NDLI: Medical Image Retrieval Based on Latent Semantic Indexing

Content Provider	IEEE Xplore Digital Library
Author	Qin Chen Xiaoying Tai Baochuan Jiang Gang Li Jieyu Zhao
Copyright Year	2008
Description	Author affiliation: Inst. of Inf. Sci. & Eng., Ningbo Univ., Ningbo (Qin Chen; Xiaoying Tai; Baochuan Jiang; Gang Li; Jieyu Zhao)
Abstract	To improve the performance of content-based medical image retrieval, herein an algorithm which makes use of latent semantic indexing (LSI) technology on gastroscopic image retrieval is proposed. First extract imagepsilas color histogram and color autocorrelogram of low-level features, and then use normalizing, term weighting and singular value decomposition to realize low-level features mapping into high-level semantic features. In this way, the retrieval results will be more in accordance with the query imagepsilas semantic content. Based on above idea, a prototype system which supports query by example image is designed and implemented. The experimental results according to the prototype system show that the approach proposed in the paper is effective to gastroscopic image retrieval.
Starting Page	561
Ending Page	564
File Size	481086
Page Count	4
File Format	PDF
ISBN	9780769533360
DOI	10.1109/CSSE.2008.1457
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Content based retrieval latent semantic indexing Image retrieval Information retrieval Data mining color histogram Histograms Prototypes color autocorrelogram Medical diagnostic imaging singular value decomposition Biomedical imaging Indexing Singular value decomposition
Content Type	Text
Resource Type	Article

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