Title :
Medical image retrieval using multiple features clustering technique
Author :
Jyothi, B. ; Latha, Y. Madhavee ; Mohan, P.G.K.
Author_Institution :
Dept. of Electron. & Commun., Mallareddy Coll. of Eng. & Technol., Maisammaguda, India
Abstract :
A mass of medical images are generated for diagnosis some unfamiliar diseases. Pathology researches and medical education require searching similar images from database in order to improve the quality and efficiency of care process. It is an imperative to build an efficient retrieval system to browse through the entire data base. To over come the draw backs of the existing systems we proposed new and effective image retrieval scheme by integrating clustering and feature extraction. In proposed technique images are clustered by improved mountain clustering technique texture and shape features are extracted using steerable filter and pseudo-zernike movements. Experimental results show that the proposed approach improves the retrieval performance than the retrieval systems based on the individual features.
Keywords :
feature extraction; filtering theory; image retrieval; image texture; medical image processing; pattern clustering; visual databases; database browsing; diseases diagnosis; feature extraction; medical care process; medical education; medical image retrieval; mountain clustering technique; multiple feature clustering technique; pathology research; pseudoZernike movements; retrieval performance; shape feature; steerable filter; texture feature; Medical Image retrieval; Pseudo-Zernike movements; improved mountain clustering; steerable filter;
Conference_Titel :
Computational Intelligence & Computing Research (ICCIC), 2012 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4673-1342-1
DOI :
10.1109/ICCIC.2012.6510257