Source reconstruction for bioluminescence tomography via L1∕2 regularization

Bioluminescence tomography (BLT) is an important noninvasive optical molecular imaging modality in preclinical research. To improve the image quality, reconstruction algorithms have to deal with the inherent ill-posedness of BLT inverse problem. The sparse characteristic of bioluminescent sources in spatial distribution has been widely explored in BLT and many L1-regularized methods have been investigated due to the sparsity-inducing properties of L1 norm. In this paper, we present a reconstruction method based on L[Formula: see text] regularization to enhance sparsity of BLT solution and solve the nonconvex L[Formula: see text] norm problem by converting it to a series of weighted L1 homotopy minimization problems with iteratively updated weights. To assess the performance of the proposed reconstruction algorithm, simulations on a heterogeneous mouse model are designed to compare it with three representative sparse reconstruction algorithms, including the weighted interior-point, L1 homotopy, and the Stagewise Orthogonal Matching Pursuit algorithm. Simulation results show that the proposed method yield stable reconstruction results under different noise levels. Quantitative comparison results demonstrate that the proposed algorithm outperforms the competitor algorithms in location accuracy, multiple-source resolving and image quality.

Download Full-text

Image reconstruction algorithm based on variable atomic number matching pursuit

Journal of Algorithms & Computational Technology ◽

10.1177/1748301816673074 ◽

2016 ◽

Vol 11 (2) ◽

pp. 103-109

Author(s):

Hongtu Zhao ◽

Chong Chen ◽

Chenxu Shi

Keyword(s):

Image Reconstruction ◽

Convex Optimization ◽

Atomic Number ◽

Matching Pursuit ◽

Greedy Algorithms ◽

Optimization Algorithms ◽

Reconstruction Algorithm ◽

Reconstruction Algorithms ◽

Reconstruction Quality ◽

Stable Reconstruction

As the most critical part of compressive sensing theory, reconstruction algorithm has an impact on the quality and speed of image reconstruction. After studying some existing convex optimization algorithms and greedy algorithms, we find that convex optimization algorithms should possess higher complexity to achieve higher reconstruction quality. Also, fixed atomic numbers used in most greedy algorithms increase the complexity of reconstruction. In this context, we propose a novel algorithm, called variable atomic number matching pursuit, which can improve the accuracy and speed of reconstruction. Simulation results show that variable atomic number matching pursuit is a fast and stable reconstruction algorithm and better than the other reconstruction algorithms under the same conditions.

Download Full-text

Selection Criteria for Determination of Optimal Reconstruction Method for Cu-64 Trastuzumab Dosimetry on Siemens Inveon PET Scanner

Journal of Clinical Medicine ◽

10.3390/jcm8040512 ◽

2019 ◽

Vol 8 (4) ◽

pp. 512 ◽

Cited By ~ 2

Author(s):

Seonhwa Lee ◽

Hyeongi Kim ◽

Ye-rin Kang ◽

Hyungwoo Kim ◽

Jung Young Kim ◽

...

Keyword(s):

