Skip to main content
Log in

L’imagerie médicale: du 2D au 3D, les problèmes particuliers posés par la reconstruction tomographique en tomographie par émission de positons

Medical imaging: From 2D to 3D, specific problems of tomographic reconstruction in positron emission tomography

  • Published:
Annales Des Télécommunications Aims and scope Submit manuscript

Résumé

1917: Radon montre que l’on peut reconstruire une fonction à partir de ses projections. Pendant soixante ans, la mise en œuvre de cette théorie sur des données analogiques est un échec car le bruit de mesure est considérablement amplifié. 1970: Hounsfield applique la théorie de Radon à des projections numérisées et met au point le scanner X. Le procédé est étendu à l’ensemble de l’imagerie médicale (médecine nucléaire,irm). 2000: la disponibilité de capteurs plans rend possible les scanners X volumétriques et la tomographie par émission de positons (tep) s’impose en cancérologie. Ceci pousse au développement de méthodes de reconstruction vraiment 3D. Cet article illustre sur l’exemple de latep l’intérêt technologique et clinique d’une approche vraiment 3D, la nécessité d’un traitement numérique des données pour exploiter l’information de façon optimale. Nous insistons sur la relation entre nature des données, technologie de détection et méthodes de traitement utilisées.

Abstract

1917: Radon shows that a function can, be recontructed from its projections. For 60 years, the implementation of this theory to analogue data is a failure because the measurement noise is drastically amplified. 1970: Hounsifeld applies Radon’s theory to digital data and builds the first x-rayct scanner. His approach is generalized to many imaging modalities (nuclear medicine,mri). 2000: 2D x-ray digital detectors make it possible to develop volumetric x-rayct and Positron Emission Tomography (PET) is recognized as a major diagnostic tool in Oncology. For these purposes, fully 3D reconstruction algorithms are developed. This paper explains the technological and clinical interest of a fully 3D approach and the need to digitally process data to optimally use information. We focus on the relationship between the nature of data, the detector technology and available reconstruction methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Bibliographie

  1. Webb (S.) ed.,The physics of medical imaging, Institute of Physics Publishing, 1988.

  2. Barrett (H.H.), Swindell (W.),Radiological Imaging: The theory of image formation, Detection and Processing, Academic Press, San Diego, 1981.

    Google Scholar 

  3. Dempster (A.P.), Laird (N.M.), Rubin (D.B.),Maximum likelihood from incomplete data via the EM algorithm, J. Royal Statistical Society, Series B-Methodological,39, no 1, pp. 1–38, 1977.

    MATH  MathSciNet  Google Scholar 

  4. Shepp (L.A.), Vardi (Y.),Maximum likelihood reconstruction for emission tomography, IEEE Trans Med. Imaging,1, no 2, pp. 113–122, 1982.

    Article  Google Scholar 

  5. Fessler (J.A.),Penalized weighted least squares image reconstruction for positron emission tomography, IEEE Trans. Med. Imaging,13, no 2, pp. 290–300, 1994.

    Article  Google Scholar 

  6. Qi (J.), Leahy (R.M.), Hsu (C.), Farquhar (T.H.), Cherry (S.R.),Fully 3D Bayesian image reconstruction for the Ecat Exact HR+, IEEE Trans Nucl. Sci.,45, pp. 1096–1103, 1998.

    Article  Google Scholar 

  7. Hudson (H.M.), Larkin (R.S.), Accelerated image reconstruction using ordered subsets of projection data, IEEE Trans. Med. Imaging,13, no 4, pp 601–609, 1994.

    Article  Google Scholar 

  8. Browne (J.A.), De Pierro (A.R.),A row action alternative to the EM algorithm for maximizing likelihoods in emission tomography, IEEE Trans. Med. Imaging,15, no 5, pp. 687–699, 1996.

    Article  Google Scholar 

  9. Matej (S.), Lewitt (R.M.),Efficient 3D grids for image reconstruction using spherically-symmetric volume elements, IEEE Trans Nucl. Sci.,42, no 4, pp. 1361–1370, 1995 Matej (82).

    Article  Google Scholar 

  10. Shepp (L.A.), Logan (B.F.),The Fourier reconstruction of a head section, IEEE Trans Nucl. Sci.,21, no 3, pp. 21–43, 1974.

    Google Scholar 

  11. Matej (S.), Lewitt (R.M.), 3D-FRP:Direct Fourier reconstruction with Fourier reprojection for fully 3D Pet, IEEE Trans. Nucl. Sci,48, no 4, pp. 1378–1385, 2001.

    Article  Google Scholar 

  12. Defrise (M.), Kinahan (P.E.), Townsend (D.W.), Michel (C.), Sibomana (M.), Newport (D.F.),Exact and approximate rebinning algorithms for 3D PET data, IEEE Trans. Med. Imaging,16, no 2, pp. 145–158, 1997.

    Article  Google Scholar 

  13. Novikov (R.G.),On the range characterization for the two-dimensional attenuated x-ray transformation, Inverse problems,18, no 3, pp. 113–119, 2001.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bizais, Y., Lamare, F., Turzo, A. et al. L’imagerie médicale: du 2D au 3D, les problèmes particuliers posés par la reconstruction tomographique en tomographie par émission de positons. Ann. Télécommun. 58, 801–819 (2003). https://doi.org/10.1007/BF03001531

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03001531

Mots clés

Key words

Navigation