Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images
Lavoie, Benjamin R.; Okoniewski, Michal; Fear, Elise C.
2016-01-01
We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range. PMID:27611785
Jørgensen, Jakob H; Pan, Xiaochuan
2011-01-01
Breast X-ray CT imaging is being considered in screening as an extension to mammography. As a large fraction of the population will be exposed to radiation, low-dose imaging is essential. Iterative image reconstruction based on solving an optimization problem, such as Total-Variation minimization, shows potential for reconstruction from sparse-view data. For iterative methods it is important to ensure convergence to an accurate solution, since important image features, such as presence of microcalcifications indicating breast cancer, may not be visible in a non-converged reconstruction, and this can have clinical significance. To prevent excessively long computational times, which is a practical concern for the large image arrays in CT, it is desirable to keep the number of iterations low, while still ensuring a sufficiently accurate reconstruction for the specific imaging task. This motivates the study of accurate convergence criteria for iterative image reconstruction. In simulation studies with a realistic...
DEFF Research Database (Denmark)
Jørgensen, Jakob Heide; Sidky, Emil Y.; Pan, Xiaochuan
2011-01-01
, shows potential for reconstruction from sparse-view data. For iterative methods it is important to ensure convergence to an accurate solution, since important diagnostic image features, such as presence of microcalcifications indicating breast cancer, may not be visible in a non-converged reconstruction......, and this can have clinical significance. To prevent excessively long computational times, which is a practical concern for the large image arrays in CT, it is desirable to keep the number of iterations low, while still ensuring a sufficiently accurate reconstruction for the specific imaging task....... This motivates the study of accurate convergence criteria for iterative image reconstruction. In simulation studies with a realistic breast phantom with microcalcifications we investigate the issue of ensuring sufficiently converged solution for reliable reconstruction. Our results show that it can...
In Situ Casting and Imaging of the Rat Airway Tree for Accurate 3D Reconstruction
Jacob, Richard E.; Colby, Sean M.; Kabilan, Senthil; Einstein, Daniel R.; Carson, James P.
2014-01-01
The use of anatomically accurate, animal-specific airway geometries is important for understanding and modeling the physiology of the respiratory system. One approach for acquiring detailed airway architecture is to create a bronchial cast of the conducting airways. However, typical casting procedures either do not faithfully preserve the in vivo branching angles or produce rigid casts that when removed for imaging are fragile and thus easily damaged. We address these problems by creating an in situ bronchial cast of the conducting airways in rats that can be subsequently imaged in situ using 3D micro-CT imaging. We also demonstrate that deformations in airway branch angles resulting from the casting procedure are small, and that these angle deformations can be reversed through an interactive adjustment of the segmented cast geometry. Animal work was approved by the Institutional Animal Care and Use Committee of Pacific Northwest National Laboratory. PMID:23786464
Giannoglou, George D.; Chatzizisis, Yiannis S.; Sianos, George; Tsikaderis, Dimitrios; Matakos, Antonis; Koutkias, Vassilios; Diamantopoulos, Panagiotis; Maglaveras, Nicos; Parcharidis, George E.; Louridas, George E.
2006-12-01
In conventional intravascular ultrasound (IVUS)-based three-dimensional (3D) reconstruction of human coronary arteries, IVUS images are arranged linearly generating a straight vessel volume. However, with this approach real vessel curvature is neglected. To overcome this limitation an imaging method was developed based on integration of IVUS and biplane coronary angiography (BCA). In 17 coronary arteries from nine patients, IVUS and BCA were performed. From each angiographic projection, a single end-diastolic frame was selected and in each frame the IVUS catheter was interactively detected for the extraction of 3D catheter path. Ultrasound data was obtained with a sheath-based catheter and recorded on S-VHS videotape. S-VHS data was digitized and lumen and media-adventitia contours were semi-automatically detected in end-diastolic IVUS images. Each pair of contours was aligned perpendicularly to the catheter path and rotated in space by implementing an algorithm based on Frenet-Serret rules. Lumen and media-adventitia contours were interpolated through generation of intermediate contours creating a real 3D lumen and vessel volume, respectively. The absolute orientation of the reconstructed lumen was determined by back-projecting it onto both angiographic planes and comparing the projected lumen with the actual angiographic lumen. In conclusion, our method is capable of performing rapid and accurate 3D reconstruction of human coronary arteries in vivo. This technique can be utilized for reliable plaque morphometric, geometrical and hemodynamic analyses.
Use of a ray-based reconstruction algorithm to accurately quantify preclinical microSPECT images
Bert Vandeghinste; Roel Van Holen; Christian Vanhove; Filip De Vos; Stefaan Vandenberghe; Steven Staelens
2014-01-01
This work aimed to measure the in vivo quantification errors obtained when ray-based iterative reconstruction is used in micro-singlephoton emission computed tomography (SPECT). This was investigated with an extensive phantom-based evaluation and two typical in vivo studies using (99m) Tc and In-111, measured on a commercially available cadmium zinc telluride (CZT)-based small-animal scanner. Iterative reconstruction was implemented on the GPU using ray tracing, including (1) scatter correcti...
Use of a ray-based reconstruction algorithm to accurately quantify preclinical microSPECT images.
Vandeghinste, Bert; Van Holen, Roel; Vanhove, Christian; De Vos, Filip; Vandenberghe, Stefaan; Staelens, Steven
2014-01-01
This work aimed to measure the in vivo quantification errors obtained when ray-based iterative reconstruction is used in micro-single-photon emission computed tomography (SPECT). This was investigated with an extensive phantom-based evaluation and two typical in vivo studies using 99mTc and 111In, measured on a commercially available cadmium zinc telluride (CZT)-based small-animal scanner. Iterative reconstruction was implemented on the GPU using ray tracing, including (1) scatter correction, (2) computed tomography-based attenuation correction, (3) resolution recovery, and (4) edge-preserving smoothing. It was validated using a National Electrical Manufacturers Association (NEMA) phantom. The in vivo quantification error was determined for two radiotracers: [99mTc]DMSA in naive mice (n = 10 kidneys) and [111In]octreotide in mice (n = 6) inoculated with a xenograft neuroendocrine tumor (NCI-H727). The measured energy resolution is 5.3% for 140.51 keV (99mTc), 4.8% for 171.30 keV, and 3.3% for 245.39 keV (111In). For 99mTc, an uncorrected quantification error of 28 ± 3% is reduced to 8 ± 3%. For 111In, the error reduces from 26 ± 14% to 6 ± 22%. The in vivo error obtained with 99mTc-dimercaptosuccinic acid ([99mTc]DMSA) is reduced from 16.2 ± 2.8% to -0.3 ± 2.1% and from 16.7 ± 10.1% to 2.2 ± 10.6% with [111In]octreotide. Absolute quantitative in vivo SPECT is possible without explicit system matrix measurements. An absolute in vivo quantification error smaller than 5% was achieved and exemplified for both [99mTc]DMSA and [111In]octreotide.
Use of a Ray-Based Reconstruction Algorithm to Accurately Quantify Preclinical MicroSPECT Images
Directory of Open Access Journals (Sweden)
Bert Vandeghinste
2014-06-01
Full Text Available This work aimed to measure the in vivo quantification errors obtained when ray-based iterative reconstruction is used in micro-single-photon emission computed tomography (SPECT. This was investigated with an extensive phantom-based evaluation and two typical in vivo studies using 99mTc and 111In, measured on a commercially available cadmium zinc telluride (CZT-based small-animal scanner. Iterative reconstruction was implemented on the GPU using ray tracing, including (1 scatter correction, (2 computed tomography-based attenuation correction, (3 resolution recovery, and (4 edge-preserving smoothing. It was validated using a National Electrical Manufacturers Association (NEMA phantom. The in vivo quantification error was determined for two radiotracers: [99mTc]DMSA in naive mice (n = 10 kidneys and [111In]octreotide in mice (n = 6 inoculated with a xenograft neuroendocrine tumor (NCI-H727. The measured energy resolution is 5.3% for 140.51 keV (99mTc, 4.8% for 171.30 keV, and 3.3% for 245.39 keV (111In. For 99mTc, an uncorrected quantification error of 28 ± 3% is reduced to 8 ± 3%. For 111In, the error reduces from 26 ± 14% to 6 ± 22%. The in vivo error obtained with “mTc-dimercaptosuccinic acid ([99mTc]DMSA is reduced from 16.2 ± 2.8% to −0.3 ± 2.1% and from 16.7 ± 10.1% to 2.2 ± 10.6% with [111In]octreotide. Absolute quantitative in vivo SPECT is possible without explicit system matrix measurements. An absolute in vivo quantification error smaller than 5% was achieved and exemplified for both [”mTc]DMSA and [111In]octreotide.
Hui-Hui, Xia; Rui-Feng, Kan; Jian-Guo, Liu; Zhen-Yu, Xu; Ya-Bai, He
2016-06-01
An improved algebraic reconstruction technique (ART) combined with tunable diode laser absorption spectroscopy(TDLAS) is presented in this paper for determining two-dimensional (2D) distribution of H2O concentration and temperature in a simulated combustion flame. This work aims to simulate the reconstruction of spectroscopic measurements by a multi-view parallel-beam scanning geometry and analyze the effects of projection rays on reconstruction accuracy. It finally proves that reconstruction quality dramatically increases with the number of projection rays increasing until more than 180 for 20 × 20 grid, and after that point, the number of projection rays has little influence on reconstruction accuracy. It is clear that the temperature reconstruction results are more accurate than the water vapor concentration obtained by the traditional concentration calculation method. In the present study an innovative way to reduce the error of concentration reconstruction and improve the reconstruction quality greatly is also proposed, and the capability of this new method is evaluated by using appropriate assessment parameters. By using this new approach, not only the concentration reconstruction accuracy is greatly improved, but also a suitable parallel-beam arrangement is put forward for high reconstruction accuracy and simplicity of experimental validation. Finally, a bimodal structure of the combustion region is assumed to demonstrate the robustness and universality of the proposed method. Numerical investigation indicates that the proposed TDLAS tomographic algorithm is capable of detecting accurate temperature and concentration profiles. This feasible formula for reconstruction research is expected to resolve several key issues in practical combustion devices. Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61205151), the National Key Scientific Instrument and Equipment Development Project of China (Grant
Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT
Sidky, Emil Y; Pan, Xiaochuan
2009-01-01
In practical applications of tomographic imaging, there are often challenges for image reconstruction due to under-sampling and insufficient data. In computed tomography (CT), for example, image reconstruction from few views would enable rapid scanning with a reduced x-ray dose delivered to the patient. Limited-angle problems are also of practical significance in CT. In this work, we develop and investigate an iterative image reconstruction algorithm based on the minimization of the image total variation (TV) that applies to divergent-beam CT. Numerical demonstrations of our TV algorithm are performed with various insufficient data problems in fan-beam CT. The TV algorithm can be generalized to cone-beam CT as well as other tomographic imaging modalities.
Speed-of-sound compensated photoacoustic tomography for accurate imaging
Jose, Jithin; Steenbergen, Wiendelt; Slump, Cornelis H; van Leeuwen, Ton G; Manohar, Srirang
2012-01-01
In most photoacoustic (PA) measurements, variations in speed-of-sound (SOS) of the subject are neglected under the assumption of acoustic homogeneity. Biological tissue with spatially heterogeneous SOS cannot be accurately reconstructed under this assumption. We present experimental and image reconstruction methods with which 2-D SOS distributions can be accurately acquired and reconstructed, and with which the SOS map can be used subsequently to reconstruct highly accurate PA tomograms. We begin with a 2-D iterative reconstruction approach in an ultrasound transmission tomography (UTT) setting, which uses ray refracted paths instead of straight ray paths to recover accurate SOS images of the subject. Subsequently, we use the SOS distribution in a new 2-D iterative approach, where refraction of rays originating from PA sources are accounted for in accurately retrieving the distribution of these sources. Both the SOS reconstruction and SOS-compensated PA reconstruction methods utilize the Eikonal equation to m...
Augmented Likelihood Image Reconstruction.
Stille, Maik; Kleine, Matthias; Hägele, Julian; Barkhausen, Jörg; Buzug, Thorsten M
2016-01-01
The presence of high-density objects remains an open problem in medical CT imaging. Data of projections passing through objects of high density, such as metal implants, are dominated by noise and are highly affected by beam hardening and scatter. Reconstructed images become less diagnostically conclusive because of pronounced artifacts that manifest as dark and bright streaks. A new reconstruction algorithm is proposed with the aim to reduce these artifacts by incorporating information about shape and known attenuation coefficients of a metal implant. Image reconstruction is considered as a variational optimization problem. The afore-mentioned prior knowledge is introduced in terms of equality constraints. An augmented Lagrangian approach is adapted in order to minimize the associated log-likelihood function for transmission CT. During iterations, temporally appearing artifacts are reduced with a bilateral filter and new projection values are calculated, which are used later on for the reconstruction. A detailed evaluation in cooperation with radiologists is performed on software and hardware phantoms, as well as on clinically relevant patient data of subjects with various metal implants. Results show that the proposed reconstruction algorithm is able to outperform contemporary metal artifact reduction methods such as normalized metal artifact reduction.
Consistent Reconstruction of Cortical Surfaces from Longitudinal Brain MR Images
Li, Gang; Nie, Jingxin; Shen, Dinggang
2011-01-01
Accurate and consistent reconstruction of cortical surfaces from longitudinal human brain MR images is of great importance in studying subtle morphological changes of the cerebral cortex. This paper presents a new deformable surface method for consistent and accurate reconstruction of inner, central and outer cortical surfaces from longitudinal MR images. Specifically, the cortical surfaces of the group-mean image of all aligned longitudinal images of the same subject are first reconstructed ...
IMAGE RECONSTRUCTION AND OBJECT CLASSIFICATION IN CT IMAGING SYSTEM
Institute of Scientific and Technical Information of China (English)
张晓明; 蒋大真; 等
1995-01-01
By obtaining a feasible filter function,reconstructed images can be got with linear interpolation and filtered backoprojection techniques.Considering the gray and spatial correlation neighbour informations of each pixel,a new supervised classification method is put forward for the reconstructed images,and an experiment with noise image is done,the result shows that the method is feasible and accurate compared with ideal phantoms.
Exercises in PET Image Reconstruction
Nix, Oliver
These exercises are complementary to the theoretical lectures about positron emission tomography (PET) image reconstruction. They aim at providing some hands on experience in PET image reconstruction and focus on demonstrating the different data preprocessing steps and reconstruction algorithms needed to obtain high quality PET images. Normalisation, geometric-, attenuation- and scatter correction are introduced. To explain the necessity of those some basics about PET scanner hardware, data acquisition and organisation are reviewed. During the course the students use a software application based on the STIR (software for tomographic image reconstruction) library 1,2 which allows them to dynamically select or deselect corrections and reconstruction methods as well as to modify their most important parameters. Following the guided tutorial, the students get an impression on the effect the individual data precorrections have on image quality and what happens if they are forgotten. Several data sets in sinogram format are provided, such as line source data, Jaszczak phantom data sets with high and low statistics and NEMA whole body phantom data. The two most frequently used reconstruction algorithms in PET image reconstruction, filtered back projection (FBP) and the iterative OSEM (ordered subset expectation maximation) approach are used to reconstruct images. The exercise should help the students gaining an understanding what the reasons for inferior image quality and artefacts are and how to improve quality by a clever choice of reconstruction parameters.
Consistent Reconstruction of Cortical Surfaces from Longitudinal Brain MR Images
Li, Gang; Nie, Jingxin; Wu, Guorong; Wang, Yaping; Shen, Dinggang
2011-01-01
Accurate and consistent reconstruction of cortical surfaces from longitudinal human brain MR images is of great importance in studying longitudinal subtle change of the cerebral cortex. This paper presents a novel deformable surface method for consistent and accurate reconstruction of inner, central and outer cortical surfaces from longitudinal brain MR images. Specifically, the cortical surfaces of the group-mean image of all aligned longitudinal images of the same subject are first reconstr...
Image Interpolation Through Surface Reconstruction
Institute of Scientific and Technical Information of China (English)
ZHANG Ling; LI Xue-mei
2013-01-01
Reconstructing an HR (high-resolution) image which preserves the image intrinsic structures from its LR ( low-resolution) counterpart is highly challenging. This paper proposes a new surface reconstruction algorithm applied to image interpolation. The interpolation surface for the whole image is generated by putting all the quadratic polynomial patches together. In order to eliminate the jaggies of the edge, a new weight function containing edge information is incorporated into the patch reconstruction procedure as a constraint. Extensive experimental results demonstrate that our method produces better results across a wide range of scenes in terms of both quantitative evaluation and subjective visual quality.
Robust and accurate multi-view reconstruction by prioritized matching
DEFF Research Database (Denmark)
Ylimaki, Markus; Kannala, Juho; Holappa, Jukka;
2012-01-01
a prioritized matching method which expands the most promising seeds first. The output of the method is a three-dimensional point cloud. Unlike previous correspondence growing approaches our method allows to use the best-first matching principle in the generic multi-view stereo setting with arbitrary number...... of input images. Our experiments show that matching the most promising seeds first provides very robust point cloud reconstructions efficiently with just a single expansion step. A comparison to the current state-of-the-art shows that our method produces reconstructions of similar quality but significantly...
GLIMPSE: Accurate 3D weak lensing reconstructions using sparsity
Leonard, Adrienne; Starck, Jean-Luc
2013-01-01
We present GLIMPSE - Gravitational Lensing Inversion and MaPping with Sparse Estimators - a new algorithm to generate density reconstructions in three dimensions from photometric weak lensing measurements. This is an extension of earlier work in one dimension aimed at applying compressive sensing theory to the inversion of gravitational lensing measurements to recover 3D density maps. Using the assumption that the density can be represented sparsely in our chosen basis - 2D transverse wavelets and 1D line of sight dirac functions - we show that clusters of galaxies can be identified and accurately localised and characterised using this method. Throughout, we use simulated data consistent with the quality currently attainable in large surveys. We present a thorough statistical analysis of the errors and biases in both the redshifts of detected structures and their amplitudes. The GLIMPSE method is able to produce reconstructions at significantly higher resolution than the input data; in this paper we show reco...
Zhang, Shunli; Zhang, Dinghua; Gong, Hao; Ghasemalizadeh, Omid; Wang, Ge; Cao, Guohua
2014-11-01
Iterative algorithms, such as the algebraic reconstruction technique (ART), are popular for image reconstruction. For iterative reconstruction, the area integral model (AIM) is more accurate for better reconstruction quality than the line integral model (LIM). However, the computation of the system matrix for AIM is more complex and time-consuming than that for LIM. Here, we propose a fast and accurate method to compute the system matrix for AIM. First, we calculate the intersection of each boundary line of a narrow fan-beam with pixels in a recursive and efficient manner. Then, by grouping the beam-pixel intersection area into six types according to the slopes of the two boundary lines, we analytically compute the intersection area of the narrow fan-beam with the pixels in a simple algebraic fashion. Overall, experimental results show that our method is about three times faster than the Siddon algorithm and about two times faster than the distance-driven model (DDM) in computation of the system matrix. The reconstruction speed of our AIM-based ART is also faster than the LIM-based ART that uses the Siddon algorithm and DDM-based ART, for one iteration. The fast reconstruction speed of our method was accomplished without compromising the image quality.
