Brain CT image similarity retrieval method based on uncertain location graph

H. Pan, P. Li, Qing Li, Q. Han, X. Feng, L. Gao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

19 Citations (Scopus)

Abstract

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. © 2013 IEEE.
Original languageEnglish
Article number6578107
Pages (from-to)574-584
Number of pages11
JournalIEEE Journal of Biomedical and Health Informatics
Volume18
Issue number2
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Keywords

  • Image modeling
  • image similarity retrieval
  • medical image
  • uncertain graph

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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