Third International conference on advances in communication, network and computing

Research Article

Classification of Medical Images Using Data Mining Techniques

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  • @INPROCEEDINGS{10.1007/978-3-642-35615-5_8,
        author={B. Prasad and Krishna A.N.},
        title={Classification of Medical Images Using Data Mining Techniques},
        proceedings={Third International conference on advances in communication, network and computing},
        proceedings_a={CNC},
        year={2012},
        month={12},
        keywords={CAD Texture features Data Mining classifiers},
        doi={10.1007/978-3-642-35615-5_8}
    }
    
  • B. Prasad
    Krishna A.N.
    Year: 2012
    Classification of Medical Images Using Data Mining Techniques
    CNC
    Springer
    DOI: 10.1007/978-3-642-35615-5_8
B. Prasad1,*, Krishna A.N.2,*
  • 1: B.N.M. Institute of Technology
  • 2: S.J.B. Institute of Technology
*Contact email: drbgprasad@gmail.com, krishna12742004@yahoo.co.in

Abstract

Automated classification of medical images is an increasingly important tool for physicians in their daily activity. This paper proposes data mining classifiers for medical image classification. In this study, we have used J48 decision tree and Random Forest (RF) classifiers for classifying CT scan brain images into three categories namely inflammatory, tumor and stroke. The proposed classification system is based on the effective use of texture information of images. Three different methods implemented are: Haralick (H), Tamura (T) and Wold (W) texture features. All three texture features and the classification methods are compared based on Precision and Recall. The experimental result on pre-diagnosed database of brain images showed Haralick features combined with Random Forest classifier is found to give best results for classification of CT-scan brain images.