Tomographic image reconstruction using training images
DEFF Research Database (Denmark)
Soltani, Sara; Andersen, Martin Skovgaard; Hansen, Per Christian
2017-01-01
We describe and examine an algorithm for tomographic image reconstruction where prior knowledge about the solution is available in the form of training images. We first construct a non-negative dictionary based on prototype elements from the training images; this problem is formulated within the ...
A fast and accurate algorithm for diploid individual haplotype reconstruction.
Wu, Jingli; Liang, Binbin
2013-08-01
Haplotypes can provide significant information in many research fields, including molecular biology and medical therapy. However, haplotyping is much more difficult than genotyping by using only biological techniques. With the development of sequencing technologies, it becomes possible to obtain haplotypes by combining sequence fragments. The haplotype reconstruction problem of diploid individual has received considerable attention in recent years. It assembles the two haplotypes for a chromosome given the collection of fragments coming from the two haplotypes. Fragment errors significantly increase the difficulty of the problem, and which has been shown to be NP-hard. In this paper, a fast and accurate algorithm, named FAHR, is proposed for haplotyping a single diploid individual. Algorithm FAHR reconstructs the SNP sites of a pair of haplotypes one after another. The SNP fragments that cover some SNP site are partitioned into two groups according to the alleles of the corresponding SNP site, and the SNP values of the pair of haplotypes are ascertained by using the fragments in the group that contains more SNP fragments. The experimental comparisons were conducted among the FAHR, the Fast Hare and the DGS algorithms by using the haplotypes on chromosome 1 of 60 individuals in CEPH samples, which were released by the International HapMap Project. Experimental results under different parameter settings indicate that the reconstruction rate of the FAHR algorithm is higher than those of the Fast Hare and the DGS algorithms, and the running time of the FAHR algorithm is shorter than those of the Fast Hare and the DGS algorithms. Moreover, the FAHR algorithm has high efficiency even for the reconstruction of long haplotypes and is very practical for realistic applications.
Spatially adaptive regularized iterative high-resolution image reconstruction algorithm
Lim, Won Bae; Park, Min K.; Kang, Moon Gi
2000-12-01
High resolution images are often required in applications such as remote sensing, frame freeze in video, military and medical imaging. Digital image sensor arrays, which are used for image acquisition in many imaging systems, are not dense enough to prevent aliasing, so the acquired images will be degraded by aliasing effects. To prevent aliasing without loss of resolution, a dense detector array is required. But it may be very costly or unavailable, thus, many imaging systems are designed to allow some level of aliasing during image acquisition. The purpose of our work is to reconstruct an unaliased high resolution image from the acquired aliased image sequence. In this paper, we propose a spatially adaptive regularized iterative high resolution image reconstruction algorithm for blurred, noisy and down-sampled image sequences. The proposed approach is based on a Constrained Least Squares (CLS) high resolution reconstruction algorithm, with spatially adaptive regularization operators and parameters. These regularization terms are shown to improve the reconstructed image quality by forcing smoothness, while preserving edges in the reconstructed high resolution image. Accurate sub-pixel motion registration is the key of the success of the high resolution image reconstruction algorithm. However, sub-pixel motion registration may have some level of registration error. Therefore, a reconstruction algorithm which is robust against the registration error is required. The registration algorithm uses a gradient based sub-pixel motion estimator which provides shift information for each of the recorded frames. The proposed algorithm is based on a technique of high resolution image reconstruction, and it solves spatially adaptive regularized constrained least square minimization functionals. In this paper, we show that the reconstruction algorithm gives dramatic improvements in the resolution of the reconstructed image and is effective in handling the aliased information. The
Image reconstruction techniques for high resolution human brain PET imaging
Energy Technology Data Exchange (ETDEWEB)
Comtat, C.; Bataille, F.; Sureau, F. [Service Hospitalier Frederic Joliot (CEA/DSV/DRM), 91 - Orsay (France)
2006-07-01
High resolution PET imaging is now a well established technique not only for small animal, but also for human brain studies. The ECAT HRRT brain PET scanner(Siemens Molecular Imaging) is characterized by an effective isotropic spatial resolution of 2.5 mm, about a factor of 2 better than for state-of-the-art whole-body clinical PET scanners. Although the absolute sensitivity of the HRRT (6.5 %) for point source in the center of the field-of-view is increased relative to whole-body scanner (typically 4.5 %) thanks to a larger co-polar aperture, the sensitivity in terms of volumetric resolution (75 (m{sup 3} at best for whole-body scanners and 16 (m{sup 3} for t he HRRT) is much lower. This constraint has an impact on the performance of image reconstruction techniques, in particular for dynamic studies. Standard reconstruction methods used with clinical whole-body PET scanners are not optimal for this application. Specific methods had to be developed, based on fully 3D iterative techniques. Different refinements can be added in the reconstruction process to improve image quality: more accurate modeling of the acquisition system, more accurate modeling of the statistical properties of the acquired data, anatomical side information to guide the reconstruction . We will present the performances these added developments for neuronal imaging in humans. (author)
Modern methods of image reconstruction.
Puetter, R. C.
The author reviews the image restoration or reconstruction problem in its general setting. He first discusses linear methods for solving the problem of image deconvolution, i.e. the case in which the data are a convolution of a point-spread function and an underlying unblurred image. Next, non-linear methods are introduced in the context of Bayesian estimation, including maximum likelihood and maximum entropy methods. Then, the author discusses the role of language and information theory concepts for data compression and solving the inverse problem. The concept of algorithmic information content (AIC) is introduced and is shown to be crucial to achieving optimal data compression and optimized Bayesian priors for image reconstruction. The dependence of the AIC on the selection of language then suggests how efficient coordinate systems for the inverse problem may be selected. The author also introduced pixon-based image restoration and reconstruction methods. The relation between image AIC and the Bayesian incarnation of Occam's Razor is discussed, as well as the relation of multiresolution pixon languages and image fractal dimension. Also discussed is the relation of pixons to the role played by the Heisenberg uncertainty principle in statistical physics and how pixon-based image reconstruction provides a natural extension to the Akaike information criterion for maximum likelihood. The author presents practical applications of pixon-based Bayesian estimation to the restoration of astronomical images. He discusses the effects of noise, effects of finite sampling on resolution, and special problems associated with spatially correlated noise introduced by mosaicing. Comparisons to other methods demonstrate the significant improvements afforded by pixon-based methods and illustrate the science that such performance improvements allow.
Computational Imaging for VLBI Image Reconstruction
Bouman, Katherine L; Zoran, Daniel; Fish, Vincent L; Doeleman, Sheperd S; Freeman, William T
2015-01-01
Very long baseline interferometry (VLBI) is a technique for imaging celestial radio emissions by simultaneously observing a source from telescopes distributed across Earth. The challenges in reconstructing images from fine angular resolution VLBI data are immense. The data is extremely sparse and noisy, thus requiring statistical image models such as those designed in the computer vision community. In this paper we present a novel Bayesian approach for VLBI image reconstruction. While other methods require careful tuning and parameter selection for different types of images, our method is robust and produces good results under different settings such as low SNR or extended emissions. The success of our method is demonstrated on realistic synthetic experiments as well as publicly available real data. We present this problem in a way that is accessible to members of the computer vision community, and provide a dataset website (vlbiimaging.csail.mit.edu) to allow for controlled comparisons across algorithms. Thi...
Accurately approximating algebraic tomographic reconstruction by filtered backprojection
Pelt, D.M.; Batenburg, K.J.; King, M.; Glick, S.; Mueller, K.
2015-01-01
In computed tomography, algebraic reconstruction methods tend to produce reconstructions with higher quality than analytical methods when presented with limited and noisy projection data. The high computational requirements of algebraic methods, however, limit their usefulness in
Towards an accurate volume reconstruction in atom probe tomography.
Beinke, Daniel; Oberdorfer, Christian; Schmitz, Guido
2016-06-01
An alternative concept for the reconstruction of atom probe data is outlined. It is based on the calculation of realistic trajectories of the evaporated ions in a recursive refinement process. To this end, the electrostatic problem is solved on a Delaunay tessellation. To enable the trajectory calculation, the order of reconstruction is inverted with respect to previous reconstruction schemes: the last atom detected is reconstructed first. In this way, the emitter shape, which controls the trajectory, can be defined throughout the duration of the reconstruction. A proof of concept is presented for 3D model tips, containing spherical precipitates or embedded layers of strongly contrasting evaporation thresholds. While the traditional method following Bas et al. generates serious distortions in these cases, a reconstruction with the proposed electrostatically informed approach improves the geometry of layers and particles significantly.
Method for position emission mammography image reconstruction
Smith, Mark Frederick
2004-10-12
An image reconstruction method comprising accepting coincidence datat from either a data file or in real time from a pair of detector heads, culling event data that is outside a desired energy range, optionally saving the desired data for each detector position or for each pair of detector pixels on the two detector heads, and then reconstructing the image either by backprojection image reconstruction or by iterative image reconstruction. In the backprojection image reconstruction mode, rays are traced between centers of lines of response (LOR's), counts are then either allocated by nearest pixel interpolation or allocated by an overlap method and then corrected for geometric effects and attenuation and the data file updated. If the iterative image reconstruction option is selected, one implementation is to compute a grid Siddon retracing, and to perform maximum likelihood expectation maiximization (MLEM) computed by either: a) tracing parallel rays between subpixels on opposite detector heads; or b) tracing rays between randomized endpoint locations on opposite detector heads.
Speed-of-sound compensated photoacoustic tomography for accurate imaging
Jose, J.; Willemink, G.H.; Steenbergen, W.; Leeuwen, van A.G.J.M.; Manohar, S.
2012-01-01
Purpose: In most photoacoustic (PA) tomographic reconstructions, variations in speed-of-sound (SOS) of the subject are neglected under the assumption of acoustic homogeneity. Biological tissue with spatially heterogeneous SOS cannot be accurately reconstructed under this assumption. The authors pres
Reconstruction Formulas for Photoacoustic Sectional Imaging
Elbau, Peter; Schulze, Rainer
2011-01-01
The literature on reconstruction formulas for photoacoustic tomography (PAT) is vast. The various reconstruction formulas differ by used measurement devices and geometry on which the data are sampled. In standard photoacoustic imaging (PAI), the object under investigation is illuminated uniformly. Recently, sectional photoacoustic imaging techniques, using focusing techniques for initializing and measuring the pressure along a plane, appeared in the literature. This paper surveys existing and provides novel exact reconstruction formulas for sectional photoacoustic imaging.
Reconstructing HST Images of Asteroids
Storrs, A. D.; Bank, S.; Gerhardt, H.; Makhoul, K.
2003-12-01
We present reconstructions of images of 22 large main belt asteroids that were observed by Hubble Space Telescope with the Wide-Field/Planetary cameras. All images were restored with the MISTRAL program (Mugnier, Fusco, and Conan 2003) at enhanced spatial resolution. This is possible thanks to the well-studied and stable point spread function (PSF) on HST. We present some modeling of this process and determine that the Strehl ratio for WF/PC (aberrated) images can be improved to 130 ratio of 80 We will report sizes, shapes, and albedos for these objects, as well as any surface features. Images taken with the WFPC-2 instrument were made in a variety of filters so that it should be possible to investigate changes in mineralogy across the surface of the larger asteroids in a manner similar to that done on 4 Vesta by Binzel et al. (1997). Of particular interest are a possible water of hydration feature on 1 Ceres, and the non-observation of a constriction or gap between the components of 216 Kleopatra. Reduction of this data was aided by grant HST-GO-08583.08A from the Space Telescope Science Institute. References: Mugnier, L.M., T. Fusco, and J.-M. Conan, 2003. JOSA A (submitted) Binzel, R.P., Gaffey, M.J., Thomas, P.C., Zellner, B.H., Storrs, A.D., and Wells, E.N. 1997. Icarus 128 pp. 95-103
Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.
Directory of Open Access Journals (Sweden)
Oscar Westesson
Full Text Available The Multiple Sequence Alignment (MSA is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history, it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.
Studies on image compression and image reconstruction
Sayood, Khalid; Nori, Sekhar; Araj, A.
1994-01-01
During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.
Sparse Image Reconstruction in Computed Tomography
DEFF Research Database (Denmark)
Jørgensen, Jakob Sauer
In recent years, increased focus on the potentially harmful effects of x-ray computed tomography (CT) scans, such as radiation-induced cancer, has motivated research on new low-dose imaging techniques. Sparse image reconstruction methods, as studied for instance in the field of compressed sensing...... and limitations of sparse reconstruction methods in CT, in particular in a quantitative sense. For example, relations between image properties such as contrast, structure and sparsity, tolerable noise levels, suficient sampling levels, the choice of sparse reconstruction formulation and the achievable image...
DCT and DST Based Image Compression for 3D Reconstruction
Siddeq, Mohammed M.; Rodrigues, Marcos A.
2017-03-01
This paper introduces a new method for 2D image compression whose quality is demonstrated through accurate 3D reconstruction using structured light techniques and 3D reconstruction from multiple viewpoints. The method is based on two discrete transforms: (1) A one-dimensional Discrete Cosine Transform (DCT) is applied to each row of the image. (2) The output from the previous step is transformed again by a one-dimensional Discrete Sine Transform (DST), which is applied to each column of data generating new sets of high-frequency components followed by quantization of the higher frequencies. The output is then divided into two parts where the low-frequency components are compressed by arithmetic coding and the high frequency ones by an efficient minimization encoding algorithm. At decompression stage, a binary search algorithm is used to recover the original high frequency components. The technique is demonstrated by compressing 2D images up to 99% compression ratio. The decompressed images, which include images with structured light patterns for 3D reconstruction and from multiple viewpoints, are of high perceptual quality yielding accurate 3D reconstruction. Perceptual assessment and objective quality of compression are compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results show that the proposed compression method is superior to both JPEG and JPEG2000 concerning 3D reconstruction, and with equivalent perceptual quality to JPEG2000.
Sheng, Qiwei; Matthews, Thomas P; Xia, Jun; Zhu, Liren; Wang, Lihong V; Anastasio, Mark A
2015-01-01
Photoacoustic computed tomography (PACT) is an emerging computed imaging modality that exploits optical contrast and ultrasonic detection principles to form images of the absorbed optical energy density within tissue. When the imaging system employs conventional piezoelectric ultrasonic transducers, the ideal photoacoustic (PA) signals are degraded by the transducers' acousto-electric impulse responses (EIRs) during the measurement process. If unaccounted for, this can degrade the accuracy of the reconstructed image. In principle, the effect of the EIRs on the measured PA signals can be ameliorated via deconvolution; images can be reconstructed subsequently by application of a reconstruction method that assumes an idealized EIR. Alternatively, the effect of the EIR can be incorporated into an imaging model and implicitly compensated for during reconstruction. In either case, the efficacy of the correction can be limited by errors in the assumed EIRs. In this work, a joint optimization approach to PACT image r...
IIR GRAPPA for parallel MR image reconstruction.
Chen, Zhaolin; Zhang, Jingxin; Yang, Ran; Kellman, Peter; Johnston, Leigh A; Egan, Gary F
2010-02-01
Accelerated parallel MRI has advantage in imaging speed, and its image quality has been improved continuously in recent years. This paper introduces a two-dimensional infinite impulse response model of inverse filter to replace the finite impulse response model currently used in generalized autocalibrating partially parallel acquisitions class image reconstruction methods. The infinite impulse response model better characterizes the correlation of k-space data points and better approximates the perfect inversion of parallel imaging process, resulting in a novel generalized image reconstruction method for accelerated parallel MRI. This k-space-based reconstruction method includes the conventional generalized autocalibrating partially parallel acquisitions class methods as special cases and has a new infinite impulse response data estimation mechanism for effective improvement of image quality. The experiments on in vivo MRI data show that the proposed method significantly reduces reconstruction errors compared with the conventional two-dimensional generalized autocalibrating partially parallel acquisitions method, particularly at the high acceleration rates.
Analytic image concept combined to SENSE reconstruction
Yankam Njiwa, J; Baltes, C.; Rudin, M.
2011-01-01
Two approaches of reconstructing undersampled partial k-space data, acquired with multiple coils are compared: homodyne detection combined with SENSE (HM_SENSE) and analytic image reconstruction combined with SENSE (AI_SENSE). The latter overcomes limitations of HM_ SENSE by considering aliased images as analytic thus avoiding the need for phase correction required for HM_SENSE. MATERIALS AND METHODS: In vivo imaging experiments were carried out in male Lewis rats using both gradient echo...
Quantitative photoacoustic image reconstruction improves accuracy in deep tissue structures.
Mastanduno, Michael A; Gambhir, Sanjiv S
2016-10-01
Photoacoustic imaging (PAI) is emerging as a potentially powerful imaging tool with multiple applications. Image reconstruction for PAI has been relatively limited because of limited or no modeling of light delivery to deep tissues. This work demonstrates a numerical approach to quantitative photoacoustic image reconstruction that minimizes depth and spectrally derived artifacts. We present the first time-domain quantitative photoacoustic image reconstruction algorithm that models optical sources through acoustic data to create quantitative images of absorption coefficients. We demonstrate quantitative accuracy of less than 5% error in large 3 cm diameter 2D geometries with multiple targets and within 22% error in the largest size quantitative photoacoustic studies to date (6cm diameter). We extend the algorithm to spectral data, reconstructing 6 varying chromophores to within 17% of the true values. This quantitiative PA tomography method was able to improve considerably on filtered-back projection from the standpoint of image quality, absolute, and relative quantification in all our simulation geometries. We characterize the effects of time step size, initial guess, and source configuration on final accuracy. This work could help to generate accurate quantitative images from both endogenous absorbers and exogenous photoacoustic dyes in both preclinical and clinical work, thereby increasing the information content obtained especially from deep-tissue photoacoustic imaging studies.
