An improved brain image classification technique with mining and shape prior segmentation procedure.
The shape prior segmentation procedure and pruned association rule with ImageApriori algorithm has been used to develop an improved brain image classification system are presented in this paper. The CT scan brain images have been classified into three categories namely normal, benign and malignant, considering the low-level features extracted from the images and high level knowledge from specialists to enhance the accuracy in decision process. The experimental results on pre-diagnosed brain images showed 97% sensitivity, 91% specificity and 98.5% accuracy. The proposed algorithm is expected to assist the physicians for efficient classification with multiple key features per image.
Rajendran
P
P
Department of Computer Science and Engineering, K. S. Rangasamy College of Technology, Tamilnadu, India. peerajendran@gmail.com
Madheswaran
M
M
D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology; D001931:Brain Mapping; D057225:Data Mining / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed