Author

L. Cutting

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 2

Signature Assays, Organisms & Methods

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Assay:imaging· 2 Research Focus:benchmarking· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:multiome· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

A. W. Anderson· 2 shared B. A. Landman· 2 shared A. T. Shafer· 1 shared B. Rogers· 1 shared C. Hansen· 1 shared D. Zald· 1 shared J. Blaber· 1 shared K. G. Schilling· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioengineering

A. W. Anderson

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2 papers

Recent·Most cited

Spatiospectral image processing workflow considerations for advanced MR spectroscopy of the brain

L. Y. Cai, S. N. Del Tufo, L. Barquero, M. D'Archangel, L. Sachs, L. Cutting, N. Glaser, S. Ghetti, S. S. Jaser, A. W. Anderson, L. C. Jordan, B. A. Landman

The paper describes a framework for processing advanced MR spectroscopy data, integrating with LCModel to improve spatial and spectral analysis of brain metabolites.

bioRxiv · Sep 7, 2023 · PreprintBioengineering

Distortion correction of diffusion weighted MRI without reverse phase-encoding scans or field-maps

K. G. Schilling, J. Blaber, C. Hansen, L. Cai, B. Rogers, A. W. Anderson, S. Smith, P. Kanakaraj, T. Rex, S. M. Resnick, A. T. Shafer, L. Cutting, N. Woodward, D. Zald, B. A. Landman

This study develops a deep learning method to correct diffusion MRI distortions without reverse phase-encoding scans or field maps, showing effective correction on diverse datasets.

bioRxiv · Jan 19, 2020 · PreprintBioengineering