- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) - Bologna, Italy (2018.9.9-2018.9.12)] 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) - Improved LAS Detector for MIMO Systems with Imperfect Channel State Information
摘要： The performance of coherent symbol detection in multiple-input multiple-output (MIMO) systems is tightly related to the channel knowledge at the receiver side. For MIMO detection, achieving near-optimal performance with a low computational complexity has been a topic of several recent researches. In this paper, we propose a robust detector for uncoded MIMO systems with imperfect CSI (ICSI). The proposed detector is based on the likelihood ascent search (LAS) algorithm which achieves near maximum likelihood (ML) performance with a reduced complexity. To take into account the channel estimation error, we propose to use a modified likelihood metric function. Moreover, to enhance the system performance, we suggest to perform the channel estimation and the data detection in an iterative manner. Simulation results show that the proposed scheme outperforms the conventional LAS detector.
关键词： LAS detector,MIMO systems,robust detection,iterative detection,imperfect CSI
更新于2025-09-23 15:23:52
-
[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) - Group Sparsity Residual with Non-Local Samples for Image Denoising
摘要： Inspired by group-based sparse coding, recently proposed group sparsity residual (GSR) scheme has demonstrated superior performance in image processing. However, one challenge in GSR is to estimate the residual by using a proper reference of the group-based sparse coding (GSC), which is desired to be as close to the truth as possible. Previous researches utilized the estimations from other algorithms (i.e., GMM or BM3D), which are either not accurate or too slow. In this paper, we propose to use the Non-Local Samples (NLS) as reference in the GSR regime for image denoising, thus termed GSR-NLS. More specifically, we first obtain a good estimation of the group sparse coefficients by the image non-local self-similarity, and then solve the GSR model by an effective iterative shrinkage algorithm. Experimental results demonstrate that the proposed GSR-NLS not only outperforms many state-of-the-art methods, but also delivers the competitive advantage of speed.
关键词： Image denoising,group sparsity residual,iterative shrinkage algorithm,group-based sparse coding,non-local self-similarity
更新于2025-09-23 15:23:52
-
[IEEE 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - Hangzhou, China (2018.10.18-2018.10.20)] 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP) - A Hybrid Decoding Algorithm for Low-Rate LDPC codes in 5G
摘要： A hybrid decoding algorithm for low-density parity-check codes is presented. The proposed algorithm applies different updating schemes, such as the normalized min-sum (NMS) simplification and linear approximation, to the check-node based on its degree. Meanwhile, to eliminate the dependence on the channel variance estimation, the proposed algorithm adopts a multiplicative factor to initialize the channel input and a fixed linear functions for check-node updating. From the iterative thresholds and decoding simulations, our proposed algorithm can be shown to achieve improved performance (much closer to that of the belief propagation decoding) at the expense of a slight increase in complexity to NMS algorithm.
关键词： LDPC codes,iterative decoding,low rate LDPC codes,hybrid decoding
更新于2025-09-23 15:23:52
-
A mathematical model and iterative inversion for fluorescent optical projection tomography
摘要： Solving the fluorophore distribution in a tomographic setting has been difficult because of the lack of physically meaningful and computationally applicable propagation models. This study concentrates on the direct modelling of fluorescence signals in optical projection tomography (OPT), and on the corresponding inverse problem. The reconstruction problem is solved using emission projections corresponding to a series of rotational imaging positions of the sample. Similarly to the bright field OPT bearing resemblance with the transmission X-ray computed tomography, the fluorescent mode OPT is analogous to X-ray fluorescence tomography (XFCT). As an improved direct model for the fluorescent OPT, we derive a weighted Radon transform based on the XFCT literature. Moreover, we propose a simple and fast iteration scheme for the slice-wise reconstruction of the sample. The developed methods are applied in both numerical experiments and inversion of fluorescent OPT data from a zebrafish embryo. The results demonstrate the importance of propagation modelling and our analysis provides a flexible modelling framework for fluorescent OPT that can easily be modified to adapt to different imaging setups.
