://doi.org/10.1002/mrm.26138 Y1 - 2016 UR - https://doi.org/10.1002/mrm.26138 SN - 1522-2594 SN - 0740-3194 VL - 77 IS - 2 SP - 559 EP - 570 PB - Wiley CY - Hoboken 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 - JOUR A1 - Sperl, Jonathan I. A1 - Sprenger, Tim A1 - Tan, Ek Tsoon A1 - Menzel, Marion Irene A1 - Hardy, Christopher J. A1 - Marinelli, Luca T1 - Model‐based denoising in diffusion‐weighted imaging using generalized spherical deconvolution JF - Magnetic Resonance in Medicine UR - https://doi.org/10.1002/mrm.26626 Y1 - 2017 UR - https://doi.org/10.1002/mrm.26626 SN - 1522-2594 VL - 78 IS - 6 SP - 2428 EP - 2438 PB - Wiley CY - Hoboken ER -