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Magnetization Transfer in Magnetic Resonance Fingerprinting [article]

Tom Hilbert, Ding Xia, Kai Tobias Block, Zidan Yu, Riccardo Lattanzi, Daniel K. Sodickson, Tobias Kober, Martijn A. Cloos
2019 arXiv   pre-print
[ 1 ] 1 Hilbert T, Kober T, Zhao T, et al. Mitigating the Effect of Magnetization Transfer in Magnetic Resonance Fingerprinting.  ... 
arXiv:1907.13262v1 fatcat:c3c4etealbdcfdn7t7jnvh2uci

Head motion detection using FID navigators

Tobias Kober, José P. Marques, Rolf Gruetter, Gunnar Krueger
2011 Magnetic Resonance in Medicine  
This work explores a concept for motion detection in brain MR examinations using high channel-count RF coil arrays. It applies ultrashort (<100 msec) free induction decay signals, making use of the knowledge that motion induces variations in these signals when compared to a reference free induction decay signal. As a proof-of-concept, the method was implemented in a standard structural MRI sequence. The stability of the free induction decay-signal was verified in phantom experiments. Human
more » ... iments demonstrated that the observed variations in the navigator data provide a sensitive measure for detection of relevant and common subject motion patterns. The proposed methodology provides a means to monitor subject motion throughout a MRI scan while causing little or no impact on the sequence timing and image contrast. It could hence complement available motion detection and correction methods, thus further reducing motion sensitivity in MR applications. Magn Reson Med 66:135-143,
doi:10.1002/mrm.22797 pmid:21337424 fatcat:k57baqrbtfcoznb4qjpraasvfi

Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI [article]

Uk-Su Choi, Hirokazu Kawaguchi, Yuichiro Matsuoka, Tobias Kober, Ikuhiro Kida
2018 bioRxiv   pre-print
We proposed a method for segmentation of brain tissues (gray matter, white matter, and cerebrospinal fluid) using multi-contrast images, including a T1 map and a uniform T1-weighted image, from a magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequence at 7 Tesla. The proposed method was evaluated with respect to the processing time and the similarity of the segmented masks of brain tissues with those obtained using FreeSurfer, FSL, and SPM12. The processing time of the
more » ... osed method (28 ± 0 s) was significantly shorter than those of FSL and SPM12 (444 ± 4 s and 159 ± 2 s for FSL and SPM12, respectively). In the similarity assessment, the tissue mask of the brain obtained by the proposed method showed higher consistency with those obtained by FSL than with those obtained by SPM12. The proposed method misclassified the subcortical structures and large vessels since it is based on the intensities of multi-contrast images obtained using MP2RAGE, which uses a similar segmentation approach as FSL but is not based on a template image or a parcellated brain atlas, which are used for FreeSurfer and SPM12, respectively. However, the proposed method showed good segmentation in the cerebellum and white matter in the medial part of the brain in comparison with the other methods. Thus, because the proposed method using different contrast images of MP2RAGE sequence showed the shortest processing time and similar segmentation ability as the other methods, it may be useful for both neuroimaging research and clinical diagnosis.
doi:10.1101/455576 fatcat:sdmpwrl3hbhchkmrie4bgtzivq

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Mário João Fartaria, Tobias Kober, Cristina Granziera, Meritxell Bach Cuadra
2019 NeuroImage: Clinical  
Another work in progress, not yet explored, is to use the quantitative T1 maps from MP2RAGE (Kober et al., 2012; Marques et al., 2010) .  ...  from the different contrasts were registered to MP2RAGE space and merged into a single mask which we considered the most comprehensive representation of lesion load per patient in both time points (Kober  ... 
doi:10.1016/j.nicl.2019.101938 pmid:31491829 pmcid:PMC6658829 fatcat:vdgusvsyg5gfjinnwtk3gfmrmu

Application of Automated Brain Segmentation and Fiber Tracking in Hemimegalencephaly

José Boto, Tobias Kober, Maria Isabel Vargas
2019 Canadian Journal of Neurological Sciences  
doi:10.1017/cjn.2018.381 pmid:30665473 fatcat:z3efjswnw5hvnao5ll3bu254e4

