Reconstruction of coronary arteries from a single rotational X-ray projection sequence

Cardiovascular diseases remain the primary cause of death in developed countries. In most cases, exploration of possibly underlying coronary artery pathologies is performed using X-ray coronary angiography. Current clinical routine in coronary angiography is directly conducted in two-dimensional projection images from several static viewing angles. However, for diagnosis and treatment purposes, coronary artery reconstruction is highly suitable. The purpose of this study is to provide physicians with a three-dimensional (3-D) model of coronary arteries, e.g., for absolute 3-D measures for lesion assessment, instead of direct projective measures deduced from the images, which are highly dependent on the viewing angle. In this paper, we propose a novel method to reconstruct coronary arteries from one single rotational X-ray projection sequence. As a side result, we also obtain an estimation of the coronary artery motion. Our method consists of three main consecutive steps: 1) 3-D reconstruction of coronary artery centerlines, including respiratory motion compensation; 2) coronary artery four-dimensional motion computation; 3) 3-D tomographic reconstruction of coronary arteries, involving compensation for respiratory and cardiac motions. We present some experiments on clinical datasets, and the feasibility of a true 3-D Quantitative Coronary Analysis is demonstrated.     

Prospective motion correction of X-ray images for coronary interventions

A method for prospective motion correction of X-ray imaging of the heart is presented. A 3D + t coronary model is reconstructed from a biplane coronary angiogram obtained during free breathing. The deformation field is parameterized by cardiac and respiratory phase, which enables the estimation of the state of the arteries at any phase of the cardiac-respiratory cycle. The motion of the three-dimensional (3-D) coronary model is projected onto the image planes and used to compute a dewarping function for motion correcting the images. The use of a 3-D coronary model facilitates motion correction of images acquired with the X-ray system at arbitrary orientations. The performance of the algorithm was measured by tracking the motion of selected left coronary landmarks using a template matching cross-correlation. In three patients, we motion corrected the same images used to construct their 3D + t coronary model. In this best case scenario, the algorithm reduced the motion of the landmarks by 84%-85%, from mean RMS displacements of 12.8-14.6 pixels to 2.1-2.2 pixels. Prospective motion correction was tested in five patients by building the coronary model from one dataset, and correcting a second dataset. The patient's cardiac and respiratory phase are monitored and used to calculate the appropriate correction parameters. The results showed a 48%-63% reduction in the motion of the landmarks, from a mean RMS displacement of 11.5-13.6 pixels to 4.4-7.1 pixels.     

Evaluation of iterative sparse object reconstruction from few projections for 3-D rotational coronary angiography

A 3-D reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular disease, compared to 2-D X-ray angiograms. Besides improved roadmapping, quantitative vessel analysis is possible. Due to the heart's motion, rotational coronary angiography typically provides only 5–10 projections for the reconstruction of each cardiac phase, which leads to a strongly undersampled reconstruction problem. Such an ill-posed problem can be approached with regularized iterative methods. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, the minimization of the ${mbi L}_1$ norm of the reconstructed image, favoring spatially sparse images, is a suitable regularization. Additional problems are overlaid background structures and projection truncation, which can be alleviated by background reduction using a morphological top-hat filter. This paper quantitatively evaluates image reconstruction based on these ideas on software phantom data, in terms of reconstructed absorption coefficients and vessel radii. Results for different algorithms and different input data sets are compared. First results for electrocardiogram-gated reconstruction from clinical catheter-based rotational X-ray coronary angiography are presented. Excellent 3-D image quality can be achieved.      

Motion estimation from tagged MR image sequences

A method for reconstructing motion from sequences of tagged magnetic resonance (MR) images is presented. MR tagging is used to create a spatial pattern of varying magnetization so that objects which may otherwise have constant intensity are textured, which reduces the motion ambiguity associated with the aperture problem in computer vision. To compensate for the decay of the tag pattern, a new optical flow algorithm is developed and implemented. The resulting estimated velocity field is then used to recursively update the implied motion reference map over time, thereby tracking the motion of individual particles. If a segmentation of the object is known at the time the tag pattern is created, then an object may be selectively tracked, using the estimated reference map to update the object's position as time progresses. Results are shown for both simulated and actual MR phantom data.     

