Author

Torben Schneider

Philips (United Kingdom)ORCID 0000-0003-4130-7220Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:multiome· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Assay:imaging· 1 Approach:matrix factorization· 1

Frequent Co-Authors

Claudia A. M. Gandini Wheeler‐KingshottiD· 2 shared Daniel C. AlexanderiD· 2 shared Francesco GrussuiD· 2 shared Marco BattistoniD· 2 shared Dmitry S. NovikoviD· 1 shared Els FieremansiD· 1 shared Jelle VeraartiD· 1 shared Julien Cohen‐AdadiD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

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10 top collaborators · 40 mutual co-author links

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2 shared papersNeuroscience

Claudia A. M. Gandini Wheeler‐KingshottORCID

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2 papers

Recent·Most cited

NeuroscienceMathematics and visualizationPeer-reviewedJan 1, 2021

Deep learning model fitting for diffusion-relaxometry: a comparative study

Francesco Grussu, Marco Battiston, Marco Palombo…·Daniel C. Alexander

This study compares two deep learning strategies for qMRI signal model fitting, finding that strategy 2 is more practical but may yield less accurate parameter estimation.

26 citationstop 1%

multiomedeep learning

𝕏 PostBluesky

NeuroscienceNeuroImagePeer-reviewedApr 29, 2020

Multi-parametric quantitative spinal cord MRI with unified signal readout and image denoising

Francesco Grussu, Marco Battiston, Jelle Veraart…·Claudia A. M. Gandini Wheeler‐Kingshott

This paper introduces a unified signal readout approach for multi-parametric spinal cord MRI, combined with MP-PCA denoising, improving the quality and consistency of microstructural metrics.

46 citations

multiomeimaging

𝕏 PostBluesky