SA2RAGE: A new sequence for fast B1+-mapping

Florent Eggenschwiler, Tobias Kober, Arthur W. Magill, Rolf Gruetter, José P. Marques
2011 Magnetic Resonance in Medicine  
At high magnetic field strengths (!3T), the radiofrequency wavelength used in MRI is of the same order of magnitude of (or smaller than) the typical sample size, making transmit magnetic field (B þ 1 ) inhomogeneities more prominent. Methods such as radiofrequency-shimming and transmit SENSE have been proposed to mitigate these undesirable effects. A prerequisite for such approaches is an accurate and rapid characterization of the B þ 1 field in the organ of interest. In this work, a new
more » ... ensitive three-dimensional B þ 1 -mapping technique is introduced that allows the acquisition of a 64 3 64 3 8 B þ 1 -map in~20 s, yielding an accurate mapping of the relative B þ 1 with a 10-fold dynamic range (0.2-2 times the nominal B þ 1 ). Moreover, the predominant use of low flip angle excitations in the presented sequence minimizes specific absorption rate, which is an important asset for in vivo B þ 1shimming procedures at high magnetic fields. The proposed methodology was validated in phantom experiments and demonstrated good results in phantom and human B þ 1 -shimming using an 8-channel transmit-receive array. Magn Reson Med 67:1609-1619,
doi:10.1002/mrm.23145 pmid:22135168 fatcat:wbkfwvq3nzch5f6ac3rbvu44na

Fat fraction mapping using bSSFP Signal Profile Asymmetries for Robust multi-Compartment Quantification (SPARCQ) [article]

Giulia MC Rossi, Tom Hilbert, Adele LC Mackowiak, Katarzyna Pierzchała, Tobias Kober, Jessica AM Bastiaansen
2020 arXiv   pre-print
Purpose: To develop a novel quantitative method for detection of different tissue compartments based on bSSFP signal profile asymmetries (SPARCQ) and to provide a validation and proof-of-concept for voxel-wise water-fat separation and fat fraction mapping. Methods: The SPARCQ framework uses phase-cycled bSSFP acquisitions to obtain bSSFP signal profiles. For each voxel, the profile is decomposed into a weighted sum of simulated profiles with specific off-resonance and relaxation time ratios.
more » ... m the obtained set of weights, voxel-wise estimations of the fractions of the different components and their equilibrium magnetization are extracted. For the entire image volume, component-specific quantitative maps as well as banding-artifact-free images are generated. A SPARCQ proof-of-concept was provided for water-fat separation and fat fraction mapping. Noise robustness was assessed using simulations. A dedicated water-fat phantom was used to validate fat fractions estimated with SPARCQ against gold-standard 1H MRS. Quantitative maps were obtained in knees of six healthy volunteers, and SPARCQ repeatability was evaluated in scan rescan experiments. Results: Simulations showed that fat fraction estimations are accurate and robust for signal-to-noise ratios above 20. Phantom experiments showed good agreement between SPARCQ and gold-standard (GS) fat fractions (fF(SPARCQ) = 1.02*fF(GS) + 0.00235). In volunteers, quantitative maps and banding-artifact-free water-fat-separated images obtained with SPARCQ demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ fat fraction was 0.0512. Conclusion: The SPARCQ framework was proposed as a novel quantitative mapping technique for detecting different tissue compartments, and its potential was demonstrated for quantitative water-fat separation.
arXiv:2005.09734v1 fatcat:apwbyfnizrfobgkt5u52hcvpcq

Partial volume-aware assessment of multiple sclerosis lesions

Mário João Fartaria, Alexandra Todea, Tobias Kober, Kieran O'brien, Gunnar Krueger, Reto Meuli, Cristina Granziera, Alexis Roche, Meritxell Bach Cuadra
2018 NeuroImage: Clinical  
., 2015; Kober et al., 2012) .  ... 
doi:10.1016/j.nicl.2018.01.011 pmid:29868448 pmcid:PMC5984601 fatcat:nqfp5b2kxjgvpcrgittznir4di

Clinical equivalence assessment of T2 synthesized pediatric brain magnetic resonance imaging

Basile Kerleroux, Tobias Kober, Tom Hilbert, Maxence Serru, Jean Philippe, Dominique Sirinelli, Baptiste Morel
2018 Journal of neuroradiology  
T2 synthesized contrasts, which also provides quantitative T2 information that could be useful, could be suggested as an equivalent technique in pediatric neuro-imaging, compared to conventional TSE T2.
doi:10.1016/j.neurad.2018.04.003 pmid:29733917 fatcat:zc5ciuqa7vashancuwxy57vsmi

Motion compensated carotid MRI using FID navigators

Petter Dyverfeldt, Vibhas S Deshpande, Tobias Kober, Gunnar Krueger, David Saloner
2013 Journal of Cardiovascular Magnetic Resonance  
Motion compensated carotid MRI using FID navigators Petter Dyverfeldt 1,2* , Vibhas S Deshpande 3 , Tobias Kober 4 , Gunnar Krueger 4 , David Saloner 1, 5 From 16th Annual SCMR Scientific Sessions San  ...  Real-time navigator processing based on that described by Kober et al [2] delivered accept/reject-andreacquire decisions to the sequence and visual feedback to the scanner user-interface. 7 volunteers  ... 
doi:10.1186/1532-429x-15-s1-p242 pmcid:PMC3559924 fatcat:v7c7lmmgdjhl3jzvb44goyap5e

