An architecture for DICOM medical images storage and retrieval adopting distributed file systems

Conventional storage and retrieval of information from telemedicine environments is usually based on ordinary database systems. Aspects such as scalability, information distribution, high performance system techniques and operational costs are well known challenges to be circumvented in the research for novel proposals in the field of large-scale telemedicine systems. In this paper we present an architecture that targets high performance levels in storing and retrieving DICOM medical images, adopting a distributed approach in a cluster configuration. Our proposal has two main components: the first element is a data model that is based on image hierarchy, considering the hierarchical data format 5 (HDF5). The second component is a distributed file system, characterised by the parallel virtual file system (PVFS) that was employed in this proposal as a distributed storage data system. As a result, this paper presents a differentiated approach for storage and retrieval of information for a telemedicine environment. Experimental results, utilising the architecture, indicate an enhanced level of performance around 16% in terms of storage process. This number represents an improved performance in comparison to a conventional database system.

[1]  D. Nurmi,et al.  A Case Study in Application I/O on Linux Clusters , 2001, ACM/IEEE SC 2001 Conference (SC'01).

[2]  Aldo von Wangenheim,et al.  A Statewide Telemedicine Network for Public Health in Brazil , 2006, 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06).

[3]  Mario A. R. Dantas,et al.  Asynchronous Data Replication: A National Integration Strategy for Databases on Telemedicine Network , 2008, 2008 21st IEEE International Symposium on Computer-Based Medical Systems.

[4]  John R. Cary,et al.  Grid service for visualization and analysis of remote fusion data , 2004, Proceedings of the Second International Workshop on Challenges of Large Applications in Distributed Environments, 2004. CLADE 2004..

[5]  P. L. Spence,et al.  view/spl I.bar/HDF: visualization and analysis tool for hierarchical data format files , 2002, OCEANS '02 MTS/IEEE.

[6]  Aldo von Wangenheim,et al.  Building a National Telemedicine Network , 2008, IT Professional.

[7]  Karl W. Schulz,et al.  Scientific formats for object-relational database systems: a study of suitability and performance , 2006, SGMD.

[8]  K M McNeill,et al.  Implementation Brief: Arizona Telemedicine Program: Implementing a Statewide Health Care Network , 1998, J. Am. Medical Informatics Assoc..

[9]  Robert Latham,et al.  High performance file I/O for the Blue Gene/L supercomputer , 2006, The Twelfth International Symposium on High-Performance Computer Architecture, 2006..

[10]  John Shalf,et al.  HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets using Fast Bitmap Indices , 2005, 18th International Conference on Scientific and Statistical Database Management (SSDBM'06).

[11]  Eros Comunello,et al.  An interoperability approach based on asynchronous replication among distributed internet databases , 2008, 2008 IEEE Symposium on Computers and Communications.