Methods Inf Med 2005; 44(02): 149-153
DOI: 10.1055/s-0038-1633936
Original Article
Schattauer GmbH

Resolving Clinicians’ Queries Across a Grid’s Infrastructure

F. Estrella
1   CCCS Research Centre, University of the West of England, Frenchay, Bristol, UK
,
C. del Frate
2   Istituto di Radiologia, Università di Udine, Udine, Italy
,
T. Hauer
1   CCCS Research Centre, University of the West of England, Frenchay, Bristol, UK
,
R. McClatchey
1   CCCS Research Centre, University of the West of England, Frenchay, Bristol, UK
,
M. Odeh
1   CCCS Research Centre, University of the West of England, Frenchay, Bristol, UK
,
D. Rogulin
1   CCCS Research Centre, University of the West of England, Frenchay, Bristol, UK
,
S. R. Amendolia
3   ETT Division, CERN, Geneva, Switzerland
,
D. Schottlander
4   Mirada Solutions Limited, Oxford, UK
,
T. Solomonides
1   CCCS Research Centre, University of the West of England, Frenchay, Bristol, UK
,
R. Warren
5   Breast Care Unit, Addensbrooke Hospital, Cambridge, UK
› Author Affiliations
Further Information

Publication History

Publication Date:
05 February 2018 (online)

Summary

Objectives: The past decade has witnessed order of magnitude increases in computing power, data storage capacity and network speed, giving birth to applications which may handle large data volumes of increased complexity, distributed over the internet.

Methods: Medical image analysis is one of the areas for which this unique opportunity likely brings revolutionary advances both for the scientist’s research study and the clinician’s everyday work. Grids [1] computing promises to resolve many of the difficulties in facilitating medical image analysis to allow radiologists to collaborate without having to co-locate.

Results: The EU-funded MammoGrid project [2] aims to investigate the feasibility of developing a Grid-enabled European database of mammograms and provide an information infrastructure which federates multiple mammogram databases. This will enable clinicians to develop new common, collaborative and co-operative approaches to the analysis of mammographic data.

Conclusion: This paper focuses on one of the key requirements for large-scale distributed mammogram analysis: resolving queries across a grid-connected federation of images.