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3D Transrectal Ultrasound (TRUS) Prostate Segmentation Based on Optimal Feature Learning Framework
We propose a 3D prostate segmentation method for transrectal ultrasound (TRUS) images, which is based on patch-based feature learning framework. Patient-specific anatomical features are extracted from aligned training images and adopted as signatures for each voxel. The most robust and informative f...
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| Publicado no: | Proc SPIE Int Soc Opt Eng |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6715140/ https://ncbi.nlm.nih.gov/pubmed/31467459 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/12.2216396 |
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