Alfonso Agatino Isola

Motion-compensated iterative cone-beam CT image reconstruction with adapted blobs as basis functions.

This paper presents a three-dimensional method to reconstruct moving objects from cone-beam X-ray projections using an iterative reconstruction algorithm and a given motion vector field. For the image representation, adapted blobs are used, which can be implemented efficiently as basis functions. Iterative reconstruction requires the calculation of line integrals (forward projections) through the image volume, which are compared with the actual measurements to update the image volume. In the existence of a divergent motion vector field, a change in the volumes of the blobs has to be taken into account in the forward and backprojections. An efficient method to calculate the line integral through the adapted blobs is proposed. It solves the problem, how to compensate for the divergence in the motion vector field on a grid of basis functions. The method is evaluated on two phantoms, which are subject to three different known motions. Moreover, a motion-compensated filtered back-projection reconstruction method is used, and the reconstructed images are compared. Using the correct motion vector field with the iterative motion-compensated reconstruction, sharp images are obtained, with a quality that is significantly better than gated reconstructions.

Fully automatic nonrigid registration-based local motion estimation for motion-corrected iterative cardiac CT reconstruction

PURPOSE Cardiac computed tomography is a rapidly emerging technique for noninvasive diagnosis of cardiovascular diseases. Nevertheless, the cardiac motion continues to be a limiting factor. Electrocardiogram-gated cardiac computed tomography reconstruction methods yield excellent results, but these are limited in their temporal resolution due to the mechanical movement of the gantry, and lead to residual motion blurring artifacts. If the motion of the cardiac region of interest is determined, motion compensated gated reconstructions can be applied to reduce motion artifacts. In this paper it is shown that elastic image registration methods can be an accurate solution to determine the cardiac motion. A method, which combines elastic registration and iterative computed tomography reconstruction methods delivering motion-corrected images of a chosen cardiac region of interest, is introduced. METHODS Using a gated four-dimensional region of interest image data set, a fully automatic elastic image registration is applied to recover a cardiac displacement field from a reference phase to a number of phases within the RR interval. Here, a stochastic optimizer and multiresolution approach are adopted to speed up the registration process. Subsequently, motion-compensated iterative reconstruction using the determined motion field is carried out. For the image representation volume-adapted spherical basis functions (blobs) are used to take the volume change caused by a divergent motion vector field into account. RESULTS The method is evaluated on phantom data and on four clinical data sets at a strong cardiac motion phase. Comparing the method to standard gated iterative reconstruction results shows that motion compensation strongly improves the image quality in these phases. A qualitative and quantitative accuracy study is presented for the estimated cardiac motion field. For the first time a blob-volume adaptation is applied on clinical data, and in the case of divergent motion it yields improved image quality. CONCLUSIONS A fully automatic local cardiac motion compensated gated iterative method with volume-adapted blobs is proposed. The method leads to excellent motion-corrected images which outperform nonmotion corrected results in phases of strong cardiac motion. In clinical cases, a volume-dependent blob-footprint adaptation proves to be a good solution to take care of the change in the blob volume caused by a divergent motion field.

Motion compensated iterative reconstruction of a region of interest in cardiac cone-beam CT

A method for motion compensated iterative CT reconstruction of a cardiac region-of-interest is presented. The algorithm is an ordered subset maximum likelihood approach with spherically symmetric basis functions, and it uses an ECG for gating. Since the straightforward application of iterative methods to CT data has the drawback that a field-of-view has to be reconstructed, which covers the complete volume contributing to the absorption, region-of-interest reconstruction is applied here. Despite gating, residual object motion within the reconstructed gating window leads to motion blurring in the reconstructed image. To limit this effect, motion compensation is applied. Hereto, a gated 4D reconstruction at multiple phases is generated for the region-of-interest, and a limited set of vascular landmarks are manually annotated throughout the cardiac phases. A dense motion vector field is obtained from these landmarks by scattered data interpolation. The method is applied to two clinical data sets at strongest motion phases. Comparing the method to standard gated iterative reconstruction results shows that motion compensation strongly improved reconstruction quality.

Image Registration and Analysis for Quantitative Myocardial Perfusion: Application to Dynamic Circular Cardiac CT

Large area detector computed tomography systems with fast rotating gantries enable volumetric dynamic cardiac perfusion studies. Prospectively, ECG-triggered acquisitions limit the data acquisition to a predefined cardiac phase and thereby reduce x-ray dose and limit motion artefacts. Even in the case of highly accurate prospective triggering and stable heart rate, spatial misalignment of the cardiac volumes acquired and reconstructed per cardiac cycle may occur due to small motion pattern variations from cycle to cycle. These misalignments reduce the accuracy of the quantitative analysis of myocardial perfusion parameters on a per voxel basis. An image-based solution to this problem is elastic 3D image registration of dynamic volume sequences with variable contrast, as it is introduced in this contribution. After circular cone-beam CT reconstruction of cardiac volumes covering large areas of the myocardial tissue, the complete series is aligned with respect to a chosen reference volume. The results of the registration process and the perfusion analysis with and without registration are evaluated quantitatively in this paper. The spatial alignment leads to improved quantification of myocardial perfusion for three different pig data sets.

