An Improved Image Mining Technique For Brain Tumour Classification Using Efficient Classifier

Details An Improved Image Mining Technique For Brain Tumour Classification Using Efficient Classifier An Improved Image Mining Technique For Brain Tumour Classification Using Efficient Classifier

2010-01-12

arxiv.org/abs/1001.1988v1

International Journal of Computer Science and Information Security, IJCSIS, Vol. 6, No. 3, pp. 107-116, December 2009, USA

Computer Science

Computer Vision and Pattern Recognition

10 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS December 2009, ISSN 1947 5500

Scientific paper

An improved image mining technique for brain tumor classification using pruned association rule with MARI algorithm is presented in this paper. The method proposed makes use of association rule mining technique to classify the CT scan brain images into three categories namely normal, benign and malign. It combines the low level features extracted from images and high level knowledge from specialists. The developed algorithm can assist the physicians for efficient classification with multiple keywords per image to improve the accuracy. The experimental result on prediagnosed database of brain images showed 96 percent and 93 percent sensitivity and accuracy respectively.

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