锥束CT去除环形伪影的方法研究

环状伪影是CT技术人员经常遇到的影响重建图像质量的一种伪影,造成环形伪影的因素很多,其中探测器缺陷引起的环形伪影最为常见。环形伪影表现在原始图像结构上是圆环或者是圆弧,理论认证发现探测器响应效率不一致,会使锥束三维CT重建结果产生环形伪影。环形伪影影响了CT图像的分析和后续处理,因此去除环形伪影显得非常具有使用价值。本...     

Reconstruction Algorithm for Fan Beam with a Displaced Center-of-Rotation

A convolutional backprojection algorithm is derived for a fan beam geometry that has its center-of-rotation displaced from the midline of the fan beam. In single photon emission computed tomography (SPECT), where a transaxial converging collimator is used with a rotating gamma camera, it is difficult to precisely align the collimator so that the mechanical center-of-rotation is colinear with the midline of the fan beam. A displacement of the center-of-rotation can also occur in X-ray CT when the X-ray source is mispositioned. Standard reconstruction algorithms which directly filter and backproject the fan beam data without rebinning into parallel beam geometry have been derived for a geometry having its center-of-rotation at the midline of the fan beam. However, in the case of a misalignment of the center-of-rotation, if these conventional reconstruction algorithms are used to reconstruct the fan beam projections, structured artifacts and a loss of resolution will result. We illustrate these artifacts with simulations and demonstrate how the news algorithm corrects for this misalignment. We also show a method to estimate the parameters of the fan beam geometry including the shift in the center-of-rotation.     

Variable pitch reconstruction using John's equation

We present an algorithm to reconstruct helical cone beam computed tomography (CT) data acquired at variable pitch. The algorithm extracts a halfscan segment of projections using an extended version of the advanced single slice rebinning (ASSR) algorithm. ASSR rebins constant pitch cone beam data to fan beam projections that approximately lie on a plane that is tilted to optimally fit the source helix. For variable pitch, the error between the tilted plane chosen by ASSR and the source helix increases, resulting in increased image artifacts. To reduce the artifacts, we choose a reconstruction plane, which is tilted and shifted relative to the source trajectory. We then correct rebinned fan beam data using John's equation to virtually move the source into the tilted and shifted reconstruction plane. Results obtained from simulated phantom images and scanner images demonstrate the applicability of the proposed algorithm.      

Suppression of Metal Artifacts in CT Using a Reconstruction Procedure That Combines MAP and Projection Completion

Metal implants such as hip prostheses and dental fillings produce streak and star artifacts in the reconstructed computed tomography (CT) images. Due to these artifacts, the CT image may not be diagnostically usable. A new reconstruction procedure is proposed that reduces the streak artifacts and that might improve the diagnostic value of the CT images. The procedure starts with a maximum a posteriori (MAP) reconstruction using an iterative reconstruction algorithm and a multimodal prior. This produces an artifact-free constrained image. This constrained image is the basis for an image-based projection completion procedure. The algorithm was validated on simulations, phantom and patient data, and compared with other metal artifact reduction algorithms.      

Evolutionary computation applied to the reconstruction of 3-D surface topography in the SEM

A genetic algorithm has been applied to the line profile reconstruction from the signals of the standard secondary electron (SE) and/or backscattered electron detectors in a scanning electron microscope. This method solves the topographical surface reconstruction problem as one of combinatorial optimization. To extend this optimization approach for three-dimensional (3-D) surface topography, this paper considers the use of a string coding where a 3-D surface topography is represented by a set of coordinates of vertices. We introduce the Delaunay triangulation, which attains the minimum roughness for any set of height data to capture the fundamental features of the surface being probed by an electron beam. With this coding, the strings are processed with a class of hybrid optimization algorithms that combine genetic algorithms and simulated annealing algorithms. Experimental results on SE images are presented.     

Single-slice rebinning reconstruction in spiral cone-beam computed tomography

At the advent of multislice computed tomography ICT) a variety of approximate cone-beam algorithms have been proposed suited for reconstruction of small cone-angle CT data in a spiral mode of operation. The goal of this study is to identify a practical and efficient approximate cone-beam method, extend its potential for medical use, and demonstrate its performance at medium cone-angles required for area detector CT. We will investigate two different approximate single-slice rebinning algorithms for cone-beam CT: the multirow Fourier reconstruction (MFR) and an extension of the advanced single-slice rebinning method (ASSR), which combines the idea of ASSR with a z-filtering approach. Thus, both algorithms, MFR and ASSR, are formulated in the framework of z-filtering using optimized spiral interpolation algorithms. In each view, X-ray samples to be used for reconstruction are identified, which describe an approximation to a virtual reconstruction plane. The performance of approximate reconstruction should improve as the virtual reconstruction plane better fits the spiral focus path. The image quality of the respective reconstruction will be assessed with respect to image artifacts, spatial resolution, contrast resolution, and image noise. It turns out that the ASSR method using tilted reconstruction planes is a practical and efficient algorithm, providing image quality comparable to that of a single-row scanning system even with a 46-row detector at a table feed of 64 mm. Both algorithms tolerate any table feed below the maximum value associated to the detector height. Due to the z-filter approach, all detector data sampled can be used for image reconstruction.     

