Deep Transfer Convolutional Neural Network and Extreme Learning Machine for lung nodule diagnosis on CT images

作者：

Highlights：

• Deep Transfer Convolutional Neural Networks (DTCNN) is used for nodule diagnosis.

• An optimal pre-trained DTCNN is adopted to capture richer features of lung nodules.

• An Extreme Learning Machine (ELM) model is used to ease the computational burden.

• Two cases study shows the effectiveness and efficiency of the proposed approach.

摘要

•Deep Transfer Convolutional Neural Networks (DTCNN) is used for nodule diagnosis.•An optimal pre-trained DTCNN is adopted to capture richer features of lung nodules.•An Extreme Learning Machine (ELM) model is used to ease the computational burden.•Two cases study shows the effectiveness and efficiency of the proposed approach.

论文关键词：Lung nodule diagnosis,Computed Tomography,Convolutional Neural Network,Extreme Learning Machine,Transfer learning

论文评审过程：Received 5 January 2020, Revised 26 May 2020, Accepted 7 July 2020, Available online 11 July 2020, Version of Record 14 July 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.106230