Building an Interactive paper supplement with Google Colab and the Open Science Foundation

For a paper we recently submitted (Improving FLAIR SAR efficiency at 7T by adaptive tailoring of adiabatic pulse power using deep convolutional neural networks – pre-print here: https://arxiv.org/abs/1911.08118 and published article here: https://doi.org/10.1002/mrm.28590) I was wondering if we can do more than just provide the source code. One problem I Read more…

Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities

NMR in Biomedicine published our special issue review article, summarising and discussing the recent developments in deep learning QSM. The paper is here: https://onlinelibrary.wiley.com/doi/abs/10.1002/nbm.4292 The preprint is here: https://arxiv.org/abs/1912.05410 We also created a github repository collecting implementations of deep learning QSM algorithms that we are keeping updated regularly: https://github.com/dlQSM/dlQSM

Non-linear Realignment Using Minimum Deformation Averaging for Single-subject fMRI at Ultra-high Field

Motion dominates the contribution to variance in fMRI time series and it is therefore important to account for this variability correctly. Currently, most correction schemes use a rigid body realignment procedure, but interactions with magnetic field inhomogeneities and physiological fluctuations lead to non-linear deformations. Non-linear realignment increased spatial resolution by Read more…