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Evaluating Reinforcement Learning Agents for Anatomical Landmark Detection
Automatic detection of anatomical landmarks is an important step for a wide range of applications in medical image analysis. Manual annotation of landmarks is a tedious task and prone to observer errors. In this paper, we evaluate novel deep reinforcement learning (RL) strategies to train agents tha...
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| Pubblicato in: | Med Image Anal |
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| Autori principali: | , , , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7610752/ https://ncbi.nlm.nih.gov/pubmed/30784956 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.media.2019.02.007 |
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