title: A graph-based approach to the retrieval of dual-modality biomedical images using spatial relationships.
abstract: The increasing size of medical image archives and the complexity of medical images have led to the development of medical content-based image retrieval (CBIR) systems. These systems use the visual content of images for image retrieval in addition to conventional textual annotation, and have become a useful technique in biomedical data management. Existing CBIR systems are typically designed for use with single-modality images, and are restricted when multi-modal images, such as co-aligned functional positron emission tomography and anatomical computed tomography (PET/CT) images, are considered. Furthermore, the inherent spatial relationships among adjacent structures in biomedical images are not fully exploited. In this study, we present an innovative retrieval system for dual-modality PET/CT images by proposing the use of graph-based methods to spatially represent the structural relationships within these images. We exploit the co-aligned functional and anatomical information in PET/CT, using attributed relational graphs (ARG) to represent both modalities spatially and applying graph matching for similarity measurements. Quantitative evaluation demonstrated that our dual-modal ARG enabled the CBIR of dual-modality PET/CT. The potential of our dual-modal ARG in clinical application was also explored.
authors.affiliation: Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Info. Tech., University of Sydney, and Department of PET and Nuclear Medicine, Royal Prince Alfred Hospital, Sydney, Australia.
authors.forename: Ashnil
authors.initials: A
authors.lastname: Kumar
authors.forename: Jinman
authors.initials: J
authors.lastname: Kim
authors.forename: Weidong
authors.initials: W
authors.lastname: Cai
authors.forename: Stefan
authors.initials: S
authors.lastname: Eberl
authors.forename: Dagan
authors.initials: D
authors.lastname: Feng
mesh_terms: D003628:Database Management Systems; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D011873:Radiology Information Systems; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*