Application
DL+DiReCT combines a deep learning-based neuroanatomy segmentation and cortex parcellation with a diffeomorphic registration technique to measure cortical thickness from T1-weighted magnetic resonance images.
Contributors
Michael Rebsamen1,2
Christian Rumme1
Mauricio Reyes3,4
Roland Wiest1
Richard McKinley1
Contact
michael.rebsamen@insel.ch
Estimated cost
Total price: Free
Progress
Stable v1
License: BSD 3
DL+DiReCT is a method using high-quality deep learning (DL) based neuroanatomy segmentations followed by diffeomorphic registration-based cortical thickness (DiReCT), yielding accurate and reliable cortical thickness measures in a short time. DiReCT is a known technique to derive such measures from non-surface-based volumetric tissue maps. ANTs provides an open-source method for estimating cortical thickness, derived by applying DiReCT to an atlas-based segmentation.
Accurate and reliable measures of cortical thickness from magnetic resonance imaging are an important biomarker to study neurodegenerative and neurological disorders.
Rebsamen, Michael, et al. “Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation.” Human brain mapping 41.17 (2020): 4804-4814.
Publications
Affiliations
1Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Inselspital, Bern University Hospital, Bern, Switzerland
2Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
3Insel Data Science Center, Inselspital, Bern University Hospital, Bern, Switzerland
4ARTORG Center for Biomedical Research, University of Bern, Bern, Switzerland