3-D Imaging of Coronary Vessels Using C-arm CT - Schwemmer, Chris (Logos Verlag Berlin, 2019)
Cardiovascular disease has become the number one cause of death worldwide. Its prevention, diagnosis and therapy are therefore highly important topics in today’s clinical practice and research. For the diagnosis and therapy of coronary artery disease, interventional C-arm-based fluoroscopy is an imaging method of choice. It delivers 2-D X-ray images from almost arbitrary directions, but a 2-D projection image is naturally limited in its depiction of complex spatial relations. While the C- arm systems are capable of rotating around the patient and thus allow a CT-like 3-D image reconstruction, their long rotation time of about five seconds leads to strong motion artefacts in 3-D coronary artery imaging. Several methods to estimate the coronary motion and compensate for it during 3-D image reconstruction can be found in the literature. All have their specific properties, advantages and disadvantages, which are discussed in the first part of this thesis. Then, a novel method is introduced that is based on a 2-D–2-D image registra- tion algorithm, henceforth called rmc (Registration-based Motion Compensation). It is embedded in an iterative algorithm for motion estimation and compensation. rmc does not require any complex segmentation or user interaction and is thus fully automatic, which is a very desirable feature for interventional applications. Motion estimation and compensation becomes more difficult when projection data from the whole heart cycle is used from the beginning. rmc overcomes this by successively increasing the utilised amount of projections in a bootstrapping process. Throughout the remainder of this thesis, rmc is first evaluated in a simulation study using a simple numerical phantom, then on the publicly available Cavarev platform (employing an anthropomorphic phantom), and finally in a study using 58 human clinical datasets. Through the simulation study, approximations for the inherent error of the investigated algorithms were established. In addition, evidence that the missing depth information of a 2-D motion model is not a limiting factor for coronary artery imaging was found. The Cavarev experiments investigated the effect of different filter kernel choices during the execution of rmc. For the quantitative evaluation on human clinical data, a new software called CoroEval was introduced to the scientific community. Overall, it could be shown from both the quantitative results as well as the human observer ratings that rmc can be successfully applied to a large set of clinical data without user interaction or parameter changes, and with a high robustness against initial 3-D image quality, while delivering results that are at least up to the current state of the art, and better in many cases.
UnivIS-Import:2019-08-15:Pub.2019.tech.IMMD.IMMD5.3dimag
Keywords: Cardiac imaging; C-arm CT; Coronary imaging; Motion estimation; Reconstruction

3-D Imaging of Coronary Vessels Using C-arm CT - Schwemmer, Chris (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2019)
Cardiovascular disease has become the number one cause of death worldwide. Its prevention, diagnosis and therapy are therefore highly important topics in today’s clinical practice and research. For the diagnosis and therapy of coronary artery disease, interventional C-arm-based fluoroscopy is an imaging method of choice. It delivers 2-D X-ray images from almost arbitrary directions, but a 2-D projection image is naturally limited in its depiction of complex spatial relations. While the C- arm systems are capable of rotating around the patient and thus allow a CT-like 3-D image reconstruction, their long rotation time of about five seconds leads to strong motion artefacts in 3-D coronary artery imaging. Several methods to estimate the coronary motion and compensate for it during 3-D image reconstruction can be found in the literature. All have their specific properties, advantages and disadvantages, which are discussed in the first part of this thesis. Then, a novel method is introduced that is based on a 2-D–2-D image registra- tion algorithm, henceforth called rmc (Registration-based Motion Compensation). It is embedded in an iterative algorithm for motion estimation and compensation. rmc does not require any complex segmentation or user interaction and is thus fully automatic, which is a very desirable feature for interventional applications. Motion estimation and compensation becomes more difficult when projection data from the whole heart cycle is used from the beginning. rmc overcomes this by successively increasing the utilised amount of projections in a bootstrapping process. Throughout the remainder of this thesis, rmc is first evaluated in a simulation study using a simple numerical phantom, then on the publicly available Cavarev platform (employing an anthropomorphic phantom), and finally in a study using 58 human clinical datasets. Through the simulation study, approximations for the inherent error of the investigated algorithms were established. In addition, evidence that the missing depth information of a 2-D motion model is not a limiting factor for coronary artery imaging was found. The Cavarev experiments investigated the effect of different filter kernel choices during the execution of rmc. For the quantitative evaluation on human clinical data, a new software called CoroEval was introduced to the scientific community. Overall, it could be shown from both the quantitative results as well as the human observer ratings that rmc can be successfully applied to a large set of clinical data without user interaction or parameter changes, and with a high robustness against initial 3-D image quality, while delivering results that are at least up to the current state of the art, and better in many case

