Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models
Abstract Recently, several convolutional neural networks have been proposed not only for 2D images, but also for 3D and 4D volume segmentation. Nevertheless, due to the large data size of the latter, acquiring a sufficient amount of training annotations is much more strenuous than in 2D images. For...
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Auteurs principaux: | Dimitrios Bellos, Mark Basham, Tony Pridmore, Andrew P. French |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/a20a76b6c52f42b2aa60d53e45e0824b |
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