Performance of Ensemble Learning Classifiers on Malignant-Benign Classification of Pulmonary Nodules

Tartar A., Akan A.

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 23 - 25 April 2014, pp.722-725 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2014.6830331
  • City: Trabzon
  • Country: Turkey
  • Page Numbers: pp.722-725
  • Istanbul University Affiliated: Yes

Abstract

Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this study, a novel Computer-aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. Proposed CAD system, providing an important support to radiologists at the diagnosis process of the disease, achieves high classification performance using ensemble learning classifiers.