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Spinal fusion is a common procedure to stabilize the spinal column by fixating parts of the spine. In such procedures, metal screws are inserted through the patients back into a vertebra, and the screws of adjacent vertebrae are connected by metal rods to generate a fixed bridge. In these procedures, 3D image guidance for intervention planning and outcome control is required. Here, for anatomical guidance, an automated approach for vertebra segmentation from C-arm CT images of the spine is introduced and evaluated. As a prerequisite, 3D C-arm CT images are acquired covering the vertebrae of interest. An automatic model-based segmentation approach is applied to delineate the outline of the vertebrae of interest. The segmentation approach is based on 24 partial models of the cervical, thoracic and lumbar vertebrae which aggregate information about (i) the basic shape itself, (ii) trained features for image based adaptation, and (iii) potential shape variations. Since the volume data sets generated by the C-arm system are limited to a certain region of the spine the target vertebra and hence initial model position is assigned interactively. The approach was trained and tested on 21 human cadaver scans. A 3-fold cross validation to ground truth annotations yields overall mean segmentation errors of 0.5 mm for T1 to 1.1 mm for C6. The results are promising and show potential to support the clinician in pedicle screw path and rod planning to allow accurate and reproducible insertions.

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

Filtered back-projection (FBP) has been commonly used as an efficient and robust reconstruction technique in tomographic X-ray imagingduring the last decades. For limited angle tomography acquisitions such as digital breast tomosynthesis, however, standard FBP reconstruction algorithms provide poor results and give rise to image artifacts due to the limited angular range and the coarse angular sampling.Therefore, iterative algorithms are often used in digital breast tomosynthesis since they potentially yield a reconstructed image thatis in better accordance with the measured data. In this work, a generalized FBP algorithm is presented, which uses the filtered projection data of all acquired views for back-projection along one direction in order to compute an image that is similar to an iteratively calculated one. The proposed method yields a computationally efficientgeneralized FBP algorithm for digital breast tomosynthesis, which provides similar image quality as iterative reconstruction techniqueswhile preserving the ability for region of interest reconstructions. Both a small number of views and a limited angular range can be handled with the generalized FBP while common FBP reconstruction yields a severe loss of the average value, which will be demonstrated onsimulated breast tomosynthesis data. Moreover, due to the filter computation as the pseudo-inverse operator, the reconstructed image provides an optimal solution in the least-squares sense, which minimizes the error between the measured data and the reprojections of thereconstructed image.

The contrast of iodine to soft tissue (water) decreases with higher tube voltage in reconstructed 3D X-ray images. Improved acquisition protocols with a tube voltage of about 80 kV for imaging iodine have been proposed earlier for diagnostic CT imaging. We investigate the contrast-to-noise ratio (CNR) and the CNR-to-dose ratio (CDR) for different concentrations of iodinated contrast agent inserts in water background. The tube voltage of the protocol is lowered from 123 kV to 83 kV in 10 kV steps. A series of measurements with 16 different settings of tube voltage, current and filter settings are investigated. The weighted computed tomography dose index CTDIW for the new protocol settings is measured. Four protocols with tube voltages between 83 kV and 103 kV and similar X-ray dose are compared to the original protocol. A low contrast phantom, containing a water filled cylinder with 5 tubes of different mixtures of iodine contrast inside a 32 cm PMMA ring, is imaged with each protocol. Increased contrast of the iodine filled tubes to the water background is clearly visible in the reconstructed volumes for lower tube voltage and less copper filtering. The best results are obtained with the (83 kV, 561 mA, 0.4 Cu) – protocol. This protocol may improve iodine contrast agent visibility in various 3D imaging applications. For large patients a higher tube voltage, e.g. the (103 kV, 325 mA, 0.4 Cu) – protocol, may be used to avoid tube power limitations at 83 kV. This protocol still has improved iodine imaging compared to the 123 kV protocol and a larger tube power reserve.

