Title :
Medical Image Retrieval and Classification Based on Morphological Shape Feature
Author :
Fu Li-dong ; Zhang Yi-fei
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
Abstract :
Medical Image Retrieval and Classification is very important in Computer-Aided Diagnosis. Feature extraction is one of the most important techniques in content based image retrieval and classification. How to extract low-level features which reflect high-level semantics of an image is crucial for medical image retrieval and classification. In allusion to this issue, there proposed a method using edge density histogram to extract shape feature of medical images in this paper. Then Euclidean distance and Support Vector Machine (SVM) are used for medical image retrieval and classification. Results of experimentation showed that the proposed algorithm has been applied to medical image retrieval with promising effect.
Keywords :
content-based retrieval; feature extraction; image classification; image retrieval; medical image processing; shape recognition; support vector machines; Euclidean distance; computer aided diagnosis; content based image retrieval; edge density histogram; high level semantics; image classification; medical image retrieval; morphological shape feature; shape feature extraction; support vector machine; histogram; image retrieval; morphological; shape feature; support vector machine;
Conference_Titel :
Intelligent Networks and Intelligent Systems (ICINIS), 2010 3rd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-8548-2
Electronic_ISBN :
978-0-7695-4249-2
DOI :
10.1109/ICINIS.2010.86