Evaluation of interpolation methods for surface-based motion compensated tomographic reconstruction for cardiac angiographic C-arm data

Journal Article · Fri Mar 15 04:00:00 EDT 2013 · Medical Physics

DOI:https://doi.org/10.1118/1.4789593· OSTI ID:22130542

Mueller, Kerstin; Schwemmer, Chris; Hornegger, Joachim ^[1]; Yefeng, Zheng; Yang, Wang ^[2]; Lauritsch, Guenter; Rohkohl, Christopher; Maier, Andreas K. ^[3]; Schultz, Carl ^[4]; Fahrig, Rebecca ^[5]

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1. Pattern Recognition Lab, Department of Computer Science, Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander-Universitaet Erlangen-Nuernberg, Erlangen 91058 (Germany)
2. Imaging and Computer Vision, Siemens Corporate Research, Princeton, New Jersey 08540 (United States)
3. Siemens AG, Healthcare Sector, Forchheim 91301 (Germany)
4. Thoraxcenter, Erasmus MC, Rotterdam 3000 (Netherlands)
5. Department of Radiology, Stanford University, Stanford, California 94305 (United States)

Purpose: For interventional cardiac procedures, anatomical and functional information about the cardiac chambers is of major interest. With the technology of angiographic C-arm systems it is possible to reconstruct intraprocedural three-dimensional (3D) images from 2D rotational angiographic projection data (C-arm CT). However, 3D reconstruction of a dynamic object is a fundamental problem in C-arm CT reconstruction. The 2D projections are acquired over a scan time of several seconds, thus the projection data show different states of the heart. A standard FDK reconstruction algorithm would use all acquired data for a filtered backprojection and result in a motion-blurred image. In this approach, a motion compensated reconstruction algorithm requiring knowledge of the 3D heart motion is used. The motion is estimated from a previously presented 3D dynamic surface model. This dynamic surface model results in a sparse motion vector field (MVF) defined at control points. In order to perform a motion compensated reconstruction, a dense motion vector field is required. The dense MVF is generated by interpolation of the sparse MVF. Therefore, the influence of different motion interpolation methods on the reconstructed image quality is evaluated. Methods: Four different interpolation methods, thin-plate splines (TPS), Shepard's method, a smoothed weighting function, and a simple averaging, were evaluated. The reconstruction quality was measured on phantom data, a porcine model as well as on in vivo clinical data sets. As a quality index, the 2D overlap of the forward projected motion compensated reconstructed ventricle and the segmented 2D ventricle blood pool was quantitatively measured with the Dice similarity coefficient and the mean deviation between extracted ventricle contours. For the phantom data set, the normalized root mean square error (nRMSE) and the universal quality index (UQI) were also evaluated in 3D image space. Results: The quantitative evaluation of all experiments showed that TPS interpolation provided the best results. The quantitative results in the phantom experiments showed comparable nRMSE of Almost-Equal-To 0.047 {+-} 0.004 for the TPS and Shepard's method. Only slightly inferior results for the smoothed weighting function and the linear approach were achieved. The UQI resulted in a value of Almost-Equal-To 99% for all four interpolation methods. On clinical human data sets, the best results were clearly obtained with the TPS interpolation. The mean contour deviation between the TPS reconstruction and the standard FDK reconstruction improved in the three human cases by 1.52, 1.34, and 1.55 mm. The Dice coefficient showed less sensitivity with respect to variations in the ventricle boundary. Conclusions: In this work, the influence of different motion interpolation methods on left ventricle motion compensated tomographic reconstructions was investigated. The best quantitative reconstruction results of a phantom, a porcine, and human clinical data sets were achieved with the TPS approach. In general, the framework of motion estimation using a surface model and motion interpolation to a dense MVF provides the ability for tomographic reconstruction using a motion compensation technique.

• OSTI ID: 22130542
• Journal Information: Medical Physics, Journal Name: Medical Physics Journal Issue: 3 Vol. 40; ISSN 0094-2405; ISSN MPHYA6
• Country of Publication: United States
• Language: English

Related Subjects

60 APPLIED LIFE SCIENCES
62 RADIOLOGY AND NUCLEAR MEDICINE
71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
COMPUTERIZED TOMOGRAPHY
CONTROL
IMAGE PROCESSING
IMAGES
IN VIVO
INTERPOLATION
PHANTOMS
SENSITIVITY
SURFACES
VECTOR FIELDS
WEIGHTING FUNCTIONS