Cargando…
A Contrast Augmentation Approach to Improve Multi-Scanner Generalization in MRI
Most data-driven methods are very susceptible to data variability. This problem is particularly apparent when applying Deep Learning (DL) to brain Magnetic Resonance Imaging (MRI), where intensities and contrasts vary due to acquisition protocol, scanner- and center-specific factors. Most publicly a...
Autores principales: | Meyer, Maria Ines, de la Rosa, Ezequiel, Pedrosa de Barros, Nuno, Paolella, Roberto, Van Leemput, Koen, Sima, Diana M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8439197/ https://www.ncbi.nlm.nih.gov/pubmed/34531715 http://dx.doi.org/10.3389/fnins.2021.708196 |
Ejemplares similares
-
Automated MRI volumetry as a diagnostic tool for Alzheimer's disease: Validation of icobrain dm
por: Struyfs, Hanne, et al.
Publicado: (2020) -
SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining
por: Billot, Benjamin, et al.
Publicado: (2023) -
First-Pass Contrast-Enhanced Myocardial Perfusion MRI in Mice on a 3-T Clinical MR Scanner
por: Makowski, Marcus, et al.
Publicado: (2010) -
A portable scanner for brain MRI
por: Cooley, Clarissa Z., et al.
Publicado: (2020) -
Editorial: Computational Neuroimage Analysis Tools for Brain (Diseases) Biomarkers
por: Sima, Diana M., et al.
Publicado: (2022)