DeepCSR: A 3D Deep Learning Approach for Cortical Surface Reconstruction
| Autor: | Jurgen Fripp, Léo Lebrat, Clinton Fookes, Olivier Salvado, Rodrigo Santa Cruz, Pierrick Bourgeat |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Surface (mathematics)
FOS: Computer and information sciences Artificial neural network business.industry Computer science Deep learning Computer Vision and Pattern Recognition (cs.CV) Feature extraction Image and Video Processing (eess.IV) Computer Science - Computer Vision and Pattern Recognition 020206 networking & telecommunications Pattern recognition 02 engineering and technology Electrical Engineering and Systems Science - Image and Video Processing 03 medical and health sciences 0302 clinical medicine Isosurface 0202 electrical engineering electronic engineering information engineering FOS: Electrical engineering electronic engineering information engineering Segmentation Artificial intelligence business 030217 neurology & neurosurgery Surface reconstruction Level of detail |
| Zdroj: | WACV |
| Popis: | The study of neurodegenerative diseases relies on the reconstruction and analysis of the brain cortex from magnetic resonance imaging (MRI). Traditional frameworks for this task like FreeSurfer demand lengthy runtimes, while its accelerated variant FastSurfer still relies on a voxel-wise segmentation which is limited by its resolution to capture narrow continuous objects as cortical surfaces. Having these limitations in mind, we propose DeepCSR, a 3D deep learning framework for cortical surface reconstruction from MRI. Towards this end, we train a neural network model with hypercolumn features to predict implicit surface representations for points in a brain template space. After training, the cortical surface at a desired level of detail is obtained by evaluating surface representations at specific coordinates, and subsequently applying a topology correction algorithm and an isosurface extraction method. Thanks to the continuous nature of this approach and the efficacy of its hypercolumn features scheme, DeepCSR efficiently reconstructs cortical surfaces at high resolution capturing fine details in the cortical folding. Moreover, DeepCSR is as accurate, more precise, and faster than the widely used FreeSurfer toolbox and its deep learning powered variant FastSurfer on reconstructing cortical surfaces from MRI which should facilitate large-scale medical studies and new healthcare applications. Accepted in 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) |
| Databáze: | OpenAIRE |
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