- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Cone-beam CT reconstruction along any orientation of interest
摘要： We present a novel method which provides X-ray CT users the flexibility to reconstruct an object along any of its internal flat features. This internal feature, which is generally not parallel to the object’s external surface, can be either an interface between two materials or one surface of an internal layer. This method is developed based on our existing CT differential reconstruction algorithm that is achieved by modifying the popular Feldkamp-Davis-Kress cone-beam reconstruction technique. The theory of this technology is described. One case-study demonstrates that this method is independent of the surface selection of several parallel features. Another case-study shows its capability to reconstruct any individual plate along the plate’s own orientation with a three-plate object.
关键词： differential CT reconstruction,cone-beam reconstruction,Computed tomography,orientation-preferred reconstruction
更新于2025-09-23 15:22:29
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Performance of Landweber iteration algorithm in tomographic image reconstruction
摘要： The rapid growth of computed tomography has been accompanied by equally advancing in image reconstruction algorithm also. The fundamental inverse problem is the reconstruction of a function from finitely many measurements, so pertaining to that function. The measured data are limited, and it cannot serve to determine one single correct solution. The iterative reconstruction image reconstruction algorithms have stable solution to the limited projection. In this paper, Landweber-based iteration image reconstruction is simulated and its performance is compared with different algorithm. Then, the quality of the reconstructed image is expressed in terms of mean absolute error and correlation coefficient as compared to the original image. The entire simulations are performed in Matlab tool.
关键词： image reconstruction,computed,Landweber algorithm,tomography,limited projection,iterative reconstruction
更新于2025-09-23 15:22:29
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The Application of a New Model-Based Iterative Reconstruction in Low-Dose Upper Abdominal CT
摘要： Rationale and Objectives: To compare upper abdominal computed tomography (CT) image quality of new model-based iterative reconstruction (MBIR) with low-contrast resolution preference (MBIRNR40), conventional MBIR (MBIRc), and adaptive statistical iterative reconstruction (ASIR) at low dose with ASIR at routine-dose. Materials and Methods: Study included phantom and 60 patients who had initial and follow-up CT scans. For patients, the delay phase was acquired at routine-dose (noise index = 10 HU) for the initial scan and low dose (noise index = 20 HU) for the follow-up. The low-dose CT was reconstructed with 40% and 60% ASIR, MBIRc, and MBIRNR40, while routine-dose CT was reconstructed with 40% ASIR. CT value and noise measurements of the subcutaneous fat, back muscle, liver, and spleen parenchyma were compared using one-way ANOVA. Two radiologists used semiquantitative 7-scale (-3 to +3) to rate image quality and artifacts. Results: The phantom study revealed superior low-contrast resolution with MBIRNR40. For patient scans, the CT dose index for the low-dose CT was 3.00 ± 1.32 mGy, 75% lower than the 11.90 ± 4.75 mGy for the routine-dose CT. Image noise for the low-dose MBIRNR40 images was significantly lower than the low-dose MBIRc and ASIR images, and routine-dose ASIR images (p < 0.05). Subjective ratings showed higher image quality for low-dose MBIRNR40, with lower noise, better low-contrast resolution for abdominal structures, and finer lesion contours than those of low-dose MBIRc and ASIR images, and routine-dose ASIR images (p < 0.05). Conclusion: MBIRNR40 with low-contrast resolution preference provides significantly lower noise and better image quality than MBIRc and ASIR in low-dose abdominal CT; significantly better objective and subjective image quality than the routine-dose ASIR with 75% dose reduction.
关键词： Model-based iterative reconstruction,Abdominal CT.,X-ray computed tomography,Adaptive statistical iterative reconstruction,Radiation dose
更新于2025-09-23 15:22:29
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Realistic Texture Reconstruction Incorporating Spectrophotometric Color Correction
摘要： With the proliferation of high resolution 3D scanners, the quality of recorded 3D models has greatly improved. Nonetheless, while geometric fidelity is important, color information is still required to achieve photo-realistic 3D models. In this regard, texture reconstruction techniques combine color images from several views in order to optimally color the mesh of a 3D model. Nonetheless, a major challenge that is often overlooked by existing approaches is the technical limitations of color acquisition devices that lead to erroneously colored 3D models. In this paper, a novel technique is presented that formulates texture reconstruction as an optimization problem incorporating a color correction term in its objective function. The underlying rationale is to exploit external to the 3D scanner color measurements that can be available from more reliable sensors such as a UV-VIS spectrometer. Such measurements are often available for objects of high aesthetic value such as artworks of cultural heritage objects. Through experimental evaluation of our method on a real painting we demonstrate the superiority of the proposed technique, compared to state-of-the-art texture reconstruction, providing a reliable representation of the artworks appearance both in terms of numerical accuracy and visual observation.
