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Interactive prostate segmentation using atlas-guided semi-supervised learning and adaptive feature selection
PURPOSE: Accurate prostate segmentation is necessary for maximizing the effectiveness of radiation therapy of prostate cancer. However, manual segmentation from 3D CT images is very time-consuming and often causes large intra- and interobserver variations across clinicians. Many segmentation methods...
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| Yayımlandı: | Med Phys |
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| Asıl Yazarlar: | , , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
American Association of Physicists in Medicine
2014
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4224685/ https://ncbi.nlm.nih.gov/pubmed/25370629 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1118/1.4898200 |
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