DocumentCode :
2513022
Title :
Medical Image Retrieval Based On Nonsubsampled Contourlet Transform and Fractal Dimension
Author :
Zhang, Qidong ; Gao, Liqun
Author_Institution :
Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China
fYear :
2009
fDate :
11-13 June 2009
Firstpage :
1
Lastpage :
4
Abstract :
A novel medical image retrieval algorithm based on texture information is proposed. The texture image retrieval based on fractal geometry is a commonly used method. However, it is inadequate only using fractal dimension to describe the texture. The nonsubsampled contourlet transform has the properties of multi-scale and multi-direction. Firstly, the nonsubsampled contourlet transform were done on original texture image, and then the fractal dimension of the transformed image was computed. The algorithm extracts fractal features with scale and orientation characteristics. To decrease the gap between high level concepts in human minds and low level features computed by computers, an improved SVM relevance feedback is introduced according to users´ intention. A database of CT images was retrieved by this algorithm. The result shows it can achieve a high precision of retrieval.
Keywords :
computerised tomography; feature extraction; image retrieval; image texture; medical image processing; relevance feedback; support vector machines; CT image database; SVM relevance feedback; fractal feature extraction; image texture; medical image retrieval algorithm; nonsubsampled contourlet transform; user intention; Biomedical imaging; Feature extraction; Feedback; Fractals; Geometry; Humans; Image databases; Image retrieval; Information retrieval; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
Type :
conf
DOI :
10.1109/ICBBE.2009.5163040
Filename :
5163040
Link To Document :
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