Motion field modeling for video sequences

We propose a model for the interframe correspondences existing between pixels of an image sequence. These correspondences form the elements of a field called the motion field. In our model, spatial neighborhoods of motion elements are related based on a generalization of autoregressive (AR) modeling of the time-series. We also propose a joint spatio-temporal model by including spatial neighborhoods of pixel intensities in the motion model. A fundamental difference of our approach with most previous approaches to modeling motion is in basing our model on concepts from statistical signal processing. The developments in this paper give rise to the promise of extending well-understood tools of signal processing (e.g., filtering) to the analysis and processing of motion fields. Simulation results presented show the performance of our models in interframe prediction; specifically, on average the motion model performs 29% better in terms of the mean squared error energy over a commonly used pel-recursive approach. The spatio-temporal model improves the prediction efficiencies by 8% over the motion model. Our model can also be used to obtain estimates of the optical flow field as the simulations demonstrate.     

Methods for reconstruction of 2-D sequences from Fourier transformmagnitude

The Gerchberg-Saxton (GS) algorithm and its generalizations have been the main tools for phase retrieval. Unfortunately, it has been observed that the reconstruction using these algorithms does not always converge to the correct result even if the desired solution satisfies the uniqueness condition. In this paper, we propose a new deautocorrelation algorithm and a few auxiliary techniques. We recommend that a combination of the iterative Fourier transform (IFT) algorithm with our new algorithm and techniques can improve the probability of success of phase retrieval. A pragmatic procedure is illustrated. Different reconstruction examples that are difficult to reconstructed using the single IFT algorithm are used to show the robustness and effectiveness of the new combination of algorithms. If the given Fourier modulus data contain no noise, it is sometimes possible to get a perfect reconstruction. Even when the signal-to-noise ratio (SNR) of the Fourier modulus data is only 10 dB, a meaningful result remains reachable for our examples. A concept concerning the intrinsic ambiguity of phase retrieval is suggested. We emphasize the necessity of verification of the solution, since the available phase retrieval algorithms are incompetent for distinguishing between an intrinsically ambiguous solution and the true solution.     

Automated motion correction for in vivo optical projection tomography

In in vivo optical projection tomography (OPT), object motion will significantly reduce the quality and resolution of the reconstructed image. Based on the well-known Helgason-Ludwig consistency condition (HLCC), we propose a novel method for motion correction in OPT under parallel beam illumination. The method estimates object motion from projection data directly and does not require any other additional information, which results in a straightforward implementation. We decompose object movement into translation and rotation, and discuss how to correct for both translation and general motion simultaneously. Since finding the center of rotation accurately is critical in OPT, we also point out that the system's geometrical offset can be considered as object translation and therefore also calibrated through the translation estimation method. In order to verify the algorithm effectiveness, both simulated and in vivo OPT experiments are performed. Our results demonstrate that the proposed approach is capable of decreasing movement artifacts significantly thus providing high quality reconstructed images in the presence of object motion.     

Real-time adaptive filtering for projection reconstruction MR fluoroscopy

Magnetic resonance (MR) imaging has faced a dramatic increase in real-time capabilities over the last years. However, the application of fast pulse sequences still suffers from low signal-to-noise ratios (SNRs), which can be the limiting factor for the actual acquisition speed. In MR fluoroscopy, filtering along the time and/or spatial domain can be applied to increase the image quality. In this paper, a projection-based noise filter is presented that significantly enhances the SNR in projection reconstruction (PR) fluoroscopy without apparent loss of resolution in the reconstructed images. In contrast to an imaged-based approach, this method allows a very efficient computational implementation. The filter algorithm was implemented on a digital signal processor and was applied to real-time processing during PR fluoroscopy. A quantitative analysis of the improvement in SNR and results for different fluoroscopic MR applications are given. Apart from MR fluoroscopy, the proposed technique has the potential to be applied to low dose computed tomography fluoroscopy.     

Image reconstruction from incomplete projection data: iterative reconstruction-reprojection techniques

This paper addresses the task of image reconstruction from an incomplete set of projection data. Several methods which first estimate the missing data and then utilize standard reconstruction algorithms to obtain an image are investigated. Results from simulations are presented which illustrate the difficulty in comparing algorithms objectively, particularly when a simple test phantom is chosen. The incorporation of a priori information into the algorithm, an approach which has previously been discussed in the literature, is shown to produce faster convergence.     

Motion compensated fan-beam reconstruction for nonrigid transformation

We develop an approximate fan-beam algorithm to reconstruct an object with time-dependent nonrigid transformation such as the heart. The method is in the form of derivative backprojection filtering with compensation of affine transformations on a local basis. Computer simulations showed the proposed method significantly reduces image artifact due to nonrigid motion. Therefore, with very little motion artifact, the proposed method allowed us to reconstruct images from projections over about one motion cycle, resulting in reduced image noise level down to 40% of the current level.      