关键词： cultural heritage,3D reconstruction,UV-VIS spectrometer,color correction,Texture reconstruction
更新于2025-09-23 15:22:29
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Dynamic Non-Rigid Objects Reconstruction with a Single RGB-D Sensor
摘要： This paper deals with the 3D reconstruction problem for dynamic non-rigid objects with a single RGB-D sensor. It is a challenging task as we consider the almost inevitable accumulation error issue in some previous sequential fusion methods and also the possible failure of surface tracking in a long sequence. Therefore, we propose a global non-rigid registration framework and tackle the drifting problem via an explicit loop closure. Our novel scheme starts with a fusion step to get multiple partial scans from the input sequence, followed by a pairwise non-rigid registration and loop detection step to obtain correspondences between neighboring partial pieces and those pieces that form a loop. Then, we perform a global registration procedure to align all those pieces together into a consistent canonical space as guided by those matches that we have established. Finally, our proposed model-update step helps fixing potential misalignments that still exist after the global registration. Both geometric and appearance constraints are enforced during our alignment; therefore, we are able to get the recovered model with accurate geometry as well as high fidelity color maps for the mesh. Experiments on both synthetic and various real datasets have demonstrated the capability of our approach to reconstruct complete and watertight deformable objects.
关键词： 3D reconstruction,non-rigid reconstruction,RGB-D sensor
更新于2025-09-23 15:22:29
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - An Interior Point Method for Nonnegative Sparse Signal Reconstruction
摘要： We present a primal-dual interior point method (IPM) with a novel preconditioner to solve the (cid:96)1-norm regularized least square problem for nonnegative sparse signal reconstruction. IPM is a second-order method that uses both gradient and Hessian information to compute effective search directions and achieve super-linear convergence rates. It therefore requires many fewer iterations than first-order methods such as iterative shrinkage/thresholding algorithms (ISTA) that only achieve sub-linear convergence rates. However, each iteration of IPM is more expensive than in ISTA because it needs to evaluate an inverse of a Hessian matrix to compute the Newton direction. We propose to approximate each Hessian matrix by a diagonal matrix plus a rank-one matrix. This approximation matrix is easily invertible using the Sherman-Morrison formula, and is used as a novel preconditioner in a preconditioned conjugate gradient method to compute a truncated Newton direction. We demonstrate the efficiency of our algorithm in compressive 3D volumetric image reconstruction. Numerical experiments show favorable results of our method in comparison with previous interior point based and iterative shrinkage/thresholding based algorithms.
关键词： nonnegative sparse,3d volumetric image reconstruction,primal-dual preconditioned interior point method,(cid:96)1-norm regularized optimization,compressive sensing
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Krakow, Poland (2018.10.16-2018.10.18)] 2018 IEEE International Conference on Imaging Systems and Techniques (IST) - Real-Time Stereo Vision for Road Surface 3-D Reconstruction
摘要： Stereo vision techniques have been widely used in civil engineering to acquire 3-D road data. The two important factors of stereo vision are accuracy and speed. However, it is very challenging to achieve both of them simultaneously and therefore the main aim of developing a stereo vision system is to improve the trade-off between these two factors. In this paper, we present a real-time stereo vision system used for road surface 3-D reconstruction. The proposed system is developed from our previously published 3-D reconstruction algorithm where the perspective view of the target image is first transformed into the reference view, which not only increases the disparity accuracy but also improves the processing speed. Then, the correlation cost between each pair of blocks is computed and stored in two 3-D cost volumes. To adaptively aggregate the matching costs from neighbourhood systems, bilateral filtering is performed on the cost volumes. This greatly reduces the ambiguities during stereo matching and further improves the precision of the estimated disparities. Finally, the subpixel resolution is achieved by conducting a parabola interpolation and the subpixel disparity map is used to reconstruct the 3-D road surface. The proposed algorithm is implemented on an NVIDIA GTX 1080 GPU for the real-time purpose. The experimental results illustrate that the reconstruction accuracy is around 3 mm.
