Authors:
F. Maghraby
1
;
H. M. Faheem
2
;
M. Roushdy
2
and
M. Amoon
3
Affiliations:
1
ELShorouk Academy, Egypt
;
2
Ain Shams University, Egypt
;
3
Menoufia University, Egypt
Keyword(s):
Alchemi, Database Partitioning, DICOM, Grid Computing, Semantic Features.
Related
Ontology
Subjects/Areas/Topics:
Coupling and Integrating Heterogeneous Data Sources
;
Data Engineering
;
Databases and Data Security
;
Databases and Information Systems Integration
;
Distributed Database Systems
;
e-Business
;
Enterprise Information Systems
;
Large Scale Databases
;
Middleware Integration
;
Middleware Platforms
;
Technology Platforms
Abstract:
This paper proposes an approach to perform retrieval process on medical image databases by extracting semantic information from the dataset values of the DICOM (Digital Imaging and Communications in Medicine) format which produces a set of images relevant to the given query. Image retrieval in general has the goal to allow for the retrieval of similar images over very heterogeneous image collections to help the diagnostic process. With modern radiology, departments produce tens of thousands of images per day. It is apparent that infrastructures are required to treat this large amount of data. Grid technologies are among those approaches deployed to make computing power available to large-scale research projects. Often, the goal is to have a very large number of resources in various locations that can be shared for performing computationally intensive tasks. Grid computing has the potential to help computer science researchers in medical institutions to better use an existing infrastr
ucture. It shows that particularly computationally–intensive tasks such as the extraction of features from large image databases can be performed much faster. Alchemi framework has been deployed in this paper to provide grid-based environment .Speeding up the retrieval process was one of the major achievements of this work.
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