DocumentCode :
2707958
Title :
Research on indexing in medical image database retrieval using self-organizing maps
Author :
Hao Zou ; Jian Sun
Author_Institution :
Sino-Dutch Biomed. & Inf. Eng. Sch., Northeastern Univ., Shenyang, China
fYear :
2012
fDate :
6-8 June 2012
Firstpage :
950
Lastpage :
955
Abstract :
High dimensional indexing scheme is a significant research issue for content-based image retrieval in medical image database. The SOM-based approach proposed in this paper uses a Kernel Density Estimation Method (Mean Shift) to describe for medical image database, which fits the complex data distribution reasonably well. And this approach trains optimized SOM network to partition data space. Experiments on a real-world medical image dataset demonstrate a good topology configuration of the data and a remarkable reduction of the amount of accessed vectors in exact NN searches compare with existing indexing schemes.
Keywords :
content-based retrieval; estimation theory; image retrieval; indexing; medical image processing; self-organising feature maps; visual databases; SOM-based approach; content-based image retrieval; high dimensional indexing; kernel density estimation method; mean shift; medical image database retrieval; self-organizing maps; Biomedical imaging; Data models; Estimation; Indexing; Kernel; Vectors; Content-based medical image retrieval; SOM; data distribution model; high-dimensional indexing scheme;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2012 International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4673-2238-6
Electronic_ISBN :
978-1-4673-2236-2
Type :
conf
DOI :
10.1109/ICInfA.2012.6246953
Filename :
6246953
Link To Document :
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