Publications
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A 3D medical image database management system
Source: Computerized Medical Imaging and Graph 1996 Jul;20(4):269-284.
Author: Arya M, Cody W, Faloutsos C, Richardson J, Toga A.
PubMed ID: 8954234
Abstract:
We describe the design and implementation of QBISM (Query By Interactive, Spatial Multimedia), a prototype for querying and visualizing 3D spatial data. Our medical image application is focused on the brain mapping requirements for multimodality relationships across multiple subjects. It incorporates data describing both structure and function. It includes data structures that describe anatomy, physiology, coordinates using rendered imagery and statistical output. The system is built on top of the Starburst DBMS extended to handle spatial data types, specially, scalar fields and arbitrary regions or space within such fields. In this paper we list the requirements of the application, discuss the logical and physical database design issues, and present timing results from our prototype. We observed that the DBMS' early spatial filtering results in significant performance savings because the system response time is dominated by the amount of data retrieved, transmitted, and rendered.
Source: Computerized Medical Imaging and Graph 1996 Jul;20(4):269-284.
Author: Arya M, Cody W, Faloutsos C, Richardson J, Toga A.
PubMed ID: 8954234
Abstract:
We describe the design and implementation of QBISM (Query By Interactive, Spatial Multimedia), a prototype for querying and visualizing 3D spatial data. Our medical image application is focused on the brain mapping requirements for multimodality relationships across multiple subjects. It incorporates data describing both structure and function. It includes data structures that describe anatomy, physiology, coordinates using rendered imagery and statistical output. The system is built on top of the Starburst DBMS extended to handle spatial data types, specially, scalar fields and arbitrary regions or space within such fields. In this paper we list the requirements of the application, discuss the logical and physical database design issues, and present timing results from our prototype. We observed that the DBMS' early spatial filtering results in significant performance savings because the system response time is dominated by the amount of data retrieved, transmitted, and rendered.