Interventional C-arm systems allow the efficient acquisition of 3D cone beam CT images. They can be used for intervention planning, navigation, and outcome assessment. We present a fast and completely automated volume of interest (VOI) delineation for cardiac interventions, covering the whole visceral cavity including mediastinum and lungs but leaving out rib-cage and spine. The problem is addressed in a model based approach. The procedure has been evaluated on 22 patient cases and achieves an average surface error below 2mm. The method is able to cope with varying image intensities, varying truncations due to the limited reconstruction volume, and partially with heavy metal and motion artifacts.

Digital breast tomosynthesis (DBT) aims for improving the diagnosis of breast cancer and reducing the false positive rates by going from 2D projection mammography to 3D volume information. With the acquisition of a series of projection images, taken over a limited angular range, DBT allows for tomographic reconstruction with high in-plane but reduced depth resolution. Therefore, anatomical structures get blurred along the depth direction and produce out-of-plane artifacts. Prominent streak artifacts can be observed for high-contrast objects such as calcifications, which degrade the image quality, see for example Figure 8(a) - (f) in [4]. In this work, a second pass method for correcting these streak-like artifacts is introduced. For evaluation of this method, a software based breast phantom has been developed from segmented MRI breast data.

Cardiac CT image reconstruction suffers from artifacts due to heart motion during acquisition. In order to mitigate these effects, it is common practice to choose a protocol with minimal gating window and fast gantry rotation. In addition, it is possible to estimate heart motion retrospectively and to incorporate the information in a motion-compensated reconstruction (MCR). If shape tracking algorithms are used for generation of the heart motion-vector field (MVF), the number and positions of the motion vectors will not coincide with the number and positions of the voxels in the reconstruction grid. In this case, data interpolation is necessary for MCR algorithms which require one motion vector at each voxel location. This work examines different data interpolation approaches for the MVF interpolation problem and the effects on the MCR results.

Rotational X-ray data acquisition in combination with gated reconstruction is applied most commonly to reconstruct 3D or 4D images of the heart on interventional X-ray systems. The data are acquired during breath hold and with intravenous contrast agent injection. Unfortunately, when using a single circular arc acquisition with parallel ECG recording, the gating of the projections leads to under-sampling artifacts in the reconstruction volume. In this contribution an artifact reduction method is suggested which is based on an initial gated reconstruction of a cardiac volume at limited quality, the subsequent segmentation of the volume and a second pass correction to enhance the signal-to-noise ratio in the reconstruction volume and to reduce the artifacts due to gating. The method is applied to both phantom and animal data.

The tomographic reconstruction of the beating heart requires dedicated methods. One possibility is gated reconstruction, where only data corresponding to a certain motion state are incorporated. Another one is motioncompensated reconstruction with a pre-computed motion vector field, which requires a preceding estimation of the motion. Here, results of a new approach are presented: simultaneous reconstruction of a three-dimensional object and its motion over time, yielding a fully four-dimensional representation. The object motion is modeled by a time-dependent elastic transformation. The reconstruction is carried out with an iterative gradient-descent algorithm which simultaneously optimizes the three-dimensional image and the motion parameters. The method was tested on a simulated rotational X-ray acquisition of a dynamic coronary artery phantom, acquired on a C-arm system with a slowly rotating C-arm. Accurate reconstruction of both absorption coefficient and motion could be achieved. First results from experiments on clinical rotational X-ray coronary angiography data are shown. The resulting reconstructions enable the analysis of both static properties, such as vessel geometry and cross-sectional areas, and dynamic properties, like magnitude, speed, and synchrony of motion during the cardiac cycle.

