alexa Analysis of Lung Nodule Classification with Feature Ext
ISSN ONLINE(2278-8875) PRINT (2320-3765)

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering
Open Access

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Research Article

Analysis of Lung Nodule Classification with Feature Extraction.

 
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Abstract

In this paper, the four types of lung nodules are classified, i.e. well circumscribed, vascularised, juxtapleural and pleural tail in low dose computed tomography (LDCT) scan. This classifier analyses both lung nodule and surrounding anatomical structures. Also, it consists of three main stages as follows: (1) Multi level concentric partition through patch based image representation, (2) Feature set design for patch description of image, and (3) SVM classifier compute the classification probability based on level nodule and pLSA calculate the classification probability based on level context. The proposed method was evaluated on a publicly available dataset and clearly demonstrated promising classification performance.

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