FastSurfer - A fast and accurate deep learning based neuroimaging pipeline

By Leonie Henschel, Sailesh Conjeti, Santiago Estrada, Kersten Diers, Bruce Fischl, Martin Reuter. NeuroImage, 2019

630 citations recorded by the source corpus.

Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large cohort studies with thousands or tens of thousands of individuals. In this work we propose a fast and accurate deep learning based neuroimaging pipeline for the automated processing of structural human brain MRI scans, replicating FreeSurfer’s anatomical segmentation including surface reconstruction and cortical parcellation. To this end, we introduce an advanced deep learning architecture capable of whole-brain segmentation into 95 classes. The network architecture incorporates local and global competition via competitive dense blocks and competitive skip pathways, as well as multi-slice information aggregation that specifically tailor network performance towards accurate segmentation of both cortical and subcortical structures. Further, we perform fast cortical surface reconstruction and thickness analysis by introducing a spectral spherical embedding and by directly mapping the cortical labels from the image to the surface. This approach provides a full FreeSurfer alternative for volumetric analysis (in under 1 min) and surface-based thickness analysis (within only around 1 h runtime). For sustainability of this approach we perform extensive validation: we assert high segmentation accuracy on several unseen datasets, measure generalizability and demonstrate increased test-retest reliability, and high sensitivity to group differences in dementia.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/0fc49d07bcbc38dd7498fcd2e252fe6c5267e1d5

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In Cognitive Neuroscience

In Computer Vision and Pattern Recognition

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

The OpenNeuro resource for sharing of neuroscience data (2021, positive): “Other software publications using OpenNeuro data include FastSurfer ( Henschel et al., 2020 ) for structural MRI analysis, and Brainstorm ( Tadel et al., 2019 ) for MEG/EEG analysis.”
Nanomedicine-Driven Modulation of the Gut–Brain Axis: Innovative Approaches to Managing Chronic Inflammation in Alzheimer’s and Parkinson’s Disease (2025, unknown): “Additionally, preprocessing techniques like Freesurfer, commonly used for brain segmentation, are time-consuming and lack reproducibility across methods, posing challenges to scalability in clinical settings [149,158–160].”