Feldkamp-type cone-beam tomography in the wavelet framework

X-ray computed tomography (CT) is in transition from fan-beam to cone-beam geometry. For cone-beam volumetric imaging, reduction of radiation exposure remains an important issue. Because the wavelet approach was shown to be effective and flexible for two-dimensional (2-D) local region reconstruction, we are motivated to perform wavelet local CT in cone-beam geometry. In this paper, we formulate the Feldkamp cone-beam reconstruction from the wavelet perspective, derive both full-scan and half-scan Feldkamp-type formulas for either global or local reconstruction, and demonstrate the feasibility and utility in synthetic and real data. It is found that using the wavelet Feldkamp approach, a three-dimensional (3-D) region of interest (ROI) can be reconstructed with neither severe image artifacts nor any significant constant bias in our simulation and experiments.     

Region of interest reconstruction from truncated data in circular cone-beam CT

The circular scanning trajectory is one of the most widely adopted data-acquisition configurations in computed tomography (CT). The Feldkamp, Davis, Kress (FDK) algorithm and its various modifications have been developed for reconstructing approximately three-dimensional images from circular cone-beam data. When data contain transverse truncations, however, these algorithms may reconstruct images with significant truncation artifacts. It is of practical significance to develop algorithms that can reconstruct region-of-interest (ROI) images from truncated circular cone-beam data that are free of truncation artifacts and that have an accuracy comparable to that obtained from nontruncated cone-beam data. In this work, we have investigated and developed a backprojection-filtration (BPF)-based algorithm for ROI-image reconstruction from circular cone-beam data containing transverse truncations. Furthermore, we have developed a weighted BPF algorithm to exploit "redundant" information in data for improving image quality. In an effort to validate and evaluate the proposed BPF algorithms for circular cone-beam CT, we have performed numerical studies by using both computer-simulation data and experimental data acquired with a radiotherapy cone-beam CT system. Quantitative results in these studies demonstrate that the proposed BPF algorithms for circular cone-beam CT can reconstruct ROI images free of truncation artifacts.     

Tomographic reconstruction for tilted helical multislice CT

One of the most recent technical advancements in computed tomography (CT) is the introduction of multislice CT (MCT). Because multiple detector rows are used for data acquisition, MCT offers higher volume coverage, faster scan speed, and reduced X-ray tube loading. Recognizing its unique data-sampling pattern, several image reconstruction algorithms were developed. These algorithms have been shown to be adequate in producing clinically acceptable images. Recent studies, however, have revealed that the image quality of MCT can be significantly degraded when helical data are acquired with a tilted gantry. The degraded image quality has rendered this feature unacceptable for clinical usage. In this paper, we first present a detailed investigation on the cause of the image quality degradation. An analytical model is derived to provide a mathematical basis for correction. Several compensation schemes are subsequently presented, and a detailed performance comparison is provided in terms of spatial resolution, noise, computation efficiency, and image artifacts.     

Respiratory compensation in projection imaging using a magnification and displacement model

Respiratory motion during the collection of computed tomography (CT) projections generates structured artifacts and a loss of resolution that can render the scans unusable. This motion is problematic in scans of those patients who cannot suspend respiration, such as the very young or intubated patients. Here, the authors present an algorithm that can be used to reduce motion artifacts in CT scans caused by respiration. An approximate model for the effect of respiration is that the object cross section under interrogation experiences time-varying magnification and displacement along two axes. Using this model an exact filtered backprojection algorithm is derived for the case of parallel projections. The result is extended to generate an approximate reconstruction formula for fan-beam projections. Computer simulations and scans of phantoms on a commercial CT scanner validate the new reconstruction algorithms for parallel and fan-beam projections. Significant reduction in respiratory artifacts is demonstrated clinically when the motion model is satisfied. The method can be applied to projection data used in CT, single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI).     

