A Novel Hybrid Framework for the Detection and Risk Severity of Chronic Obstructive Pulmonary Disease
DOI:
https://doi.org/10.51983/ajes-2018.7.2.2063Keywords:
Chronic Obstructive Pulmonary Disease, Block Variation of Local Correlation Coefficient, Support Vector MachineAbstract
The COPD is a limitation in airflow and is not completely reversible, and affects up to one quarter of adults with 40 or more years. The risk factors of COPD typically include tobacco smoke, masculine gender, exposure to chemicals and dusts, asthma, air pollution and genetic reasons as rare hereditary deficiency of α1-antitrypsin. The COPD leads to death if it is treated properly. So if it recognized earlier and more correctly, the life span of affected people will increase. Thus, in this paper, new framework based on block variation of local correlation coefficients (BVLC) and support vector machine (SVM) is suggested to identify chronic obstructive pulmonary disease in CT images. The experiments on benchmark database clearly proven that recommended approach is suggestively good in terms of accuracy and time.
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