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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Detalhes bibliográficos
Publicado no:Med Image Anal
Main Authors: Alansary, Amir, Oktay, Ozan, Li, Yuanwei, Le Folgoc, Loic, Hou, Benjamin, Vaillant, Ghislain, Kamnitsas, Konstantinos, Vlontzos, Athanasios, Glocker, Ben, Kainz, Bernhard, Rueckert, Daniel
Formato: Artigo
Idioma:Inglês
Publicado em: 2019
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Article
Acesso em linha: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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