Feature Extraction and Principal Component Analysis for Lung Cancer Detection in CT scan Images
نویسنده
چکیده
A hybrid technique based on feature extraction and Principal Component Analysis (PCA) is presented for lung detection in CT scan images. Lung cancer, if detected successfully at early stages, enables many treatment options, reduced risk of invasive surgery and increased survival rate. .In this paper features are extracted using principal component analysis and Histogram Equalization is used for preprocessing of the images. The system produces promising results for lung cancer detection. KeywordsLung Cancer Detection, CT-scan Images, Principle Component Analysis, Histogram Equalization.
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