Segmented Trajectory Optimization of Flexible Needles Based on Deep Reinforcement Learning
Minimally invasive liver tumor ablation relies heavily on safe and accurate flexible needle trajectory planning. Traditional methods optimize the entire path uniformly and ignore distinct clinical requirements of extrahepatic and intrahepatic tissues. They also suffer from premature convergence in c...
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| Principais autores: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2026-01-01
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| Colecção: | IEEE Access |
| Assuntos: | |
| Acesso em linha: | https://ieeexplore.ieee.org/document/11509322/ |
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