A Connectome-Based Comparison of Diffusion MRI Schemes

Xavier Gigandet, Alessandra Griffa, Tobias Kober, Alessandro Daducci, Guillaume Gilbert, Alan Connelly, Patric Hagmann, Reto Meuli, Jean-Philippe Thiran, Gunnar Krueger, Christian Beaulieu
2013 PLoS ONE  
Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion
more » ... ding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, qball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.
doi:10.1371/journal.pone.0075061 pmid:24073235 pmcid:PMC3779224 fatcat:56tyfomqi5efpjp5t4o7sd3tum

Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI

Uk-Su Choi, Hirokazu Kawaguchi, Yuichiro Matsuoka, Tobias Kober, Ikuhiro Kida, Viktor Vegh
2019 PLoS ONE  
Data curation: Uk-Su Choi, Hirokazu Kawaguchi, Tobias Kober, Ikuhiro Kida. Formal analysis: Uk-Su Choi. Funding acquisition: Ikuhiro Kida. Investigation: Uk-Su Choi, Yuichiro Matsuoka, Ikuhiro Kida.  ... 
doi:10.1371/journal.pone.0210803 pmid:30818328 pmcid:PMC6394968 fatcat:4wekn3tpqrgbrfd6bzyg6vp7n4

Model-Informed Machine Learning for Multi-component T2 Relaxometry [article]

Thomas Yu, Erick Jorge Canales Rodriguez, Marco Pizzolato, Gian Franco Piredda, Tom Hilbert, Elda Fischi-Gomez, Matthias Weigel, Muhamed Barakovic, Meritxell Bach-Cuadra, Cristina Granziera, Tobias Kober, Jean-Philippe Thiran
2020 arXiv   pre-print
Recovering the T2 distribution from multi-echo T2 magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to combine machine learning and aspects of parametric (fitting from the MRI signal using biophysical models) and non-parametric (model-free fitting of the T2 distribution from the signal) approaches to T2 relaxometry in brain tissue by using a
more » ... ulti-layer perceptron (MLP) for the distribution reconstruction. For training our network, we construct an extensive synthetic dataset derived from biophysical models in order to constrain the outputs with a priori knowledge of in vivo distributions. The proposed approach, called Model-Informed Machine Learning (MIML), takes as input the MR signal and directly outputs the associated T2 distribution. We evaluate MIML in comparison to non-parametric and parametric approaches on synthetic data, an ex vivo scan, and high-resolution scans of healthy subjects and a subject with Multiple Sclerosis. In synthetic data, MIML provides more accurate and noise-robust distributions. In real data, MWF maps derived from MIML exhibit the greatest conformity to anatomical scans, have the highest correlation to a histological map of myelin volume, and the best unambiguous lesion visualization and localization, with superior contrast between lesions and normal appearing tissue. In whole-brain analysis, MIML is 22 to 4980 times faster than non-parametric and parametric methods, respectively.
arXiv:2007.10225v1 fatcat:n3qimwaw4rc67edcdy4soi2m4q

Multi T1-weighted contrast imaging and T1 mapping with Compressed sensing FLAWS at 3T [article]

Jeremy Beaumont, Jurgen Fripp, Parnesh Raniga, Oscar Acosta, Jean-Christophe Ferre, Katie McMahon, Julie Trinder, Tobias Kober, Giulio Gambarota
2021 bioRxiv   pre-print
Conflict of interest Tobias Kober is fully employed at Siemens Healthcare, Switzerland. None of the other authors has any conflict of interest to disclose.  ... 
doi:10.1101/2021.12.18.473283 fatcat:fe4pvj4h55dmvkbns6utzsjs6e

Basic MR sequence parameters systematically bias automated brain volume estimation

Sven Haller, Pavel Falkovskiy, Reto Meuli, Jean-Philippe Thiran, Gunnar Krueger, Karl-Olof Lovblad, Tobias Kober, Alexis Roche, Bénédicte Marechal
2016 Neuroradiology  
Synopsis Standard MR parameters, notably spatial resolution, contrast and image filtering, systematically bias results of automated brain MRI morphometry by up to 4.8%. This is in the same range as early disease-related brain volume alterations, for example in Alzheimer's disease. Automated brain segmentation software packages should therefore require strict MR parameter selection or include compensatory algorithms to avoid MR-parameter-related bias of brain morphometry results.
doi:10.1007/s00234-016-1737-3 pmid:27623782 fatcat:6s47beabxbdyrhlb2v4t7xz2d4
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