title: Brain CT image similarity retrieval method based on uncertain location graph.
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.
authors.forename: Haiwei
authors.initials: H
authors.lastname: Pan
authors.forename: Pengyuan
authors.initials: P
authors.lastname: Li
authors.forename: Qing
authors.initials: Q
authors.lastname: Li
authors.forename: Qilong
authors.initials: Q
authors.lastname: Han
authors.forename: Xiaoning
authors.initials: X
authors.lastname: Feng
authors.forename: Linlin
authors.initials: L
authors.lastname: Gao
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*