4-D Motion Field Estimation by Combined Multiple Heart Phase Registration (CMHPR) for Cardiac C-arm Data - Müller, Kerstin; Rohkohl, Christopher; Lauritsch, Günter; Schwemmer, Chris; Heidbüchel, Hein; De Buck, Stijn; Nuyens, Dieter; Kyriakou, Yiannis; Köhler, Christoph; Hornegger, Joachim (2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC), 2012)
In interventional cardiology three-dimensionalanatomical and functional information of the cardiac chamberswould have an important impact on diagnosis and therapy. Withthe technology of C-arm CT it is possible to reconstruct intraprocedural3-D images from angiographic projection data. Inorder to generate accurate and artifact-free reconstructions fromdynamic cardiac projections, the motion needs to be taken intoaccount. We present the novel Combined Multiple Heart PhaseRegistration (CMHPR) method. CMHPR is an iterative motionestimation and compensation algorithm that uses projection dataacquired during a single C-arm sweep. Filtered-backprojection(FBP) volumes from electrocardiogram (ECG)-gated data are reconstructedfor different motion states of the heart. According toan unknown 4-D motion vector field the ECG-gated FBP imagesare deformed and accumulated to a sum volume for representingthe status of a particular heart phase. In an iterative optimizationprocedure the 4-D motion vector field is computed by registeringthe sum volume to a reference volume of the same heart phase.The negative normalized cross correlation (NCC) of both volumesis used as a cost function. In this paper, the reference image isgenerated using the prior image constrained compressed sensing(PICCS) algorithm combined with the improved total variation(iTV). First preliminary experiments on clinical porcine datasets show promising results. CMHPR reduces streak artifactsand simultaneously preserves sharp edges without producing theartificial comic-like appearance of the PICCS + iTV referencevolume.

Automatic Removal of Externally Attached Fiducial Markers in Cone Beam C-arm CT - Berger, Martin; Forman, Christoph; Schwemmer, Chris; Choi, Jang-Hwan; Müller, Kerstin; Maier, Andreas; Hornegger, Joachim; Fahrig, Rebecca (Bildverarbeitung für die Medizin 2014, 2014)
In computed tomography fiducial markers are frequently used to obtain accurate point correspondences for further processing. These markers typically cause metal artefacts, decreasing image quality of the subsequent reconstruction and are therefore often removed from the projection data. The placement of such markers is usually done on a surface, separating two materials, e.g. skin and air. Hence, a correct restoration of the occluded area is difficult. In this work six state-of-the-art interpolation techniques for the removal of high-density fiducial markers from cone-beam CT projection data are compared. We conducted a qualitative and quantitative evaluation for the removal of such markers and the ability to reconstruct the adjoining edge. Results indicate that an iterative spectral deconvolution is best suited for this application, showing promising results in terms of edge, as well as noise restoration.
UnivIS-Import:2015-07-08:Pub.2014.tech.IMMD.IMMD5.automa_5
Keywords: GRK-1773; Interpolation; C-arm CT; Metal Artifact

Catheter artifact reduction (CAR) in dynamic cardiac chamber imaging with interventional C-arm CT - Müller, Kerstin; Lauritsch, Günter; Schwemmer, Chris; Maier, Andreas; Taubmann, Oliver; Abt, Bernd; Köhler, Henning; Nöttling, Alois; Hornegger, Joachim; Fahrig, Rebecca (Proceedings of the third international conference on image formation in x-ray computed tomography, 2014)
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD5.cathet_3