Effective Dose ◽

Selection Criteria ◽

Absorbed Dose ◽

Reconstruction Algorithm ◽

Reconstruction Method ◽

Reconstruction Algorithms ◽

Recovery Coefficient ◽

Optimal Reconstruction ◽

Iteration Number

The goal of this study was to suggest criteria for the determination of the optimal image reconstruction algorithm for image-based dosimetry of Cu-64 trastuzumab PET in a mouse model. Image qualities, such as recovery coefficient (RC), spill-over ratio (SOR), and non-uniformity (NU), were measured according to National Electrical Manufacturers Association (NEMA) NU4-2008. Mice bearing a subcutaneous tumor ( 200 mm 3 , HER2 NCI N87) were injected with monoclonal antibodies (trastuzumab) with Cu-64. Preclinical mouse PET images were acquired at 4 time points after injection (2, 15, 40 and 64 h). Phantom and Cu-64 trastuzumab PET images were reconstructed using various reconstruction algorithms (filtered back projection (FBP), 3D reprojection algorithm (FBP-3DRP), 2D ordered subset expectation maximization (OSEM 2D), and OSEM 3D maximum a posteriori (OSEM3D-MAP)) and filters. The absorbed dose for the tumor and the effective dose for organs for Cu-64 trastuzumab PET were calculated using the OLINDA/EXM program with various reconstruction algorithms. Absorbed dose for the tumor ranged from 923 mGy/MBq to 1830 mGy/MBq with application of reconstruction algorithms and filters. When OSEM2D was used, the effective osteogenic dose increased from 0.0031 to 0.0245 with an increase in the iteration number (1 to 10). In the region of kidney, the effective dose increased from 0.1870 to 1.4100 when OSEM2D was used with iteration number 1 to 10. To determine the optimal reconstruction algorithms and filters, a correlation between RC and NU was plotted and selection criteria (0.9 < RC < 1.0 and < 10% of NU) were suggested. According to the selection criteria, OSEM2D (iteration 1) was chosen for the optimal reconstruction algorithm. OSEM2D (iteration 10) provided 154.7% overestimated effective dose and FBP with a Butterworth filter provided 20.9% underestimated effective dose. We suggested OSEM2D (iteration 1) for the calculation of the effective dose of Cu-64 trastuzumab on an Inveon PET scanner.

Download Full-text

Improved Reconstruction Quality of Bioluminescent Images by Combining SP3Equations and Bregman Iteration Method

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/767296 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Qiang Wu ◽

Jinchao Feng ◽

Kebin Jia ◽

Xiangyu Wang

Keyword(s):

Drug Development ◽

Iteration Method ◽

Tumor Therapy ◽

Reconstruction Algorithm ◽

Reconstruction Algorithms ◽

Bregman Iteration ◽

Bioluminescence Tomography ◽

Practical Applications ◽

Reconstruction Quality

Bioluminescence tomography (BLT) has a great potential to provide a powerful tool for tumor detection, monitoring tumor therapy progress, and drug development; developing new reconstruction algorithms will advance the technique to practical applications. In the paper, we propose a BLT reconstruction algorithm by combining SP3equations and Bregman iteration method to improve the quality of reconstructed sources. The numerical results for homogeneous and heterogeneous phantoms are very encouraging and give significant improvement over the algorithms without the use of SP3equations and Bregman iteration method.

Download Full-text

Sparse Reconstruction for Bioluminescence Tomography Based on the Semigreedy Method

Computational and Mathematical Methods in Medicine ◽

10.1155/2012/494808 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Wei Guo ◽

Kebin Jia ◽

Qian Zhang ◽

Xueyan Liu ◽

Jinchao Feng ◽

...

Keyword(s):

Imaging Modality ◽

Source Region ◽

Computational Cost ◽

Reconstruction Algorithm ◽

Search Tree ◽

Whole Body ◽

Penalty Term ◽

Bioluminescence Tomography ◽

Stable Source

Bioluminescence tomography (BLT) is a molecular imaging modality which can three-dimensionally resolve the molecular processes in small animalsin vivo. The ill-posedness nature of BLT problem makes its reconstruction bears nonunique solution and is sensitive to noise. In this paper, we proposed a sparse BLT reconstruction algorithm based on semigreedy method. To reduce the ill-posedness and computational cost, the optimal permissible source region was automatically chosen by using an iterative search tree. The proposed method obtained fast and stable source reconstruction from the whole body and imposed constraint without using a regularization penalty term. Numerical simulations on a mouse atlas, andin vivomouse experiments were conducted to validate the effectiveness and potential of the method.

