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A Multi-Element Detector System for Intelligent Imaging: I-maS

Abstract

I-ImaS is a European project aiming to produce new, intelligent X-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems concentrate on mammography and encephalography. Later development will yield systems for other types of radiography such as industrial QA and homeland security. The I-ImaS system intelligence, due to APS technology and FPGAs, allows 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. A companion paper deals with the DAQ system and preliminary characterization. This paper considers the laboratory X-ray characterization of the detector elements of the I-ImaS system. The characterization of the sensors when tiled to form a strip detector will be discussed, along with the appropriate correction techniques formulated to take into account the misalignments between individual sensors within the array. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems under construction and this paper will further discuss the testing of these systems and the iterative processes used for intelligence upgrade in order to obtain the optimal algorithms and settings.

Category

Academic chapter

Language

English

Author(s)

  • Jennifer A. Griffiths
  • Marinos G. Metaxas
  • Gary J. Royle
  • Cristian Venanzi
  • Colin Esbrand
  • Paul F. van der Stelt
  • Hans Verheij
  • Gang Li
  • Renato Turchetta
  • Andrea Fant
  • Przemyslaw Gasiorek
  • Sergios Theodoridis
  • Harris Georgiou
  • Dionissis Cavouras
  • Geoff Hall
  • Matthew Noy
  • John Jones
  • James D.G. Leaver
  • Davy Machin
  • S. L. Greenwood
  • M. Khaleeq
  • Helene Schulerud
  • Joar Martin Østby
  • Frixos A. Triantis
  • Asimakis Asimidis
  • Dimos Bolanakis
  • Nikos Manthos
  • Renata Longo
  • Anna Bergamaschi
  • Robert D. Speller

Affiliation

  • SINTEF Digital / Sustainable Communication Technologies
  • SINTEF Digital / Smart Sensors and Microsystems
  • Greece
  • National Technical University of Athens
  • Panepistimion Ioanninon
  • University of Trieste
  • Free University Amsterdam
  • Imperial College London
  • University College London
  • CCLRC Rutherford Appleton Laboratory

Year

2006

Publisher

IEEE

Book

IEEE Nuclear Science Symposium Conference Record, San Diego Oct 29-Nov 1, 2006

ISBN

9781424405619

Page(s)

2554 - 2558

View this publication at Norwegian Research Information Repository