Location of Repository

Lung Nodule Detection Using Fuzzy Clustering and Support Vector Machines S.Sivakumar #1, Dr.C.Chandrasekar *2

By A. Lung Cancer

Abstract

Abstract — Lung cancer is the primary cause of tumor deaths for both sexes in most countries. Lung nodule, an abnormality which leads to lung cancer is detected by various medical imaging techniques like X-ray, Computerized Tomography (CT), etc. Detection of lung nodules is a challenging task since the nodules are commonly attached to the blood vessels. Many studies have shown that early diagnosis is the most efficient way to cure this disease. This paper aims to develop an efficient lung nodule detection scheme by performing nodule segmentation through fuzzy based clustering models; classification by using a machine learning technique called Support Vector Machine (SVM). This methodology uses three different types of kernels among these RBF kernel gives better class performance

Topics: Image segmentation, FCM, WPFCM, Classification, Support Vector Machines
Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.412.90
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.enggjournals.com/ij... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.