title: Content-based retrieval of dynamic PET functional images.
abstract: The recent information explosion has led to massively increased demand for multimedia data storage in integrated database systems. Content-based retrieval is an important alternative and complement to traditional keyword-based searching for multimedia data and can greatly enhance information management. However, current content-based image retrieval techniques have some deficiencies when applied in the biomedical functional imaging domain. In this paper, we presented a prototype design for a content-based functional image retrieval database system for dynamic positron emission tomography. The system supports efficient content-based retrieval based on physiological kinetic features and reduces image storage requirements. This design makes it possible to maintain a large number of patient data sets online and to rapidly retrieve dynamic functional image sequences for interpretation and generation of physiological parametric images, and offers potential advantages in medical image data management and telemedicine, as well as providing possible opportunities in the statistical and comparative analysis of functional image data.
authors.affiliation: Basser Department of Computer Science, The University of Sydney, NSW, Australia.
authors.forename: W
authors.initials: W
authors.lastname: Cai
authors.forename: D D
authors.initials: DD
authors.lastname: Feng
authors.forename: R
authors.initials: R
authors.lastname: Fulton
mesh_terms: D003196:Computer Graphics; D016247:Information Storage and Retrieval; D049268:Positron-Emission Tomography; D014584:User-Computer Interface