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Can the Coronary Artery Centerline Extraction in Computed Tomography Images Be Improved by Use of a Partial Volume Model?

  • Maria A. Zuluaga
  • Edgar J. F. Delgado Leyton
  • Marcela Hernández Hoyos
  • Maciej Orkisz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6375)

Abstract

We propose the use of a statistical partial volume (PV) model to improve coronary artery tracking in 3D cardiac computed tomography images, combined with a modified centerline extraction algorithm. PV effect is a challenge when trying to separate arteries from blood-filled cardiac cavities, causing leakage and erroneous segmentations. We include a Markov Random Field with a modified weighting scheme. First, synthetic phantoms were used to evaluate the robustness and accuracy of PV detection, as well as to determine the best settings. Average Dice similarity index obtained for PV voxels was 86%. Then cardiac images from eight patients were used to evaluate the usefulness of PV detection to separate real arteries from cavities, compared to Fuzzy C-means classification. Our PV detection scheme reduced approximately by half the number of leakages between artery and cavity. The new version of artery centerline extraction algorithm takes advantage of the PV detection capacity to separate arteries from cavities and to retrieve low-signal small vessels. We show some preliminary qualitative results of the complete method.

Keywords

Image Moment Cardiac Cavity Pure Classis Centerline Extraction Arterial Lumen Narrowing 
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 2010

Authors and Affiliations

  • Maria A. Zuluaga
    • 1
    • 2
  • Edgar J. F. Delgado Leyton
    • 1
  • Marcela Hernández Hoyos
    • 1
  • Maciej Orkisz
    • 2
  1. 1.Grupo IMAGINE, Grupo de Ingeniería BiomédicaUniversidad de los AndesBogotáColombia
  2. 2.Université de Lyon; Université Lyon 1; INSA-Lyon; CNRS UMR5220; INSERM U630; CREATISVilleurbanneFrance

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