Automatic detection and diagnosis of lung nodules on CT images based on LDA and SVM.
- Author:
Lei CAO
1
;
Wei-juan LI
;
Qian-jin FENG
Author Information
1. School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China. caolei@fimmu.com
- Publication Type:Journal Article
- MeSH:
Humans;
Image Interpretation, Computer-Assisted;
methods;
Image Processing, Computer-Assisted;
Linear Models;
Solitary Pulmonary Nodule;
diagnostic imaging;
Support Vector Machine;
Tomography, X-Ray Computed;
methods
- From:
Journal of Southern Medical University
2011;31(2):324-328
- CountryChina
- Language:Chinese
-
Abstract:
Based on suspected pulmonary nodule segmentation images obtained previously and with a large-sample training, automatic detection and diagnosis of the pulmonary nodules on CT images was realized by extracting the multi-dimensional features of the pulmonary nodule images and the application of LDA and SVM statistical classifiers. Experimental results showed that this detection and diagnosis method produced better classification results, and is practical for application in CAD systems.
