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Automatic Extraction of 3D Dynamic Left Ventricle Model from 2D Rotational Angiocardiogram

  • Mingqing Chen
  • Yefeng Zheng
  • Kerstin Mueller
  • Christopher Rohkohl
  • Guenter Lauritsch
  • Jan Boese
  • Gareth Funka-Lea
  • Joachim Hornegger
  • Dorin Comaniciu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6893)

Abstract

In this paper, we propose an automatic method to directly extract 3D dynamic left ventricle (LV) model from sparse 2D rotational angiocardiogram (each cardiac phase contains only five projections). The extracted dynamic model provides quantitative cardiac function for analysis. The overlay of the model onto 2D real-time fluoroscopic images provides valuable visual guidance during cardiac intervention. Though containing severe cardiac motion artifacts, an ungated CT reconstruction is used in our approach to extract a rough static LV model. The initialized LV model is projected onto each 2D projection image. The silhouette of the projected mesh is deformed to match the boundary of LV blood pool. The deformation vectors of the silhouette are back-projected to 3D space and used as anchor points for thin plate spline (TPS) interpolation of other mesh points. The proposed method is validated on 12 synthesized datasets. The extracted 3D LV meshes match the ground truth quite well with a mean point-to-mesh error of 0.51±0.11mm. The preliminary experiments on two real datasets (included a patient and a pig) show promising results too.

Keywords

Left Ventricle Cardiac Phase Dynamic Mesh Left Ventricle Volume Deformation Vector 
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 2011

Authors and Affiliations

  • Mingqing Chen
    • 1
  • Yefeng Zheng
    • 1
  • Kerstin Mueller
    • 2
    • 3
  • Christopher Rohkohl
    • 2
  • Guenter Lauritsch
    • 2
  • Jan Boese
    • 2
  • Gareth Funka-Lea
    • 1
  • Joachim Hornegger
    • 3
  • Dorin Comaniciu
    • 1
  1. 1.Image Analytics and InformaticsSiemens Corporate ResearchPrincetonUSA
  2. 2.Healthcare SectorSiemens AGForchheimGermany
  3. 3.Pattern Recognition LabUniversity Erlangen-NurembergGermany

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