Feature Subset Selection for Improving the Performance of False Positive Reduction in Lung Nodule CAD.

We propose a feature subset selection method based on genetic algorithms to improve the performance of false positive reduction in lung nodule computer-aided detection (CAD). It is coupled with a classifier based on support vector machines. The proposed approach determines automatically the optimal...

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Τόπος έκδοσης:	IEEE Transactions on information technology in biomedicine 10, 3 (2006).
Κύριος συγγραφέας:	Boroczky, L.
Μορφή:	Άρθρο
Γλώσσα:	English
Θέματα:	CAD. False positive reduction. Feature subset selection. Genetic algorithms. Lung nodule computer-aided detection. Lung nodule database. Medical decision making. Multislice CT scans. Supervised machine learning. Support vector machines.