Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation
Abstract The study explores end-to-end deep learning frameworks and ensemble methods to enhance the accuracy of anatomical landmark identification in cephalometric radiographs, crucial for precise cephalometric analysis and effective orthodontic treatment planning. The methodology is strategically d...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2024-11-01
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| Series: | Discover Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44163-024-00207-3 |
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