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A.L. Rowland, M.
Burns, T. Hartkens, J.V. Hajnal, D. Rueckert, D.L.G. Hill, "Image
Processing Workflows Using A Grid Enabled Image Database", DiDaMIC
Workshop - MICCAI 2004, Rennes, France |
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Grid services offer a number of advantages in the field of medical imaging.
Many image processing algorithms are computationally intensive and require
high specification hardware or take a long time to run. The prospect of
being able to use dedicated clusters of high end workstations on a remote
network, or indeed several networks, with only a few clicks of the mouse
is now within reach.
An image database removes the need for the user to know the exact location
of the image data they are using. Similarly a grid portal hides the complexity
of grid technology from the interface by handling service invocations
at a lower level. Integrating these two concepts enables an end-to-end
solution that brings all the capabilities of distributed supercomputing
to the average user who is often more interested in the end result of
execution rather than the means by which it is accomplished.
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B Sneller, J Vickers,
MA Dresner, RA Heckemann, J Fitzpatrick, ME Miquel, JV Hajnal, DLG Hill,
"A comparison of serial MR neuroimaging at 1.5T and 3T", Proceedings
MIUA 2004. 224-227, 23 Sep 2004 |
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For serial studies that seek to identify subtle changes over time, it
is desirable to aggregate results from studies acquired on different scanners
potentially at different field strengths, and using different RF coil
technology. We compare serial magnetic resonance (MR) image registration
results from similar acquisitions at 1.5T and 3T, using both birdcage
and array coils.
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A.L. Rowland, T.
Hartkens, M. Burns, J.V. Hajnal, D. Rueckert, D.L.G. Hill, "A Grid
Enabled Medical Image Database", UK e-Science All Hands Meeting,
Nottingham 2004 |
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Medical image processing involves a large amount of data that can be
difficult to store and manage. This project uses an automated process
to extract clinical and technical information from image file headers
which is used to construct a database of medical images. A web based search
and retrieval interface is used to present the data to the user with on-line
access to images via a choice of viewing tools. A grid-enabled image processing
portal is provided with access to a suite of image processing algorithms
implemented as grid services which can then be seamlessly invoked from
the web interface.
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K.K. Leung, M. Holden, R.A.
Heckmann, N. Saeed, K.J. Brooks, J.B. Buckton, K. Changani, D.G. Reid,
D. Rueckert, J.V. Hajnal, and D.L. Hill, "Use of data provenance
and the Grid in medical image analysis and drug discovery - an IXI exemplar,"
UK e-Science All Hands Meeting, 09/2004 |
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Medical research and drug discovery rely increasingly on comparisons
between magnetic resonance images from large numbers of subjects, often
with multiple time points for each subject. We applied image registration
and visualisation techniques for quantitative and qualitative assessment
of changes over time in an experimental model of rheumatoid arthritis.
We used the Grid to enable remote invocation and parallel execution of
the algorithms. Data provenance was stored in a database to provide information
about the validity, accuracy and timeliness of the data, which establishes
a data integrity framework that is very important in the process of drug
discovery and development.
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K.K. Leung, R.A. Heckmann,
N. Saeed, K.J. Brooks, J.B. Buckton, K. Changani, D.G. Reid, D. Rueckert,
J.V. Hajnal, M. Holden and D.L. Hill, "Analysis of serial MR images
of joints," IEEE International Symposium on Biomedical Imaging (ISBI
2004), 04/2004. |
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Medical research and drug discovery rely increasingly on making comparisons
between MR images from large numbers of subjects, often with multiple
time points for each subject. We show how image registration and visualisation
technique can be used for quantitative and qualitative assessment of changes
over time in an experimental model of rheumatoid arthritis. We applied
the technique to automatically delineate two separate bones (the calcaneus
and talus) from the in vivo MR images of an ankle (6 subjects, 6 time
points each) by propagating labels from pre-labelled "atlas"
MRI scans. As an initial analysis, we calculated their volume and rendered
their surfaces in 3D to study the disease progression over time. Finally,
we investigated the use of Grid computing by coupling it with image analysis
and visualisation algorithms to enable remote invocation, parallel execution,
and source data input from heterogeneous distributed image repositories.
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