M. Riding

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Existing Grid visualization systems typically focus on the distribution onto remote machines of some or all of the processes encompassing the visualization pipeline, with the aim of increasing the maximum data size, achievable frame rates or display resolution. Such systems may rely on a particular piece of visualization software, and require that the end(More)
Two sisters with autosomal recessive cerebellar hypoplasia and severe nonprogressive retinal pigmentary disease are presented. This syndrome has been previously described in only 1 patient. The retinal changes may be difficult to discern and we suggest that all patients with congenital ataxia have a detailed ophthalmologic assessment, including(More)
We have implemented an interactive imaging system for the interpretation of UroVysion fluorescence in situ hybridization (FISH) to improve throughput, productivity, quality control and diagnostic accuracy. We describe the Duet imaging system, our experiences with implementation, and outline the financial investment, space requirements, information(More)
Magnetic resonance imaging brain scans and neuropsychological assessments of 17 children who met the NIH consensus diagnostic criteria for neurofibromatosis Type 1 were carried out in order to determine if there is a relationship between presence of high intensity signal abnormalities on MRI scans and nonverbal cognitive deficits. Cranial MRI scans in 10(More)
The Seamless Access to Multiple Datasets (SAMD) project is designed to demonstrate the benefits of Grid (e-Science) technologies for dataset manipulation and analyses in a social science context. Grid technologies run over existing internet infrastructures and offer a faster alternative to the world wide web for the transfer and analysis of large datasets.(More)
In situations where the size of a remotely stored dataset hinders its transmission over public networks, it becomes feasible to visualize using hardware resources local to the data rather than the user. A difficulty with this approach is that the visualization user often has no control over the software resources available on remote visualization machines.(More)
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