Estimation of the heart respiratory motion with applications for cone beam computed tomography imaging: a simulation study

Computed tomography (CT) reconstruction methods assume imaging of static objects; object movement during projection data acquisition causes tomogram artifacts. The continuously moving heart, therefore, represents a complicated imaging case. The associated problems due to the heart beating can be overcome either by using very short projection acquisition times, during which the heart may be considered static, or by ECG-gated acquisition. In the latter case, however, the acquisition of a large number of projections may not be completed in a single breath hold, thus heart displacement occurs as an additional problem. This problem has been addressed by applying heart motion models in various respiratory motion compensation algorithms. Our paper focuses on cone beam computed tomography (CBCT), performed in conjunction with isocentric, fluoroscopic equipment, and continuous ECG and respiratory monitoring. Such equipment is used primarily for in-theater three-dimensional (3-D) imaging and benefits particularly from the recent developments in flat panel detector technologies. The objectives of this paper are: (i) to develop a model for the motion of the heart due to respiration during the respiratory cycle; (ii) to apply this model to the tomographic reconstruction algorithm, in order to account for heart movement due to respiration in the reconstruction; and (iii) to initially evaluate this method by means of simulation studies. Based on simulation studies, we were able to demonstrate that heart displacement due to respiration can be estimated from the same projection data, required for a CBCT reconstruction. Our paper includes semiautomatic segmentation of the heart on the X-ray projections and reconstruction of a convex 3-D-heart object that performs the same motion as the heart during respiration, and use of this information into the CBCT reconstruction algorithm. The results reveal significant image quality improvements in cardiac image reconstruction.     

Three-dimensional artifact induced by projection weighting andmisalignment

In recent years, the use of computer graphic techniques to produce three-dimensional (3-D) and reformatted images from a set of axial computed tomography (CT) images has gained significant interest. In most cases, the CT images are generated with the projection data set weighted prior to reconstruction, to combat motion artifacts, data inconsistency, or redundant data samples. In this paper, we investigate the potential bias introduced to the reconstruction as a result of the interaction of the projection weights and the isocenter misalignment (ISM). We demonstrate that when the weights applied to the conjugate rays are significantly different, bias will result which favors the sample with a higher weight. Although the error is not easily detected in axial CT images, it can be quite visible in 3-D or multiplanar reformatted (MPR) images. In this paper, we first present a theoretical framework to analyze and predict the bias. The theoretical prediction is validated by both computer simulations and phantom experiments. Several schemes to combat this artifact are subsequently presented; and their effectiveness is demonstrated.     

A Fast Implementation of a Minimum Variance Estimator for Computerized Tomography Image Reconstruction

Most present day computerized tomography (CT) systems are based on reconstruction algorithms that produce only approximate deterministic solutions of the image reconstruction problem. These algorithms yield reasonable results in cases of low measurement noise and regular measurement geometry, and are considered acceptable because they require far less computation and storage than more powerful algorithms that can yield near optimal results. However, the special geometry of the CT image reconstruction problem can be used to reduce by orders of magnitude the computation required for optimal reconstruction methods, such as the minimum variance estimator. These simplifications can make the minimum variance technique very competitive with well-known approximate techniques such as the algebraic reconstruction technique (ART) and convolution-back projection. The general minimum variance estimator for CT is first presented, and then a fast algorithm is described that uses Fourier transform techniques to implement the estimator for either fan beam or parallel beam geometries. The computational requirements of these estimators are examined and compared to other techniques. To allow further comparison with the commonly used convolution-back projection method, a representation of the fast algorithm is derived which allows its equivalent convolving function to be examined. Several examples are presented.     

Registration of real and CT-derived virtual bronchoscopic images toassist transbronchial biopsy

This paper describes research work motivated by an innovative medical application: computer-assisted transbronchial biopsy. This project involves the registration, with no external localization device, of a preoperative three-dimensional (3-D) computed tomography (CT) scan of the thoracic cavity (showing a tumor that requires a needle biopsy), and an intraoperative endoscopic two-dimensional (2-D) image sequence, in order to provide assistance in transbronchial puncture of the tumor. Because of the specific difficulties resulting from the data being processed, a multilevel strategy was introduced. For each analysis level, the relevant information to process and the corresponding algorithms were defined. This multilevel strategy, thus, provides the best possible accuracy. Original image processing methods were elaborated, dealing with segmentation, registration and 3-D reconstruction of the bronchoscopic images. In particular, these methods involve adapted mathematical morphology tools, a “daemon-based” registration algorithm, and a model-based shape-from-shading algorithm. This pilot study presents the application of these algorithms to recorded bronchoscopic video sequences for five patients. The preliminary results presented here demonstrate that it is possible to precisely localize the endoscopic camera within the CT data coordinate system. The computer can thus synthesize in near real-time the CT-derived virtual view that corresponds to the actual endoscopic view     

Alternating minimization algorithms for transmission tomography

A family of alternating minimization algorithms for finding maximum-likelihood estimates of attenuation functions in transmission X-ray tomography is described. The model from which the algorithms are derived includes polyenergetic photon spectra, background events, and nonideal point spread functions. The maximum-likelihood image reconstruction problem is reformulated as a double minimization of the I-divergence. A novel application of the convex decomposition lemma results in an alternating minimization algorithm that monotonically decreases the objective function. Each step of the minimization is in closed form. The family of algorithms includes variations that use ordered subset techniques for increasing the speed of convergence. Simulations demonstrate the ability to correct the cupping artifact due to beam hardening and the ability to reduce streaking artifacts that arise from beam hardening and background events.     

