Ensemble classification for predicting the malignancy level of pulmonary nodules on chest computed tomography images

  • Authors:
    • Ning Xiao
    • Yan Qiang
    • Muhammad Bilal Zia
    • Sanhu Wang
    • Jianhong Lian
  • View Affiliations

  • Published online on: April 27, 2020     https://doi.org/10.3892/ol.2020.11576
  • Pages: 401-408
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Abstract

Early identification and classification of pulmonary nodules are essential for improving the survival rates of individuals with lung cancer and are considered to be key requirements for computer‑assisted diagnosis. To address this topic, the present study proposed a method for predicting the malignant phenotype of pulmonary nodules based on weighted voting rules. This method used the pulmonary nodule regions of interest as the input data and extracted the features of the pulmonary nodules using the Denoising Auto Encoder, ResNet‑18. Moreover, the software also modifies texture and shape features to assess the malignant phenotype of the pulmonary nodules. Based on their classification accuracy (Acc), the different classifiers were assigned to different weights. Finally, an integrated classifier was obtained to score the malignant phenotype of the pulmonary nodules. The present study included training and testing experiments conducted by extracting the corresponding lung nodule image data from the Lung Image Database Consortium‑Image Database Resource Initiative. The results of the present study indicated a final classification Acc of 93.10±2.4%, demonstrating the feasibility and effectiveness of the proposed method. This method includes the powerful feature extraction ability of deep learning combined with the ability to use traditional features in image representation.

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July 2020
Volume 20 Issue 1

Print ISSN: 1792-1074
Online ISSN:1792-1082

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APA
Xiao, N., Qiang, Y., Bilal Zia, M., Wang, S., & Lian, J. (2020). Ensemble classification for predicting the malignancy level of pulmonary nodules on chest computed tomography images. Oncology Letters, 20, 401-408. https://doi.org/10.3892/ol.2020.11576
MLA
Xiao, N., Qiang, Y., Bilal Zia, M., Wang, S., Lian, J."Ensemble classification for predicting the malignancy level of pulmonary nodules on chest computed tomography images". Oncology Letters 20.1 (2020): 401-408.
Chicago
Xiao, N., Qiang, Y., Bilal Zia, M., Wang, S., Lian, J."Ensemble classification for predicting the malignancy level of pulmonary nodules on chest computed tomography images". Oncology Letters 20, no. 1 (2020): 401-408. https://doi.org/10.3892/ol.2020.11576