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Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging
Structured sparsity penalization has recently improved statistical models applied to high-dimensional data in various domains. As an extension to medical imaging, the present work incorporates priors on network hierarchies of brain regions into logistic-regression to distinguish neural activity effe...
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| 出版年: | Inf Process Med Imaging |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5937695/ https://ncbi.nlm.nih.gov/pubmed/29743804 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-319-59050-9_26 |
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