Clinical Data Evaluation of C-arm-based Motion Compensated Coronary Artery Reconstruction - Schwemmer, Chris; Lauritsch, Günter; Kleinfeld, Albrecht; Rohkohl, Christopher; Müller, Kerstin; Hornegger, Joachim (Proceedings of the third international conference on image formation in x-ray computed tomography, 2014)
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD5.clinic_7

CONRAD - A software framework for cone-beam imaging in radiology - Maier, Andreas; Hofmann, Hannes; Berger, Martin; Fischer, Peter; Schwemmer, Chris; Wu, Haibo; Müller, Kerstin; Hornegger, Joachim; Choi, Jang-Hwan; Riess, Christian; Keil, Andreas; Fahrig, Rebecca (Medical Physics, 2013)

Convolution-Based Truncation Correction for C-Arm CT Using Scattered Radiation - Bier, Bastian; Schwemmer, Chris; Maier, Andreas; Hofmann, Hannes; Xia, Yan; Hornegger, Joachim; Struffert, Tobias (Bildverarbeitung für die Medizin 2013, 2013)

CoroEval: a multi-platform, multi-modality tool for the evaluation of 3D coronary vessel reconstructions - Schwemmer, Chris; Forman, Christoph; Wetzl, Jens; Maier, Andreas; Hornegger, Joachim (Physics in Medicine and Biology, 2014)
With default settings, measurements are taken at 1 mm intervals along the vessel centreline and from 10 different angles at each measurement point. This allows for outlier detection and noise-robust measurements without the burden and subjectivity a manual measurement process would incur. Graphical measurement results can be directly exported to vector or bitmap graphics for integration into scientific publications. Centreline and lumen segmentations can be exported as point clouds and in various mesh formats. We evaluated the diameter measurement process using three phantom datasets. An average deviation of 0.03 +/- 0.03 mm was found.
UnivIS-Import:2015-03-09:Pub.2014.tech.IMMD.IMMD5.coroev
Keywords: medical imaging; coronary vessels; evaluation; software

Evaluation of Interpolation Methods for Motion Compensated Tomographic Reconstruction for Cardiac Angiographic C-arm Data - Müller, Kerstin; Zheng, Yefeng; Lauritsch, Günter; Rohkohl, Christopher; Schwemmer, Chris; Maier, Andreas; Fahrig, Rebecca; Hornegger, Joachim (Proceedings of the second international conference on image formation in x-ray computed tomography, 2012)
http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2012/Mueller12-EOI.pdf

Evaluation of interpolation methods for surface-based motion compensated tomographic reconstruction for cardiac angiographic C-arm data - Müller, Kerstin; Schwemmer, Chris; Hornegger, Joachim; Zheng, Yefeng; Wang, Yang; Lauritsch, Günter; Rohkohl, Christopher; Maier, Andreas; Schultz, Carl; Fahrig, Rebecca (Medical Physics, 2013)
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 ≈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 ≈ 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. © 2013 American Association of Physicists in Medicine.

Fast simulation of x-ray projections of spline-based surfaces using an append buffer - Maier, Andreas; Hofmann, Hannes; Schwemmer, Chris; Hornegger, Joachim; Keil, Andreas; Fahrig, Rebecca (Physics in Medicine and Biology, 2012)
Many scientists in the field of x-ray imaging rely on the simulation of x-ray images. As the phantom models become more and more realistic, their projection requires high computational effort. Since x-ray images are based on transmission, many standard graphics acceleration algorithms cannot be applied to this task. However, if adapted properly, the simulation speed can be increased dramatically using state-of-the-art graphics hardware. A custom graphics pipeline that simulates transmission projections for tomographic reconstruction was implemented based on moving spline surface models. All steps from tessellation of the splines, projection onto the detector and drawing are implemented in OpenCL. We introduced a special append buffer for increased performance in order to store the intersections with the scene for every ray. Intersections are then sorted and resolved to materials. Lastly, an absorption model is evaluated to yield an absorption value for each projection pixel. Projection of a moving spline structure is fast and accurate. Projections of size 640×480 can be generated within 254ms. Reconstructions using the projections show errors below 1 HU with a sharp reconstruction kernel. Traditional GPU-based acceleration schemes are not suitable for our reconstruction task. Even in the absence of noise, they result in errors up to 9HU on average, although projection images appear to be correct under visual examination. Projections generated with our new method are suitable for the validation of novel CT reconstruction algorithms. For complex simulations, such as the evaluation of motion-compensated reconstruction algorithms, this kind of x-ray simulation will reduce the computation time dramatically. © 2012 Institute of Physics and Engineering in Medicine.

