Name
Title | ||
|---|---|---|
An Improved Image Mining Technique For Brain Tumour Classification Using Efficient Classifier |
Abstract | ||
|---|---|---|
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. |
Year | Venue | Keywords |
|---|---|---|
2010 | Clinical Orthopaedics and Related Research | feature extraction,classification,medical imaging,pattern recognition,brain imaging,ct scan,information retrieval,association rule,association rule mining,data mining |
Field | DocType | Volume |
Data mining,Pattern recognition,Computer science,Tumour classification,Association rule learning,Artificial intelligence,Computed tomography,Classifier (linguistics),Machine learning | Journal | abs/1001.1 |
ISSN | Citations | PageRank |
International Journal of Computer Science and Information
Security, IJCSIS, Vol. 6, No. 3, pp. 107-116, December 2009, USA | 3 | 0.50 |
References | Authors | |
17 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. Rajendran | 1 | 32 | 5.01 |
| M. Madheswaran | 2 | 102 | 15.57 |