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M Sitta

Publications and source records attributed to M Sitta.

2 recordsLinked to original sources
PubMed2005

Contrast cancellation technique applied to digital x-ray imaging using silicon strip detectors.

Dual-energy mammographic imaging experimental tests have been performed using a compact dichromatic imaging system based on a conventional x-ray tube, a mosaic crystal, and a 384-strip silicon detector equipped with full-custom electronics with single photon counting capability. For simulating mammal tissue, a three-component phantom, made of Plexiglass, polyethylene, and water, has been used. Images have been collected with three different pairs of x-ray energies: 16-32 keV, 18-36 keV, and 20-40 keV. A Monte Carlo simulation of the experiment has also been carried out using the MCNP-4C transport code. The Alvarez-Macovski algorithm has been applied both to experimental and simulated data to remove the contrast between two of the phantom materials so as to enhance the visibility of the third one.

Algorithms↗
PubMed2005

GPCALMA: a Grid-based tool for mammographic screening.

OBJECTIVES: The next generation of high energy physics (HEP) experiments requires a GRID approach to a distributed computing system: the key concept is the Virtual ORGANISATION (VO), a group of distributed users with a common goal and the will to share their resources. METHODS: A similar approach, applied to a group of hospitals that joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. The application code makes use of neural networks for the image analysis and is useful in improving the radiologists' diagnostic performance. GRID services allow remote image analysis and interactive online diagnosis, with a potential for a relevant reduction of the delays presently associated with screening programs. RESULTS AND CONCLUSIONS: A prototype of the system, based on AliEn GRID Services [1], is already available, with a central server running common services [2] and several clients connecting to it. Mammograms can be acquired in any location; the related information required to select and access them at any time is stored in a common service called Data Catalogue, which can be queried by any client. Thanks to the PROOF facility [3], the result of a query can be used as input for analysis algorithms, which are executed on the nodes where the input images are stored,. The selected approach avoids data transfers for all the images with a negative diagnosis and allows an almost real time diagnosis for the set of images with high cancer probability.

Algorithms↗