Three-dimensional (3D) reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular diseases, compared to two-dimensional X-ray angiograms. Besides improved roadmapping, quantitative analysis of vessel lesions is possible. To perform 3D reconstruction, rotational projection data of the selectively contrast agent enhanced coronary arteries are acquired with simultaneous ECG recording. For the reconstruction of one cardiac phase, the corresponding projections are selected from the rotational sequence by nearest-neighbor ECG gating. This typically provides only 5-10 projections per cardiac phase. The severe angular undersampling leads to an ill-posed reconstruction problem. In this contribution, an iterative reconstruction method is presented which employs regularizations especially suited for the given reconstruction problem. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, we formulate the reconstruction problem as a minimization of the L 1 -norm of the reconstructed image, which results in a spatially sparse object. Two additional regularization terms are introduced: a 3D vesselness prior, which is reconstructed from vesselness-filtered projection data, and a Gibbs smoothing prior. The regularizations favor the reconstruction of the desired object, while taking care not to over-constrain the reconstruction by too detailed a-priori assumptions. Simulated projection data of a coronary artery software phantom are used to evaluate the performance of the method. Human data of clinical cases are presented to show the method's potential for clinical application.

In this contribution, the results of a phantom study for in-stent restenosis imaging with ECG gated continuous circular acquisition and reconstruction are summarized. Different rotation speeds and angular ranges are used to enable high resolution 3D and 4D reconstruction of objects covered by the cone at a high temporal resolution. Though the detector coverage of today's CT scanners is not large enough to irradiate the complete human heart, the coverage is sufficient to image smaller objects like conventional stents. We applied the proposed method to the visualization of an in-stent re-stenoses phantom covered by a clinical stent, attached to a dynamic heart phantom. The method delivers images of stents in vitro at an excellent visibility and is able to rule out in-stent occlusions.

In this contribution, we introduce a retrospectively gated cardiac cone-beam reconstruction scheme for continuous circular acquisition with parallel ECG recording. The technique is capable of handling variable angular ranges and enables high resolution 3D and 4D reconstruction of objects covered by the cone at a high temporal resolution. Though the detector coverage of nowadays CT scanners is not large enough to cover the complete human heart, it is sufficient to image smaller objects like conventional stents. We applied the proposed reconstruction method to the visualization of an in-stent re-stenoses phantom covered by a clinical stent, attached to a dynamic heart phantom. The method delivers images of stents in vitro at an excellent visibility and is able to rule out in-stent occlusions.

In this contribution, we investigate the spatial and temporal resolution of retrospectively gated cardiac cone-beam CT. Data of a static and a dynamic resolution phantom are acquired for various heart rates, table speeds and scanner rotation times. The projection data are reconstructed in different motion states with the help of a retrospectively gated helical cardiac cone-beam reconstruction method. This multi-cycle method automatically adapts the number of heart cycles used for the reconstruction, based on the scan parameters and the ECG data. The spatial resolution is derived from a resolution phantom by multi-planar reformation (MPR) along the scan direction.© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

With the introduction of ultra-fast cone beam scanners, cardiac CT imaging has become feasible. In order to achieve excellent image quality, cardiac phases must be found during which the heart is quasi-stationary. Electrocardiogram (ECG) information does not always correspond to the exact motion-state of the heart, and there is high patient variability with respect to the motion pattern. The clinician has to select stable phases manually without an exact knowledge about the patient-specific motion. Therefore, several high-resolution volumes corresponding to different phases have to be reconstructed, which is an inefficient task. In this contribution, a simple and efficient image-based technique is introduced which is able to deliver patient-specific stable cardiac phases in an automatic fashion. For this purpose, a low-resolution 4D data set is reconstructed in advance. The most stable phases are derived from this 4D data set by calculating the similarity between subsequent positions in the cardiac cycle. Information about the patient-specific motion of the heart can be determined. High-resolution reconstructions are shown at the automatically predicted phase points corresponding to systole and diastole. The images are superior to images reconstructed at other phase points.

