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Complementing canonical fMRI with functional Quantitative Susceptibility Mapping (fQSM) in modern neuroimaging research.

, , , , , , and . NeuroImage, (2021)

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Quantitative Scoring of Muscle Involvement in MRI of Neuromuscular Diseases., , , , , and . BIOIMAGING, page 100-105. SciTePress, (2015)Complementing canonical fMRI with functional Quantitative Susceptibility Mapping (fQSM) in modern neuroimaging research., , , , , , and . NeuroImage, (2021)Processing Magnetic Resonance Image Features with One-class Support Vector Machines - Investigation of the Autism Spectrum Disorder Heterogeneity., , , , , , and . BIOIMAGING, page 111-117. SciTePress, (2016)A Semiautomatic Image Processing Tool to Measure Small Structures in Magnetic Resonance Images of the Brain at 7 Tesla - Application to Hippocampus Subfields of Patients with Mild Cognitive Impairment., , , , , , , , and . BIOIMAGING, page 124-128. SciTePress, (2016)Subject-specific knee SAR prediction using a degenerate birdcage at 7T., , , , , , , and . MeMeA, page 1-5. IEEE, (2018)Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T., , , , , , , , , and 6 other author(s). NeuroImage, (2021)Female children with autism spectrum disorder: An insight from mass-univariate and pattern classification analyses., , , , , and . NeuroImage, 59 (2): 1013-1022 (2012)Residual learning for 3D motion corrected quantitative MRI: Robust clinical T1, T2 and proton density mapping., , , , , , , , , and 5 other author(s). MIDL, volume 143 of Proceedings of Machine Learning Research, page 618-632. PMLR, (2021)A non-invasive method for a quantitative evaluation of muscle involvement in MRI of Neuromuscular Diseases., , , , , and . MeMeA, page 74-78. IEEE, (2015)Investigating Time-Varying Brain Connectivity with Functional Magnetic Resonance Imaging using Sequential Monte Carlo., , , , , and . EUSIPCO, page 1-5. IEEE, (2019)