Directory of Open Access Journals (Sweden)
Tianyun Wang
2014-03-01
Full Text Available In recent years, various applications regarding sparse continuous signal recovery such as source localization, radar imaging, communication channel estimation, etc., have been addressed from the perspective of compressive sensing (CS theory. However, there are two major defects that need to be tackled when considering any practical utilization. The first issue is off-grid problem caused by the basis mismatch between arbitrary located unknowns and the pre-specified dictionary, which would make conventional CS reconstruction methods degrade considerably. The second important issue is the urgent demand for low-complexity algorithms, especially when faced with the requirement of real-time implementation. In this paper, to deal with these two problems, we have presented three fast and accurate sparse reconstruction algorithms, termed as HR-DCD, Hlog-DCD and Hlp-DCD, which are based on homotopy, dichotomous coordinate descent (DCD iterations and non-convex regularizations, by combining with the grid refinement technique. Experimental results are provided to demonstrate the effectiveness of the proposed algorithms and related analysis.
Thermographic image reconstruction using ultrasound reconstruction from virtual waves
Burgholzer, Peter; Gruber, Jürgen; Mayr, Günther
2016-01-01
Reconstruction of subsurface features from ultrasound signals measured on the surface is widely used in medicine and non-destructive testing. In this work, we introduce a concept how to use image reconstruction methods known from ultrasonic imaging for thermographic signals, i.e. on the measured temperature evolution on a sample surface. Before using these imaging methods a virtual signal is calculated by applying a transformation to the measured temperature evolution. The virtual signal is calculated locally for every detection point and has the same initial temperature distribution as the measured signal, but is a solution of the wave equation. The introduced transformation can be used for every shape of the detection surface and in every dimension. It describes all the irreversibility of the heat diffusion, which is responsible that the spatial resolution gets worse with increasing depth. Up to now, for thermographic imaging mostly one-dimensional methods, e.g., for depth-profiling were used, which are sui...
4D image reconstruction for emission tomography
Reader, Andrew J.; Verhaeghe, Jeroen
2014-11-01
An overview of the theory of 4D image reconstruction for emission tomography is given along with a review of the current state of the art, covering both positron emission tomography and single photon emission computed tomography (SPECT). By viewing 4D image reconstruction as a matter of either linear or non-linear parameter estimation for a set of spatiotemporal functions chosen to approximately represent the radiotracer distribution, the areas of so-called ‘fully 4D’ image reconstruction and ‘direct kinetic parameter estimation’ are unified within a common framework. Many choices of linear and non-linear parameterization of these functions are considered (including the important case where the parameters have direct biological meaning), along with a review of the algorithms which are able to estimate these often non-linear parameters from emission tomography data. The other crucial components to image reconstruction (the objective function, the system model and the raw data format) are also covered, but in less detail due to the relatively straightforward extension from their corresponding components in conventional 3D image reconstruction. The key unifying concept is that maximum likelihood or maximum a posteriori (MAP) estimation of either linear or non-linear model parameters can be achieved in image space after carrying out a conventional expectation maximization (EM) update of the dynamic image series, using a Kullback-Leibler distance metric (comparing the modeled image values with the EM image values), to optimize the desired parameters. For MAP, an image-space penalty for regularization purposes is required. The benefits of 4D and direct reconstruction reported in the literature are reviewed, and furthermore demonstrated with simple simulation examples. It is clear that the future of reconstructing dynamic or functional emission tomography images, which often exhibit high levels of spatially correlated noise, should ideally exploit these 4D
Reconstruction of Undersampled Atomic Force Microscopy Images
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm; Arildsen, Thomas; Østergaard, Jan
2013-01-01
, or a special case of compressed sensing. We argue that the preferred approach depends upon the type of image. Of the methods proposed for AFM, images containing high frequencies should be reconstructed using basis pursuit from data collected in a spiral pattern. Images without too much high frequency content...
Scattering Correction For Image Reconstruction In Flash Radiography
Energy Technology Data Exchange (ETDEWEB)
Cao, Liangzhi; Wang, Mengqi; Wu, Hongchun; Liu, Zhouyu; Cheng, Yuxiong; Zhang, Hongbo [Xi' an Jiaotong Univ., Xi' an (China)
2013-08-15
Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency.
Image reconstruction for robot assisted ultrasound tomography
Aalamifar, Fereshteh; Zhang, Haichong K.; Rahmim, Arman; Boctor, Emad M.
2016-04-01
An investigation of several image reconstruction methods for robot-assisted ultrasound (US) tomography setup is presented. In the robot-assisted setup, an expert moves the US probe to the location of interest, and a robotic arm automatically aligns another US probe with it. The two aligned probes can then transmit and receive US signals which are subsequently used for tomographic reconstruction. This study focuses on reconstruction of the speed of sound. In various simulation evaluations as well as in an experiment with a millimeter-range inaccuracy, we demonstrate that the limited data provided by two probes can be used to reconstruct pixel-wise images differentiating between media with different speeds of sound. Combining the results of this investigation with the developed robot-assisted US tomography setup, we envision feasibility of this setup for tomographic imaging in applications beyond breast imaging, with potentially significant efficacy in cancer diagnosis.
Accurate particle position measurement from images
Feng, Yan; Liu, Bin; 10.1063/1.2735920
2011-01-01
The moment method is an image analysis technique for sub-pixel estimation of particle positions. The total error in the calculated particle position includes effects of pixel locking and random noise in each pixel. Pixel locking, also known as peak locking, is an artifact where calculated particle positions are concentrated at certain locations relative to pixel edges. We report simulations to gain an understanding of the sources of error and their dependence on parameters the experimenter can control. We suggest an algorithm, and we find optimal parameters an experimenter can use to minimize total error and pixel locking. Simulating a dusty plasma experiment, we find that a sub-pixel accuracy of 0.017 pixel or better can be attained. These results are also useful for improving particle position measurement and particle tracking velocimetry (PTV) using video microscopy, in fields including colloids, biology, and fluid mechanics.
Image Reconstruction for Prostate Specific Nuclear Medicine imagers
Energy Technology Data Exchange (ETDEWEB)
Mark Smith
2007-01-11
There is increasing interest in the design and construction of nuclear medicine detectors for dedicated prostate imaging. These include detectors designed for imaging the biodistribution of radiopharmaceuticals labeled with single gamma as well as positron-emitting radionuclides. New detectors and acquisition geometries present challenges and opportunities for image reconstruction. In this contribution various strategies for image reconstruction for these special purpose imagers are reviewed. Iterative statistical algorithms provide a framework for reconstructing prostate images from a wide variety of detectors and acquisition geometries for PET and SPECT. The key to their success is modeling the physics of photon transport and data acquisition and the Poisson statistics of nuclear decay. Analytic image reconstruction methods can be fast and are useful for favorable acquisition geometries. Future perspectives on algorithm development and data analysis for prostate imaging are presented.
3D Reconstruction of NMR Images
Directory of Open Access Journals (Sweden)
Peter Izak
2007-01-01
Full Text Available This paper introduces experiment of 3D reconstruction NMR images scanned from magnetic resonance device. There are described methods which can be used for 3D reconstruction magnetic resonance images in biomedical application. The main idea is based on marching cubes algorithm. For this task was chosen sophistication method by program Vision Assistant, which is a part of program LabVIEW.
Li, Hechao; Kaira, Shashank; Mertens, James; Chawla, Nikhilesh; Jiao, Yang
2016-12-01
An accurate knowledge of the complex microstructure of a heterogeneous material is crucial for its performance prediction, prognosis and optimization. X-ray tomography has provided a nondestructive means for microstructure characterization in 3D and 4D (i.e. structural evolution over time), in which a material is typically reconstructed from a large number of tomographic projections using filtered-back-projection (FBP) method or algebraic reconstruction techniques (ART). Here, we present in detail a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of absorption contrast x-ray tomographic projections. This discrete tomography reconstruction procedure is in contrast to the commonly used FBP and ART, which usually requires thousands of projections for accurate microstructure rendition. The utility of our stochastic procedure is first demonstrated by reconstructing a wide class of two-phase heterogeneous materials including sandstone and hard-particle packing from simulated limited-angle projections in both cone-beam and parallel beam projection geometry. It is then applied to reconstruct tailored Sn-sphere-clay-matrix systems from limited-angle cone-beam data obtained via a lab-scale tomography facility at Arizona State University and parallel-beam synchrotron data obtained at Advanced Photon Source, Argonne National Laboratory. In addition, we examine the information content of tomography data by successively incorporating larger number of projections and quantifying the accuracy of the reconstructions. We show that only a small number of projections (e.g. 20-40, depending on the complexity of the microstructure of interest and desired resolution) are necessary for accurate material reconstructions via our stochastic procedure, which indicates its high efficiency in using limited structural information. The ramifications of the stochastic reconstruction procedure in 4D materials science are also
Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography
wang, Kun; Oraevsky, Alexander A; Anastasio, Mark A
2012-01-01
Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely, a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By ...
Bayesian image reconstruction: Application to emission tomography
Energy Technology Data Exchange (ETDEWEB)
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
Image reconstruction from incomplete convolution data via total variation regularization
Directory of Open Access Journals (Sweden)
Zhida Shen
2015-02-01
Full Text Available Variational models with Total Variation (TV regularization have long been known to preserve image edges and produce high quality reconstruction. On the other hand, recent theory on compressive sensing has shown that it is feasible to accurately reconstruct images from a few linear measurements via TV regularization. However, in general TV models are difficult to solve due to the nondifferentiability and the universal coupling of variables. In this paper, we propose the use of alternating direction method for image reconstruction from highly incomplete convolution data, where an image is reconstructed as a minimizer of an energy function that sums a TV term for image regularity and a least squares term for data fitting. Our algorithm, called RecPK, takes advantage of problem structures and has an extremely low per-iteration cost. To demonstrate the efficiency of RecPK, we compare it with TwIST, a state-of-the-art algorithm for minimizing TV models. Moreover, we also demonstrate the usefulness of RecPK in image zooming.
Image reconstruction under non-Gaussian noise
DEFF Research Database (Denmark)
Sciacchitano, Federica
During acquisition and transmission, images are often blurred and corrupted by noise. One of the fundamental tasks of image processing is to reconstruct the clean image from a degraded version. The process of recovering the original image from the data is an example of inverse problem. Due......D thesis intends to solve some of the many open questions for image restoration under non-Gaussian noise. The two main kinds of noise studied in this PhD project are the impulse noise and the Cauchy noise. Impulse noise is due to for instance the malfunctioning pixel elements in the camera sensors, errors...... that the CM estimate outperforms the MAP estimate, when the error depends on Bregman distances. This PhD project can have many applications in the modern society, in fact the reconstruction of high quality images with less noise and more details enhances the image processing operations, such as edge detection...
Elasticity reconstructive imaging by means of stimulated echo MRI.
Chenevert, T L; Skovoroda, A R; O'Donnell, M; Emelianov, S Y
1998-03-01
A method is introduced to measure internal mechanical displacement and strain by means of MRI. Such measurements are needed to reconstruct an image of the elastic Young's modulus. A stimulated echo acquisition sequence with additional gradient pulses encodes internal displacements in response to an externally applied differential deformation. The sequence provides an accurate measure of static displacement by limiting the mechanical transitions to the mixing period of the simulated echo. Elasticity reconstruction involves definition of a region of interest having uniform Young's modulus along its boundary and subsequent solution of the discretized elasticity equilibrium equations. Data acquisition and reconstruction were performed on a urethane rubber phantom of known elastic properties and an ex vivo canine kidney phantom using elastic properties are well represented on Young's modulus images. The long-term objective of this work is to provide a means for remote palpation and elasticity quantitation in deep tissues otherwise inaccessible to manual palpation.
Tomographic image reconstruction from continuous projections
Cant, J.; Palenstijn, W.J.; Behiels, G.; Sijbers, J.
2014-01-01
An important design aspect in tomographic image reconstruction is the choice between a step-and-shoot protocol versus continuous X-ray tube movement for image acquisition. A step-and-shoot protocol implies a perfectly still tube during X-ray exposure, and hence involves moving the tube to its next p
Iterative Reconstruction for Differential Phase Contrast Imaging
Koehler, T.; Brendel, B.; Roessl, E.
2011-01-01
Purpose: The purpose of this work is to combine two areas of active research in tomographic x-ray imaging. The first one is the use of iterative reconstruction techniques. The second one is differential phase contrast imaging (DPCI). Method: We derive an SPS type maximum likelihood (ML) reconstructi
Reconstruction Algorithms in Undersampled AFM Imaging
DEFF Research Database (Denmark)
Arildsen, Thomas; Oxvig, Christian Schou; Pedersen, Patrick Steffen
2016-01-01
This paper provides a study of spatial undersampling in atomic force microscopy (AFM) imaging followed by different image reconstruction techniques based on sparse approximation as well as interpolation. The main reasons for using undersampling is that it reduces the path length and thereby the s...
Techniques in Iterative Proton CT Image Reconstruction
Penfold, Scott
2015-01-01
This is a review paper on some of the physics, modeling, and iterative algorithms in proton computed tomography (pCT) image reconstruction. The primary challenge in pCT image reconstruction lies in the degraded spatial resolution resulting from multiple Coulomb scattering within the imaged object. Analytical models such as the most likely path (MLP) have been proposed to predict the scattered trajectory from measurements of individual proton location and direction before and after the object. Iterative algorithms provide a flexible tool with which to incorporate these models into image reconstruction. The modeling leads to a large and sparse linear system of equations that can efficiently be solved by projection methods-based iterative algorithms. Such algorithms perform projections of the iterates onto the hyperlanes that are represented by the linear equations of the system. They perform these projections in possibly various algorithmic structures, such as block-iterative projections (BIP), string-averaging...
Monte-Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography
Energy Technology Data Exchange (ETDEWEB)
Gillam, John E. [The University of Sydney, Faculty of Health Sciences and The Brain and Mind Centre, Camperdown (Australia); Rafecas, Magdalena, E-mail: rafecas@imt.uni-luebeck.de [University of Lubeck, Institute of Medical Engineering, Ratzeburger Allee 160, 23538 Lübeck (Germany)
2016-02-11
Emission imaging incorporates both the development of dedicated devices for data acquisition as well as algorithms for recovering images from that data. Emission tomography is an indirect approach to imaging. The effect of device modification on the final image can be understood through both the way in which data are gathered, using simulation, and the way in which the image is formed from that data, or image reconstruction. When developing novel devices, systems and imaging tasks, accurate simulation and image reconstruction allow performance to be estimated, and in some cases optimized, using computational methods before or during the process of physical construction. However, there are a vast range of approaches, algorithms and pre-existing computational tools that can be exploited and the choices made will affect the accuracy of the in silico results and quality of the reconstructed images. On the one hand, should important physical effects be neglected in either the simulation or reconstruction steps, specific enhancements provided by novel devices may not be represented in the results. On the other hand, over-modeling of device characteristics in either step leads to large computational overheads that can confound timely results. Here, a range of simulation methodologies and toolkits are discussed, as well as reconstruction algorithms that may be employed in emission imaging. The relative advantages and disadvantages of a range of options are highlighted using specific examples from current research scenarios.
Directory of Open Access Journals (Sweden)
Mingjian Sun
2015-01-01
Full Text Available Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO optimized support vector machine (SVM interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.
Bayesian Image Reconstruction Based on Voronoi Diagrams
Cabrera, G F; Hitschfeld, N
2007-01-01
We present a Bayesian Voronoi image reconstruction technique (VIR) for interferometric data. Bayesian analysis applied to the inverse problem allows us to derive the a-posteriori probability of a novel parameterization of interferometric images. We use a variable Voronoi diagram as our model in place of the usual fixed pixel grid. A quantization of the intensity field allows us to calculate the likelihood function and a-priori probabilities. The Voronoi image is optimized including the number of polygons as free parameters. We apply our algorithm to deconvolve simulated interferometric data. Residuals, restored images and chi^2 values are used to compare our reconstructions with fixed grid models. VIR has the advantage of modeling the image with few parameters, obtaining a better image from a Bayesian point of view.
Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction
Yin, Xiaoxia; Abbott, Derek
2012-01-01
Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...
Proton computed tomography images with algebraic reconstruction
Bruzzi, M.; Civinini, C.; Scaringella, M.; Bonanno, D.; Brianzi, M.; Carpinelli, M.; Cirrone, G. A. P.; Cuttone, G.; Presti, D. Lo; Maccioni, G.; Pallotta, S.; Randazzo, N.; Romano, F.; Sipala, V.; Talamonti, C.; Vanzi, E.
2017-02-01
A prototype of proton Computed Tomography (pCT) system for hadron-therapy has been manufactured and tested in a 175 MeV proton beam with a non-homogeneous phantom designed to simulate high-contrast material. BI-SART reconstruction algorithms have been implemented with GPU parallelism, taking into account of most likely paths of protons in matter. Reconstructed tomography images with density resolutions r.m.s. down to 1% and spatial resolutions CT in hadron-therapy.
Superresolution images reconstructed from aliased images
Vandewalle, Patrick; Susstrunk, Sabine E.; Vetterli, Martin
2003-06-01
In this paper, we present a simple method to almost quadruple the spatial resolution of aliased images. From a set of four low resolution, undersampled and shifted images, a new image is constructed with almost twice the resolution in each dimension. The resulting image is aliasing-free. A small aliasing-free part of the frequency domain of the images is used to compute the exact subpixel shifts. When the relative image positions are known, a higher resolution image can be constructed using the Papoulis-Gerchberg algorithm. The proposed method is tested in a simulation where all simulation parameters are well controlled, and where the resulting image can be compared with its original. The algorithm is also applied to real, noisy images from a digital camera. Both experiments show very good results.
3D Lunar Terrain Reconstruction from Apollo Images
Broxton, Michael J.; Nefian, Ara V.; Moratto, Zachary; Kim, Taemin; Lundy, Michael; Segal, Alkeksandr V.
2009-01-01
Generating accurate three dimensional planetary models is becoming increasingly important as NASA plans manned missions to return to the Moon in the next decade. This paper describes a 3D surface reconstruction system called the Ames Stereo Pipeline that is designed to produce such models automatically by processing orbital stereo imagery. We discuss two important core aspects of this system: (1) refinement of satellite station positions and pose estimates through least squares bundle adjustment; and (2) a stochastic plane fitting algorithm that generalizes the Lucas-Kanade method for optimal matching between stereo pair images.. These techniques allow us to automatically produce seamless, highly accurate digital elevation models from multiple stereo image pairs while significantly reducing the influence of image noise. Our technique is demonstrated on a set of 71 high resolution scanned images from the Apollo 15 mission
3-D Reconstruction From Satellite Images
DEFF Research Database (Denmark)
Denver, Troelz
1999-01-01
The aim of this project has been to implement a software system, that is able to create a 3-D reconstruction from two or more 2-D photographic images made from different positions. The height is determined from the disparity difference of the images. The general purpose of the system is mapping...... of planetary surfaces, but other purposes is considered as well. The system performance is measured with respect to the precision and the time consumption.The reconstruction process is divided into four major areas: Acquisition, calibration, matching/reconstruction and presentation. Each of these areas...... are treated individually. A detailed treatment of various lens distortions is required, in order to correct for these problems. This subject is included in the acquisition part. In the calibration part, the perspective distortion is removed from the images. Most attention has been paid to the matching problem...
