eFis: A Fuzzy Inference Method for Predicting Malignancy of Small Pulmonary Nodules

KAYA A., CAN A. B.

11th International Conference on Image Analysis and Recognition (ICIAR), Portugal, 22 - 24 October 2014, vol.8815, pp.255-262 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 8815
  • Doi Number: 10.1007/978-3-319-11755-3_29
  • Country: Portugal
  • Page Numbers: pp.255-262
  • Hacettepe University Affiliated: Yes

Abstract

Predicting malignancy of small pulmonary nodules from computer tomography scans is a difficult and important problem to diagnose lung cancer. This paper presents a rule based fuzzy inference method for predicting malignancy rating of small pulmonary nodules. We use the nodule characteristics provided by Lung Image Database Consortium dataset to determine malignancy rating. The proposed fuzzy inference method uses outputs of ensemble classifiers and rules from radiologist agreements on the nodules. The results are evaluated over classification accuracy performance and compared with single classifier methods. We observed that the preliminary results are very promising and system is open to development.