- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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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) - Superresolution Contour Reconstruction Approach to a Linear Thermal Expansion Measurement
摘要： Optical imaging delivers absolute, non-contact, and high-dynamic-range measurement of thermal expansion. However, to achieve high accuracy, various factors should be accounted within the image analysis, including: image spatial sampling, lens aberrations, brightness nonuniformity and object edge deformations. Approach based on the object contour reconstruction is presented. Measurement procedure consists of two stages. Firstly, object edge contours corresponding to different temperatures are estimated. This is done by the novel contour-retrieving image reconstruction, capable of optical and spatial sampling superresolution as well as compensation of brightness nonuniformity. Secondly, the reference retrieved contour is reconstructed to fit retrieved contours for other temperatures, considering a linear expansion model. With the nonlinear algorithms for contour retrieval and reconstruction, small sub-resolution random edge distortions are detected and filtered out, increasing the measurement accuracy. Second improvement of the proposed approach is an opportunity to validate the measurement, given by its fully reconstructive nature.
关键词： computational imaging,edge detection,active contour,deformation measurement,image reconstruction
更新于2025-09-09 09:28:46
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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) - Spatially-variant Strength for Anatomical Priors in PET Reconstruction
摘要： This study explores the use of a spatially-variant penalty strength, proposed initially for quadratic penalties, in penalized image reconstruction using anatomical information. We have used the recently proposed Parallel Level Sets (PLS) anatomical prior as it has shown promising results in the literature. It was incorporated into the previously proposed preconditioned algorithm (L-BFGS-B-PC) for achieving both good image quality and fast convergence rate. A 2-dimensional (2D) disc phantom with a hot spot at the center and a 3D XCAT thorax phantom with lesions inserted in different slices are used to study how surrounding activity and lesion location affect both the visual appearance and quantitative consistency, respectively. Anatomical information is provided and assumed to be well-aligned with the corresponding activity images. For the XCAT phantom, the inserted lesions are either present or absent in the anatomical images to investigate the influence of the anatomical penalty. The reconstructed images for both phantoms with and without applying the spatially-variant penalty strength are compared. Preliminary results demonstrate that applying the spatially-variant penalization with an anatomical prior can reduce the dependence of local contrast on background activity and lesion location. Further work to explore the potential benefit in clinical imaging is warranted.
关键词： spatially-variant penalty strength,penalized image reconstruction,L-BFGS-B-PC,Parallel Level Sets,anatomical prior
更新于2025-09-09 09:28:46
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The attenuated spline reconstruction technique for single photon emission computed tomography
摘要： We present the attenuated spline reconstruction technique (aSRT) which provides an innovative algorithm for single photon emission computed tomography (SPECT) image reconstruction. aSRT is based on an analytic formula of the inverse attenuated Radon transform. It involves the computation of the Hilbert transforms of the linear attenuation function and of two sinusoidal functions of the so-called attenuated sinogram. These computations are achieved by employing the attenuation information provided by computed tomography (CT) scans and by utilizing custom-made cubic spline interpolation. The purpose of this work is: (i) to present the mathematics of aSRT, (ii) to reconstruct simulated and real SPECT/CT data using aSRT and (iii) to evaluate aSRT by comparing it to filtered backprojection (FBP) and to ordered subsets expectation minimization (OSEM) reconstruction algorithms. Simulation studies were performed by using an image quality phantom and an appropriate attenuation map. Reconstructed images were generated for 45, 90 and 180 views over 360 degrees with 20 realizations and involved Poisson noise of three different levels (NL), namely 100% (NL1), 50% (NL2) and 10% (NL3) of the total counts, respectively. Moreover, real attenuated SPECT sinograms were reconstructed from a real study of a Jaszczak phantom, as well as from a real clinical myocardial SPECT/CT study. Comparisons between aSRT, FBP and OSEM reconstructions were performed using contrast, bias and image roughness. The results suggest that aSRT can efficiently produce accurate attenuation-corrected reconstructions for simulated and real phantoms, as well as for clinical data. In particular, in the case of the clinical myocardial study, aSRT produced reconstructions with higher cold contrast than both FBP and OSEM. aSRT, by incorporating the attenuation correction within itself, may provide an improved alternative to FBP. This is particularly promising for ‘cold’ regions as those occurring in myocardial ischaemia.
关键词： analytic image reconstruction,single photon emission computed tomography (SPECT),attenuated Radon transform
更新于2025-09-09 09:28:46
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Discrete Total Variation with Finite Elements and Applications to Imaging
摘要： The total variation (TV)-seminorm is considered for piecewise polynomial, globally discontinuous (DG) and continuous (CG) finite element functions on simplicial meshes. A novel, discrete variant (DTV) based on a nodal quadrature formula is defined. DTV has favorable properties, compared to the original TV-seminorm for finite element functions. These include a convenient dual representation in terms of the supremum over the space of Raviart–Thomas finite element functions, subject to a set of simple constraints. It can therefore be shown that a variety of algorithms for classical image reconstruction problems, including TV-L 2 denoising and inpainting, can be implemented in low- and higher-order finite element spaces with the same efficiency as their counterparts originally developed for images on Cartesian grids.
关键词： Image reconstruction,Discrete total variation,Dual problem,Numerical algorithms
更新于2025-09-09 09:28:46
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Image Reconstruction Using Analysis Model Prior
摘要： The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims.