Fu, Jian; Tan, Renbo; Chen, Liyuan
2014-01-01
X-ray differential phase-contrast computed tomography (DPC-CT) is a powerful physical and biochemical analysis tool. In practical applications, there are often challenges for DPC-CT due to insufficient data caused by few-view, bad or missing detector channels, or limited scanning angular range. They occur quite frequently because of experimental constraints from imaging hardware, scanning geometry, and the exposure dose delivered to living specimens. In this work, we analyze the influence of incomplete data on DPC-CT image reconstruction. Then, a reconstruction method is developed and investigated for incomplete data DPC-CT. It is based on an algebraic iteration reconstruction technique, which minimizes the image total variation and permits accurate tomographic imaging with less data. This work comprises a numerical study of the method and its experimental verification using a dataset measured at the W2 beamline of the storage ring DORIS III equipped with a Talbot-Lau interferometer. The numerical and experimental results demonstrate that the presented method can handle incomplete data. It will be of interest for a wide range of DPC-CT applications in medicine, biology, and nondestructive testing.
Image Reconstruction Image reconstruction by using local inverse for full field of view
Yang, Kang; Yang, Xintie; Zhao, Shuang-Ren
2015-01-01
The iterative refinement method (IRM) has been very successfully applied in many different fields for examples the modern quantum chemical calculation and CT image reconstruction. It is proved that the refinement method can create an exact inverse from an approximate inverse with a few iterations. The IRM has been used in CT image reconstruction to lower the radiation dose. The IRM utilize the errors between the original measured data and the recalculated data to correct the reconstructed images. However if it is not smooth inside the object, there often is an over-correction along the boundary of the organs in the reconstructed images. The over-correction increase the noises especially on the edges inside the image. One solution to reduce the above mentioned noises is using some kind of filters. Filtering the noise before/after/between the image reconstruction processing. However filtering the noises also means reduce the resolution of the reconstructed images. The filtered image is often applied to the imag...
Diwakar, Mithun; Tal, Omer; Liu, Thomas T; Harrington, Deborah L; Srinivasan, Ramesh; Muzzatti, Laura; Song, Tao; Theilmann, Rebecca J; Lee, Roland R; Huang, Ming-Xiong
2011-06-15
Beamformer spatial filters are commonly used to explore the active neuronal sources underlying magnetoencephalography (MEG) recordings at low signal-to-noise ratio (SNR). Conventional beamformer techniques are successful in localizing uncorrelated neuronal sources under poor SNR conditions. However, the spatial and temporal features from conventional beamformer reconstructions suffer when sources are correlated, which is a common and important property of real neuronal networks. Dual-beamformer techniques, originally developed by Brookes et al. to deal with this limitation, successfully localize highly-correlated sources and determine their orientations and weightings, but their performance degrades at low correlations. They also lack the capability to produce individual time courses and therefore cannot quantify source correlation. In this paper, we present an enhanced formulation of our earlier dual-core beamformer (DCBF) approach that reconstructs individual source time courses and their correlations. Through computer simulations, we show that the enhanced DCBF (eDCBF) consistently and accurately models dual-source activity regardless of the correlation strength. Simulations also show that a multi-core extension of eDCBF effectively handles the presence of additional correlated sources. In a human auditory task, we further demonstrate that eDCBF accurately reconstructs left and right auditory temporal responses and their correlations. Spatial resolution and source localization strategies corresponding to different measures within the eDCBF framework are also discussed. In summary, eDCBF accurately reconstructs source spatio-temporal behavior, providing a means for characterizing complex neuronal networks and their communication.
Energy Technology Data Exchange (ETDEWEB)
Poulin, Eric; Racine, Emmanuel; Beaulieu, Luc, E-mail: Luc.Beaulieu@phy.ulaval.ca [Département de physique, de génie physique et d’optique et Centre de recherche sur le cancer de l’Université Laval, Université Laval, Québec, Québec G1V 0A6, Canada and Département de radio-oncologie et Axe Oncologie du Centre de recherche du CHU de Québec, CHU de Québec, 11 Côte du Palais, Québec, Québec G1R 2J6 (Canada); Binnekamp, Dirk [Integrated Clinical Solutions and Marketing, Philips Healthcare, Veenpluis 4-6, Best 5680 DA (Netherlands)
2015-03-15
Purpose: In high dose rate brachytherapy (HDR-B), current catheter reconstruction protocols are relatively slow and error prone. The purpose of this technical note is to evaluate the accuracy and the robustness of an electromagnetic (EM) tracking system for automated and real-time catheter reconstruction. Methods: For this preclinical study, a total of ten catheters were inserted in gelatin phantoms with different trajectories. Catheters were reconstructed using a 18G biopsy needle, used as an EM stylet and equipped with a miniaturized sensor, and the second generation Aurora{sup ®} Planar Field Generator from Northern Digital Inc. The Aurora EM system provides position and orientation value with precisions of 0.7 mm and 0.2°, respectively. Phantoms were also scanned using a μCT (GE Healthcare) and Philips Big Bore clinical computed tomography (CT) system with a spatial resolution of 89 μm and 2 mm, respectively. Reconstructions using the EM stylet were compared to μCT and CT. To assess the robustness of the EM reconstruction, five catheters were reconstructed twice and compared. Results: Reconstruction time for one catheter was 10 s, leading to a total reconstruction time inferior to 3 min for a typical 17-catheter implant. When compared to the μCT, the mean EM tip identification error was 0.69 ± 0.29 mm while the CT error was 1.08 ± 0.67 mm. The mean 3D distance error was found to be 0.66 ± 0.33 mm and 1.08 ± 0.72 mm for the EM and CT, respectively. EM 3D catheter trajectories were found to be more accurate. A maximum difference of less than 0.6 mm was found between successive EM reconstructions. Conclusions: The EM reconstruction was found to be more accurate and precise than the conventional methods used for catheter reconstruction in HDR-B. This approach can be applied to any type of catheters and applicators.
Optimizing modelling in iterative image reconstruction for preclinical pinhole PET
Goorden, Marlies C.; van Roosmalen, Jarno; van der Have, Frans; Beekman, Freek J.
2016-05-01
The recently developed versatile emission computed tomography (VECTor) technology enables high-energy SPECT and simultaneous SPECT and PET of small animals at sub-mm resolutions. VECTor uses dedicated clustered pinhole collimators mounted in a scanner with three stationary large-area NaI(Tl) gamma detectors. Here, we develop and validate dedicated image reconstruction methods that compensate for image degradation by incorporating accurate models for the transport of high-energy annihilation gamma photons. Ray tracing software was used to calculate photon transport through the collimator structures and into the gamma detector. Input to this code are several geometric parameters estimated from system calibration with a scanning 99mTc point source. Effects on reconstructed images of (i) modelling variable depth-of-interaction (DOI) in the detector, (ii) incorporating photon paths that go through multiple pinholes (‘multiple-pinhole paths’ (MPP)), and (iii) including various amounts of point spread function (PSF) tail were evaluated. Imaging 18F in resolution and uniformity phantoms showed that including large parts of PSFs is essential to obtain good contrast-noise characteristics and that DOI modelling is highly effective in removing deformations of small structures, together leading to 0.75 mm resolution PET images of a hot-rod Derenzo phantom. Moreover, MPP modelling reduced the level of background noise. These improvements were also clearly visible in mouse images. Performance of VECTor can thus be significantly improved by accurately modelling annihilation gamma photon transport.
Anthropomorphic image reconstruction via hypoelliptic diffusion
Boscain, Ugo; Gauthier, Jean-Paul; Rossi, Francesco
2010-01-01
In this paper we present a model of geometry of vision which generalizes one due to Petitot, Citti and Sarti. One of its main features is that the primary visual cortex V1 lifts the image from $R^2$ to the bundle of directions of the plane $PTR^2=R^2\\times P^1$. Neurons are grouped into orientation columns, each of them corresponding to a point of the bundle $PTR^2$. In this model a corrupted image is reconstructed by minimizing the energy necessary for the activation of the orientation columns corresponding to regions in which the image is corrupted. The minimization process gives rise to an hypoelliptic heat equation on $PTR^2$. The hypoelliptic heat equation is studied using the generalized Fourier transform. It transforms the hypoelliptic equation into a 1-d heat equation with Mathieu potential, which one can solve numerically. Preliminary examples of image reconstruction are hereby provided.
Approximate Sparsity and Nonlocal Total Variation Based Compressive MR Image Reconstruction
Directory of Open Access Journals (Sweden)
Chengzhi Deng
2014-01-01
Full Text Available Recent developments in compressive sensing (CS show that it is possible to accurately reconstruct the magnetic resonance (MR image from undersampled k-space data by solving nonsmooth convex optimization problems, which therefore significantly reduce the scanning time. In this paper, we propose a new MR image reconstruction method based on a compound regularization model associated with the nonlocal total variation (NLTV and the wavelet approximate sparsity. Nonlocal total variation can restore periodic textures and local geometric information better than total variation. The wavelet approximate sparsity achieves more accurate sparse reconstruction than fixed wavelet l0 and l1 norm. Furthermore, a variable splitting and augmented Lagrangian algorithm is presented to solve the proposed minimization problem. Experimental results on MR image reconstruction demonstrate that the proposed method outperforms many existing MR image reconstruction methods both in quantitative and in visual quality assessment.
Image reconstruction for brain CT slices
Institute of Scientific and Technical Information of China (English)
吴建明; 施鹏飞
2004-01-01
Different modalities in biomedical images, like CT, MRI and PET scanners, provide detailed cross-sectional views of human anatomy. This paper introduces three-dimensional brain reconstruction based on CT slices. It contains filtering, fuzzy segmentation, matching method of contours, cell array structure and image animation. Experimental results have shown its validity. The innovation is matching method of contours and fuzzy segmentation algorithm of CT slices.
Stochastic image reconstruction for a dual-particle imaging system
Energy Technology Data Exchange (ETDEWEB)
Hamel, M.C., E-mail: mchamel@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Blvd, Ann Arbor, MI 48109 (United States); Polack, J.K., E-mail: kpolack@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Blvd, Ann Arbor, MI 48109 (United States); Poitrasson-Rivière, A., E-mail: alexispr@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Blvd, Ann Arbor, MI 48109 (United States); Flaska, M., E-mail: mflaska@psu.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Blvd, Ann Arbor, MI 48109 (United States); Department of Mechanical and Nuclear Engineering, Pennsylvania State University, 137 Reber Building, University Park, PA 16802 (United States); Clarke, S.D., E-mail: clarkesd@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Blvd, Ann Arbor, MI 48109 (United States); Pozzi, S.A., E-mail: pozzisa@umich.edu [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2355 Bonisteel Blvd, Ann Arbor, MI 48109 (United States); Tomanin, A., E-mail: alice.tomanin@jrc.ec.europa.eu [European Commission, Joint Research Centre, Institute for Transuranium Elements, 21027 Ispra, VA (Italy); Lainsa-Italia S.R.L., via E. Fermi 2749, 21027 Ispra, VA (Italy); Peerani, P., E-mail: paolo.peerani@jrc.ec.europa.eu [European Commission, Joint Research Centre, Institute for Transuranium Elements, 21027 Ispra, VA (Italy)
2016-02-21
Stochastic image reconstruction has been applied to a dual-particle imaging system being designed for nuclear safeguards applications. The dual-particle imager (DPI) is a combined Compton-scatter and neutron-scatter camera capable of producing separate neutron and photon images. The stochastic origin ensembles (SOE) method was investigated as an imaging method for the DPI because only a minimal estimation of system response is required to produce images with quality that is comparable to common maximum-likelihood methods. This work contains neutron and photon SOE image reconstructions for a {sup 252}Cf point source, two mixed-oxide (MOX) fuel canisters representing point sources, and the MOX fuel canisters representing a distributed source. Simulation of the DPI using MCNPX-PoliMi is validated by comparison of simulated and measured results. Because image quality is dependent on the number of counts and iterations used, the relationship between these quantities is investigated.
Implementation of efficient image reconstruction for CT
Institute of Scientific and Technical Information of China (English)
Jie Liu; Guangfei Wang
2005-01-01
@@ The operational procedures for efficiently reconstructing the two-dimensional image of a body by the filtered back projection are described in this paper. The projections are interpolated for four times of original projection by zero-padding the original projection in frequency-domain and then inverse fast Fourier transform (FFT) is taken to improve accuracy.
Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography
Wang, Kun; Su, Richard; Oraevsky, Alexander A.; Anastasio, Mark A.
2012-09-01
Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By the use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications.
Mirror Surface Reconstruction from a Single Image.
Liu, Miaomiao; Hartley, Richard; Salzmann, Mathieu
2015-04-01
This paper tackles the problem of reconstructing the shape of a smooth mirror surface from a single image. In particular, we consider the case where the camera is observing the reflection of a static reference target in the unknown mirror. We first study the reconstruction problem given dense correspondences between 3D points on the reference target and image locations. In such conditions, our differential geometry analysis provides a theoretical proof that the shape of the mirror surface can be recovered if the pose of the reference target is known. We then relax our assumptions by considering the case where only sparse correspondences are available. In this scenario, we formulate reconstruction as an optimization problem, which can be solved using a nonlinear least-squares method. We demonstrate the effectiveness of our method on both synthetic and real images. We then provide a theoretical analysis of the potential degenerate cases with and without prior knowledge of the pose of the reference target. Finally we show that our theory can be similarly applied to the reconstruction of the surface of transparent object.
Reconstructing light curves from HXMT imaging observations
Huo, Zhuo-Xi; Li, Yi-Ming; Zhou, Jian-Feng
2014-01-01
The Hard X-ray Modulation Telescope (HXMT) is a Chinese space telescope mission. It is scheduled for launch in 2015. The telescope will perform an all-sky survey in hard X-ray band (1 - 250 keV), a series of deep imaging observations of small sky regions as well as pointed observations. In this work we present a conceptual method to reconstruct light curves from HXMT imaging observation directly, in order to monitor time-varying objects such as GRB, AXP and SGR in hard X-ray band with HXMT imaging observations.
Sparse image reconstruction for molecular imaging
Ting, Michael; Hero, Alfred O
2008-01-01
The application that motivates this paper is molecular imaging at the atomic level. When discretized at sub-atomic distances, the volume is inherently sparse. Noiseless measurements from an imaging technology can be modeled by convolution of the image with the system point spread function (psf). Such is the case with magnetic resonance force microscopy (MRFM), an emerging technology where imaging of an individual tobacco mosaic virus was recently demonstrated with nanometer resolution. We also consider additive white Gaussian noise (AWGN) in the measurements. Many prior works of sparse estimators have focused on the case when H has low coherence; however, the system matrix H in our application is the convolution matrix for the system psf. A typical convolution matrix has high coherence. The paper therefore does not assume a low coherence H. A discrete-continuous form of the Laplacian and atom at zero (LAZE) p.d.f. used by Johnstone and Silverman is formulated, and two sparse estimators derived by maximizing t...
Jørgensen, Jakob H; Pan, Xiaochuan
2011-01-01
Discrete-to-discrete imaging models for computed tomography (CT) are becoming increasingly ubiquitous as the interest in iterative image reconstruction algorithms has heightened. Despite this trend, all the intuition for algorithm and system design derives from analysis of continuous-to-continuous models such as the X-ray and Radon transform. While the similarity between these models justifies some crossover, questions such as what are sufficient sampling conditions can be quite different for the two models. This sampling issue is addressed extensively in the first half of the article using singular value decomposition analysis for determining sufficient number of views and detector bins. The question of full sampling for CT is particularly relevant to current attempts to adapt compressive sensing (CS) motivated methods to application in CT image reconstruction. The second half goes in depth on this subject and discusses the link between object sparsity and sufficient sampling for accurate reconstruction. Par...
Calibration of time-of-flight cameras for accurate intraoperative surface reconstruction
Energy Technology Data Exchange (ETDEWEB)
Mersmann, Sven; Seitel, Alexander; Maier-Hein, Lena [Division of Medical and Biological Informatics, Junior Group Computer-assisted Interventions, German Cancer Research Center (DKFZ), Heidelberg, Baden-Wurttemberg 69120 (Germany); Erz, Michael; Jähne, Bernd [Heidelberg Collaboratory for Image Processing (HCI), University of Heidelberg, Baden-Wurttemberg 69115 (Germany); Nickel, Felix; Mieth, Markus; Mehrabi, Arianeb [Department of General, Visceral and Transplant Surgery, University of Heidelberg, Baden-Wurttemberg 69120 (Germany)
2013-08-15
Purpose: In image-guided surgery (IGS) intraoperative image acquisition of tissue shape, motion, and morphology is one of the main challenges. Recently, time-of-flight (ToF) cameras have emerged as a new means for fast range image acquisition that can be used for multimodal registration of the patient anatomy during surgery. The major drawbacks of ToF cameras are systematic errors in the image acquisition technique that compromise the quality of the measured range images. In this paper, we propose a calibration concept that, for the first time, accounts for all known systematic errors affecting the quality of ToF range images. Laboratory and in vitro experiments assess its performance in the context of IGS.Methods: For calibration the camera-related error sources depending on the sensor, the sensor temperature and the set integration time are corrected first, followed by the scene-specific errors, which are modeled as function of the measured distance, the amplitude and the radial distance to the principal point of the camera. Accounting for the high accuracy demands in IGS, we use a custom-made calibration device to provide reference distance data, the cameras are calibrated too. To evaluate the mitigation of the error, the remaining residual error after ToF depth calibration was compared with that arising from using the manufacturer routines for several state-of-the-art ToF cameras. The accuracy of reconstructed ToF surfaces was investigated after multimodal registration with computed tomography (CT) data of liver models by assessment of the target registration error (TRE) of markers introduced in the livers.Results: For the inspected distance range of up to 2 m, our calibration approach yielded a mean residual error to reference data ranging from 1.5 ± 4.3 mm for the best camera to 7.2 ± 11.0 mm. When compared to the data obtained from the manufacturer routines, the residual error was reduced by at least 78% from worst calibration result to most accurate
A fast and accurate method for echocardiography strain rate imaging
Tavakoli, Vahid; Sahba, Nima; Hajebi, Nima; Nambakhsh, Mohammad Saleh
2009-02-01
Recently Strain and strain rate imaging have proved their superiority with respect to classical motion estimation methods in myocardial evaluation as a novel technique for quantitative analysis of myocardial function. Here in this paper, we propose a novel strain rate imaging algorithm using a new optical flow technique which is more rapid and accurate than the previous correlation-based methods. The new method presumes a spatiotemporal constancy of intensity and Magnitude of the image. Moreover the method makes use of the spline moment in a multiresolution approach. Moreover cardiac central point is obtained using a combination of center of mass and endocardial tracking. It is proved that the proposed method helps overcome the intensity variations of ultrasound texture while preserving the ability of motion estimation technique for different motions and orientations. Evaluation is performed on simulated, phantom (a contractile rubber balloon) and real sequences and proves that this technique is more accurate and faster than the previous methods.
