Selective labeling: identifying representative sub-volumes for interactive segmentation
Automatic segmentation of challenging biomedical volumes with multiple objects is still an open research field. Automatic approaches usually require a large amount of training data to be able to model the complex and often noisy appearance and structure of biological organelles and their boundaries....
| Main Authors: | , , |
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| Format: | Article |
| Published: |
Springer Verlag
2016
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/44843/ |