Image data model for an efficient multi-criteria query: a case in medical databases
Proceedings 14th International Conference on Scientific and Statistical Database Management - Trang 165-174
Tóm tắt
Since the last two decades, image database management has been practiced using different image representation methods. In the literature, images are represented using two paradigms: the metadata-based and the content-based representations. Image retrieval using the metadata is done using the traditional database operations. However, image retrieval by its low-level features requires similarity-based operations. Practice has shown that both types of operations are needed for an efficient image database management system. Particularly in medical image databases, such a mixed form of retrieval is very important. We first present a global image data model that supports both metadata and low-level descriptions of images. We illustrate our work with real examples in the medical domain. Then, using an original image data repository model, we show how relational and similarity-based operations can be integrated. Both image and salient object are considered in our model. A prototype called MIMS (medical image management system) has been realized to validate the main aspects of our approach.
Từ khóa
#Data models #Computer aided software engineering #Biomedical imaging #Image databases #Image retrieval #Content based retrieval #Information retrieval #Image representation #Shape #Spatial databasesTài liệu tham khảo
10.1145/265563.265574
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