00000cab a22000003a 4500 UP-99796217609532979 Buklod 20231007234407.0 m |o d | ta 101110s xx d | ||r ||||| || DENGII eng Jinman Kim A New Way for Multidimensional Medical Data Management Volume of Interest (VOI)-Based Retrieval of Medical Images With Visual and Functional Features. pp. 598-607 The advances in digital medical imaging and storage in integrated databases are resulting in growing demands for efficient image retrieval and management. Content-based image retrieval (CBIR) refers to the retrieval of images from a database, using the visual features derived from the information in the image, and has become an attractive approach to managing large medical image archives. In conventional CBIR systems for medical images, images are often segmented into regions which are used to derive two-dimensional visual features for region-based queries. Although such approach has the advantage of including only relevant regions in the formulation of a query, medical images that are inherently multidimensional can potentially benefit from the multidimensional feature extraction which could open up new opportunities in visual feature extraction and retrieval. In this study, we present a volume of interest (VOI) based content-based retrieval of four-dimensional (three spatial and one temporal) dynamic PET images. By segmenting the images into VOIs consisting of functionally similar voxels (e.g., a tumor structure), multidimensional visual and functional features were extracted and used as region-based query features. A prototype VOI-based functional image retrieval system (VOI-FIRS) has been designed to demonstrate the proposed multidimensional feature extraction and retrieval. Experimental results show that the proposed system allows for the retrieval of related images that constitute similar visual and functional VOI features, and can find potential applications in medical data management, such as to aid in education, diagnosis, and statistical analysis Content-based image retrieval. Digital medical imaging. Dynamic PET images. Functional image retrieval system. Image segmentation. Image storage. Integrated databases. Medical data management. Medical image archives. Medical images. Multidimensional feature extraction. Multidimensional medical data management. Region-based query feature. Statistical analysis. Visual feature extraction. Volume-of-interest-based image retrieval. IEEE Transactions on information technology in biomedicine 10, 3 (2006). FO UPD DENG-II Article