Interactive Learning Based Nodule Detection in CT Lung Volumes


Cam I., Tek F. B.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16 - 19 May 2016, pp.2021-2024 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2016.7496166
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.2021-2024
  • Keywords: interactive segmentation, nodule detection, lung, computed tomography
  • Istanbul Technical University Affiliated: No

Abstract

We present a novel method to automatically detect lung nodules in CT lung scans. Our method is generalized in the sense that it does not assume/depend a particular organ or a particular nodule type. hence it does not require an organ segmentation. We test our method in a challenging set (Anode09) that is comprised of low dose CT scans which include all types of nodules (solid, ground glass opacity, juxta-fissural, juxta-vascular) of less than 10mm in size. Our method produces 8 false positives per scan for true positive rate of 52%, which is comparable to the first 6 results from the contest.