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Effective nuclei segmentation with sparse shape prior and dynamic occlusion constraint for glioblastoma pathology images
We propose a segmentation method for nuclei in glioblastoma histopathologic images based on a sparse shape prior guided variational level set framework. By spectral clustering and sparse coding, a set of shape priors is exploited to accommodate complicated shape variations. We automate the object co...
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| 出版年: | J Med Imaging (Bellingham) |
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| 主要な著者: | , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Society of Photo-Optical Instrumentation Engineers
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6416527/ https://ncbi.nlm.nih.gov/pubmed/30891467 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.6.1.017502 |
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