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Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles
We propose a hierarchical pipeline for skull-stripping and segmentation of anatomical structures of interest from T1-weighted images of the human brain. The pipeline is constructed based on a two-level Bayesian parameter estimation algorithm called multi-atlas likelihood fusion (MALF). In MALF, esti...
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| 出版年: | Front Neurosci |
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| 主要な著者: | , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2015
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4347448/ https://ncbi.nlm.nih.gov/pubmed/25784852 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2015.00061 |
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