Computer-Aided Grading of Gliomas Combining Automatic Segmentation and Radiomics
Joint Authors
Chen, Wei
Liu, Boqiang
Peng, Suting
Sun, Jiawei
Qiao, Xu
Source
International Journal of Biomedical Imaging
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-08
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Gliomas are the most common primary brain tumors, and the objective grading is of great importance for treatment.
This paper presents an automatic computer-aided diagnosis of gliomas that combines automatic segmentation and radiomics, which can improve the diagnostic ability.
The MRI data containing 220 high-grade gliomas and 54 low-grade gliomas are used to evaluate our system.
A multiscale 3D convolutional neural network is trained to segment whole tumor regions.
A wide range of radiomic features including first-order features, shape features, and texture features is extracted.
By using support vector machines with recursive feature elimination for feature selection, a CAD system that has an extreme gradient boosting classifier with a 5-fold cross-validation is constructed for the grading of gliomas.
Our CAD system is highly effective for the grading of gliomas with an accuracy of 91.27%, a weighted macroprecision of 91.27%, a weighted macrorecall of 91.27%, and a weighted macro-F1 score of 90.64%.
This demonstrates that the proposed CAD system can assist radiologists for high accurate grading of gliomas and has the potential for clinical applications.
American Psychological Association (APA)
Chen, Wei& Liu, Boqiang& Peng, Suting& Sun, Jiawei& Qiao, Xu. 2018. Computer-Aided Grading of Gliomas Combining Automatic Segmentation and Radiomics. International Journal of Biomedical Imaging،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1169489
Modern Language Association (MLA)
Chen, Wei…[et al.]. Computer-Aided Grading of Gliomas Combining Automatic Segmentation and Radiomics. International Journal of Biomedical Imaging No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1169489
American Medical Association (AMA)
Chen, Wei& Liu, Boqiang& Peng, Suting& Sun, Jiawei& Qiao, Xu. Computer-Aided Grading of Gliomas Combining Automatic Segmentation and Radiomics. International Journal of Biomedical Imaging. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1169489
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1169489