Wavelet-based reconstruction for limited-angle X-ray tomography

The aim of X-ray tomography is to reconstruct an unknown physical body from a collection of projection images. When the projection images are only available from a limited angle of view, the reconstruction problem is a severely ill-posed inverse problem. Statistical inversion allows stable solution of the limited-angle tomography problem by complementing the measurement data by a priori information. In this work, the unknown attenuation distribution inside the body is represented as a wavelet expansion, and a Besov space prior distribution together with positivity constraint is used. The wavelet expansion is thresholded before reconstruction to reduce the dimension of the computational problem. Feasibility of the method is demonstrated by numerical examples using in vitro data from mammography and dental radiology.     

机器人视觉导航传感器光栅投射误差校正系统

当前传感器光栅投射误差校正系统,没有计算光栅投射条纹的倾斜角度,导致系统应用效率低、稳定性差、精准度低,严重影响了机器人的使用效果。因此,提出机器人视觉导航传感器光栅投射误差校正系统。首先采用光栅读数头、细分盒完成系统的硬件组成,提高系统的应用效率;软件部分采用了高频数字计数滤波的方法,滤除掉频率高于该临界点的干扰脉冲;最后通过基于投影序列融合的光栅投射误差校正算法,分析光栅投射条纹的倾斜角度实现误差校正,提高系统的精准度。实验对比结果表明,机器人视觉导航传感器光栅投射误差校正系统的应用效率最高为96%、稳定性最高为98%、精准度最高为97%,所设计系统具有较高性能。     

Translational motion compensation for coronary angiogram sequences

A method of compensating for the lag of the video cameras typically used in angiographic systems is presented for use in sequences of digitized X-ray images. The lag effect is reduced by a straightforward weighted subtraction, which has the undesirable side effect of increasing noise. By superimposing several lag-corrected and appropriately shifted images, however, the signal-to-noise ratio can be restored. The algorithm uses the phase-correlation method to measure the two-dimensional shift of a mobile coronary arterial structure. Processing is confined to a rectangular area of interest (AOI), which encloses a feature of clinical significance. The differences of the phases of the Fourier transforms of two frames is computed, combined with an appropriate filter, and inverse Fourier-transformed to produce a phase-correlation image. The vector separation from the origin of image space of the peak of the phase-correlation image is the estimate of the shift of the artery's position in the second frame as compared to the first. The isolation of the AOI from the surrounding image is achieved by the application of a window and correction for any linear trend in the background intensity.     

Three-dimensional guide-wire reconstruction from biplane image sequences for integrated display in 3-D vasculature

Using three-dimensional rotational X-ray angiography (3DRA), three-dimensional (3-D) information of the vasculature can be obtained prior to endovascular interventions. However, during interventions, the radiologist has to rely on fluoroscopy images to manipulate the guide wire. In order to take full advantage of the 3-D information from 3DRA data during endovascular interventions, a method is presented that yields an integrated display of the position of the guide wire and vasculature in 3-D. The method relies on an automated method that tracks the guide wire simultaneously in biplane fluoroscopy images. Based on the calibrated geometry of the C-arm, the 3-D guide-wire position is determined and visualized in the 3-D coordinate system of the vasculature. The method is evaluated in an intracranial anthropomorphic vascular phantom. The influence of the angle between projections, distortion correction of the projection images, and accuracy of geometry knowledge on the accuracy of 3-D guide-wire reconstruction from biplane images is determined. If the calibrated geometry information is used and the images are corrected for distortion, a mean distance to the reference standard of 0.42 mm and a tip distance of 0.65 mm is found, which means that accurate guide-wire reconstruction from biplane images can be performed.     

Target materials suitable for projection X-ray microscope observation of biological samples

Trials for improving the contrast of projection X-ray images by finding better target materials than Ti (lambda K alpha: 2.75 A), which has been found to be suitable for many kinds of specimens, were carried out, considering the factors of melting point, thermal conductivity, mechanical strength, chemical stability, absorption of the X-ray, etc. Au, Ta, and Ge were found to be suitable, giving 5-10 A X-rays when low electron beam energies around 10 kV were used. In order to take advantage of the long wavelength X-rays of these targets, we tried to minimize the attenuation of the imaging X-rays in the air or to use a vacuum camera. Even in non-stained biological samples such as HeLa cells and lingual muscle section, their microstructures were visible with sufficient contrast.     

