Estimation of the Deformation Field for the Left Ventricle Walls in 4-D Multislice Computerized Tomography

  • Antonio Bravo
  • Rubén Medina
  • Gianfranco Passariello
  • Mireille Garreau
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3773)

Abstract

This paper describes a method for estimating the deformation field of the Left Ventricle (LV) walls from a 4–D Multi Slice Computerized Tomography (MSCT) database. The approach is composed of two stages: in the first, a 2–D non–rigid correspondence algorithm matches a set of contours on the LV at consecutive time instants. In the second, a 3–D curvature–based correspondence algorithm is used to optimize the initial approximate correspondence. The dense displacement field is obtained based on the optimized correspondence. Parameters like LV volume, radial contraction and torsion are estimated. The algorithm is validated on synthetic objects and tested using a 4–D MSCT database. Results are promising as the error of the displacement vectors is 2.69 ± 1.38 mm using synthetic objects and, when tested in real data, local parameters extracted agree with values obtained using tagged magnetic resonance imaging.

Keywords

Multi Slice Computerize Tomography Left Ventricle Wall Correspondence Algorithm Radial Contraction Synthetic Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Antonio Bravo
    • 1
  • Rubén Medina
    • 2
  • Gianfranco Passariello
    • 3
  • Mireille Garreau
    • 4
  1. 1.Grupo de BioingenieríaUniversidad Nacional Experimental del Táchira, Decanato de InvestigaciónSan CristóbalVenezuela
  2. 2.Grupo de Ingeniería BiomédicaUniversidad de Los Andes, Facultad de IngenieríaMéridaVenezuela
  3. 3.Grupo de Bioingeniería y Biofísica Aplicada (GBBA)Universidad Simón BolívarSartenejasVenezuela
  4. 4.Laboratoire Traitement du Signal et de L’ImageUniversité de Rennes 1RennesFrance

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