High resolution images of coronary arteries are reconstructed with the algebraic reconstruction technique (ART) applied to cone-beam CT cardiac imaging. Due to the motion of the heart during the scan, only data belonging to the same phase of the heart cycle can be used in the reconstruction process. Currently, all known analytical image reconstruction algorithms for this problem are approximate and do not take the cone-angle fully into account. ART models the scanner geometry exactly and does not suffer from large-cone angles, which is especially important with the current trend in CT to use detectors with more and more rows and larger cone-angles. In this study, the influence of the cardiac weighting function on image quality is investigated. Cardiac ART (CART) is used to reconstruct images from clinical data obtained with current 16-row CT scanners. The results are compared to an analytical reconstruction method.

Fan-beam coherent scatter computed tomography (CSCT) is a novel X-ray based imaging method revealing structural information of tissue under investigation. The source of contrast is the angular-dependent coherent scatter cross-section, which is determined by the molecular structure. In this work a phantom consisting of water, tricalcium phosphate, collagen and fat was used to investigate the contrast resolution of these four tissue constituents. Scatter projections were measured in fan-beam 3rd generation CT-geometry using an experimental demonstrator set-up equipped with a 4.5 kW DC power X-ray tube and photon-counting detectors. Reconstruction was performed using two algorithms, one based on algebraic reconstruction technique (ART) and the other based on filtered back-projection (FBP). The reconstruction results of the two techniques are compared. Furthermore, scatter functions of the four components were extracted from the 3D data sets and compared to previous measurements. The applicability of this technique for medical diagnosis is discussed.

Fast 16-slice spiral CT delivers superior cardiac visualization in comparison to older generation 2- to 8-slice scanners due to the combination of high temporal resolution along with isotropic spatial resolution and large coverage. The large beam opening of such scanners necessitates the use of adequate algorithms to avoid cone beam artifacts. We have developed a multi-cycle phase selective 3D back projection reconstruction algorithm that provides excellent temporal and spatial resolution for 16-slice CT cardiac images free of cone beam artifacts.

For the first time, a reconstruction technique based on filtered back-projection (FBP) using curved 3D back-projection lines is applied to 2D coherent-scatter computed tomography (CSCT) projection data. It has been demonstrated, that CSCT yields information about the molecular structure of an object. So far, the acquired projection data are reconstructed with the help of algebraic reconstruction techniques. Due to the computational complexity of iterative reconstruction, these methods lead to relatively long reconstruction times. In this contribution, a reconstruction algorithm based on 3D FBP is introduced and tested with simulated projection data as well as with projection data acquired with a demonstrator setup similar to a multi-line CT scanner geometry. Within a fraction of computation time at least a comparable image quality is achieved when using FBP reconstruction. In addition, it has the advantage, that - in contrast to iterative reconstruction schemes - sub-field-of-view reconstruction becomes feasible. This allows a selective reconstruction of the scatter function for a region of interest. The method is based on a row by row high-pass filtering of the scatter data, with or without fan to parallel beam rebinning. The 3D back-projection is performed along curved lines through a volume defined by the in-plane spatial coordinates and the wave-vector transfer.

During the last years, three-dimensional X-ray imaging has become a well-established imaging modality, setting the golden standard for spatial resolution in three-dimensional X-ray imaging. Firstly introduced on a motorized C-arm system, it gained benefit from the high spatial resolution of the image intensifier. Using cone-beam reconstruction, it provided fast access to truly three-dimensional imaging with isotropic voxel dimensions. However, the non-rigid mechanics and the image distortion in the image intensifier required dedicated calibration processes and obligated the developers to use the most stable and reliable system in the C-arm device family. The need for system calibration also required the system to be able to reproducibly adjust the C-arm to the pre-calibrated positions, which seemed only possible with the motorized movement of a high-end system. On mobile, non-motorized C-arm systems, which are often used for guiding surgical procedures, however, 3D application has not been feasible due to the non-reproducibility of the mechanical movement. In this paper, first results regarding the feasibility of this approach are presented. The data were acquired on a Philips BV 26 surgical C-arm. This device is fully movable. The C arc is adjusted manually.