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Real-time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registration
With an aim to increase the capture range and accelerate the performance of state-of-the-art inter-subject and subject-to-template 3D rigid registration, we propose deep learning-based methods that are trained to find the 3D position of arbitrarily oriented subjects or anatomy in a canonical space b...
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| Publicado no: | IEEE Trans Med Imaging |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6438698/ https://ncbi.nlm.nih.gov/pubmed/30138909 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2018.2866442 |
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