IJMTES – LUNG NODULE CLASSIFICATION WITH MULTILEVEL PATCH BASED CONTEXT ANALYSIS AND DECISION TREE

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : LUNG NODULE CLASSIFICATION WITH MULTILEVEL PATCH BASED CONTEXT ANALYSIS AND DECISION TREE

Author’s Name : A Santhanalakshmi | L Saranya  unnamed

Volume 03 Issue 07 2016

ISSN no:  2348-3121

Page no: 187-188

Abstract – Early detection of lung cancer can help in a sharp decrease in the lung cancer mortality rate, which accounts for more than 17% percent of the total cancer related deaths. Our purpose is to develop an efficient system for detection of lung nodules from parenchyma region of lung and classify the nodule into either cancerous (Malignant) or non-cancerous(Benign). The proposed system consists of following steps: i) the image taken is enhanced initially and then the region of interest is cropped, where the user can select the area to be cropped.  ii) The multilevel patch-based context analysis are extracted. iii) decision tree classifier are implemented as the classifiers. The proposed work was able to detect the lung nodule that falls in close proximity to the lung wall. Expected results demonstrate promising classification performance.     

Keywords— Decision Tree; Lung Nodule; Multilevel Patch  

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