Lung Cancer Detection Based On Ct Images Using Feature Extraction And Classification Techniques

Main Article Content

Dr. S G Balakrishnan , Dr. P.Ramya , Thallam Venkata Naga Hanumatha Rao , Dr. G. Manikandan , Hemavathi S , R. Selvameena

Abstract

The image detection in medical field is a difficult task due to small lesions which are not identifiable in an early stage. The early medical diagnosis is important because it increases the mortality rate. Therefore prediction of lung cancer in its early stage is important. Here Linear Discriminant Analysis (LDA) classification is used to predict lung nodules and normal cells on MRI images. Dual Tree M-Band Wavelet Transform is used for feature extraction and LDA concentrates on the image classification. The proposed method undergoes three important stages includes in lung cancer detection such as pre-processing, feature extraction and classification. The accuracy results up to 95% of the images have been identified precisely.

Article Details

Section
Articles