An iterative maximum-likelihood polychromatic algorithm for CT

A new iterative maximum-likelihood reconstruction algorithm for X-ray computed tomography is presented. The algorithm prevents beam hardening artifacts by incorporating a polychromatic acquisition model. The continuous spectrum of the X-ray tube is modeled as a number of discrete energies. The energy dependence of the attenuation is taken into account by decomposing the linear attenuation coefficient into a photoelectric component and a Compton scatter component. The relative weight of these components is constrained based on prior material assumptions. Excellent results are obtained for simulations and for phantom measurements. Beam-hardening artifacts are effectively eliminated. The relation with existing algorithms is discussed. The results confirm that improving the acquisition model assumed by the reconstruction algorithm results in reduced artifacts. Preliminary results indicate that metal artifact reduction is a very promising application for this new algorithm.     

A survey of motion-parallax-based 3-D reconstruction algorithms

The task of recovering three-dimensional (3-D) geometry from two-dimensional views of a scene is called 3-D reconstruction. It is an extremely active research area in computer vision. There is a large body of 3-D reconstruction algorithms available in the literature. These algorithms are often designed to provide different tradeoffs between speed, accuracy, and practicality. In addition, even the output of various algorithms can be quite different. For example, some algorithms only produce a sparse 3-D reconstruction while others are able to output a dense reconstruction. The selection of the appropriate 3-D reconstruction algorithm relies heavily on the intended application as well as the available resources. The goal of this paper is to review some of the commonly used motion-parallax-based 3-D reconstruction techniques and make clear the assumptions under which they are designed. To do so efficiently, we classify the reviewed reconstruction algorithms into two large categories depending on whether a prior calibration of the camera is required. Under each category, related algorithms are further grouped according to the common properties they share.     

Pulmonary airways: 3-D reconstruction from multislice CT and clinical investigation

In the framework of computer-aided diagnosis, this paper proposes a novel functionality for the computerized tomography (CT)-based investigation of the pulmonary airways. It relies on an energy-based three-dimensional (3-D) reconstruction of the bronchial tree from multislice CT acquisitions, up to the sixth- to seventh-order subdivisions. Global and local analysis of the reconstructed airways is possible by means of specific visualization modalities, respectively, the CT bronchography and the virtual bronchoscopy. The originality of the 3-D reconstruction approach consists in combining axial and radial propagation potentials to control the growth of a subset of low-order airways extracted from the CT volume by means of a robust mathematical morphology operator-the selective marking and depth constrained (SMDC) connection cost. The proposed approach proved to be robust with respect to a large spectrum of airway pathologies, including even severe stenosis (bronchial lumen obstruction/collapse). Validated by expert radiologists, examples of airway 3-D reconstructions are presented and discussed for both normal and pathological cases. They highlight the interest in considering CT bronchography and virtual bronchoscopy as complementary tools for clinical diagnosis and follow-up of airway diseases.     

A Reconstruction Algorithm for Photoacoustic Imaging Based on the Nonuniform FFT

Fourier reconstruction algorithms significantly outperform conventional backprojection algorithms in terms of computation time. In photoacoustic imaging, these methods require interpolation in the Fourier space domain, which creates artifacts in reconstructed images. We propose a novel reconstruction algorithm that applies the one-dimensional nonuniform fast Fourier transform to photoacoustic imaging. It is shown theoretically and numerically that our algorithm avoids artifacts while preserving the computational effectiveness of Fourier reconstruction.      

Multislice helical CT: image temporal resolution

A multislice helical computed tomography (CT) halfscan (HS) reconstruction algorithm is proposed for cardiac applications. The imaging performances (in terms of the temporal resolution, z-axis resolution, image noise, and image artifacts) of the HS algorithm are compared to the existing algorithms using theoretical models and clinical data. A theoretical model of the temporal resolution performance (in terms of the temporal sensitivity profile) is established for helical CT, in general, i.e., for any number of detector rows and any reconstruction algorithm used. It is concluded that the HS reconstruction results in improved image temporal resolution than the corresponding 180 degrees LI (linear interpolation) reconstruction and is more immune to the inconsistent data problem induced by cardiac motions. The temporal resolution of multislice helical CT with the HS algorithm is comparable to that of single-slice helical CT with the HS algorithm. In practice, the 180 degrees LI and HS-LI algorithms can be used in parallel to generate two image sets from the same scan acquisition, one (180 degrees LI) for improved z-resolution and noises, and the other (HS-LI) for improved image temporal resolution.