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EnglishIn this paper we present a cascade-based framework to detect clusters of microcalcifications on mammograms. The algorithm is based on a sliding window technique where a detector is structured as a “cascade” of simple boosting classifiers with increasing complexity. Such a method couples the effectiveness of the cascade approach with the Rank- Boost algorithm that is aimed at maximizing the area under the ROC curve and represents a good choice when dealing with unbalanced data sets.
| Titolo: | Detecting Clusters of Microcalcifications with a Cascade-Based Approach |
| Autori: | |
| Data di pubblicazione: | 2012 |
| Serie: | |
| Abstract: | In this paper we present a cascade-based framework to detect clusters of microcalcifications on mammograms. The algorithm is based on a sliding window technique where a detector is structured as a “cascade” of simple boosting classifiers with increasing complexity. Such a method couples the effectiveness of the cascade approach with the Rank- Boost algorithm that is aimed at maximizing the area under the ROC curve and represents a good choice when dealing with unbalanced data sets. |
| Handle: | http://hdl.handle.net/11580/21523 |
| ISBN: | 9783642312700 |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
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