Download Full-text

A new route for the interpretationof reconstructed wavefunctions in HRTEM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100171444 ◽

1994 ◽

Vol 52 ◽

pp. 742-743

Author(s):

M. Op de Beeck ◽

D. Van Dyck ◽

W. Coene

Keyword(s):

Reconstruction Algorithm ◽

Real Space ◽

Reconstruction Method ◽

Reconstruction Algorithms ◽

Axis Orientation ◽

Dynamical Diffraction ◽

Column Structure ◽

Structure Reconstruction ◽

Focus Variation ◽

Electron Wavefunction

During the last years the renewed interest in focus variation wavefunction reconstruction algorithms has lead to a spectacular improvement of the obtainable resolution in FEG-HRTEM. Unfortunately, it was found that only for thin specimens the reconstructed wavefunction is directly interpretable in terms of the projected atomic potential. Hence there is a need for a direct structure reconstruction algorithm, starting from the reconstructed electron wavefunction. Here we propose a new channelling method in real space that only relies on the very basic concepts of dynamical diffraction in zone axis orientation, and which is very suitable to reveal the correspondence between the wavefunction and the column structure. In this way, a parametrised analytical expression can be obtained so as to reconstruct the projected structure of the object, requiring minimal prior knowledge.In order to develop a sensible structure reconstruction method, a good understanding of the multiple dynamical diffraction process is required.

Download Full-text

Implementation and Performance Assessment of Biomedical Image Compression and Reconstruction Algorithms for Telemedicine Applications

Medical Data Security for Bioengineers - Advances in Bioinformatics and Biomedical Engineering ◽

10.4018/978-1-5225-7952-6.ch003 ◽

2019 ◽

pp. 52-80

Author(s):

Charu Bhardwaj ◽

Urvashi Sharma ◽

Shruti Jain ◽

Meenakshi Sood

Keyword(s):

Compressive Sensing ◽

Performance Metrics ◽

Matching Pursuit ◽

Similarity Index ◽

Structural Similarity ◽

Least Square ◽

Reconstruction Method ◽

Reconstruction Algorithms ◽

Biomedical Image ◽

And Performance

Compression serves as a significant feature for efficient storage and transmission of medical, satellite, and natural images. Transmission speed is a key challenge in transmitting a large amount of data especially for magnetic resonance imaging and computed tomography scan images. Compressive sensing is an optimization-based option to acquire sparse signal using sub-Nyquist criteria exploiting only the signal of interest. This chapter explores compressive sensing for correct sensing, acquisition, and reconstruction of clinical images. In this chapter, distinctive overall performance metrics like peak signal to noise ratio, root mean square error, structural similarity index, compression ratio, etc. are assessed for medical image evaluation by utilizing best three reconstruction algorithms: basic pursuit, least square, and orthogonal matching pursuit. Basic pursuit establishes a well-renowned reconstruction method among the examined recovery techniques. At distinct measurement samples, on increasing the number of measurement samples, PSNR increases significantly and RMSE decreases.

Download Full-text

A novel reconstruction tool (syngo DynaCT Head Clear) in the post-processing of DynaCT images to reduce artefacts and improve image quality

Journal of NeuroInterventional Surgery ◽

10.1136/neurintsurg-2015-012128 ◽

2016 ◽

Vol 8 (12) ◽

pp. 1268-1272 ◽

Cited By ~ 1

Author(s):

Stephanie Lescher ◽

Christina Reh ◽

Maya Christina Hoelter ◽

Katja Czeppan ◽

Luciana Porto ◽

...

Keyword(s):

