Kidney tumor detection and classification using image processing

  • Rohith V Department of Computer Science, Amrita Vishwa Vidyapeetham university, Amrita School of Arts and Sciences, Mysuru, India
  • Simmi Department of Computer Science, Amrita Vishwa Vidyapeetham university, Amrita School of Arts and Sciences, Mysuru, India
  • Ramya N Department of Computer Science, Amrita Vishwa Vidyapeetham university, Amrita School of Arts and Sciences, Mysuru, India

Abstract

Kidney cancer is a disorder where the cells of the kidney become abnormal and develop into a tumor. It is also referred to as renal cell carcinoma. The detection of kidney tumor in the early stages is very important; it is said that different imaging techniques can help doctors to decide the cancer stage and determine the appropriate treatment method. The detection and diagnosis of kidney tumors are performed by scanning images of computed tomography. Most existing works in renal kidney cancer is detection and diagnosis of the existence or absence of tumor in the kidney and classify the tumor as harmless or malevolent. The fundamental goal of this paper is to propose a strategy that will characterize the type of cells present in the kidney tumor. This can be accomplished through methods like segmentation, feature extraction using GLCM and classification using multiSVM.

Keywords: Segmentation, Computed Tomography, GLCM, multiSVM

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Published
2019-07-12
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How to Cite
Rohith V, Simmi, & Ramya N. (2019). Kidney tumor detection and classification using image processing. International Journal of Research in Pharmaceutical Sciences, 10(3), 2017-2024. https://doi.org/10.26452/ijrps.v10i3.1412
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Original Articles
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