Automatic Detection of Liver Tumor in CT Image Using Region Growing and SVM Classifier

Authors

  • Sreeraj R Bharathiyar University, Coimbatore, India
  • Raju G Department of IT, Kannur University

Keywords:

Region-growing, preprocessing, feature extraction, Segmentation, SVM Classifier

Abstract

This paper presents an approach to automatic detection of liver tumor in CT images by using region-growing and Support Vector Machine (SVM) which is successfully classifies the liver cancer types such as hepatoma, hemangioma and carcinoma.The method rectifies the problem of manual segmentation and classification which is time consuming due to the variance in the characteristics of CT images.Our proposed method has been tested on a group of CT images obtained from hospitals in Kerala with a promising results both in liver and tumor segmentation. The average error rate and accuracy rate obtained from our proposed method is 0.02 and 0.9.

References

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Published

2025-11-11

How to Cite

[1]
R. Sreeraj and G. Raju, “Automatic Detection of Liver Tumor in CT Image Using Region Growing and SVM Classifier”, Int. J. Comp. Sci. Eng., vol. 4, no. 11, pp. 26–29, Nov. 2025.

Issue

Vol. 4 No. 11 (2016): IJCSE November Edition

Section

Research Article

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