Cargando…
Brain Morphometry Estimation: From Hours to Seconds Using Deep Learning
Motivation: Brain morphometry from magnetic resonance imaging (MRI) is a promising neuroimaging biomarker for the non-invasive diagnosis and monitoring of neurodegenerative and neurological disorders. Current tools for brain morphometry often come with a high computational burden, making them hard t...
Autores principales: | Rebsamen, Michael, Suter, Yannick, Wiest, Roland, Reyes, Mauricio, Rummel, Christian |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7156625/ https://www.ncbi.nlm.nih.gov/pubmed/32322235 http://dx.doi.org/10.3389/fneur.2020.00244 |
Ejemplares similares
-
A Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis Derived From Deep Learning-Based Segmentation of T1w-MRI
por: Rebsamen, Michael, et al.
Publicado: (2022) -
Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation
por: Rebsamen, Michael, et al.
Publicado: (2020) -
Reliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosis
por: Rebsamen, Michael, et al.
Publicado: (2022) -
Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation
por: Rebsamen, Michael, et al.
Publicado: (2019) -
More Than Spikes: On the Added Value of Non-linear Intracranial EEG Analysis for Surgery Planning in Temporal Lobe Epilepsy
por: Müller, Michael, et al.
Publicado: (2022)