Categorizing the stages of lung cancer using Multi SVM Classifier

  • Ashwini P Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham Campus, Mysuru, Karnataka, India
  • Sherin Antony Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham Campus, Mysuru, Karnataka, India
  • Kanchana V Department of Computer Science, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham Campus, Mysuru, Karnataka, India

Abstract

Detection of cancer is the utmost fascinating analysis space for scientists in the early period. The projected method is meant to identify cancer in the beginning phase. The projected method comprises several phases, such as image acquisition, pre-processing, segmentation, feature extraction, and classification. In our proposed work, segmentation is done to fragment the CT image. We use solid feature extraction (GLCM) technique to extract certain essential features from the segmented images. Further extracted features are considered for classification (Multi SVM) process to check whether cancerous or non-cancerous.

Keywords: Computed tomography image, gray level co-occurrence matrix (GLCM), Multi Support vector machine (Multi SVM)

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Published
2012-07-25
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How to Cite
Ashwini P, Sherin Antony, & Kanchana V. (2012). Categorizing the stages of lung cancer using Multi SVM Classifier. International Journal of Research in Pharmaceutical Sciences, 10(3), 2323-2328. https://doi.org/10.26452/ijrps.v10i3.1472
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