Fast MRI whole brain segmentation with fully convolutional neural networks
Roy AG, Conjeti S, Navab N, Wachinger C (2018)
Publication Type: Conference contribution
Publication year: 2018
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 0
Pages Range: 42-
Conference Proceedings Title: Informatik aktuell
Event location: Erlangen, DEU
ISBN: 9783540295945
DOI: 10.1007/978-3-662-56537-7_26
Abstract
Whole brain segmentation from structural MRI-T1 scan is a prerequisite for most morphological analyses, but requires hours of processing time and therefore delays the availability of image markers after scan acquisition. We introduced a fully convolution neural network (F-CNN) that segments a brain scan in several seconds [1]. Training deep F-CNNs for semantic image segmentation requires access to abundant labeled data.
Involved external institutions
Germany (DE)How to cite
APA:
Roy, A.G., Conjeti, S., Navab, N., & Wachinger, C. (2018). Fast MRI whole brain segmentation with fully convolutional neural networks. In Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus H. Maier-Hein, Christoph Palm, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 42-). Erlangen, DEU: Springer Science and Business Media Deutschland GmbH.
MLA:
Roy, Abhijit Guha, et al. "Fast MRI whole brain segmentation with fully convolutional neural networks." Proceedings of the Workshop on Bildverarbeitung fur die Medizin, 2018, Erlangen, DEU Ed. Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus H. Maier-Hein, Christoph Palm, Thomas Tolxdorff, Springer Science and Business Media Deutschland GmbH, 2018. 42-.
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