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Automatic detection and diagnosis of lung nodules on CT images based on LDA and SVM / 南方医科大学学报
Journal of Southern Medical University ; (12): 324-328, 2011.
Article in Chinese | WPRIM | ID: wpr-307940
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.
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Image Processing, Computer-Assisted / Diagnostic Imaging / Image Interpretation, Computer-Assisted / Tomography, X-Ray Computed / Linear Models / Solitary Pulmonary Nodule / Support Vector Machine / Methods Type of study: Diagnostic study Limits: Humans Language: Chinese Journal: Journal of Southern Medical University Year: 2011 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Image Processing, Computer-Assisted / Diagnostic Imaging / Image Interpretation, Computer-Assisted / Tomography, X-Ray Computed / Linear Models / Solitary Pulmonary Nodule / Support Vector Machine / Methods Type of study: Diagnostic study Limits: Humans Language: Chinese Journal: Journal of Southern Medical University Year: 2011 Type: Article