Towards Effcient Label Fusion by Pre-Alignment of Training Data.
Label fusion is a multi-atlas segmentation approach that explicitly maintains and exploits the entire training dataset, rather than a parametric summary of it. Recent empirical evidence suggests that label fusion can achieve significantly better segmentation accuracy over classical parametric atlas...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/1721.1/135745 |