Propagation phasor approach for holographic image reconstruction
Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan
2016-03-01
To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears.
Probabilistic image reconstruction for radio interferometers
Sutter, P M; McEwen, Jason D; Bunn, Emory F; Karakci, Ata; Korotkov, Andrei; Timbie, Peter; Tucker, Gregory S; Zhang, Le
2013-01-01
We present a novel, general-purpose method for deconvolving and denoising images from gridded radio interferometric visibilities using Bayesian inference based on a Gaussian process model. The method automatically takes into account incomplete coverage of the uv-plane and mode coupling due to the beam. Our method uses Gibbs sampling to efficiently explore the full posterior distribution of the underlying signal image given the data. We use a set of widely diverse mock images with a realistic interferometer setup and level of noise to assess the method. Compared to results from a proxy for the CLEAN method we find that in terms of RMS error and signal-to-noise ratio our approach performs better than traditional deconvolution techniques, regardless of the structure of the source image in our test suite. Our implementation scales as O(np log np), provides full statistical and uncertainty information of the reconstructed image, requires no supervision, and provides a robust, consistent framework for incorporating...
Performance-based assessment of reconstructed images
Energy Technology Data Exchange (ETDEWEB)
Hanson, Kenneth [Los Alamos National Laboratory
2009-01-01
During the early 90s, I engaged in a productive and enjoyable collaboration with Robert Wagner and his colleague, Kyle Myers. We explored the ramifications of the principle that tbe quality of an image should be assessed on the basis of how well it facilitates the performance of appropriate visual tasks. We applied this principle to algorithms used to reconstruct scenes from incomplete and/or noisy projection data. For binary visual tasks, we used both the conventional disk detection and a new challenging task, inspired by the Rayleigh resolution criterion, of deciding whether an object was a blurred version of two dots or a bar. The results of human and machine observer tests were summarized with the detectability index based on the area under the ROC curve. We investigated a variety of reconstruction algorithms, including ART, with and without a nonnegativity constraint, and the MEMSYS3 algorithm. We concluded that the performance of the Raleigh task was optimized when the strength of the prior was near MEMSYS's default 'classic' value for both human and machine observers. A notable result was that the most-often-used metric of rms error in the reconstruction was not necessarily indicative of the value of a reconstructed image for the purpose of performing visual tasks.
Energy Technology Data Exchange (ETDEWEB)
Passeri, A. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); Formiconi, A.R. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); De Cristofaro, M.T.E.R. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); Pupi, A. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); Meldolesi, U. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy)
1997-04-01
It is well known that the quantitative potential of emission computed tomography (ECT) relies on the ability to compensate for resolution, attenuation and scatter effects. Reconstruction algorithms which are able to take these effects into account are highly demanding in terms of computing resources. The reported work aimed to investigate the use of a parallel high-performance computing platform for ECT reconstruction taking into account an accurate model of the acquisition of single-photon emission tomographic (SPET) data. An iterative algorithm with an accurate model of the variable system response was ported on the MIMD (Multiple Instruction Multiple Data) parallel architecture of a 64-node Cray T3D massively parallel computer. The system was organized to make it easily accessible even from low-cost PC-based workstations through standard TCP/IP networking. A complete brain study of 30 (64 x 64) slices could be reconstructed from a set of 90 (64 x 64) projections with ten iterations of the conjugate gradients algorithm in 9 s, corresponding to an actual speed-up factor of 135. This work demonstrated the possibility of exploiting remote high-performance computing and networking resources from hospital sites by means of low-cost workstations using standard communication protocols without particular problems for routine use. The achievable speed-up factors allow the assessment of the clinical benefit of advanced reconstruction techniques which require a heavy computational burden for the compensation effects such as variable spatial resolution, scatter and attenuation. The possibility of using the same software on the same hardware platform with data acquired in different laboratories with various kinds of SPET instrumentation is appealing for software quality control and for the evaluation of the clinical impact of the reconstruction methods. (orig.). With 4 figs., 1 tab.
Reconstructing building mass models from UAV images
Li, Minglei
2015-07-26
We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.
Image-reconstruction methods in positron tomography
Townsend, David W; CERN. Geneva
1993-01-01
Physics and mathematics for medical imaging\tIn the two decades since the introduction of the X-ray scanner into radiology, medical imaging techniques have become widely established as essential tools in the diagnosis of disease. As a consequence of recent technological and mathematical advances, the non-invasive, three-dimensional imaging of internal organs such as the brain and the heart is now possible, not only for anatomical investigations using X-rays but also for studies which explore the functional status of the body using positron-emitting radioisotopes and nuclear magnetic resonance. Mathematical methods which enable three-dimentional distributions to be reconstructed from projection data acquired by radiation detectors suitably positioned around the patient will be described in detail. The lectures will trace the development of medical imaging from simpleradiographs to the present-day non-invasive measurement of in vivo boichemistry. Powerful techniques to correlate anatomy and function that are cur...
Building Reconstruction Using DSM and Orthorectified Images
Directory of Open Access Journals (Sweden)
Peter Reinartz
2013-04-01
Full Text Available High resolution Digital Surface Models (DSMs produced from airborne laser-scanning or stereo satellite images provide a very useful source of information for automated 3D building reconstruction. In this paper an investigation is reported about extraction of 3D building models from high resolution DSMs and orthorectified images produced from Worldview-2 stereo satellite imagery. The focus is on the generation of 3D models of parametric building roofs, which is the basis for creating Level Of Detail 2 (LOD2 according to the CityGML standard. In particular the building blocks containing several connected buildings with tilted roofs are investigated and the potentials and limitations of the modeling approach are discussed. The edge information extracted from orthorectified image has been employed as additional source of information in 3D reconstruction algorithm. A model driven approach based on the analysis of the 3D points of DSMs in a 2D projection plane is proposed. Accordingly, a building block is divided into smaller parts according to the direction and number of existing ridge lines for parametric building reconstruction. The 3D model is derived for each building part, and finally, a complete parametric model is formed by merging the 3D models of the individual building parts and adjusting the nodes after the merging step. For the remaining building parts that do not contain ridge lines, a prismatic model using polygon approximation of the corresponding boundary pixels is derived and merged to the parametric models to shape the final model of the building. A qualitative and quantitative assessment of the proposed method for the automatic reconstruction of buildings with parametric roofs is then provided by comparing the final model with the existing surface model as well as some field measurements.
Roelandts, T.; Batenburg, K.J.; Dekker, A.J. den; Sijbers, J.
2014-01-01
In this paper, we present the reconstructed residual error, which evaluates the quality of a given segmentation of a reconstructed image in tomography. This novel evaluation method, which is independent of the methods that were used to reconstruct and segment the image, is applicable to segmentation
Qiao, Yao-Bin; Qi, Hong; Zhao, Fang-Zhou; Ruan, Li-Ming
2016-12-01
Reconstructing the distribution of optical parameters in the participating medium based on the frequency-domain radiative transfer equation (FD-RTE) to probe the internal structure of the medium is investigated in the present work. The forward model of FD-RTE is solved via the finite volume method (FVM). The regularization term formatted by the generalized Gaussian Markov random field model is used in the objective function to overcome the ill-posed nature of the inverse problem. The multi-start conjugate gradient (MCG) method is employed to search the minimum of the objective function and increase the efficiency of convergence. A modified adjoint differentiation technique using the collimated radiative intensity is developed to calculate the gradient of the objective function with respect to the optical parameters. All simulation results show that the proposed reconstruction algorithm based on FD-RTE can obtain the accurate distributions of absorption and scattering coefficients. The reconstructed images of the scattering coefficient have less errors than those of the absorption coefficient, which indicates the former are more suitable to probing the inner structure. Project supported by the National Natural Science Foundation of China (Grant No. 51476043), the Major National Scientific Instruments and Equipment Development Special Foundation of China (Grant No. 51327803), and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51121004).
2016-01-01
Compressive Sensing (CS) theory has great potential for reconstructing Computed Tomography (CT) images from sparse-views projection data and Total Variation- (TV-) based CT reconstruction method is very popular. However, it does not directly incorporate prior images into the reconstruction. To improve the quality of reconstructed images, this paper proposed an improved TV minimization method using prior images and Split-Bregman method in CT reconstruction, which uses prior images to obtain valuable previous information and promote the subsequent imaging process. The images obtained asynchronously were registered via Locally Linear Embedding (LLE). To validate the method, two studies were performed. Numerical simulation using an abdomen phantom has been used to demonstrate that the proposed method enables accurate reconstruction of image objects under sparse projection data. A real dataset was used to further validate the method. PMID:27689076
Analysis of Galileo Style Geostationary Satellite Imaging: Image Reconstruction
2012-09-01
obtained using only baselines longer than 8 m does not sample the short spacial frequencies, and the image reconstruction is not able to recover the...the long spacial frequencies sampled in a shorter baseline overlap the short spacial frequencies sampled in a longer baseline. This technique will
A new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging
Pinheiro, Manuel
2015-01-01
In this work it is proposed a medical image segmentation pipeline for accurate bone segmentation from CT imaging. It is a two-step methodology, with a pre-segmentation step and a segmentation refinement step. First, the user performs a rough segmenting of the desired region of interest. Next, a fully automatic refinement step is applied to the pre-segmented data. The automatic segmentation refinement is composed by several sub-stpng, namely image deconvolution, image cropping and interpolation. The user-defined pre-segmentation is then refined over the deconvolved, cropped, and up-sampled version of the image. The algorithm is applied in the segmentation of CT images of a composite femur bone, reconstructed with different reconstruction protocols. Segmentation outcomes are validated against a gold standard model obtained with coordinate measuring machine Nikon Metris LK V20 with a digital line scanner LC60-D that guarantees an accuracy of 28 $\\mu m$. High sub-pixel accuracy models were obtained for all tested...
Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data.
Amat, Fernando; Lemon, William; Mossing, Daniel P; McDole, Katie; Wan, Yinan; Branson, Kristin; Myers, Eugene W; Keller, Philipp J
2014-09-01
The comprehensive reconstruction of cell lineages in complex multicellular organisms is a central goal of developmental biology. We present an open-source computational framework for the segmentation and tracking of cell nuclei with high accuracy and speed. We demonstrate its (i) generality by reconstructing cell lineages in four-dimensional, terabyte-sized image data sets of fruit fly, zebrafish and mouse embryos acquired with three types of fluorescence microscopes, (ii) scalability by analyzing advanced stages of development with up to 20,000 cells per time point at 26,000 cells min(-1) on a single computer workstation and (iii) ease of use by adjusting only two parameters across all data sets and providing visualization and editing tools for efficient data curation. Our approach achieves on average 97.0% linkage accuracy across all species and imaging modalities. Using our system, we performed the first cell lineage reconstruction of early Drosophila melanogaster nervous system development, revealing neuroblast dynamics throughout an entire embryo.
An improved image reconstruction method for optical intensity correlation Imaging
Gao, Xin; Feng, Lingjie; Li, Xiyu
2016-12-01
The intensity correlation imaging method is a novel kind of interference imaging and it has favorable prospects in deep space recognition. However, restricted by the low detecting signal-to-noise ratio (SNR), it's usually very difficult to obtain high-quality image of deep space object like high-Earth-orbit (HEO) satellite with existing phase retrieval methods. In this paper, based on the priori intensity statistical distribution model of the object and characteristics of measurement noise distribution, an improved method of Prior Information Optimization (PIO) is proposed to reduce the ambiguous images and accelerate the phase retrieval procedure thus realizing fine image reconstruction. As the simulations and experiments show, compared to previous methods, our method could acquire higher-resolution images with less error in low SNR condition.
Prior image constrained image reconstruction in emerging computed tomography applications
Brunner, Stephen T.
Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation
Image reconstruction using projections from a few views by discrete steering combined with DART
Kwon, Junghyun; Song, Samuel M.; Kauke, Brian; Boyd, Douglas P.
2012-03-01
In this paper, we propose an algebraic reconstruction technique (ART) based discrete tomography method to reconstruct an image accurately using projections from a few views. We specifically consider the problem of reconstructing an image of bottles filled with various types of liquids from X-ray projections. By exploiting the fact that bottles are usually filled with homogeneous material, we show that it is possible to obtain accurate reconstruction with only a few projections by an ART based algorithm. In order to deal with various types of liquids in our problem, we first introduce our discrete steering method which is a generalization of the binary steering approach for our proposed multi-valued discrete reconstruction. The main idea of the steering approach is to use slowly varying thresholds instead of fixed thresholds. We further improve reconstruction accuracy by reducing the number of variables in ART by combining our discrete steering with the discrete ART (DART) that fixes the values of interior pixels of segmented regions considered as reliable. By simulation studies, we show that our proposed discrete steering combined with DART yields superior reconstruction than both discrete steering only and DART only cases. The resulting reconstructions are quite accurate even with projections using only four views.
Homotopy Based Reconstruction from Acoustic Images
DEFF Research Database (Denmark)
Sharma, Ojaswa
of the inherent arrangement. The problem of reconstruction from arbitrary cross sections is a generic problem and is also shown to be solved here using the mathematical tool of continuous deformations. As part of a complete processing, segmentation using level set methods is explored for acoustic images and fast...... GPU (Graphics Processing Unit) based methods are suggested for a streaming computation on large volumes of data. Validation of results for acoustic images is not straightforward due to unavailability of ground truth. Accuracy figures for the suggested methods are provided using phantom object......This thesis presents work in the direction of generating smooth surfaces from linear cross sections embedded in R2 and R3 using homotopy continuation. The methods developed in this research are generic and can be applied to higher dimensions as well. Two types of problems addressed in this research...
Singular value decomposition-based 2D image reconstruction for computed tomography.
Liu, Rui; He, Lu; Luo, Yan; Yu, Hengyong
2017-01-01
Singular value decomposition (SVD)-based 2D image reconstruction methods are developed and evaluated for a broad class of inverse problems for which there are no analytical solutions. The proposed methods are fast and accurate for reconstructing images in a non-iterative fashion. The multi-resolution strategy is adopted to reduce the size of the system matrix to reconstruct large images using limited memory capacity. A modified high-contrast Shepp-Logan phantom, a low-contrast FORBILD head phantom, and a physical phantom are employed to evaluate the proposed methods with different system configurations. The results show that the SVD methods can accurately reconstruct images from standard scan and interior scan projections and that they outperform other benchmark methods. The general SVD method outperforms the other SVD methods. The truncated SVD and Tikhonov regularized SVD methods accurately reconstruct a region-of-interest (ROI) from an internal scan with a known sub-region inside the ROI. Furthermore, the SVD methods are much faster and more flexible than the benchmark algorithms, especially in the ROI reconstructions in our experiments.
Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors.
Chan, Stanley H; Elgendy, Omar A; Wang, Xiran
2016-11-22
A quanta image sensor (QIS) is a class of single-photon imaging devices that measure light intensity using oversampled binary observations. Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal of image reconstruction is to recover the underlying image from these bits. In this paper, we present a non-iterative image reconstruction algorithm for QIS. Unlike existing reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising algorithm. By skipping the usual optimization procedure, we achieve orders of magnitude improvement in speed and even better image reconstruction quality. We validate the new algorithm on synthetic datasets, as well as real videos collected by one-bit single-photon avalanche diode (SPAD) cameras.
Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors
Directory of Open Access Journals (Sweden)
Stanley H. Chan
2016-11-01
Full Text Available A quanta image sensor (QIS is a class of single-photon imaging devices that measure light intensity using oversampled binary observations. Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal of image reconstruction is to recover the underlying image from these bits. In this paper, we present a non-iterative image reconstruction algorithm for QIS. Unlike existing reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising algorithm. By skipping the usual optimization procedure, we achieve orders of magnitude improvement in speed and even better image reconstruction quality. We validate the new algorithm on synthetic datasets, as well as real videos collected by one-bit single-photon avalanche diode (SPAD cameras.
Gibbs artifact reduction for POCS super-resolution image reconstruction
Institute of Scientific and Technical Information of China (English)
Chuangbai XIAO; Jing YU; Kaina SU
2008-01-01
The topic of super-resolution image reconstruc-tion has recently received considerable attention among the research community. Super-resolution image reconstruc-tion methods attempt to create a single high-resolution image from a number of low-resolution images (or a video sequence). The method of projections onto convex sets (POCS) for super-resolution image reconstruction attracts many researchers' attention. In this paper, we propose an improvement to reduce the amount of Gibbs artifacts pre-senting on the edges of the high-resolution image recon-structed by the POCS method. The proposed method weights the blur PSF centered at an edge pixel with an exponential function, and consequently decreases the coef-ficients of the PSF in the direction orthogonal to the edge. Experiment results show that the modification reduces effectively the visibility of Gibbs artifacts on edges and improves obviously the quality of the reconstructed high-resolution image.
Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)
McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian
2006-03-01
To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the
3D Reconstruction of Human Motion from Monocular Image Sequences.
Wandt, Bastian; Ackermann, Hanno; Rosenhahn, Bodo
2016-08-01
This article tackles the problem of estimating non-rigid human 3D shape and motion from image sequences taken by uncalibrated cameras. Similar to other state-of-the-art solutions we factorize 2D observations in camera parameters, base poses and mixing coefficients. Existing methods require sufficient camera motion during the sequence to achieve a correct 3D reconstruction. To obtain convincing 3D reconstructions from arbitrary camera motion, our method is based on a-priorly trained base poses. We show that strong periodic assumptions on the coefficients can be used to define an efficient and accurate algorithm for estimating periodic motion such as walking patterns. For the extension to non-periodic motion we propose a novel regularization term based on temporal bone length constancy. In contrast to other works, the proposed method does not use a predefined skeleton or anthropometric constraints and can handle arbitrary camera motion. We achieve convincing 3D reconstructions, even under the influence of noise and occlusions. Multiple experiments based on a 3D error metric demonstrate the stability of the proposed method. Compared to other state-of-the-art methods our algorithm shows a significant improvement.
Neural net classification and LMS reconstruction to halftone images
Chang, Pao-Chi; Yu, Che-Sheng
1998-01-01
The objective of this work is to reconstruct high quality gray-level images from halftone images, or the inverse halftoning process. We develop high performance halftone reconstruction methods for several commonly used halftone techniques. For better reconstruction quality, image classification based on halftone techniques is placed before the reconstruction process so that the halftone reconstruction process can be fine tuned for each halftone technique. The classification is based on enhanced 1D correlation of halftone images and processed with a three- layer back propagation neural network. This classification method reached 100 percent accuracy with a limited set of images processed by dispersed-dot ordered dithering, clustered-dot ordered dithering, constrained average, and error diffusion methods in our experiments. For image reconstruction, we apply the least-mean-square adaptive filtering algorithm which intends to discover the optimal filter weights and the mask shapes. As a result, it yields very good reconstruction image quality. The error diffusion yields the best reconstructed quality among the halftone methods. In addition, the LMS method generates optimal image masks which are significantly different for each halftone method. These optimal masks can also be applied to more sophisticated reconstruction methods as the default filter masks.
