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CAVAREV

CArdiac VAsculature Reconstruction EValuation

The main goal of CAVAREV is to enable an easy and objective comparison of different dynamic reconstruction algorithms.

The area of application is the 3-D and 4-D reconstruction of contrasted cardiac vessels, e.g. the coronary arteries using C-arm CT (rotational angiography). Various methods exist in literature with lots of nice results. However, the results can vary significantly between phantom and real clinical data.

Therefore, we provide:

  • Open (i.e. public) and easy accessible projection data.
  • Anatomically and physiologically correct projection data based on patient data.
  • Two degrees of difficulty: (a) Strictly periodic cardiac motion and (b) an aperiodic combination of cardiac and breathing motion.

Hall of Fame

Method Description Q3D (card) Q3D (card+resp) Q4D (card) Q4D (card+resp)
Spatio-temporally Regularized ECG-Gated Reconstruction [1] Iterative reconstruction minimizing spatial and temporal total variation using narrowest gating windows possible 0.87618 0 0 0
Motion Compensation for ECG-Gated Reconstruction with Large Window Sizes [2] ECG-Gated reconstruction & 2-D--2-D registration-based motion compensation 0.822566 0.385929 0.319175 0.105012
Residual Motion Compensation for ECG-Gated Reconstruction [3] ECG-Gated reconstruction & 2-D--2-D registration-based motion compensation 0.776345 0 0.279786 0
Streak-Reduced ECG-Gated FDK Reconstruction [4] ECG-Gated FDK reconstruction using an additional weighting function for reducing streaks artefacts 0.743538 0.2084 0.617927 0.107976
Dynamic Level Set Reconstruction [5] Symbolic 4D Reconstruction Using Variational Dynamic Level Sets 0.691807 0 0.605452 0
ECG-Gated FDK Reconstruction ECG-Gated FDK reconstruction using a cosine-square based weighting function 0.594723 0.156411 0.500699 0.0965542
Standard FDK Reconstruction Non-gated FDK-Reconstruction without Gating, i.e. all projection data is used without any correction 0.431399 0.206042 0.347023 0.105329

 

[1] O Taubmann et al. 2017: Spatio-temporally Regularized 4-D Cardiovascular C-arm CT Reconstruction Using a Proximal Algorithm. IEEE International Symposium on Biomedical Imaging (ISBI), Melbourne, Australia, pp. 52-55

[2] C Schwemmer et al. 2013: Opening Windows ‒ Increasing Window Size in Motion-Compensated ECG-gated Cardiac Vasculature Reconstruction. Proc. 12th intl. meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Lake Tahoe, CA, USA, pp. 50-53

[3] C Schwemmer et al. 2013: Residual Motion Compensation in ECG-Gated Interventional Cardiac Vasculature Reconstruction. Phys. Med. Biol. 58(11), pp. 3717-3737

[4] C Rohkohl et al. 2008: C-Arm CT: Reconstruction of Dynamic High Contrast Objects Applied to the Coronary Sinus. IEEE NSS-MIC (Nuclear Science Symposium-Medical Imaging Conference), Dresden, Germany, pp. M10-328

[5] A Keil et al. 2009: Dynamic Cone-Beam Reconstruction Using a Variational Level Set Formulation. Fully3D, Beijing, China

Some results for iterative methods which were not made public on the web platform have been published in:

H Wu et al. 2011: Total Variation Regularization Method for 3-D Rotational Coronary Angiography. BVM (Bildverarbeitung für die Medizin), Lübeck, Germany, pp. 434-438