Inherent brain segmentation quality control from fully convnet monte carlo sampling
Roy AG, Conjeti S, Navab N, Wachinger C (2018)
Publication Type: Conference contribution
Publication year: 2018
Journal
Publisher: Springer Verlag
Book Volume: 11070 LNCS
Pages Range: 664-672
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Granada, ESP
ISBN: 9783030009274
DOI: 10.1007/978-3-030-00928-1_75
Abstract
We introduce inherent measures for effective quality control of brain segmentation based on a Bayesian fully convolutional neural network, using model uncertainty. Monte Carlo samples from the posterior distribution are efficiently generated using dropout at test time. Based on these samples, we introduce next to a voxel-wise uncertainty map also three metrics for structure-wise uncertainty. We then incorporate these structure-wise uncertainty in group analyses as a measure of confidence in the observation. Our results show that the metrics are highly correlated to segmentation accuracy and therefore present an inherent measure of segmentation quality. Furthermore, group analysis with uncertainty results in effect sizes closer to that of manual annotations. The introduced uncertainty metrics can not only be very useful in translation to clinical practice but also provide automated quality control and group analyses in processing large data repositories.
Involved external institutions
Ludwig-Maximilians-Universität (LMU)
Germany (DE)
Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE)
Germany (DE)
Technische Universität München (TUM)
Germany (DE)
Germany (DE)
Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE)
Germany (DE)
Technische Universität München (TUM)
Germany (DE)
How to cite
APA:
Roy, A.G., Conjeti, S., Navab, N., & Wachinger, C. (2018). Inherent brain segmentation quality control from fully convnet monte carlo sampling. In Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger, Alejandro F. Frangi (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 664-672). Granada, ESP: Springer Verlag.
MLA:
Roy, Abhijit Guha, et al. "Inherent brain segmentation quality control from fully convnet monte carlo sampling." Proceedings of the 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018, Granada, ESP Ed. Julia A. Schnabel, Christos Davatzikos, Carlos Alberola-López, Gabor Fichtinger, Alejandro F. Frangi, Springer Verlag, 2018. 664-672.
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