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Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering
BACKGROUND: Cancer typically exhibits genotypic and phenotypic heterogeneity, which can have prognostic significance and influence therapy response. Computed Tomography (CT)-based radiomic approaches calculate quantitative features of tumour heterogeneity at a mesoscopic level, regardless of macrosc...
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| Publicado no: | Comput Biol Med |
|---|---|
| Main Authors: | , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Elsevier
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7248575/ https://ncbi.nlm.nih.gov/pubmed/32421652 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.compbiomed.2020.103751 |
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