Cardiac motion-corrected iterative cone-beam CT reconstruction using a semi-automatic minimum cost path-based coronary centerline extraction☆

In this paper a method which combines iterative computed tomography reconstruction and coronary centerline extraction technique to obtain motion artifact-free reconstructed images of the coronary arteries are proposed and evaluated. The method relies on motion-vector fields derived from a set of coronary centerlines extracted at multiple cardiac phases within the R-R interval. Hereto, start and end points are provided by the user in one time-frame only. Using an elastic image registration, these points are propagated to all the remaining cardiac phases. Consequently, a multi-phase three-dimensional coronary centerline is determined by applying a semi-automatic minimum cost path based extraction method. Corresponding centerline positions are used to determine the relative motion-vector fields from phase to phase. Finally, dense motion-vector fields are achieved by thin-plate-spline interpolation and used to perform a motion-corrected iterative reconstruction of a selected region of interest. The performance of the method is validated on five patients, showing the improved sharpness of cardiac motion-corrected gated iterative reconstructions compared to the results achieved by a classical gated iterative method. The results are also compared to known manual and fully automatic coronary artery motion estimation methods.

Coronary segmentation based motion corrected cardiac CT reconstruction

A method to obtain motion artifact-free reconstructed images of the coronary arteries is proposed and evaluated. The method relies on the integration of coronary motion estimation in an iterative computed tomography reconstruction technique. Coronary motion fields are derived from a set of coronary centerlines extracted at multiple cardiac phases within the R-R interval. Start and end points are provided by the user in one time-frame only. Corresponding centerline positions are used to determine the motion fields from phase to phase. Finally, dense motion fields are achieved by thin-plate-spline interpolation and are used to perform a motion-corrected iterative reconstruction of a selected region of interest, which results in an effective improvement of the reconstructed image quality.

Image registration and perfusion imaging: Application to dynamic circular cardiac CT

Large area detector computed tomography systems with fast rotating gantries enable volumetric dynamic cardiac perfusion studies. Prospectively ECG-triggered acquisitions limit the data acquisition to a predefined cardiac phase and thereby reduce X-ray dose and limit motion artifacts. Even in the case of highly accurate prospective triggering and stable heart rate, spatial misalignment of the cardiac volumes acquired and reconstructed per cardiac cycle may occur due to small motion pattern variations from cycle to cycle. These misalignments reduce the accuracy of the quantitative analysis of myocardial perfusion parameters on a per voxel basis. An image based solution to this problem is elastic 3D image registration of dynamic volume sequences with variable contrast, as it is introduced in this contribution. After circular cone-beam CT reconstruction of cardiac volumes covering large areas of the myocardial tissue, the data set with maximum contrast enhancement is selected as reference data set. The complete series is aligned with respect to this reference volume. The results are evaluated on pig data comparing perfusion measures using the non-registered versus the registered data set. The reduced spatial misalignment leads to an improved characterization of myocardial perfusion confirming the potential of this method.

Cardiac-motion correction for helical CT

The motion of the heart is a major challenge for cardiac imaging using computed tomography. An approach to decrease motion blur and to improve the signal-to-noise ratio is motion-corrected reconstruction which takes motion-vector fields into account in order to compensate motion. In this paper, the determination of a motion-vector field is described in a cardiac region-of-interest using elastic image registration while the reconstruction algorithm remains the same. The method can be applied to high contrast objects moving with the heart, such as vessels filled with contrast agent, calcified plaques or devices like stents.

Motion compensated iterative reconstruction of a cardiac region of interest for CT

A method for motion compensated iterative CT reconstruction of a cardiac region of interest is presented. The 4D motion field used during reconstruction is obtained from a three-dimensional thin-plate spline warping of a limited number of anatomical point landmarks of the right coronary artery. Results on a clinical case are compared with standard gated iterative reconstruction. The motion compensated iterative reconstruction provides sharp images of the right coronary artery with significantly better image quality compared to traditional gated reconstruction.

Efficient projection model for blobs in motion-compensated iterative cone-beam CT

We present a three-dimensional method to reconstruct moving objects from cone-beam X-ray projections using an iterative reconstruction algorithm and a given motion vector field. For the image representation, adapted blobs are used which can be implemented efficiently as basis functions. In the case of a divergent motion vector field, blob volume change has to be taken into account in the forward-projections. An efficient method to calculate the line integral through the adapted blobs is proposed, and in two simulated data sets it is shown that this method prevents blurring and streak artifacts.