DocumentCode :
2215308
Title :
Medical image retrieval system using GGRE framework
Author :
Yogapriya, J. ; Vennila, Ila
Author_Institution :
Dept. of Comput. Sci. & Eng., Paavai Eng. Coll., Namakkal, India
fYear :
2012
fDate :
21-23 March 2012
Firstpage :
246
Lastpage :
251
Abstract :
This paper seeks to focus on Medical Image Retrieval based on Feature extraction, Classification and Similarity Measurements which will aid for computer assisted diagnosis. The selected features are Shape(Generic Fourier Descriptor (GFD)and Texture(Gabor Filter(GF)) that are extracted and classified as positive and negative features using a classification technique called Relevance Vector Machine (RVM) that provides a natural way to classify multiple features of images. The similarity model is used to measure the relevance between the query image and the target images based on Euclidean Distance(ED). This type of Medical Image Retrieval System framework is called GGRE. The retrieval algorithm performances are evaluated in terms of precision and recall. The results show that the multiple feature classifier system yields good retrieval performance than the retrieval systems based on the individual features.
Keywords :
Fourier transforms; Gabor filters; feature extraction; image retrieval; medical image processing; support vector machines; ED; GFD; GGRE framework; Gabor filter; RVM; classification technique; computer assisted diagnosis; euclidean distance; feature classification; feature extraction; generic Fourier descriptor; medical image retrieval system; relevance vector machine; similarity measurements; Feature extraction; Image retrieval; Medical diagnostic imaging; Shape; Support vector machines; Training; CBMIR; Classification; Shape; Similarity Measurements; Texture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, Informatics and Medical Engineering (PRIME), 2012 International Conference on
Conference_Location :
Salem, Tamilnadu
Print_ISBN :
978-1-4673-1037-6
Type :
conf
DOI :
10.1109/ICPRIME.2012.6208352
Filename :
6208352
Link To Document :
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