Statistical image reconstruction for polyenergetic X-ray computed tomography

This paper describes a statistical image reconstruction method for X-ray computed tomography (CT) that is based on a physical model that accounts for the polyenergetic X-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. We assume that the object consists of a given number of nonoverlapping materials, such as soft tissue and bone. The attenuation coefficient of each voxel is the product of its unknown density and a known energy-dependent mass attenuation coefficient. We formulate a penalized-likelihood function for this polyenergetic model and develop an ordered-subsets iterative algorithm for estimating the unknown densities in each voxel. The algorithm monotonically decreases the cost function at each iteration when one subset is used. Applying this method to simulated X-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artifacts.     

Ex vivo assessment of trabecular bone structure from three-dimensional projection reconstruction MR micro-images

Magnetic resonance (MR) imaging has recently been proposed for assessing osteoporosis and predicting fracture risks. However, accurate acquisition techniques and image analysis protocols for the determination of the trabecular bone structure are yet to be defined. The aim of this study was to assess the potential of projection reconstruction (PR) MR microscopy in the analysis of the three-dimensional (3-D) architecture of trabecular bone and in the prediction of its biomechanical properties. High-resolution 3-D PR images (41 x 41 x 82 microm3 voxels) of 15 porcine trabecular bone explants were analyzed to determine the trabecular bone volume fraction (Vv), the mean trabecular thickness (Tb.Th), and the mean trabecular separation (Tb.Sp) using the method of directed secants. These parameters were then compared with those derived from 3-D conventional spin-echo microimages. In both cases, segmentation of the high-resolution images into bone and bone marrow was obtained using a spatial adaptive threshold. The contemporary inclusion of Vv, Tb.Th and 1/Tb.Sp in a multiple regression analysis significantly improved the prediction of Young's modulus (YM). The parameters derived from the PR spin-echo images were found to be stronger predictors of YM (R2 = 0.94, p = 0.004) than those derived from conventional spin-echo images (R2 = 0.79, p = 0.051). Our study indicates that projection reconstruction MR microscopy appears to be more accurate than the conventional Fourier transform method in the quantification of trabecular bone structure and in the prediction of its bioimechanical properties. The proposed PR approach should be readily adaptable to the in vivo MRI studies of osteoporosis.     

Binary reconstruction of the heart chambers from biplane angiographic image sequences

The aim of this work is the three-dimensional (3-D) reconstruction of the left or right heart chamber from digital biplane angiograms. The approach used, the binary reconstruction, exploits the density information of subtracted ventriculograms from two orthogonal views in addition to the ventricular contours. The ambiguity of the problem is largely reduced by incorporating a priori knowledge of human ventricles. A model-based reconstruction program is described that is applicable to routinely acquired biplane ventriculographic studies. Prior to reconstruction, several geometric and densitometric imaging errors are corrected. The finding of corresponding density profiles and anatomical landmarks is supported by a biplane image pairing procedure that takes the movement of the gantry system into account. Absolute measurements are based on geometric isocenter calibration and a slice-wise density calibration technique. The reconstructed ventricles allow 3-D visualization and regional wall motion analysis independently of the gantry setting. The method is applied to clinical angiograms and tested in left- and right-ventricular phantoms yielding a well shape conformity even with few model information. The results indicate that volumes of binary reconstructed ventricles are less projection-dependent compared to volume data derived by purely contour-based methods. A limitation is that the heart chamber must not be superimposed by other dye-filled structures in both projections.     

Motion artifact correction for MR images based on convolutional neural network

Magnetic resonance imaging (MRI) is a common way to diagnose related diseases. However, the magnetic resonance (MR) images are easily defected by motion artifacts in their acquisition process, which affects the clinicians'' diagnosis. In order to correct the motion artifacts of MR images, we propose a convolutional neural network (CNN)-based method to solve the problem. Our method achieves a mean peak signal-to-noise ratio (PSNR) of (35.212±3.321) dB and a mean structural similarity (SSIM) of 0.974 ± 0.015 on the test set, which are better than those of the comparison methods.     

Reconstruction of three-dimensional coronary arterial dynamics from multi-view angiogram sequences

Since actual cardiac and arterial motion is non-rigidand non-uniformbothin space andinti me[1],the quan-tification of dynamic 3-Dcurves with 2-D projections isinaccurate and sensitive to view angles . Ruan[2]andPuentes[3]reconstructed 3-D arterial centerl…