Photogrammetric 3D reconstruction using mobile imaging
Fritsch, Dieter; Syll, Miguel
2015-03-01
In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.
鞍形CT的感兴趣区图像重建%ROI-image Reconstruction for a Saddle Trajectory
Institute of Scientific and Technical Information of China (English)
夏丹; 余立锋; 邹宇
2005-01-01
Recently, we have developed a general formula for 3D cone-beam CT reconstruction, which can accommondate general, smooth trajectories. From the formula, algorithms can be derived for image reconstruction within a region of interest (ROI) from truncated data. In this work, we apply the derived backprojection filteration (BPF) algorithm and the minimum-data filtered backprojection (MD-FBP) algorithm to reconstructing ROI images from cone-beam projection data acquired with a saddle trajec-tory. Our numerical results in these studies demonstrate that the BPF and MD-FBP algorithms can accurately reconstruct ROI images from truncated data.
Model-Based Reconstructive Elasticity Imaging Using Ultrasound
Directory of Open Access Journals (Sweden)
Salavat R. Aglyamov
2007-01-01
Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.
CDP mapping and image reconstruction by using offset VSP data
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Because zero-offset VSP (Vertical Seismic Profile) data can only provide the information of rock properties and structure in the area around the Fresnel zone within the well, the scheme of VSP with offset was developed to acquire the reflection information away from the borehole in order to widen the range of VSP survey and to improve the precision of imaging.In this paper, we present a new CDP (Common Depth Point) mapping approach to image the reflecting structure by using offset VSP data. For the processing of offset VSP data, we firstly separated the up-going and down-going wave-fields from VSP data by means of F-K filtering technique, and we can calculate the mapping conditions (position and reflecting traveltime for CDP point) in homogeneous media, and then reconstruct the inner structure of the earth.This method is tested by using the offset VSP data which are used to simulate the case of super-deep borehole by means of finite-difference method. The imaged structure matches the real model very well. The results show that the method present here could accurately image the inner structure of the earth if the deviation of initial velocity model from the true model is less than 10%. Finally, we presented the imaged results for the real offset data by using this method.
TREE STEM RECONSTRUCTION USING VERTICAL FISHEYE IMAGES: A PRELIMINARY STUDY
Directory of Open Access Journals (Sweden)
A. Berveglieri
2016-06-01
Full Text Available A preliminary study was conducted to assess a tree stem reconstruction technique with panoramic images taken with fisheye lenses. The concept is similar to the Structure from Motion (SfM technique, but the acquisition and data preparation rely on fisheye cameras to generate a vertical image sequence with height variations of the camera station. Each vertical image is rectified to four vertical planes, producing horizontal lateral views. The stems in the lateral view are rectified to the same scale in the image sequence to facilitate image matching. Using bundle adjustment, the stems are reconstructed, enabling later measurement and extraction of several attributes. The 3D reconstruction was performed with the proposed technique and compared with SfM. The preliminary results showed that the stems were correctly reconstructed by using the lateral virtual images generated from the vertical fisheye images and with the advantage of using fewer images and taken from one single station.
Tree STEM Reconstruction Using Vertical Fisheye Images: a Preliminary Study
Berveglieri, A.; Tommaselli, A. M. G.
2016-06-01
A preliminary study was conducted to assess a tree stem reconstruction technique with panoramic images taken with fisheye lenses. The concept is similar to the Structure from Motion (SfM) technique, but the acquisition and data preparation rely on fisheye cameras to generate a vertical image sequence with height variations of the camera station. Each vertical image is rectified to four vertical planes, producing horizontal lateral views. The stems in the lateral view are rectified to the same scale in the image sequence to facilitate image matching. Using bundle adjustment, the stems are reconstructed, enabling later measurement and extraction of several attributes. The 3D reconstruction was performed with the proposed technique and compared with SfM. The preliminary results showed that the stems were correctly reconstructed by using the lateral virtual images generated from the vertical fisheye images and with the advantage of using fewer images and taken from one single station.
Reconstruction of Optical Thickness from Hoffman Modulation Contrast Images
DEFF Research Database (Denmark)
Olsen, Niels Holm; Sporring, Jon; Nielsen, Mads;
2003-01-01
Hoffman microscopy imaging systems are part of numerous fertility clinics world-wide. We discuss the physics of the Hoffman imaging system from optical thickness to image intensity, implement a simple, yet fast, reconstruction algorithm using Fast Fourier Transformation and discuss the usability...... of the method on a number of cells from a human embryo. Novelty is identifying the non-linearity of a typical Hoffman imaging system, and the application of Fourier Transformation to reconstruct the optical thickness....
Undersampled MR Image Reconstruction with Data-Driven Tight Frame
Jianbo Liu; Shanshan Wang; Xi Peng; Dong Liang
2015-01-01
Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven ...
Energy Technology Data Exchange (ETDEWEB)
Tan, Tien Jin, E-mail: tien_jin_tan@cgh.com.sg [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada); Aljefri, Ahmad M. [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada); Clarkson, Paul W.; Masri, Bassam A. [Department of Orthopaedics, University of British Columbia, Vancouver, BC (Canada); Ouellette, Hugue A.; Munk, Peter L.; Mallinson, Paul I. [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada)
2015-09-15
Highlights: • Advances in reconstructive orthopaedic techniques now allow for limb salvage and prosthetic reconstruction procedures to be performed on patients who would otherwise be required to undergo debilitating limb amputations for malignant bone tumours. • The resulting post-operative imaging of such cases can be daunting for the radiologist to interpret, particularly in the presence of distorted anatomy and unfamiliar hardware. • This article reviews the indications for limb salvage surgery, prosthetic reconstruction devices involved, expected post-operative imaging findings, as well as the potential hardware related complications that may be encountered in the management of such cases. • By being aware of the various types of reconstructive techniques used in limb salvage surgery as well as the potential complications, the reporting radiologist should possess greater confidence in making an accurate assessment of the expected post-operative imaging findings in the management of such cases. - Abstract: Advances in reconstructive orthopaedic techniques now allow for limb salvage and prosthetic reconstruction procedures to be performed on patients who would otherwise be required to undergo debilitating limb amputations for malignant bone tumours. The resulting post-operative imaging of such cases can be daunting for the radiologist to interpret, particularly in the presence of distorted anatomy and unfamiliar hardware. This article reviews the indications for limb salvage surgery, prosthetic reconstruction devices involved, expected post-operative imaging findings, as well as the potential hardware related complications that may be encountered in the management of such cases.
Three-dimensional microscopy and sectional image reconstruction using optical scanning holography.
Lam, Edmund Y; Zhang, Xin; Vo, Huy; Poon, Ting-Chung; Indebetouw, Guy
2009-12-01
Fast acquisition and high axial resolution are two primary requirements for three-dimensional microscopy. However, they are sometimes conflicting: imaging modalities such as confocal imaging can deliver superior resolution at the expense of sequential acquisition at different axial planes, which is a time-consuming process. Optical scanning holography (OSH) promises to deliver a good trade-off between these two goals. With just a single scan, we can capture the entire three-dimensional volume in a digital hologram; the data can then be processed to obtain the individual sections. An accurate modeling of the imaging system is key to devising an appropriate image reconstruction algorithm, especially for real data where random noise and other imaging imperfections must be taken into account. In this paper we demonstrate sectional image reconstruction by applying an inverse imaging sectioning technique to experimental OSH data of biological specimens and visualizing the sections using the OSA Interactive Science Publishing software.
Accelerated gradient methods for total-variation-based CT image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Joergensen, Jakob H.; Hansen, Per Christian [Technical Univ. of Denmark, Lyngby (Denmark). Dept. of Informatics and Mathematical Modeling; Jensen, Tobias L.; Jensen, Soeren H. [Aalborg Univ. (Denmark). Dept. of Electronic Systems; Sidky, Emil Y.; Pan, Xiaochuan [Chicago Univ., Chicago, IL (United States). Dept. of Radiology
2011-07-01
Total-variation (TV)-based CT image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-intensive methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits prohibitively slow convergence. In the present work we address the question of how to reduce the number of gradient method iterations needed to achieve a high-accuracy TV reconstruction. We consider the use of two accelerated gradient-based methods, GPBB and UPN, to solve the 3D-TV minimization problem in CT image reconstruction. The former incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping criterion to ensure that the TV reconstruction has indeed been found. An implementation of the methods (in C with interface to Matlab) is available for download from http://www2.imm.dtu.dk/~pch/TVReg/. We compare the proposed methods with the standard gradient method, applied to a 3D test problem with synthetic few-view data. We find experimentally that for realistic parameters the proposed methods significantly outperform the standard gradient method. (orig.)
Accelerated gradient methods for total-variation-based CT image reconstruction
Jørgensen, Jakob Heide; Hansen, Per Christian; Jensen, Søren Holdt; Sidky, Emil Y; Pan, Xiaochuan
2011-01-01
Total-variation (TV)-based Computed Tomography (CT) image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is very well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is much more demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large-scale systems arising in CT image reconstruction preclude the use of memory-demanding methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits slow convergence. In the present work we consider the use of two accelerated gradient-based methods, GPBB and UP...
Undersampled MR Image Reconstruction with Data-Driven Tight Frame
Directory of Open Access Journals (Sweden)
Jianbo Liu
2015-01-01
Full Text Available Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.
Undersampled MR Image Reconstruction with Data-Driven Tight Frame.
Liu, Jianbo; Wang, Shanshan; Peng, Xi; Liang, Dong
2015-01-01
Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.
Reconstruction of biofilm images: combining local and global structural parameters
Energy Technology Data Exchange (ETDEWEB)
Resat, Haluk; Renslow, Ryan S.; Beyenal, Haluk
2014-10-20
Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parameters into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process.
Directory of Open Access Journals (Sweden)
Muralidhar Mupparapu
2013-01-01
Full Text Available This review is the first of series of CBCT. Multiplanar reconstructions for continuing education in three dimensional head and neck anatomy. This review gives the reader the needed anatomical references and clinical relevance for accurate interpretation of CBCT anatomy. The information is useful to all dental clinicians. All images are labeled and complete with legends. Only bone window settings are used for display of the CBCT images. The selected slices are displayed at a resolution of 300 micrometers.
Imaging tests for accurate diagnosis of acute biliary pancreatitis.
Şurlin, Valeriu; Săftoiu, Adrian; Dumitrescu, Daniela
2014-11-28
Gallstones represent the most frequent aetiology of acute pancreatitis in many statistics all over the world, estimated between 40%-60%. Accurate diagnosis of acute biliary pancreatitis (ABP) is of outmost importance because clearance of lithiasis [gallbladder and common bile duct (CBD)] rules out recurrences. Confirmation of biliary lithiasis is done by imaging. The sensitivity of the ultrasonography (US) in the detection of gallstones is over 95% in uncomplicated cases, but in ABP, sensitivity for gallstone detection is lower, being less than 80% due to the ileus and bowel distension. Sensitivity of transabdominal ultrasonography (TUS) for choledocolithiasis varies between 50%-80%, but the specificity is high, reaching 95%. Diameter of the bile duct may be orientative for diagnosis. Endoscopic ultrasonography (EUS) seems to be a more effective tool to diagnose ABP rather than endoscopic retrograde cholangiopancreatography (ERCP), which should be performed only for therapeutic purposes. As the sensitivity and specificity of computerized tomography are lower as compared to state-of-the-art magnetic resonance cholangiopancreatography (MRCP) or EUS, especially for small stones and small diameter of CBD, the later techniques are nowadays preferred for the evaluation of ABP patients. ERCP has the highest accuracy for the diagnosis of choledocholithiasis and is used as a reference standard in many studies, especially after sphincterotomy and balloon extraction of CBD stones. Laparoscopic ultrasonography is a useful tool for the intraoperative diagnosis of choledocholithiasis. Routine exploration of the CBD in cases of patients scheduled for cholecystectomy after an attack of ABP was not proven useful. A significant rate of the so-called idiopathic pancreatitis is actually caused by microlithiasis and/or biliary sludge. In conclusion, the general algorithm for CBD stone detection starts with anamnesis, serum biochemistry and then TUS, followed by EUS or MRCP. In the end
Sub- Angstrom microscopy through incoherent imaging and image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Pennycook, S.J.; Jesson, D.E.; Chisholm, M.F. (Oak Ridge National Lab., TN (United States)); Ferridge, A.G.; Seddon, M.J. (Wellcome Research Lab., Beckenham (United Kingdom))
1992-03-01
Z-contrast scanning transmission electron microscopy (STEM) with a high-angle annular detector breaks the coherence of the imaging process, and provides an incoherent image of a crystal projection. Even in the presence of strong dynamical diffraction, the image can be accurately described as a convolution between an object function, sharply peaked at the projected atomic sites, and the probe intensity profile. Such an image can be inverted intuitively without the need for model structures, and therefore provides the important capability to reveal unanticipated interfacial arrangements. It represents a direct image of the crystal projection, revealing the location of the atomic columns and their relative high-angle scattering power. Since no phase is associated with a peak in the object function or the contrast transfer function, extension to higher resolution is also straightforward. Image restoration techniques such as maximum entropy, in conjunction with the 1.3 {Angstrom} probe anticipated for a 300 kV STEM, appear to provide a simple and robust route to the achievement of sub-{Angstrom} resolution electron microscopy.
Sub-{Angstrom} microscopy through incoherent imaging and image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Pennycook, S.J.; Jesson, D.E.; Chisholm, M.F. [Oak Ridge National Lab., TN (United States); Ferridge, A.G.; Seddon, M.J. [Wellcome Research Lab., Beckenham (United Kingdom)
1992-03-01
Z-contrast scanning transmission electron microscopy (STEM) with a high-angle annular detector breaks the coherence of the imaging process, and provides an incoherent image of a crystal projection. Even in the presence of strong dynamical diffraction, the image can be accurately described as a convolution between an object function, sharply peaked at the projected atomic sites, and the probe intensity profile. Such an image can be inverted intuitively without the need for model structures, and therefore provides the important capability to reveal unanticipated interfacial arrangements. It represents a direct image of the crystal projection, revealing the location of the atomic columns and their relative high-angle scattering power. Since no phase is associated with a peak in the object function or the contrast transfer function, extension to higher resolution is also straightforward. Image restoration techniques such as maximum entropy, in conjunction with the 1.3 {Angstrom} probe anticipated for a 300 kV STEM, appear to provide a simple and robust route to the achievement of sub-{Angstrom} resolution electron microscopy.
Photoacoustic image reconstruction based on Bayesian compressive sensing algorithm
Institute of Scientific and Technical Information of China (English)
Mingjian Sun; Naizhang Feng; Yi Shen; Jiangang Li; Liyong Ma; Zhenghua Wu
2011-01-01
The photoacoustic tomography (PAT) method, based on compressive sensing (CS) theory, requires that,for the CS reconstruction, the desired image should have a sparse representation in a known transform domain. However, the sparsity of photoacoustic signals is destroyed because noises always exist. Therefore,the original sparse signal cannot be effectively recovered using the general reconstruction algorithm. In this study, Bayesian compressive sensing (BCS) is employed to obtain highly sparse representations of photoacoustic images based on a set of noisy CS measurements. Results of simulation demonstrate that the BCS-reconstructed image can achieve superior performance than other state-of-the-art CS-reconstruction algorithms.%@@ The photoacoustic tomography (PAT) method, based on compressive sensing (CS) theory, requires that,for the CS reconstruction, the desired image should have a sparse representation in a known transform domain.However, the sparsity of photoacoustic signals is destroyed because noises always exist.Therefore,the original sparse signal cannot be effectively recovered using the general reconstruction algorithm.In this study, Bayesian compressive sensing (BCS) is employed to obtain highly sparse representations of photoacoustic inages based on a set of noisy CS measurements.Results of simulation demonstrate that the BCS-reconstructed image can achieve superior performance than other state-of-the-art CS-reconstruction algorithms.
Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging
Desmal, Abdulla
2016-03-01
synthetically generated or actually measured scattered fields, show that the images recovered by these sparsity-regularized methods are sharper and more accurate than those produced by existing methods. The methods developed in this work have potential application areas ranging from oil/gas reservoir engineering to biological imaging where sparse domains naturally exist.
Quantitative image quality evaluation for cardiac CT reconstructions
Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.; Balhorn, William; Okerlund, Darin R.
2016-03-01
Maintaining image quality in the presence of motion is always desirable and challenging in clinical Cardiac CT imaging. Different image-reconstruction algorithms are available on current commercial CT systems that attempt to achieve this goal. It is widely accepted that image-quality assessment should be task-based and involve specific tasks, observers, and associated figures of merits. In this work, we developed an observer model that performed the task of estimating the percentage of plaque in a vessel from CT images. We compared task performance of Cardiac CT image data reconstructed using a conventional FBP reconstruction algorithm and the SnapShot Freeze (SSF) algorithm, each at default and optimal reconstruction cardiac phases. The purpose of this work is to design an approach for quantitative image-quality evaluation of temporal resolution for Cardiac CT systems. To simulate heart motion, a moving coronary type phantom synchronized with an ECG signal was used. Three different percentage plaques embedded in a 3 mm vessel phantom were imaged multiple times under motion free, 60 bpm, and 80 bpm heart rates. Static (motion free) images of this phantom were taken as reference images for image template generation. Independent ROIs from the 60 bpm and 80 bpm images were generated by vessel tracking. The observer performed estimation tasks using these ROIs. Ensemble mean square error (EMSE) was used as the figure of merit. Results suggest that the quality of SSF images is superior to the quality of FBP images in higher heart-rate scans.
Krings, Thomas; Mauerhofer, Eric
2011-06-01
This work improves the reliability and accuracy in the reconstruction of the total isotope activity content in heterogeneous nuclear waste drums containing point sources. The method is based on χ(2)-fits of the angular dependent count rate distribution measured during a drum rotation in segmented gamma scanning. A new description of the analytical calculation of the angular count rate distribution is introduced based on a more precise model of the collimated detector. The new description is validated and compared to the old description using MCNP5 simulations of angular dependent count rate distributions of Co-60 and Cs-137 point sources. It is shown that the new model describes the angular dependent count rate distribution significantly more accurate compared to the old model. Hence, the reconstruction of the activity is more accurate and the errors are considerably reduced that lead to more reliable results. Furthermore, the results are compared to the conventional reconstruction method assuming a homogeneous matrix and activity distribution.