关键词： weighted Radon transform,optical projection tomography,fluorescence tomography,beam modelling,iterative reconstruction
更新于2025-09-23 15:23:52
-
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
-
[IEEE 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - Stuttgart, Germany (2018.11.20-2018.11.22)] 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - 3D Point Cloud Coarse Registration based on Convex Hull Refined by ICP and NDT
摘要： Non-rigid registration is a crucial step for many applications such as motion tracking, model retrieval, and object recognition. The accuracy of these applications is highly dependent on the initial position used in registration step. In this paper we propose a novel Convex Hull Aided Coarse Registration refined by two algorithms applied on projected points.Firstly,the proposed approach uses a statistical method to find the best plane that represents each point cloud. Secondly, all the points of each cloud are projected onto the corresponding planes. Then, two convex hulls are extracted from the two projected point sets and then matched optimally. Next, the non-rigid transformation from the reference to the model is robustly estimated through minimizing the distance between the matched point's pairs of the two convex hulls.Finally, this transformation estimation is refined by two methods. The first one is the refinement of coarse registration by Iterative Closest Point (ICP). The second one consists of the refinement of coarse registration by the Normal Distribution Transform (NDT). An experimental study ,carried out on several clouds, shows that the refinement of coarse registration with ICP gives, in the most cases, a better result than refinement with NDT.
关键词： Iterative Closest Point (ICP),Convex Hull,Normal Distribution Transform (NDT),Non rigid registration,3D point cloud,Principal Component Analysis (PCA)
更新于2025-09-23 15:22:29
-
[IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Hybrid Change Detection Based on ISFA for High-Resolution Imagery
摘要： Hybrid change detection (HCD) for high-resolution imagery usually adopt decision-level method and rely on artificial design. To address this issue, we propose a novel feature-level fusion strategy for HCD based on iterative slow feature analysis (ISFA). First, objects are obtained by multi-resolution segmentation of bi-temporal images respectively, and corresponding feature sets are constructed through stacking pixel- and object-level spectral features. Then, slow feature analysis (SFA) is used for transforming the feature sets into a new feature space at the first time. And iteration method with variable weights is introduced to get the last slow feature fusion map, where the changed pixels and unchanged pixels can be separated more easily. At last, K-means cluster is adopted to separate changed area and unchanged area automatically and generate final change result. Experiments were conducted on bi-temporal multi-spectral images, demonstrating the good performance of the proposed approach.
关键词： hybrid change detection,multi-scale fusion,feature-level fusion,iterative slow feature analysis
更新于2025-09-23 15:22:29
-
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
-
Submillisievert CT angiography for carotid arteries using wide array CT scanner and latest iterative reconstruction algorithm in comparison with previous generations technologies: Feasibility and diagnostic accuracy
摘要： Objectives: To assess evaluability and diagnostic accuracy of a low dose CT angiography (CTA) protocol for carotid arteries using latest Iterative Reconstruction (IR) algorithm in comparison with standard 100 kVp protocol using previous generation CT and IR. Materials and Methods: 105 patients, referred for CTA of the carotid arteries were prospectively enrolled in our study and underwent CTA with 80 kVp and latest IR algorithm (group 1). Data were retrospectively compared with 100 consecutive patients with similar examination indications that had previously undergone CTA of carotid arteries with a standard 100 kVp protocol and a first generation IR algorithm (group 2). Image quality was evaluated with a 4-point Likert-scale. For each exam CT number, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) at level of common carotid artery (CCA), internal carotid artery (ICA) and at level of Circle of Willis and Effective Dose (ED) were evaluated. 62 Group 1 patients underwent a clinically indicated DSA and results were compared with CTA. Results: No exams reported as not diagnostic. The overall mean CT number value of all arterial segments was above 450 HU in both groups. Significant lower noise, and higher SNR and CNR values were found in group 1 in comparison with group 2 despite the use of 80 kVp. In 62-group 1 patients studied by DSA, CTA showed in a segment-based analysis a sensitivity, negative predictive value and accuracy of 100%, 100% and 99% respectively. Mean ED in group 1 was 0.54±0.1 mSv with a dose reduction up to 86%. Conclusions: CTA for carotid arteries using latest IR algorithm allows to perform exams with submillisievert radiation exposure maintaining good image quality, overall evaluability and diagnostic accuracy.
关键词： atherosclerosis,Carotid arteries,Computed Tomography Angiography,Iterative reconstruction algorithm.,dose reduction
更新于2025-09-23 15:22:29
-
Caracterización y simulación de ruido en las imágenes de PET reconstruidas con OSEM: desarrollo de un método para la generación de imágenes sintéticas
摘要： Introduction: The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. Material and methods: The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. Results: The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. Conclusions: The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF.
关键词： PET,Autocorrelation function,OSEM,Iterative reconstruction,Noise power spectrum,Point spread function
更新于2025-09-23 15:22:29