High-Density Object Removal from Projection Images using Low-Frequency-Based Object Masking - Schwemmer, Chris; Prümmer, Marcus; Daum, Volker; Hornegger, Joachim (Bildverarbeitung für die Medizin 2010 - Algorithmen - Systeme - Anwendungen, 2010)

Image artefact propagation in motion estimation and reconstruction in interventional cardiac C-arm CT - Müller, Kerstin; Maier, Andreas; Schwemmer, Chris; Lauritsch, Günter; De Buck, Stijn; Wielandts, Jean-Yves; Hornegger, Joachim; Fahrig, Rebecca (Physics in Medicine and Biology, 2014)
The acquisition of data for cardiac imaging using a C-arm computed tomography system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable three-dimensional (3D)/3D registration performed on initial 3D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3D images. In this paper, the sensitivity of the 3D/3D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing combined with the improved total variation algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical phantom data set with and without a catheter and on two porcine models using qualitative and quantitative measures. The quantitative results of the phantom experiments show that if no dense object is present within the scan field of view, the quality of the FDK initial images is sufficient for motion estimation via 3D/3D registration. When a catheter or pacing electrode is present, the shadow of these objects needs to be removed before the initial image reconstruction. An additional bilateral filter shows no major improvement with respect to the final motion-compensated reconstruction quality. The results with respect to image quality of the cathFDK, cathFFDK and FV images are comparable. In conclusion, in terms of computational complexity, the algorithm of choice is the cathFDK algorithm © 2014 Institute of Physics and Engineering in Medicine.
UnivIS-Import:2015-03-09:Pub.2014.tech.IMMD.IMMD5.imagea_5
Keywords: C-arm CT; cardiac imaging; dynamic imaging; motion compensation; motion-compensated tomographic reconstruction

Image Artifact Influence on Motion Compensated Tomographic Reconstruction in Cardiac C-arm CT - Müller, Kerstin; Schwemmer, Chris; Lauritsch, Günter; Rohkohl, Christopher; Maier, Andreas; Heidbüchel, Hein; De Buck, Stijn; Nuyens, Dieter; Kyriakou, Yiannis; Köhler, Christopher; Fahrig, Rebecca; Hornegger, Joachim (Proceedings of the 12th Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2013)

Interventional heart wall motion analysis with cardiac C-arm CT systems - Müller, Kerstin; Maier, Andreas; Zheng, Yefeng; Wang, Yang; Lauritsch, Günter; Schwemmer, Chris; Rohkohl, Christopher; Hornegger, Joachim; Fahrig, Rebecca (Physics in Medicine and Biology, 2014)
Today, quantitative analysis of three-dimensional (3D) dynamics of the left ventricle (LV) cannot be performed directly in the catheter lab using a current angiographic C-arm system, which is the workhorse imaging modality for cardiac interventions. Therefore, myocardial wall analysis is completely based on the 2D angiographic images or pre-interventional 3D/4D imaging. In this paper, we present a complete framework to study the ventricular wall motion in 4D (3D+t) directly in the catheter lab. From the acquired 2D projection images, a dynamic 3D surface model of the LV is generated, which is then used to detect ventricular dyssynchrony. Different quantitative features to evaluate LV dynamics known from other modalities (ultrasound, magnetic resonance imaging) are transferred to the C-arm CT data. We use the ejection fraction, the systolic dyssynchrony index a 3D fractional shortening and the phase to maximal contraction (φi, max) to determine an indicator of LV dyssynchrony and to discriminate regionally pathological from normal myocardium. The proposed analysis tool was evaluated on simulated phantom LV data with and without pathological wall dysfunctions. The LV data used is publicly available online at https://conrad.stanford.edu/data/heart. In addition, the presented framework was tested on eight clinical patient data sets. The first clinical results demonstrate promising performance of the proposed analysis tool and encourage the application of the presented framework to a larger study in clinical practice. © 2014 Institute of Physics and Engineering in Medicine.
UnivIS-Import:2015-03-09:Pub.2014.tech.IMMD.IMMD5.interv
Keywords: C-arm CT; cardiac dynamics; functional imaging; interventional imaging; wall motion analysis