Rumple, C.; Richter, J.; Craven, B. A.; Krane, M.
2012-11-01
A summary of the research being carried out by our multidisciplinary team to better understand the form and function of the nose in different mammalian species that include humans, carnivores, ungulates, rodents, and marine animals will be presented. The mammalian nose houses a convoluted airway labyrinth, where two hallmark features of mammals occur, endothermy and olfaction. Because of the complexity of the nasal cavity, the anatomy and function of these upper airways remain poorly understood in most mammals. However, recent advances in high-resolution medical imaging, computational modeling, and experimental flow measurement techniques are now permitting the study of airflow and respiratory and olfactory transport phenomena in anatomically-accurate reconstructions of the nasal cavity. Here, we focus on efforts to manufacture transparent, anatomically-accurate models for stereo particle image velocimetry (SPIV) measurements of nasal airflow. Challenges in the design and manufacture of index-matched anatomical models are addressed and preliminary SPIV measurements are presented. Such measurements will constitute a validation database for concurrent computational fluid dynamics (CFD) simulations of mammalian respiration and olfaction. Supported by the National Science Foundation.
Basis Functions in Image Reconstruction From Projections: A Tutorial Introduction
Herman, Gabor T.
2015-11-01
The series expansion approaches to image reconstruction from projections assume that the object to be reconstructed can be represented as a linear combination of fixed basis functions and the task of the reconstruction algorithm is to estimate the coefficients in such a linear combination based on the measured projection data. It is demonstrated that using spherically symmetric basis functions (blobs), instead of ones based on the more traditional pixels, yields superior reconstructions of medically relevant objects. The demonstration uses simulated computerized tomography projection data of head cross-sections and the series expansion method ART for the reconstruction. In addition to showing the results of one anecdotal example, the relative efficacy of using pixel and blob basis functions in image reconstruction from projections is also evaluated using a statistical hypothesis testing based task oriented comparison methodology. The superiority of the efficacy of blob basis functions over that of pixel basis function is found to be statistically significant.
Sparse Reconstruction for Micro Defect Detection in Acoustic Micro Imaging
Directory of Open Access Journals (Sweden)
Yichun Zhang
2016-10-01
Full Text Available Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging. A finite element model with a micro defect is developed to emulate the physical scanning. Then we obtain the point spread function, a blur kernel for sparse reconstruction. We reconstruct deblurred images from the oversampled C-scan images based on l1-norm regularization, which can enhance the signal-to-noise ratio and improve the accuracy of micro defect detection. The method is further verified by experimental data. The results demonstrate that the sparse reconstruction is effective for micro defect detection in acoustic micro imaging.
Kudrolli, Haris A.
2001-04-01
A three dimensional (3D) reconstruction procedure for Positron Emission Tomography (PET) based on inverse Monte Carlo analysis is presented. PET is a medical imaging modality which employs a positron emitting radio-tracer to give functional images of an organ's metabolic activity. This makes PET an invaluable tool in the detection of cancer and for in-vivo biochemical measurements. There are a number of analytical and iterative algorithms for image reconstruction of PET data. Analytical algorithms are computationally fast, but the assumptions intrinsic in the line integral model limit their accuracy. Iterative algorithms can apply accurate models for reconstruction and give improvements in image quality, but at an increased computational cost. These algorithms require the explicit calculation of the system response matrix, which may not be easy to calculate. This matrix gives the probability that a photon emitted from a certain source element will be detected in a particular detector line of response. The ``Three Dimensional Stochastic Sampling'' (SS3D) procedure implements iterative algorithms in a manner that does not require the explicit calculation of the system response matrix. It uses Monte Carlo techniques to simulate the process of photon emission from a source distribution and interaction with the detector. This technique has the advantage of being able to model complex detector systems and also take into account the physics of gamma ray interaction within the source and detector systems, which leads to an accurate image estimate. A series of simulation studies was conducted to validate the method using the Maximum Likelihood - Expectation Maximization (ML-EM) algorithm. The accuracy of the reconstructed images was improved by using an algorithm that required a priori knowledge of the source distribution. Means to reduce the computational time for reconstruction were explored by using parallel processors and algorithms that had faster convergence rates
Energy Technology Data Exchange (ETDEWEB)
Chang, L.T.
1976-05-01
Two techniques for radionuclide imaging and reconstruction have been studied;; both are used for improvement of depth resolution. The first technique is called coded aperture imaging, which is a technique of tomographic imaging. The second technique is a special 3-D image reconstruction method which is introduced as an improvement to the so called focal-plane tomography. (auth)
Image Reconstruction Algorithm for Electrical Charge Tomography System
Directory of Open Access Journals (Sweden)
M. F. Rahmat
2010-01-01
Full Text Available Problem statement: Many problems in scientific computing can be formulated as inverse problem. A vast majority of these problems are ill-posed problems. In Electrical Charge Tomography (EChT, normally the sensitivity matrix generated from forward modeling is very ill-condition. This condition posts difficulties to the inverse problem solution especially in the accuracy and stability of the image being reconstructed. The objective of this study is to reconstruct the image cross-section of the material in pipeline gravity dropped mode conveyor as well to solve the ill-condition of matrix sensitivity. Approach: Least Square with Regularization (LSR method had been introduced to reconstruct the image and the electrodynamics sensor was used to capture the data that installed around the pipe. Results: The images were validated using digital imaging technique and Singular Value Decomposition (SVD method. The results showed that image reconstructed by this method produces a good promise in terms of accuracy and stability. Conclusion: This implied that LSR method provides good and promising result in terms of accuracy and stability of the image being reconstructed. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.
Rau, Urvashi; Owen, Frazer N
2016-01-01
Many deep wide-band wide-field radio interferometric surveys are being designed to accurately measure intensities, spectral indices and polarization properties of faint source populations. In this paper we compare various wideband imaging methods to evaluate the accuracy to which intensities and spectral indices of sources close to the confusion limit can be reconstructed. We simulated a wideband single-pointing (C-array, L-Band (1-2GHz)) and 46-pointing mosaic(D-array, C-Band (4-8GHz)) JVLA observation using realistic brightness distribution ranging from $1\\mu$Jy to $100m$Jy and time-,frequency-, polarization- and direction-dependent instrumental effects. The main results from these comparisons are (a) errors in the reconstructed intensities and spectral indices are larger for weaker sources even in the absence of simulated noise, (b) errors are systematically lower for joint reconstruction methods (such as MT-MFS) along with A-Projection for accurate primary beam correction, and (c) use of MT-MFS for image ...
Visions of Reconstruction: Layers of Moving Images
Paalman, Floris Jan Willem
2015-01-01
abstractAfter WWII, films accompanied the reconstruction of Europe’s destroyed cities. Many contained historical footage. How was this material used, to articulate visions of reconstruction, what happened to the material later on, and how do the films relate to municipal film archives? This question
Fully Automatic 3D Reconstruction of Histological Images
Bagci, Ulas
2009-01-01
In this paper, we propose a computational framework for 3D volume reconstruction from 2D histological slices using registration algorithms in feature space. To improve the quality of reconstructed 3D volume, first, intensity variations in images are corrected by an intensity standardization process which maps image intensity scale to a standard scale where similar intensities correspond to similar tissues. Second, a subvolume approach is proposed for 3D reconstruction by dividing standardized slices into groups. Third, in order to improve the quality of the reconstruction process, an automatic best reference slice selection algorithm is developed based on an iterative assessment of image entropy and mean square error of the registration process. Finally, we demonstrate that the choice of the reference slice has a significant impact on registration quality and subsequent 3D reconstruction.
Rahmim, Arman; Tang, Jing; Zaidi, Habib
2009-08-01
In this article, the authors review novel techniques in the emerging field of spatiotemporal four-dimensional (4D) positron emission tomography (PET) image reconstruction. The conventional approach to dynamic PET imaging, involving independent reconstruction of individual PET frames, can suffer from limited temporal resolution, high noise (especially when higher frame sampling is introduced to better capture fast dynamics), as well as complex reconstructed image noise distributions that can be very difficult and time consuming to model in kinetic parameter estimation tasks. Various approaches that seek to address some or all of these limitations are described, including techniques that utilize (a) iterative temporal smoothing, (b) advanced temporal basis functions, (c) principal components transformation of the dynamic data, (d) wavelet-based techniques, as well as (e) direct kinetic parameter estimation methods. Future opportunities and challenges with regards to the adoption of 4D and higher dimensional image reconstruction techniques are also outlined.
MREJ: MRE elasticity reconstruction on ImageJ.
Xiang, Kui; Zhu, Xia Li; Wang, Chang Xin; Li, Bing Nan
2013-08-01
Magnetic resonance elastography (MRE) is a promising method for health evaluation and disease diagnosis. It makes use of elastic waves as a virtual probe to quantify soft tissue elasticity. The wave actuator, imaging modality and elasticity interpreter are all essential components for an MRE system. Efforts have been made to develop more effective actuating mechanisms, imaging protocols and reconstructing algorithms. However, translating MRE wave images into soft tissue elasticity is a nontrivial issue for health professionals. This study contributes an open-source platform - MREJ - for MRE image processing and elasticity reconstruction. It is established on the widespread image-processing program ImageJ. Two algorithms for elasticity reconstruction were implemented with spatiotemporal directional filtering. The usability of the method is shown through virtual palpation on different phantoms and patients. Based on the results, we conclude that MREJ offers the MRE community a convenient and well-functioning program for image processing and elasticity interpretation.
Sparsity-constrained PET image reconstruction with learned dictionaries
Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie
2016-09-01
PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging.
An adaptive reconstruction algorithm for spectral CT regularized by a reference image
Wang, Miaoshi; Zhang, Yanbo; Liu, Rui; Guo, Shuxu; Yu, Hengyong
2016-12-01
The photon counting detector based spectral CT system is attracting increasing attention in the CT field. However, the spectral CT is still premature in terms of both hardware and software. To reconstruct high quality spectral images from low-dose projections, an adaptive image reconstruction algorithm is proposed that assumes a known reference image (RI). The idea is motivated by the fact that the reconstructed images from different spectral channels are highly correlated. If a high quality image of the same object is known, it can be used to improve the low-dose reconstruction of each individual channel. This is implemented by maximizing the patch-wise correlation between the object image and the RI. Extensive numerical simulations and preclinical mouse study demonstrate the feasibility and merits of the proposed algorithm. It also performs well for truncated local projections, and the surrounding area of the region- of-interest (ROI) can be more accurately reconstructed. Furthermore, a method is introduced to adaptively choose the step length, making the algorithm more feasible and easier for applications.
Surface Reconstruction and Image Enhancement via $L^1$-Minimization
Dobrev, Veselin
2010-01-01
A surface reconstruction technique based on minimization of the total variation of the gradient is introduced. Convergence of the method is established, and an interior-point algorithm solving the associated linear programming problem is introduced. The reconstruction algorithm is illustrated on various test cases including natural and urban terrain data, and enhancement oflow-resolution or aliased images. Copyright © by SIAM.
Rau, U.; Bhatnagar, S.; Owen, F. N.
2016-11-01
Many deep wideband wide-field radio interferometric surveys are being designed to accurately measure intensities, spectral indices, and polarization properties of faint source populations. In this paper, we compare various wideband imaging methods to evaluate the accuracy to which intensities and spectral indices of sources close to the confusion limit can be reconstructed. We simulated a wideband single-pointing (C-array, L-Band (1-2 GHz)) and 46-pointing mosaic (D-array, C-Band (4-8 GHz)) JVLA observation using a realistic brightness distribution ranging from 1 μJy to 100 mJy and time-, frequency-, polarization-, and direction-dependent instrumental effects. The main results from these comparisons are (a) errors in the reconstructed intensities and spectral indices are larger for weaker sources even in the absence of simulated noise, (b) errors are systematically lower for joint reconstruction methods (such as Multi-Term Multi-Frequency-Synthesis (MT-MFS)) along with A-Projection for accurate primary beam correction, and (c) use of MT-MFS for image reconstruction eliminates Clean-bias (which is present otherwise). Auxiliary tests include solutions for deficiencies of data partitioning methods (e.g., the use of masks to remove clean bias and hybrid methods to remove sidelobes from sources left un-deconvolved), the effect of sources not at pixel centers, and the consequences of various other numerical approximations within software implementations. This paper also demonstrates the level of detail at which such simulations must be done in order to reflect reality, enable one to systematically identify specific reasons for every trend that is observed, and to estimate scientifically defensible imaging performance metrics and the associated computational complexity of the algorithms/analysis procedures. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.
Dynamic Data Updating Algorithm for Image Superresolution Reconstruction
Institute of Scientific and Technical Information of China (English)
TAN Bing; XU Qing; ZHANG Yan; XING Shuai
2006-01-01
A dynamic data updating algorithm for image superesolution is proposed. On the basis of Delaunay triangulation and its local updating property, this algorithm can update the changed region directly under the circumstances that only a part of the source images has been changed. For its high efficiency and adaptability, this algorithm can serve as a fast algorithm for image superesolution reconstruction.
Park, Min K.; Lee, Eun S.; Park, Jin Y.; Kang, Moon Gi; Kim, Jaihie
2002-02-01
The demand for high-resolution images is gradually increasing, whereas many imaging systems have been designed to enable a certain level of aliasing during image acquisition. In this sense, digital image processing approaches have recently been investigated to reconstruct a high-resolution image from aliased low-resolution images. However, since the subpixel motion information is assumed to be accurate in most conventional approaches, the satisfactory high-resolution image cannot be obtained when the subpixel motion information is inaccurate. Hence, we propose a new algorithm to reduce the distortion in the reconstructed high-resolution image due to the inaccuracy of subpixel motion information. For this purpose, we analyze the effect of inaccurate subpixel motion information on a high-resolution image reconstruction, and model it as zero-mean additive Gaussian errors added respectively to each low- resolution image. To reduce the distortion, we apply the modified multichannel image deconvolution approach to the problem. The validity of the proposed algorithm is demonstrated both theoretically and experimentally.
Acoustic imaging for temperature distribution reconstruction
Jia, Ruixi; Xiong, Qingyu; Liang, Shan
2016-12-01
For several industrial processes, such as burning and drying, temperature distribution is important because it can reflect the internal running state of industrial equipment and assist to develop control strategy and ensure safety in operation of industrial equipment. The principle of this technique is mainly based on the relationship between acoustic velocity and temperature. In this paper, an algorithm for temperature distribution reconstruction is considered. Compared with reconstruction results of simulation experiments with the least square algorithm and the proposed one, the latter indicates a better information reflection of temperature distribution and relatively higher reconstruction accuracy.
Acoustic imaging for temperature distribution reconstruction
Directory of Open Access Journals (Sweden)
Ruixi Jia
2016-12-01
Full Text Available For several industrial processes, such as burning and drying, temperature distribution is important because it can reflect the internal running state of industrial equipment and assist to develop control strategy and ensure safety in operation of industrial equipment. The principle of this technique is mainly based on the relationship between acoustic velocity and temperature. In this paper, an algorithm for temperature distribution reconstruction is considered. Compared with reconstruction results of simulation experiments with the least square algorithm and the proposed one, the latter indicates a better information reflection of temperature distribution and relatively higher reconstruction accuracy.
Online reconstruction of 3D magnetic particle imaging data
Knopp, T.; Hofmann, M.
2016-06-01
Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s-1. However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time.
Electromagnetic tomography (EMT): image reconstruction based on the inverse problem
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
Starting from Maxwell's equations for inhomogeneous media, nonlinear integral equations of the inverse problem of the electromagnetic tomography (EMT) are derived, whose kernel is the dyadic Green's function for the EMT sensor with a homogeneous medium in the object space. Then in terms of ill-posedness of the inverse problem, a Tikhonov-type regularization model is established based on a linearization-approximation of the nonlinear inverse problem. Finally, an iterative algorithm of image reconstruction based on the inverse problem and reconstruction images of some object flows for simplified sensor are given. Initial results of the image reconstruction show that the algorithm based on the inverse problem is superior to those based on the linear back-projection in the quality of image reconstruction.
Compressed Sensing Inspired Image Reconstruction from Overlapped Projections
Directory of Open Access Journals (Sweden)
Lin Yang
2010-01-01
Full Text Available The key idea discussed in this paper is to reconstruct an image from overlapped projections so that the data acquisition process can be shortened while the image quality remains essentially uncompromised. To perform image reconstruction from overlapped projections, the conventional reconstruction approach (e.g., filtered backprojection (FBP algorithms cannot be directly used because of two problems. First, overlapped projections represent an imaging system in terms of summed exponentials, which cannot be transformed into a linear form. Second, the overlapped measurement carries less information than the traditional line integrals. To meet these challenges, we propose a compressive sensing-(CS- based iterative algorithm for reconstruction from overlapped data. This algorithm starts with a good initial guess, relies on adaptive linearization, and minimizes the total variation (TV. Then, we demonstrated the feasibility of this algorithm in numerical tests.
Robust sparse image reconstruction of radio interferometric observations with PURIFY
Pratley, Luke; d'Avezac, Mayeul; Carrillo, Rafael E; Onose, Alexandru; Wiaux, Yves
2016-01-01
Next-generation radio interferometers, such as the Square Kilometre Array (SKA), will revolutionise our understanding of the universe through their unprecedented sensitivity and resolution. However, to realise these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN and its variants, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and they are not scalable for big data. In this work we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers (P-ADMM) algorithm presented in a recen...
Image reconstruction in optical interferometry: Benchmarking the regularization
Renard, Stéphanie; Malbet, Fabien
2011-01-01
With the advent of infrared long-baseline interferometers with more than two telescopes, both the size and the completeness of interferometric data sets have significantly increased, allowing images based on models with no a priori assumptions to be reconstructed. Our main objective is to analyze the multiple parameters of the image reconstruction process with particular attention to the regularization term and the study of their behavior in different situations. The secondary goal is to derive practical rules for the users. Using the Multi-aperture image Reconstruction Algorithm (MiRA), we performed multiple systematic tests, analyzing 11 regularization terms commonly used. The tests are made on different astrophysical objects, different (u,v) plane coverages and several signal-to-noise ratios to determine the minimal configuration needed to reconstruct an image. We establish a methodology and we introduce the mean-square errors (MSE) to discuss the results. From the ~24000 simulations performed for the benc...
Wahbeh, W.; Nebiker, S.; Fangi, G.
