Brain CT Image Similarity Retrieval Method Based on Uncertain Location Graph

A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases....

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Bibliographic Details
Published in:IEEE journal of biomedical and health informatics 2014-03, Vol.18 (2), p.574-584
Main Authors: Pan, Haiwei, Li, Pengyuan, Li, Qing, Han, Qilong, Feng, Xiaoning, Gao, Linlin
Format: Article
Language:English
Subjects:
Algorithms
Biomedical imaging
Brain - diagnostic imaging
Brain modeling
Computed tomography
Humans
Image modeling
Image Processing, Computer-Assisted - methods
Image retrieval
image similarity retrieval
Indexes
Information Storage and Retrieval - methods
medical image
Medical services
R&D
Reproducibility of Results
Research & development
Sensitivity and Specificity
Tomography, X-Ray Computed - methods
uncertain graph
Uncertainty
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Summary:A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases. However, the similarity retrieval for brain CT images requires much higher accuracy than the general images. In this paper, a new model of uncertain location graph (ULG) is presented for brain CT image modeling and similarity retrieval. According to the characteristics of brain CT image, we propose a novel method to model brain CT image to ULG based on brain CT image texture. Then, a scheme for ULG similarity retrieval is introduced. Furthermore, an effective index structure is applied to reduce the searching time. Experimental results reveal that our method functions well on brain CT images similarity retrieval with higher accuracy and efficiency.
ISSN:2168-2194
2168-2208
DOI:10.1109/JBHI.2013.2274798