Left Ventricular Heart Phantom for Wall Motion Analysis - Müller, Kerstin; Maier, Andreas; Fischer, Peter; Bier, Bastian; Lauritsch, Günter; Schwemmer, Chris; Fahrig, Rebecca; Hornegger, Joachim (2013 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC), 2013)
In interventional cardiology, three-dimensional anatomical and functional information of the cardiac chambers, e.g. the left ventricle, would have an important impact on diagnosis and therapy. With the technology of C-arm CT it is possible to reconstruct intraprocedural 3-D images from angiographic projection data. Due to the long acquisition time of several seconds, motion-related artifacts, like blurring or streaks, occur. Therefore, the heart dynamics need to be taken into account in order to improve the reconstruction results. When it comes to the evaluation of different motion estimation and compensation algorithms and techniques of motion analysis, there is still a lack of comparability of the final reconstructions and motion parameters between the research groups. Since the results are heavily dependent on the applied motion pattern and simulation parameters, the experiments are not reproducible. We try to overcome these problems by providing varying left heart ventricle phantom datasets, consisting of projection images as well as extracted surface meshes. Up to now, there are six different datasets available: one with a normal sinus rhythm, one with a normal sinus rhythm and a catheter, one with a lateral wall defect of the ventricle, two with a lateral contraction phase shift and one without any motion. The existing datasets are based on a phantom similar to the 4D XCAT phantom with a contrasted left ventricle, myocardium, and aorta. The geometry calibration and acquisition protocol from a real clinical C-arm scanner are used. A webpage is provided where the data and the necessary files are publicly available for download at conrad.stanford.edu/data/heart. © 2013 IEEE.
UnivIS-Import:2015-04-16:Pub.2013.tech.IMMD.IMMD5.leftve_0

Opening Windows - Increasing Window Size in Motion-Compensated ECG-gated Cardiac Vasculature Reconstruction - Schwemmer, Chris; Rohkohl, Christopher; Lauritsch, Günter; Müller, Kerstin; Hornegger, Joachim (Proceedings of the 12th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2013)

Residual Motion Compensation in ECG-Gated Cardiac Vasculature Reconstruction - Schwemmer, Chris; Rohkohl, Christopher; Lauritsch, Günter; Müller, Kerstin; Hornegger, Joachim (Proceedings of the second international conference on image formation in x-ray computed tomography, 2012)
Generating 3-D reconstructions of cardiac vasculature from angiographic C-arm CT (rotational angiography) data is a challenging problem. Currently, many approaches depend on a reconstruction from ECG-gated projection data either as a reference for further processing or as the final result. Due to imperfect gating, e.g. caused by irregular heart movement, residual motion corrupts these reconstructions. We present an algorithm to compensate for this residual motion. The approach is based on a deformable 2-D-2-D registration between the acquired projection data and a forward projection of the initial ECG-gated reconstruction. It does not depend on an explicit segmentation of vasculature or markers, and works without user interaction. The estimated 2-D deformation field is compensated for in the backprojection step of a subsequent reconstruction. The algorithm is evaluated on two clinical datasets, showing a clear decrease in artefact level and better visibility of structure in the compensated reconstructions.

Residual Motion Compensation in ECG-Gated Interventional Cardiac Vasculature Reconstruction - Schwemmer, Chris; Rohkohl, Christopher; Lauritsch, Günter; Müller, Kerstin; Hornegger, Joachim (Physics in Medicine and Biology, 2013)