关键词： stereo vision,3-D reconstruction,bilateral filtering,subpixel disparity map,real-time
更新于2025-09-23 15:22:29
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Geometric Distortion Correction of Spaceborne GNSS-R Delay-Doppler Map Using Reconstruction
摘要： For spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R), the delay difference of direct and reflected GNSS signals among successive snapshots changes rapidly because of the high dynamics of low earth orbital and GNSS satellites. This change has to be compensated to avoid the distortion of incoherently averaged delay-Doppler map (DDM). The method to refresh the correlation window on each coherent integration time period may require too many instrument resources or too much data to be uploaded from the ground station. This letter proposes a new postprocessing approach based on the motion degradation model of DDM and the reconstruction to replace real-time compensation. Raw sampled data from UK TechDemoSat-1 are used to verify the availability of proposed approach. The results show that after reconstruction for the distorted DDM, the DDM accuracies relative to that compensated in real time are significantly improved.
关键词： Global Navigation Satellite System-Reflectometry (GNSS-R),reconstruction,Distorted delay-Doppler map (DDM)
更新于2025-09-23 15:22:29
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[IEEE 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Atlanta, GA (2017.10.21-2017.10.28)] 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Joint Reconstruction of PET Attenuation and Activity from Scattered and Unscattered Data
摘要： In previous work, we have proposed scatter-to-attenuation reconstruction for positron emission tomography (PET). Scatter-to-attenuation reconstruction aims at recovering object attenuation information in the form of spatial electron-density distributions from pairs of coincident photons, one of which has been single-scattered. One idea is to interleave scatter-to-attenuation reconstruction, which inputs an activity distribution and outputs an attenuation map, with trues-to-activity reconstruction, which inputs said attenuation map and outputs an improved activity distribution. However, major uncertainties regarding the applicability of this approach revolve around a) the unknown impact of the initial activity estimate; b) evaluation of reconstructed activity distributions, and c) convergence to the correct solution. Methods: Using low-dimensional simulated PET data (mouse-sized, 18x18-voxels phantom), we start with mostly uniform initial activity and attenuation estimates and iteratively apply maximum-likelihood expectation-maximization (MLEM) and a maximum-likelihood gradient-ascent (MLGA) algorithm to update activity (from unscattered data) and attenuation (from scattered data), respectively. We evaluate results in terms of log-likelihoods of the expected scatter histograms, and normalized mean squared errors with respect to reference image-space distributions of activity and attenuation. Results: In our study, both attenuation and activity converged to the reference distributions, despite MLEM and MLGA starting with incorrect attenuation and activity estimates, respectively. Conclusion: The MLGA scatter-to-attenuation reconstruction algorithm, in combination with MLEM trues-to-activity reconstruction, jointly reconstructs attenuation maps and attenuation-corrected activity distributions from scattered and unscattered coincidences without reliance on a-priori information about the activity distribution.
关键词： image reconstruction,PET,attenuation,Compton scattering,algorithms
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM) - Sheffield (2018.7.8-2018.7.11)] 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM) - Single-Snapshot Adaptive Beamforming
摘要： Adaptive beamformers are sensitive to model mismatch, especially when the number of training samples is small or the training samples are contaminated by the signal component. In this paper, we consider an extreme scenario where only a single signal-contaminated snapshot is available for adaptive beamformer design. In such a case, we cannot perform direct inversion or eigen-decomposition of the rank-one sample covariance matrix required in adaptive beamformer design. To address this issue, we formulate a sparsity-constrained covariance matrix fitting problem to estimate the spatial spectrum distribution over the observed spatial domain, which is then used for adaptive beamformer design via the sparse reconstruction of the interference-plus-noise covariance matrix. Simulation results demonstrate the performance advantage of the proposed adaptive beamforming algorithm over other beamforming algorithms suitable for the single-snapshot scenario.
关键词： single snapshot,sparsity,covariance matrix reconstruction,Adaptive beamforming,covariance matrix fitting
更新于2025-09-23 15:22:29