Grid Computing: Concepts and Applications

The challenge of CERN experiments at the Large Hadron Collider (LHC), which will collect data at rates in the range of PBs/year, requires the development of GRID technologies to optimize the exploitation of distributed computing power and the automatic access to distributed data storage. Several projects are addressing the problem of setting up the hardware infrastructure of a GRID, as well as the development of the middleware required to manage it: a working GRID should look like a set of services, accessible to registered applications, which will help cooperate the different computing and storage resources. As it happened for the World Wide Web, GRID concepts are in principle important not only for High Energy Physics (HEP): for this reason, GRID developers, while keeping in mind the needs of HEP experiments, are trying to design GRID services in the most general way. As examples, two applications are described: the CERN/ALICE experiment at the LHC and a recently approved INFN project (GPCALMA) which will set up a GRID prototype between several mammographic centres in Italy

GPCALMA: a Grid Approach to Mammographic Screening

The next generation of High Energy Physics experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the "Virtual Organisation" (VO), a group of geographycally distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and shows performances similar to radiologists in the diagnosis. GRID technologies will allow remote image analysis and interactive online diagnosis, with a relevant reduction of the delays presently associated to screening programs.Comment: 4 pages, 3 figures; to appear in the Proceedings of Frontier Detectors For Frontier Physics, 9th Pisa Meeting on Advanced Detectors, 25-31 May 2003, La Biodola, Isola d'Elba, Ital

AliEn - EDG Interoperability in ALICE

AliEn (ALICE Environment) is a GRID-like system for large scale job submission and distributed data management developed and used in the context of ALICE, the CERN LHC heavy-ion experiment. With the aim of exploiting upcoming Grid resources to run AliEn-managed jobs and store the produced data, the problem of AliEn-EDG interoperability was addressed and an in-terface was designed. One or more EDG (European Data Grid) User Interface machines run the AliEn software suite (Cluster Monitor, Storage Element and Computing Element), and act as interface nodes between the systems. An EDG Resource Broker is seen by the AliEn server as a single Computing Element, while the EDG storage is seen by AliEn as a single, large Storage Element; files produced in EDG sites are registered in both the EDG Replica Catalogue and in the AliEn Data Catalogue, thus ensuring accessibility from both worlds. In fact, both registrations are required: the AliEn one is used for the data management, the EDG one to guarantee the integrity and access to EDG produced data. A prototype interface has been successfully deployed using the ALICE AliEn Server and the EDG and DataTAG Testbeds.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003,4 pages, PDF, 2 figures. PSN TUCP00

Predictive models based on Support Vector Machines: whole-brain versus regional analysis of structural MRI in the Alzheimer’s disease

Decision-making systems trained on structural magnetic resonance imaging data of subjects affected by the Alzheimer's disease (AD) and healthy controls (CTRL) are becoming widespread prognostic tools for subjects with mild cognitive impairment (MCI). This study compares the performances of three classification methods based on support vector machines (SVMs), using as initial sets of brain voxels (ie, features): (1) the segmented grey matter (GM); (2) regions of interest (ROIs) by voxel-wise t-test filtering; (3) parceled ROIs, according to prior knowledge. The recursive feature elimination (RFE) is applied in all cases to investigate whether feature reduction improves the classification accuracy. We analyzed more than 600 AD Neuroimaging Initiative (ADNI) subjects, training the SVMs on the AD/CTRL dataset, and evaluating them on a trial MCI dataset. The classification performance, evaluated as the area under the receiver operating characteristic curve (AUC), reaches AUC = (88.9 ± .5)% in 20-fold cross-validation on the AD/CTRL dataset, when the GM is classified as a whole. The highest discrimination accuracy between MCI converters and nonconverters is achieved when the SVM-RFE is applied to the whole GM: with AUC reaching (70.7 ± .9)%, it outperforms both ROI-based approaches in predicting the AD conversion

A Computer Aided Detection system for mammographic images implemented on a GRID infrastructure

The use of an automatic system for the analysis of mammographic images has proven to be very useful to radiologists in the investigation of breast cancer, especially in the framework of mammographic-screening programs. A breast neoplasia is often marked by the presence of microcalcification clusters and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. In the framework of the GPCALMA (GRID Platform for Computer Assisted Library for MAmmography) project, the co-working of italian physicists and radiologists built a large distributed database of digitized mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) system, able to make an automatic search of massive lesions and microcalcification clusters. The CAD is implemented in the GPCALMA integrated station, which can be used also for digitization, as archive and to perform statistical analyses. Some GPCALMA integrated stations have already been implemented and are currently on clinical trial in some italian hospitals. The emerging GRID technology can been used to connect the GPCALMA integrated stations operating in different medical centers. The GRID approach will support an effective tele- and co-working between radiologists, cancer specialists and epidemiology experts by allowing remote image analysis and interactive online diagnosis.Comment: 5 pages, 5 figures, to appear in the Proceedings of the 13th IEEE-NPSS Real Time Conference 2003, Montreal, Canada, May 18-23 200

Lung Nodule Detection in Screening Computed Tomography

A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images with 1.25 mm slice thickness is presented. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a neural classifier for false-positive finding reduction, are described. The results obtained on the collected database of lung CT scans are discussed.Comment: 3 pages, 4 figures; Proceedings of the IEEE NNS and MIC Conference, Oct. 29 - Nov. 4, 2006, San Diego, Californi

HEP Applications Evaluation of the EDG Testbed and Middleware

Workpackage 8 of the European Datagrid project was formed in January 2001 with representatives from the four LHC experiments, and with experiment independent people from five of the six main EDG partners. In September 2002 WP8 was strengthened by the addition of effort from BaBar and D0. The original mandate of WP8 was, following the definition of short- and long-term requirements, to port experiment software to the EDG middleware and testbed environment. A major additional activity has been testing the basic functionality and performance of this environment. This paper reviews experiences and evaluations in the areas of job submission, data management, mass storage handling, information systems and monitoring. It also comments on the problems of remote debugging, the portability of code, and scaling problems with increasing numbers of jobs, sites and nodes. Reference is made to the pioneeering work of Atlas and CMS in integrating the use of the EDG Testbed into their data challenges. A forward look is made to essential software developments within EDG and to the necessary cooperation between EDG and LCG for the LCG prototype due in mid 2003.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics Conference (CHEP03), La Jolla, CA, USA, March 2003, 7 pages. PSN THCT00

Characteristics of the ALICE Silicon Drift Detector

A Silicon Drift Detector (SDD) with an active area of 7.0 x 7.5 cm2 has been designed, produced and tested for the ALICE Inner Tracking System. The development of the SDD has been focussed on the capability of the detector to work without an external support to the integrated high voltage divider. Severalfeatures have been implemented in the design in order to increase the robustness and the long-term electrical stability of the detector. One of the prototypes has been tested in a pion beam at the CERN SPS. Preliminary results on the position resolution are given