3D cephalometric landmark detection by multiple stage deep reinforcement learning
Abstract The lengthy time needed for manual landmarking has delayed the widespread adoption of three-dimensional (3D) cephalometry. We here propose an automatic 3D cephalometric annotation system based on multi-stage deep reinforcement learning (DRL) and volume-rendered imaging. This system consider...
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Autores principales: | , , , |
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Formato: | article |
Lenguaje: | EN |
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Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/14c3583b99004793a05cc73915f23c71 |
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