Image Quality ◽

Comparative Evaluation ◽

Reconstruction Algorithm ◽

Field Of View ◽

Reconstruction Algorithms ◽

Point Scale ◽

Flat Detector ◽

Improve Image Quality ◽

Standard Algorithm ◽

Advanced Algorithm

BackgroundLatest generations of flat detector (FD) neuroangiography systems are able to obtain CT-like images of the brain parenchyma. Owing to the geometry of the C-arm system, cone beam artifacts are common and reduce image quality, especially at the periphery of the field of view. An advanced reconstruction algorithm (syngo DynaCT Head Clear) tackles these artifacts by using a modified interpolation-based 3D correction algorithm to improve image quality.Materials and methodsEleven volumetric datasets from FD-CT scans were reconstructed with the standard algorithm as well as with the advanced algorithm. In a two-step data analysis process, two reviewers compared dedicated regions of the skull and brain in both reconstruction modes using a 5-point scale (1, much better; 5, much worse; advanced vs standard algorithm). Both reviewers were blinded to the reconstruction mode. In a second step, two additional observers independently evaluated image quality of the 3D data (non-comparative evaluation) in dedicated regions also using a 5-point scale (1, not diagnostically evaluable; 5, good quality, perfectly usable for diagnosis) for both reconstruction algorithms.ResultsBoth in the comparative evaluation of dedicated brain regions and in the independent analysis of the FD-CT datasets the observers rated a better image quality if the advanced algorithm was used. The improvement in image quality was statistically significant at both the supraganglionic (p=0.018) and the infratentorial (p=0.002) levels.ConclusionsThe advanced reconstruction algorithm reduces typical artifacts in FD-CT images and improves image quality at the periphery of the field of view.

Download Full-text

The Role of Spiral CT Pulmonary Angiography in the Diagnosis of Postoperative Complications in Patients with Acute Pulmonary Embolism

Journal of Medical Imaging and Health Informatics ◽

10.1166/jmihi.2020.3144 ◽

2020 ◽

Vol 10 (9) ◽

pp. 2118-2123

Author(s):

Yong Xie ◽

Shushu Zhang

Keyword(s):

Image Quality ◽

Background Noise ◽

Reconstruction Algorithm ◽

Spiral Ct ◽

Reconstruction Algorithms ◽

Tube Voltage ◽

Dose Length Product ◽

The Difference ◽

Acute Pe ◽

Ct Volume

The purpose is to explore the effect of iterative model reconstruction (IMR) algorithm on improving quality of spiral computed tomography angiography (SCTA) image and its clinical application in the diagnosis of acute pulmonary embolism (PE) complications. 88 patients with acute PE who visited Chongqing Zhongxian People’s Hospital hospital from October 2017 to October 2019 were selected as the study objects, and their CT values, standard deviation (SD) value of background noise, CT volume dose index, and dose length product of pulmonary artery trunk and the erector spines of the spinal column were measured by spiral CT scanning at the tube voltage of 80 kv and 100 kv, respectively. As for image reconstruction, IMR, IDose4 algorithm in hybrid iterative reconstruction (HIR) and Filtering back-projection (FBP) were utilized. By comparing signal-noise ratio (SNR), contrast-noise ratio (CNR) and figure of merit (FOM), the image quality, radiation dose, sensitivity and specificity of different reconstruction algorithms in diagnosis of acute PE were analyzed. The results showed that the background noise of the IMR reconstruction algorithm was lower than that of IDose4 and FBP, and the difference was statistically significant (P < 0.05). The CT value of IMR reconstruction algorithm was significantly higher than that of IDose4 and FBP reconstruction algorithm, and the difference was not statistically significant (P > 0.05). The SNR and CNR of IMR were significantly higher than those of IDose4 and FBP, and the difference was statistically significant (P < 0.05). The FOM values of IMR were significantly higher than those of IDose4 and FBP, and the differences were statistically significant (P < 0.05). CT volume dose index, dose length product, and effective dose of the 80 kv tube voltage group were all lower than that of the 100 kv tube voltage group, accounting for 49.34%, 50.50%, and 52.53% of the 100 kv tube voltage group. And the FOM of 80 kv tube voltage group was higher than that of 100 kv tube voltage group. The sensitivity and specificity of IMR reconstructed images in diagnosis of acute PE complications were higher than those of reconstructed images of IDose4 and FBP, which were 97.67% and 92.0%, respectively. Therefore, the improved SCTA information technology based on the IMR algorithm has better image quality than the IDose4 and FBP reconstruction algorithms, and the image quality index of low-dose scan (80 kv) of the improved SCTA information technology based on the IMR algorithm is higher than that of normal-dose scan (100 kv).

