Lung nodule classification using artificial crawlers, directional texture and support vector machine

作者：

Highlights：

• We develop a methodology to classify lung nodule and non-nodules.

• 833 lung scans were extracted from LIDC-IRDI database.

• Three methods used was artificial crawlers, rose diagram and hybrid model.

• The artificial crawlers was adapted to work on 3D images.

• The best result was achieved from hybrid model, with accuracy of 94,3%.

摘要

•We develop a methodology to classify lung nodule and non-nodules.•833 lung scans were extracted from LIDC-IRDI database.•Three methods used was artificial crawlers, rose diagram and hybrid model.•The artificial crawlers was adapted to work on 3D images.•The best result was achieved from hybrid model, with accuracy of 94,3%.

论文关键词：Artificial life,Artificial crawlers,Rose diagram,Lung nodule classification

论文评审过程：Received 12 January 2016, Revised 5 September 2016, Accepted 17 October 2016, Available online 17 October 2016, Version of Record 28 October 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.10.039