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Exploring nonlinear feature space dimension reduction and data representation in breast CADx with Laplacian eigenmaps and t-SNE
Purpose: In this preliminary study, recently developed unsupervised nonlinear dimension reduction (DR) and data representation techniques were applied to computer-extracted breast lesion feature spaces across three separate imaging modalities: Ultrasound (U.S.) with 1126 cases, dynamic contrast enha...
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| 主要な著者: | , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
American Association of Physicists in Medicine
2010
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2807447/ https://ncbi.nlm.nih.gov/pubmed/20175497 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1118/1.3267037 |
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