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Proceedings Paper

A scanning system for intelligent imaging: I-ImaS
Author(s): R. Longo; A. Asimidis; D. Cavouras; C. Esbrand; A. Fant; P. Gasiorek; H. Georgiou; G. Hall; J. Jones; J. Leaver; G. Li; J. Griffiths; D. Machin; N. Manthos; M. Metaxas; M. Noy; J. M. Østby; F. Psomadellis; T. Rokvic; G. Royle; H. Schulerud; R. Speller; PF. van der Stelt; S. Theodoridis; F. Triantis; R. Turchetta; C. Venanzi
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Paper Abstract

I-ImaS (Intelligent Imaging Sensors) is a European project aiming to produce adaptive x-ray imaging systems using Monolithic Active Pixel Sensors (MAPS) to create optimal diagnostic images. Initial systems concentrate on mammography and cephalography. The on-chip intelligence available to MAPS technology will allow real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. In our system, the exposure in each image region is optimized and the beam intensity is a function not only of tissue thickness and attenuation, but also of local physical and statistical parameters found in the image itself. Using a linear array of detectors with on-chip intelligence, the system will perform an on-line analysis of the image during the scan and then will optimize the X-ray intensity in order to obtain the maximum diagnostic information from the region of interest while minimizing exposure of less important, or simply less dense, regions. This paper summarizes the testing of the sensors and their electronics carried out using synchrotron radiation, x-ray sources and optical measurements. The sensors are tiled to form a 1.5D linear array. These have been characterised and appropriate correction techniques formulated to take into account misalignments between individual sensors. Full testing of the mammography and cephalography I-ImaS prototypes is now underway and the system intelligence is constantly being upgraded through iterative testing in order to obtain the optimal algorithms and settings.

Paper Details

Date Published: 13 March 2007
PDF: 7 pages
Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 65100M (13 March 2007); doi: 10.1117/12.708457
Show Author Affiliations
R. Longo, Univ. of Trieste (Italy)
A. Asimidis, Univ. of Ioannina (Greece)
D. Cavouras, Technological Education Institution of Athens (Greece)
C. Esbrand, Univ. College London (United Kingdom)
A. Fant, Rutherford Appleton Lab. (United Kingdom)
P. Gasiorek, Rutherford Appleton Lab. (United Kingdom)
H. Georgiou, Univ. of Athens (Greece)
G. Hall, Imperial College High Energy Physics Group (United Kingdom)
J. Jones, Imperial College High Energy Physics Group (United Kingdom)
J. Leaver, Imperial College High Energy Physics Group (United Kingdom)
G. Li, Academic Ctr. for Dentistry (Netherlands)
J. Griffiths, Univ. College London (United Kingdom)
D. Machin, Imperial College High Energy Physics Group (United Kingdom)
N. Manthos, Univ. of Ioannina (Greece)
M. Metaxas, Univ. College London (United Kingdom)
M. Noy, Imperial College High Energy Physics Group (United Kingdom)
J. M. Østby, SINTEF ICT (Norway)
F. Psomadellis, ANCO S.A. (Greece)
T. Rokvic, Univ. of Trieste (Italy)
G. Royle, Univ. College London (United Kingdom)
H. Schulerud, SINTEF ICT (Norway)
R. Speller, Univ. College London (United Kingdom)
PF. van der Stelt, Academic Ctr. for Dentistry (Netherlands)
S. Theodoridis, Univ. of Athens (Greece)
F. Triantis, Univ. of Ioannina (Greece)
R. Turchetta, Rutherford Appleton Lab. (United Kingdom)
C. Venanzi, Univ. of Trieste (United Kingdom)
Univ. College London (United Kingdom)

Published in SPIE Proceedings Vol. 6510:
Medical Imaging 2007: Physics of Medical Imaging
Jiang Hsieh; Michael J. Flynn, Editor(s)

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