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Journal of Imaging Informatics in Medicine

Published in:

01-08-2013

Combination of Radiological and Gray Level Co-occurrence Matrix Textural Features Used to Distinguish Solitary Pulmonary Nodules by Computed Tomography

Authors: Haifeng Wu, Tao Sun, Jingjing Wang, Xia Li, Wei Wang, Da Huo, Pingxin Lv, Wen He, Keyang Wang, Xiuhua Guo

Published in: Journal of Imaging Informatics in Medicine | Issue 4/2013

Abstract

The objective of this study was to investigate the method of the combination of radiological and textural features for the differentiation of malignant from benign solitary pulmonary nodules by computed tomography. Features including 13 gray level co-occurrence matrix textural features and 12 radiological features were extracted from 2,117 CT slices, which came from 202 (116 malignant and 86 benign) patients. Lasso-type regularization to a nonlinear regression model was applied to select predictive features and a BP artificial neural network was used to build the diagnostic model. Eight radiological and two textural features were obtained after the Lasso-type regularization procedure. Twelve radiological features alone could reach an area under the ROC curve (AUC) of 0.84 in differentiating between malignant and benign lesions. The 10 selected characters improved the AUC to 0.91. The evaluation results showed that the method of selecting radiological and textural features appears to yield more effective in the distinction of malignant from benign solitary pulmonary nodules by computed tomography.

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Title: Combination of Radiological and Gray Level Co-occurrence Matrix Textural Features Used to Distinguish Solitary Pulmonary Nodules by Computed Tomography
Authors: Haifeng Wu
Tao Sun
Jingjing Wang
Xia Li
Wei Wang
Da Huo
Pingxin Lv
Wen He
Keyang Wang
Xiuhua Guo
Publication date: 01-08-2013
Publisher: Springer US
Published in: Journal of Imaging Informatics in Medicine / Issue 4/2013
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI: https://doi.org/10.1007/s10278-012-9547-6

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Combination of Radiological and Gray Level Co-occurrence Matrix Textural Features Used to Distinguish Solitary Pulmonary Nodules by Computed Tomography

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

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