MammoGrid: A Service Oriented Architecture Based Medical Grid Application

Amendolia, S. R.; Estrella, Florida; Hassan, Waseem; Hauer, Tamás; Manset, David; McClatchey, Richard; Rogulin, Dmitry; Solomonides, Tony

doi:10.1007/978-3-540-30208-7_143

Cited by 27 publications

(19 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…NeuGRID exploits the experience developed during the earlier FP5 MammoGrid project (this provided knowledge related to the middleware and upperware that allowed specific applications to 'talk' to the Grid while remaining independent) [43][44][45][46][47][48], and the AddNeuroMed study (the collection, archiving and retrieval of multicenter clinical data, biomedical images and computerized image analysis) from the FP6 InnoMed project.…”

Section: Neugrid's Gridmentioning

confidence: 99%

See 1 more Smart Citation

Grid Infrastructures for Computational Neuroscience: The neuGRID Example

et al. 2009

Self Cite

View full text Add to dashboard Cite

Evolution of brain imaging in neurodegenerative diseasesBrain imaging was regarded as an elective examination in patients with cognitive decline 15 years ago [1]. The practice parameters for diagnosis and evaluation of dementia defined by the American Academy of Neurology regarded computed tomography (CT) and magnetic resonance (MR) as 'optional' assessments [2,3]. Over time, imaging in dementia has moved from a negative, exclusionary role to one that added positive diagnostic and prognostic information. In the late 1990s, the traditional exclusionary approach was abandoned in favor of the inclusive approach [4,5]. Rapid advances in neuroimaging technologies such as PET, single photon emission CT, MR spectroscopy, diffusion tensor imaging and functional MRI have offered new vision into the pathophysiology of Alzheimer's desease (AD) [6] and, consequently, increasingly new powerful data-analysis methods have been developed [7].Since the beginning of the 21st Century, the development of innovative techniques for region-of-interest-based volumetry, automated voxel-based morphometry, cortical thickness measurement, basal forebrain volumetry and multivariate statistics have emerged [7][8][9] and those measurements most feasible and accurate have started to be used in clinical settings. The availability to the neuroimaging community of large prospective image data repositories has led to the development of web-based interfaces to access data and online image analysis tools to assess longitudinal brain changes [10][11][12][13].With the development of novel analysis techniques, the computational complexity of neuroimaging analysis has also increased signifi cantly. Higher spatial resolution images and longer time scans are being acquired so that more voxels will need to be processed for each acquisition. The same applies to the computational resources required by algorithms, since these have become increasingly central processing Neuroscience is increasingly making use of statistical and mathematical tools to extract information from images of biological tissues. Computational neuroimaging tools require substantial computational resources and the increasing availability of large image datasets will further enhance this need. Many efforts have been directed towards creating brain image repositories including the recent US Alzheimer Disease Neuroimaging Initiative. Multisite-distributed computing infrastructures have been launched with the goal of fostering shared resources and facilitating data analysis in the study of neurodegenerative diseases. Currently, some Grid-and non-Grid-based projects are aiming to establish distributed e-infrastructures, interconnecting compatible imaging datasets and to supply neuroscientists with the most advanced information and communication technologies tools to study markers of Alzheimer's and other brain diseases, but they have so far failed to make a difference in the larger neuroscience community. NeuGRID is an Europeon comission-funded effort arising from the needs of the Alzheimer's...

show abstract

Section: Neugrid's Gridmentioning

confidence: 99%

“…A SOA separates functions into distinct units termed services [53]. The MammoGrid project proposed perhaps the first healthcare example of a Grid-based SOA [43]. The MammoGrid philosophy was to provide a set of services that were i ndependent both of the front-end clinician-facing software and of the back-end Grid-facing software.…”

Section: Neugrid Architecturementioning

confidence: 99%

Grid Infrastructures for Computational Neuroscience: The neuGRID Example

et al. 2009

Self Cite

View full text Add to dashboard Cite

show abstract

“…This research advocates the use of semantic grid services to medical applications and more specifically to medical images. Some examples of work being done in the area of semantic grid services can be seen in the following references: [4]; [10]; [22]; [53].…”

Section: Knowledge and Semantic Gridmentioning

confidence: 99%

“…It is a concept that hinges on using grid services to federate a collection of heterogeneous data bases for medical images analysis [4].…”

Section: Federation Of Gridsmentioning

confidence: 99%

Strategies for Working with Digital Medical Images

Sneha

Dulipovici

2006

Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06)

View full text Add to dashboard Cite

show abstract

“…Also, they have proven to be a reliable and efficient distributed infrastructure for the management of medical images. A number of grid projects and developments in the biomedical area include: the European mammogram database MammoGrid, 4 the biomedical platform MedIGrid, 5 Virtual-PACS (a grid client application for the digital imaging and communications in medicine [DICOM] DataService), 6 caGrid (an open source grid software infrastructure aimed at enabling multi-institutional data sharing and analysis originated at the NCI Cancer Biomedical Informatics Grid [caBIG™]), 7 and the European grid-based pediatrics platform Health-e-Child, 8 among others. In addition, several research projects, focused on the augmented computing power of grids, have been reported in applications such as radiation therapy dosimetry planning through Monte Carlo simulations, 1 multiple sclerosis brain segmentation, 9 and tomographic image reconstruction.…”

Section: Introductionmentioning

confidence: 99%