Download Full-text

The Sparsity Adaptive Reconstruction Algorithm Based on Simulated Annealing for Compressed Sensing

Journal of Electrical and Computer Engineering ◽

10.1155/2019/6950819 ◽

2019 ◽

Vol 2019 ◽

pp. 1-8

Author(s):

Yangyang Li ◽

Jianping Zhang ◽

Guiling Sun ◽

Dongxue Lu

Keyword(s):

Simulated Annealing ◽

Simulated Annealing Algorithm ◽

Matching Pursuit ◽

Optimal Solution ◽

Sparse Reconstruction ◽

Reconstruction Method ◽

Reconstruction Algorithms ◽

Adaptive Simulated Annealing ◽

Annealing Algorithm ◽

Adaptive Simulated Annealing Algorithm

This paper proposes a novel sparsity adaptive simulated annealing algorithm to solve the issue of sparse recovery. This algorithm combines the advantage of the sparsity adaptive matching pursuit (SAMP) algorithm and the simulated annealing method in global searching for the recovery of the sparse signal. First, we calculate the sparsity and the initial support collection as the initial search points of the proposed optimization algorithm by using the idea of SAMP. Then, we design a two-cycle reconstruction method to find the support sets efficiently and accurately by updating the optimization direction. Finally, we take advantage of the sparsity adaptive simulated annealing algorithm in global optimization to guide the sparse reconstruction. The proposed sparsity adaptive greedy pursuit model has a simple geometric structure, it can get the global optimal solution, and it is better than the greedy algorithm in terms of recovery quality. Our experimental results validate that the proposed algorithm outperforms existing state-of-the-art sparse reconstruction algorithms.

Download Full-text

Impact of metal implants on xSPECT/CT Bone reconstruction: the “shining metal artefact”

European Journal of Hybrid Imaging ◽

10.1186/s41824-020-00087-7 ◽

2020 ◽

Vol 4 (1) ◽

Author(s):

Thiago V. M. Lima ◽

Ujwal Bhure ◽

Maria de Sol Pérez Lago ◽

Yannick Thali ◽

Savo Matijasevic ◽

...

Keyword(s):

Image Quality ◽

New Technology ◽

Reconstruction Algorithm ◽

Tracer Uptake ◽

Bone Reconstruction ◽

Reconstruction Algorithms ◽

Metal Implants ◽

Metal Artefacts ◽

Metal Artefact ◽

Xspect Bone

Abstract Background Novel reconstruction algorithms, such as xSPECT Bone, are gaining more and more importance in Nuclear Medicine. With xSPECT Bone, the reconstructed emission image is enhanced by the information obtained in the corresponding CT image. The CT defines tissue classes according to the Hounsfield units. In the iterative reconstruction, each tissue class is handled separately in the forward projection step, and all together in the back projection step. As a consequence, xSPECT Bone reconstruction generates images with improved boundary delineation and better anatomic representation of tracer activity. Applying this technique, however, showed that artefacts may occur, when no uptake regions, like metal implants, exhibit fictitious uniform tracer uptake. Due to limitations in spatial resolution in gamma cameras, the xSPECT Bone reconstructed image resulted in spill-out activity from surrounding high uptake region being uniformly distributed over the metal implants. This new technology of xSPECT Bone reconstruction in general enhances the image quality of SPECT/CT; however, the potential introduction of specific artefacts which inadvertently come along with this new technology and their frequency have not yet been addressed in the literature. Therefore, the purpose of this work was to identify and characterize these specific metal artefacts (the so-called shining metal artefact) in order to reduce false positives and avoid potentially misdiagnosing loosened or infected implants. Case presentation In this work, we report five cases imaged with bone SPECT/CT of 5 anatomical regions (foot, elbow, spine, shoulder, ribs and knee). All cases demonstrated “shining metal artefacts” in xSPECT Bone reconstruction. Conclusion While xSPECT Bone reconstruction algorithm significantly improves image quality for the diagnosis of bone and joint disorders with SPECT/CT, specific “shining metal artefacts” caused by the xSPECT Bone have to be recognized in order to avoid image misinterpretation suggesting metallic implant loosening or possible infection. The simultaneous analysis of conventionally reconstructed SPECT images (for Siemens the Flash3D reconstruction) helps to avoid misinterpretation of potential artefacts introduced by xSPECT Bone reconstruction.

Download Full-text