Ensemble of deep convolutional neural networks with Monte Carlo dropout sampling for automated image segmentation quality control and robust deep learning using small datasets
Recent progress on deep learning (DL)-based medical image segmentation can enable fast extraction of clinical parameters for efficient clinical workflows. However, current DL methods can still fail and require manual visual inspection of outputs, which is time-consuming and diminishes the advantages...
| Main Authors: | , , , , , |
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| 格式: | Conference item |
| 語言: | English |
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Springer
2021
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