A temporal evolutionary object-oriented data model for medical image management

Abstract

The authors present a temporal evolutionary object-oriented data model (TEDM) for modeling medical images. The intelligent medical image management system (IMIS) lies on top of a picture archive and communication system (PACS) infrastructure. The IMIS can retrieve medical images (e.g. X-rays, computed tomography scans, magnetic resonance scans, etc.) by image features and contents rather than by traditional artificial keys such as a patient hospital identification number. As a result, solutions to queries which associate the radiographic findings of an image, the disease pathology and the categorical patient subpopulation can be obtained. The proposed model and language constructs can also be applied to other domains that exemplify the evolutionary transformations of objects, such as modeling the growth of brain tumors.<>