Region based stellate features combined with variable selection using AdaBoost learning in mammographic computer-aided detection.
In this paper, a new method is developed for extracting so-called region-based stellate features to correctly differentiate spiculated malignant masses from normal tissues on mammograms. In the proposed method, a given region of interest (ROI) for feature extraction is divided into three individual...
| Publicado en: | Computers in Biology & Medicine Vol. 63; pp. 238 - 251 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Elsevier B.V.
Aug2015
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| Acceso en línea: | Ver este registro en EBSCOhost |