Robust lumen segmentation of coronary arteries in 2D angiographic images - Polyanskaya, Maria; Schwemmer, Chris; Linarth, Andre Guilherme; Lauritsch, Günter; Hornegger, Joachim (Medical Imaging 2012: Image Processing, 2012)
Diagnosis and treatment of coronary diseases depends on the data acquired during angiographic investigations. To provide better assistance for angiographic procedures, a segmentation of the lumen is required. A new algorithm for vessel centerline computation and lumen segmentation in 2D projection coronary angiograms is presented. Centerlines are extracted by a graph-based optimization technique, which searches for paths with minimal costs. The search starts from a source point, which is automatically set by the proposed algorithm. A new objective function for determining the costs of the graph edges is proposed. It consists of the response from the medialness filter and is regularized by the centerline potential function. In the medialness filter a vessel cross-section is represented by a 1D profile parameterized by center position and radius. The medialness filter at a point optimizes a gradient-based response over the profile radius. The proposed centerline potential function defines likeliness of each point of the image to be a centerline. Both the medialness filter and the centerline potential function are multi-scale. The entire lumen segmentation is achieved by the radii extracted during the medialness response computation. Application to clinical data shows that the presented algorithm segments coronary lumen with good accuracy and allows for subsequent assessment of the quantitative characteristics (i.e. diameter, curvature, etc.) of the vessels. © 2012 SPIE.

Towards Clinical Application of a Laplace Operator-based Region of Interest Reconstruction Algorithm in C-arm CT - Xia, Yan; Hofmann, Hannes; Dennerlein, Frank; Müller, Kerstin; Schwemmer, Chris; Bauer, Sebastian; Chintalapani, Gouthami; Chinnadurai, Ponraj; Hornegger, Joachim; Maier, Andreas (IEEE Transactions on Medical Imaging, 2014)
It is known that a reduction of the field-of-view in 3-D X-ray imaging is proportional to a reduction in radiation dose. The resulting truncation, however, is incompatible with conventional reconstruction algorithms. Recently, a novel method for region of interest reconstruction that uses neither prior knowledge nor extrapolation has been published, named approximated truncation robust algorithm for computed tomography (ATRACT). It is based on a decomposition of the standard ramp filter into a 2-D Laplace filtering and a 2-D Radon-based residual filtering step. In this paper, we present two variants of the original ATRACT. One is based on expressing the residual filter as an efficient 2-D convolution with an analytically derived kernel. The second variant is to apply ATRACT in 1-D to further reduce computational complexity. The proposed algorithms were evaluated by using a reconstruction benchmark, as well as two clinical data sets. The results are encouraging since the proposed algorithms achieve a speed-up factor of up to 245 compared to the 2-D Radon-based ATRACT. Reconstructions of high accuracy are obtained, e.g., even real-data reconstruction in the presence of severe truncation achieve a relative root mean square error of as little as 0.92% with respect to nontruncated data. © 1982-2012 IEEE.
UnivIS-Import:2015-03-09:Pub.2014.tech.IMMD.IMMD5.toward_3
Keywords: C-arm CT; dose reduction; image reconstruction; region of interest; truncation; truncation artifact

Truncation correction for VOI C-arm CT using scattered radiation - Bier, Bastian; Maier, Andreas; Hofmann, Hannes; Schwemmer, Chris; Xia, Yan; Struffert, Tobias; Hornegger, Joachim (Medical Imaging 2013: Physics of Medical Imaging, 2013)
In C-arm computed tomography, patient dose reduction by volume-of-interest (VOI) imaging is of increasing interest for many clinical applications. A remaining limitation of VOI imaging is the truncation artifact when reconstructing a 3D volume. It can either be cupping towards the boundaries of the field-of-view (FOV) or an incorrect offset in the Hounsfield values of the reconstructed voxels. In this paper, we present a new method for correction of truncation artifacts in a collimated scan. When axial or lateral collimation are applied, scattered radiation still reaches the detector and is recorded outside of the FOV. If the full area of the detector is read out we can use this scattered signal to estimate the truncated part of the object. We apply three processing steps: detection of the collimator edge, adjustment of the area outside the FOV, and interpolation of the collimator edge. Compared to heuristic truncation correction methods we were able to reconstruct high contrast structures like bones outside of the FOV. Inside the FOV we achieved similar reconstruction results as with water cylinder truncation correction. These preliminary results indicate that scattered radiation outside the FOV can be used to improve image quality and further research in this direction seems beneficial. © 2013 SPIE.