Abstract
Computational systems are successfully used in distinct areas of health. However, the use of digital imaging in pathology is taking its first steps when compared with the radiology sector. For instance, inter-institutional web platforms interoperable with various scanners through standard communications are very rare. This is due to the fact that the technology is only now being mature enough to meet the major challenges of this sector in terms of data storage and data access for efficient visualization of images with several gigabytes. The remote access to those images proves to be a challenge in an open and heterogeneous environment. This paper proposes a scalable and efficient architecture for storing and dynamic data retrieval on distributed large-scale systems. The adopted methodology relies on intra-query parallelism to retrieve a large number of image segments in a scalable distributed environment.
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