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Segmentation and Detection of Lung Cancer Using Image Processing and Clustering Techniques

  • Preeti JoonEmail author
  • Shalini Bhaskar Bajaj
  • Aman Jatain
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 713)

Abstract

Lung cancer is a most common disease nowadays, so to get rid of it we have made a detection system. In this paper, an active spline model is used to segment the X-ray images of lung cancer. The system formed acquired medical images of lung X-ray. First, in preprocessing median filter is used for noise detection. Then, segmentation is applied and further K-mean and fuzzy C-mean clustering is applied for feature extraction. This paper is an extension of techniques of image processing of lung cancer detection and produces the final results of feature extraction after X-ray image segmentation. Here, the proposed model is developed using SVM algorithm used for classification. Using MATLAB, simulation results are obtained for cancer detection system. This paper focuses thus on segmentation and detection of lung cancer by finding normality and abnormality of the images.

Keywords

Median filtration Segmentation Active spline model Clustering Feature extraction Support vector machine X-ray images 

Notes

Acknowledgements

Initially, we would like to thank our almighty in the success of completing this work. We want to thank the RJ Superspecialities Hospital & Heart Center for supporting and providing large collection of lung X-ray images, which have been valuable for this research.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Preeti Joon
    • 1
    Email author
  • Shalini Bhaskar Bajaj
    • 1
  • Aman Jatain
    • 1
  1. 1.Department of Computer ScienceAmity University, GurugramGurugramIndia

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