关键词： cosparsity,iterative cosupport detection,magnetic resonance imaging,analysis model,image reconstruction
更新于2025-09-09 09:28:46
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[IEEE ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Calgary, AB (2018.4.15-2018.4.20)] 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Image Reconstruction for Quanta Image Sensors Using Deep Neural Networks
摘要： Quanta Image Sensor (QIS) is a single-photon image sensor that oversamples the light field to generate binary measurements. Its single-photon sensitivity makes it an ideal candidate for the next generation image sensor after CMOS. However, image reconstruction of the sensor remains a challenging issue. Existing image reconstruction algorithms are largely based on optimization. In this paper, we present the first deep neural network approach for QIS image reconstruction. Our deep neural network takes the binary bitstream of QIS as input, learns the nonlinear transformation and denoising simultaneously. Experimental results show that the proposed network produces significantly better reconstruction results compared to existing methods.
关键词： single-photon imaging,Quanta Image Sensor,deep neural networks,image reconstruction
更新于2025-09-04 15:30:14
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Singular Value Decomposition Approximation via Kronecker Summations for Imaging Applications
摘要： In this paper we propose an approach to approximate a truncated singular value decomposition of a large structured matrix. By first decomposing the matrix into a sum of Kronecker products, our approach can be used to approximate a large number of singular values and vectors more efficiently than other well-known schemes, such as iterative algorithms based on Golub–Kahan–Lanczos bidiagonalization. We provide theoretical results and numerical experiments to demonstrate the accuracy of our approximation and show how the approximation can be used to solve large scale ill-posed inverse problems, either as an approximate filtering method, or as a preconditioner to accelerate iterative algorithms.
关键词： regularization,inverse problems,image restoration,SVD,image reconstruction,Kronecker products
更新于2025-09-04 15:30:14
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Why chromatic imaging matters
摘要： During the last two decades, the first generation of beam combiners at the Very Large Telescope Interferometer has proved the importance of optical interferometry for high-angular resolution astrophysical studies in the near- and mid-infrared. With the advent of 4-beam combiners at the VLTI, the u ? v coverage per pointing increases significantly, providing an opportunity to use reconstructed images as powerful scientific tools. Therefore, interferometric imaging is already a key feature of the new generation of VLTI instruments, as well as for other interferometric facilities like CHARA and JWST. It is thus imperative to account for the current image reconstruction capabilities and their expected evolutions in the coming years. Here, we present a general overview of the current situation of optical interferometric image reconstruction with a focus on new wavelength-dependent information, highlighting its main advantages and limitations. As an Appendix we include several cookbooks describing the usage and installation of several state-of-the art image reconstruction packages. To illustrate the current capabilities of the software available to the community, we recovered chromatic images, from simulated MATISSE data, using the MCMC software SQUEEZE. With these images, we aim at showing the importance of selecting good regularization functions and their impact on the reconstruction.
关键词： Optical interferometry,High angular resolution,Image reconstruction
更新于2025-09-04 15:30:14
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Imaging With 3-D Aperture Synthesis Radiometers
摘要： The spatial resolution is still a problem in passive microwave remote sensing, especially in low frequency. In recent years, the satellite formation flying has been proposed. Based on this technique, a large array is able to be synthesized in orbit to achieve higher spatial resolution. However, it is a big challenge for the control system to constrain all the satellites in a coplane in orbit. The 3-D array configuration is a good choice for a synthesized array based on satellite formation flying. In this paper, the complete formulation of visibility functions, including system imperfections, in a 3-D aperture synthesis radiometer (3-D ASR) is derived. The array factor of a 3-D ASR is defined. The reconstructed modified brightness temperature (BT) is a 3-D linear convolution of the modified BT and the array factor. Based on this relationship, the reconstruction method for a practical 3-D ASR is studied. The numerical results demonstrate that the reconstruction method is correct and stable. Finally, a discussion is given to analyze several existing methods that were proposed to reconstruct BT image for 3-D arrays in radio astronomy and earth observation. Compared with these existing methods, our imaging method is more suitable for earth observation based on the technique of satellites formation flying in low earth orbit. In addition, according to the derivations, some mature techniques that were developed for 2-D ASRs may be applied to 3-D ASRs.
关键词： visibility functions,image reconstruction,array factor,3-D aperture synthesis radiometers (3-D ASRs),modified brightness temperature (BT)
更新于2025-09-04 15:30:14
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PET Image Reconstruction Using Deep Image Prior
摘要： Recently deep neural networks have been widely and successfully applied in computer vision tasks and attracted growing interests in medical imaging. One barrier for the application of deep neural networks to medical imaging is the need of large amounts of prior training pairs, which is not always feasible in clinical practice. This is especially true for medical image reconstruction problems, where raw data are needed. Inspired by the deep image prior framework, in this work we proposed a personalized network training method where no prior training pairs are needed, but only the patient’ own prior information. The network is updated during the iterative reconstruction process using the patient specific prior information and measured data. We formulated the maximum likelihood estimation as a constrained optimization problem and solved it using the alternating direction method of multipliers (ADMM) algorithm. Magnetic resonance imaging (MRI) guided Positron emission tomography (PET) reconstruction was employed as an example to demonstrate the effectiveness of the proposed framework. Quantification results based on simulation and real data show that the proposed reconstruction framework can outperform Gaussian post-smoothing and anatomically-guided reconstructions using the kernel method or the neural network penalty.
关键词： positron emission tomography,unsupervised learning,Medical image reconstruction,deep neural network
更新于2025-09-04 15:30:14