2016-06-01
This paper exploits the potential of dense multi-image 3d reconstruction of destroyed cultural heritage monuments by either using public domain touristic imagery only or by combining the public domain imagery with professional panoramic imagery. The focus of our work is placed on the reconstruction of the temple of Bel, one of the Syrian heritage monuments, which was destroyed in September 2015 by the so called "Islamic State". The great temple of Bel is considered as one of the most important religious buildings of the 1st century AD in the East with a unique design. The investigations and the reconstruction were carried out using two types of imagery. The first are freely available generic touristic photos collected from the web. The second are panoramic images captured in 2010 for documenting those monuments. In the paper we present a 3d reconstruction workflow for both types of imagery using state-of-the art dense image matching software, addressing the non-trivial challenges of combining uncalibrated public domain imagery with panoramic images with very wide base-lines. We subsequently investigate the aspects of accuracy and completeness obtainable from the public domain touristic images alone and from the combination with spherical panoramas. We furthermore discuss the challenges of co-registering the weakly connected 3d point cloud fragments resulting from the limited coverage of the touristic photos. We then describe an approach using spherical photogrammetry as a virtual topographic survey allowing the co-registration of a detailed and accurate single 3d model of the temple interior and exterior.
Loomis, E N; Grim, G P; Wilde, C; Wilson, D C; Morgan, G; Wilke, M; Tregillis, I; Merrill, F; Clark, D; Finch, J; Fittinghoff, D; Bower, D
2010-10-01
Development of analysis techniques for neutron imaging at the National Ignition Facility is an important and difficult task for the detailed understanding of high-neutron yield inertial confinement fusion implosions. Once developed, these methods must provide accurate images of the hot and cold fuels so that information about the implosion, such as symmetry and areal density, can be extracted. One method under development involves the numerical inversion of the pinhole image using knowledge of neutron transport through the pinhole aperture from Monte Carlo simulations. In this article we present results of source reconstructions based on simulated images that test the methods effectiveness with regard to pinhole misalignment.
Advanced photoacoustic image reconstruction using the k-Wave toolbox
Treeby, B. E.; Jaros, J.; Cox, B. T.
2016-03-01
Reconstructing images from measured time domain signals is an essential step in tomography-mode photoacoustic imaging. However, in practice, there are many complicating factors that make it difficult to obtain high-resolution images. These include incomplete or undersampled data, filtering effects, acoustic and optical attenuation, and uncertainties in the material parameters. Here, the processing and image reconstruction steps routinely used by the Photoacoustic Imaging Group at University College London are discussed. These include correction for acoustic and optical attenuation, spatial resampling, material parameter selection, image reconstruction, and log compression. The effect of each of these steps is demonstrated using a representative in vivo dataset. All of the algorithms discussed form part of the open-source k-Wave toolbox (available from http://www.k-wave.org).
Park, Sang Joon; Kim, Tae Jung; Kim, Kwang Gi; Lee, Sang Ho; Goo, Jin Mo; Kim, Jong Hyo
2008-03-01
Airway wall thickness (AWT) is an important bio-marker for evaluation of pulmonary diseases such as chronic bronchitis, bronchiectasis. While an image-based analysis of the airway tree can provide precise and valuable airway size information, quantitative measurement of AWT in Multidetector-Row Computed Tomography (MDCT) images involves various sources of error and uncertainty. So we have developed an accurate AWT measurement technique for small airways with three-dimensional (3-D) approach. To evaluate performance of these techniques, we used a set of acryl tube phantom was made to mimic small airways to have three different sizes of wall diameter (4.20, 1.79, 1.24 mm) and wall thickness (1.84, 1.22, 0.67 mm). The phantom was imaged with MDCT using standard reconstruction kernel (Sensation 16, Siemens, Erlangen). The pixel size was 0.488 mm × 0.488 mm × 0.75 mm in x, y, and z direction respectively. The images were magnified in 5 times using cubic B-spline interpolation, and line profiles were obtained for each tube. To recover faithful line profile from the blurred images, the line profiles were deconvolved with a point spread kernel of the MDCT which was estimated using the ideal tube profile and image line profile. The inner diameter, outer diameter, and wall thickness of each tube were obtained with full-width-half-maximum (FWHM) method for the line profiles before and after deconvolution processing. Results show that significant improvement was achieved over the conventional FWHM method in the measurement of AWT.
Application of mathematical modelling methods for acoustic images reconstruction
Bolotina, I.; Kazazaeva, A.; Kvasnikov, K.; Kazazaev, A.
2016-04-01
The article considers the reconstruction of images by Synthetic Aperture Focusing Technique (SAFT). The work compares additive and multiplicative methods for processing signals received from antenna array. We have proven that the multiplicative method gives a better resolution. The study includes the estimation of beam trajectories for antenna arrays using analytical and numerical methods. We have shown that the analytical estimation method allows decreasing the image reconstruction time in case of linear antenna array implementation.
Three-dimensional surface reconstruction from multistatic SAR images.
Rigling, Brian D; Moses, Randolph L
2005-08-01
This paper discusses reconstruction of three-dimensional surfaces from multiple bistatic synthetic aperture radar (SAR) images. Techniques for surface reconstruction from multiple monostatic SAR images already exist, including interferometric processing and stereo SAR. We generalize these methods to obtain algorithms for bistatic interferometric SAR and bistatic stereo SAR. We also propose a framework for predicting the performance of our multistatic stereo SAR algorithm, and, from this framework, we suggest a metric for use in planning strategic deployment of multistatic assets.
Beyond maximum entropy: Fractal Pixon-based image reconstruction
Puetter, Richard C.; Pina, R. K.
1994-01-01
We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other competing methods, including Goodness-of-Fit methods such as Least-Squares fitting and Lucy-Richardson reconstruction, as well as Maximum Entropy (ME) methods such as those embodied in the MEMSYS algorithms. Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME. Our past work has shown how uniform information content pixons can be used to develop a 'Super-ME' method in which entropy is maximized exactly. Recently, however, we have developed a superior pixon basis for the image, the Fractal Pixon Basis (FPB). Unlike the Uniform Pixon Basis (UPB) of our 'Super-ME' method, the FPB basis is selected by employing fractal dimensional concepts to assess the inherent structure in the image. The Fractal Pixon Basis results in the best image reconstructions to date, superior to both UPB and the best ME reconstructions. In this paper, we review the theory of the UPB and FPB pixon and apply our methodology to the reconstruction of far-infrared imaging of the galaxy M51. The results of our reconstruction are compared to published reconstructions of the same data using the Lucy-Richardson algorithm, the Maximum Correlation Method developed at IPAC, and the MEMSYS ME algorithms. The results show that our reconstructed image has a spatial resolution a factor of two better than best previous methods (and a factor of 20 finer than the width of the point response function), and detects sources two orders of magnitude fainter than other methods.
Landweber Iterative Methods for Angle-limited Image Reconstruction
Institute of Scientific and Technical Information of China (English)
Gang-rong Qu; Ming Jiang
2009-01-01
We introduce a general itcrative scheme for angle-limited image reconstruction based on Landwe-ber's method. We derive a representation formula for this scheme and consequently establish its convergence conditions. Our results suggest certain relaxation strategies for an accelerated convergcnce for angle-limited im-age reconstruction in L2-norm comparing with alternative projection methods. The convolution-backprojection algorithm is given for this iterative process.
Accurate Image Retrieval Algorithm Based on Color and Texture Feature
Directory of Open Access Journals (Sweden)
Chunlai Yan
2013-06-01
Full Text Available Content-Based Image Retrieval (CBIR is one of the most active hot spots in the current research field of multimedia retrieval. According to the description and extraction of visual content (feature of the image, CBIR aims to find images that contain specified content (feature in the image database. In this paper, several key technologies of CBIR, e. g. the extraction of the color and texture features of the image, as well as the similarity measures are investigated. On the basis of the theoretical research, an image retrieval system based on color and texture features is designed. In this system, the Weighted Color Feature based on HSV space is adopted as a color feature vector, four features of the Co-occurrence Matrix, saying Energy, Entropy, Inertia Quadrature and Correlation, are used to construct texture vectors, and the Euclidean distance for similarity measure is employed as well. Experimental results show that this CBIR system is efficient in image retrieval.
Super-Resolution Image Reconstruction Applied to Medical Ultrasound
Ellis, Michael
Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in
Reconstruction of images from radiofrequency electron paramagnetic resonance spectra.
Smith, C M; Stevens, A D
1994-12-01
This paper discusses methods for obtaining image reconstructions from electron paramagnetic resonance (EPR) spectra which constitute object projections. An automatic baselining technique is described which treats each spectrum consistently; rotating the non-horizontal baselines which are caused by stray magnetic effects onto the horizontal axis. The convolved backprojection method is described for both two- and three-dimensional reconstruction and the effect of cut-off frequency on the reconstruction is illustrated. A slower, indirect, iterative method, which does a non-linear fit to the projection data, is shown to give a far smoother reconstructed image when the method of maximum entropy is used to determine the value of the final residual sum of squares. Although this requires more computing time than the convolved backprojection method, it is more flexible and overcomes the problem of numerical instability encountered in deconvolution. Images from phantom samples in vitro are discussed. The spectral data for these have been accumulated quickly and have a low signal-to-noise ratio. The results show that as few as 16 spectra can still be processed to give an image. Artifacts in the image due to a small number of projections using the convolved backprojection reconstruction method can be removed by applying a threshold, i.e. only plotting contours higher than a given value. These artifacts are not present in an image which has been reconstructed by the maximum entropy technique. At present these techniques are being applied directly to in vivo studies.
Adaptive Deep Supervised Autoencoder Based Image Reconstruction for Face Recognition
Directory of Open Access Journals (Sweden)
Rongbing Huang
2016-01-01
Full Text Available Based on a special type of denoising autoencoder (DAE and image reconstruction, we present a novel supervised deep learning framework for face recognition (FR. Unlike existing deep autoencoder which is unsupervised face recognition method, the proposed method takes class label information from training samples into account in the deep learning procedure and can automatically discover the underlying nonlinear manifold structures. Specifically, we define an Adaptive Deep Supervised Network Template (ADSNT with the supervised autoencoder which is trained to extract characteristic features from corrupted/clean facial images and reconstruct the corresponding similar facial images. The reconstruction is realized by a so-called “bottleneck” neural network that learns to map face images into a low-dimensional vector and reconstruct the respective corresponding face images from the mapping vectors. Having trained the ADSNT, a new face image can then be recognized by comparing its reconstruction image with individual gallery images, respectively. Extensive experiments on three databases including AR, PubFig, and Extended Yale B demonstrate that the proposed method can significantly improve the accuracy of face recognition under enormous illumination, pose change, and a fraction of occlusion.
Fast MR Spectroscopic Imaging Technologies and Data Reconstruction Methods
Institute of Scientific and Technical Information of China (English)
HUANGMin; LUSong-tao; LINJia-rui; ZHANYing-jian
2004-01-01
MRSI plays a more and more important role in clinical application. In this paper, we compare several fast MRSI technologies and data reconstruction methods. For the conventional phase encoding MRSI, the data reconstruction using FFT is simple. But the data acquisition is very time consuming and thus prohibitive in clinical settings. Up to now, the MRSI technologies based on echo-planar, spiral trajectories and sensitivity encoding are the fastest in data acquisition, but their data reconstruction is complex. EPSI reconstruction uses shift of odd and even echoes. Spiral SI uses gridding FFT. SENSE-SI, a new approach to reducing the acquisition time, uses the distinct spatial sensitivities of the individual coil elements to recover the missing encoding information. These improvements in data acquisition and image reconstruction provide a potential value of metabolic imaging as a clinical tool.
Wang, A. S.; Stayman, J. W.; Otake, Y.; Khanna, A. J.; Gallia, G. L.; Siewerdsen, J. H.
2014-03-01
Purpose: A new method for accurately portraying the impact of low-dose imaging techniques in C-arm cone-beam CT (CBCT) is presented and validated, allowing identification of minimum-dose protocols suitable to a given imaging task on a patient-specific basis in scenarios that require repeat intraoperative scans. Method: To accurately simulate lower-dose techniques and account for object-dependent noise levels (x-ray quantum noise and detector electronics noise) and correlations (detector blur), noise of the proper magnitude and correlation was injected into the projections from an initial CBCT acquired at the beginning of a procedure. The resulting noisy projections were then reconstructed to yield low-dose preview (LDP) images that accurately depict the image quality at any level of reduced dose in both filtered backprojection and statistical image reconstruction. Validation studies were conducted on a mobile C-arm, with the noise injection method applied to images of an anthropomorphic head phantom and cadaveric torso across a range of lower-dose techniques. Results: Comparison of preview and real CBCT images across a full range of techniques demonstrated accurate noise magnitude (within ~5%) and correlation (matching noise-power spectrum, NPS). Other image quality characteristics (e.g., spatial resolution, contrast, and artifacts associated with beam hardening and scatter) were also realistically presented at all levels of dose and across reconstruction methods, including statistical reconstruction. Conclusion: Generating low-dose preview images for a broad range of protocols gives a useful method to select minimum-dose techniques that accounts for complex factors of imaging task, patient-specific anatomy, and observer preference. The ability to accurately simulate the influence of low-dose acquisition in statistical reconstruction provides an especially valuable means of identifying low-dose limits in a manner that does not rely on a model for the nonlinear
Application of Super-Resolution Image Reconstruction to Digital Holography
Directory of Open Access Journals (Sweden)
Zhang Shuqun
2006-01-01
Full Text Available We describe a new application of super-resolution image reconstruction to digital holography which is a technique for three-dimensional information recording and reconstruction. Digital holography has suffered from the low resolution of CCD sensors, which significantly limits the size of objects that can be recorded. The existing solution to this problem is to use optics to bandlimit the object to be recorded, which can cause the loss of details. Here super-resolution image reconstruction is proposed to be applied in enhancing the spatial resolution of digital holograms. By introducing a global camera translation before sampling, a high-resolution hologram can be reconstructed from a set of undersampled hologram images. This permits the recording of larger objects and reduces the distance between the object and the hologram. Practical results from real and simulated holograms are presented to demonstrate the feasibility of the proposed technique.
Compensation for air voids in photoacoustic computed tomography image reconstruction
Matthews, Thomas P.; Li, Lei; Wang, Lihong V.; Anastasio, Mark A.
2016-03-01
Most image reconstruction methods in photoacoustic computed tomography (PACT) assume that the acoustic properties of the object and the surrounding medium are homogeneous. This can lead to strong artifacts in the reconstructed images when there are significant variations in sound speed or density. Air voids represent a particular challenge due to the severity of the differences between the acoustic properties of air and water. In whole-body small animal imaging, the presence of air voids in the lungs, stomach, and gastrointestinal system can limit image quality over large regions of the object. Iterative reconstruction methods based on the photoacoustic wave equation can account for these acoustic variations, leading to improved resolution, improved contrast, and a reduction in the number of imaging artifacts. However, the strong acoustic heterogeneities can lead to instability or errors in the numerical wave solver. Here, the impact of air voids on PACT image reconstruction is investigated, and procedures for their compensation are proposed. The contributions of sound speed and density variations to the numerical stability of the wave solver are considered, and a novel approach for mitigating the impact of air voids while reducing the computational burden of image reconstruction is identified. These results are verified by application to an experimental phantom.
Iterative image reconstruction and its role in cardiothoracic computed tomography.
Singh, Sarabjeet; Khawaja, Ranish Deedar Ali; Pourjabbar, Sarvenaz; Padole, Atul; Lira, Diego; Kalra, Mannudeep K
2013-11-01
Revolutionary developments in multidetector-row computed tomography (CT) scanner technology offer several advantages for imaging of cardiothoracic disorders. As a result, expanding applications of CT now account for >85 million CT examinations annually in the United States alone. Given the large number of CT examinations performed, concerns over increase in population-based risk for radiation-induced carcinogenesis have made CT radiation dose a top safety concern in health care. In response to this concern, several technologies have been developed to reduce the dose with more efficient use of scan parameters and the use of "newer" image reconstruction techniques. Although iterative image reconstruction algorithms were first introduced in the 1970s, filtered back projection was chosen as the conventional image reconstruction technique because of its simplicity and faster reconstruction times. With subsequent advances in computational speed and power, iterative reconstruction techniques have reemerged and have shown the potential of radiation dose optimization without adversely influencing diagnostic image quality. In this article, we review the basic principles of different iterative reconstruction algorithms and their implementation for various clinical applications in cardiothoracic CT examinations for reducing radiation dose.
Directory of Open Access Journals (Sweden)
Chris L. de Korte
2013-03-01
Full Text Available Atherosclerotic plaque rupture can initiate stroke or myocardial infarction. Lipid-rich plaques with thin fibrous caps have a higher risk to rupture than fibrotic plaques. Elastic moduli differ for lipid-rich and fibrous tissue and can be reconstructed using tissue displacements estimated from intravascular ultrasound radiofrequency (RF data acquisitions. This study investigated if modulus reconstruction is possible for noninvasive RF acquisitions of vessels in transverse imaging planes using an iterative 2D cross-correlation based displacement estimation algorithm. Furthermore, since it is known that displacements can be improved by compounding of displacements estimated at various beam steering angles, we compared the performance of the modulus reconstruction with and without compounding. For the comparison, simulated and experimental RF data were generated of various vessel-mimicking phantoms. Reconstruction errors were less than 10%, which seems adequate for distinguishing lipid-rich from fibrous tissue. Compounding outperformed single-angle reconstruction: the interquartile range of the reconstructed moduli for the various homogeneous phantom layers was approximately two times smaller. Additionally, the estimated lateral displacements were a factor of 2–3 better matched to the displacements corresponding to the reconstructed modulus distribution. Thus, noninvasive elastic modulus reconstruction is possible for transverse vessel cross sections using this cross-correlation method and is more accurate with compounding.
Visions of Reconstruction: Layers of Moving Images
Directory of Open Access Journals (Sweden)
Floris Jan Willem Paalman
2015-12-01
Full Text Available After WWII, films accompanied the reconstruction of Europe’s destroyed cities. Many contained historical footage. How was this material used, to articulate visions of reconstruction, what happened to the material later on, and how do the films relate to municipal film archives? This question is approached in terms of collective cognitive functions, applied to a media archaeological case study of Rotterdam. In focus are two audiovisual landmarks, from 1950 and 1966, and their historical footage, all with different temporal horizons. This study attempts to position the city film archive in media history.
Efficient and Accurate Gaussian Image Filtering Using Running Sums
Elboher, Elhanan
2011-01-01
This paper presents a simple and efficient method to convolve an image with a Gaussian kernel. The computation is performed in a constant number of operations per pixel using running sums along the image rows and columns. We investigate the error function used for kernel approximation and its relation to the properties of the input signal. Based on natural image statistics we propose a quadratic form kernel error function so that the output image l2 error is minimized. We apply the proposed approach to approximate the Gaussian kernel by linear combination of constant functions. This results in very efficient Gaussian filtering method. Our experiments show that the proposed technique is faster than state of the art methods while preserving a similar accuracy.
Proposal of fault-tolerant tomographic image reconstruction
Kudo, Hiroyuki; Yamazaki, Fukashi; Nemoto, Takuya
2016-01-01
This paper deals with tomographic image reconstruction under the situation where some of projection data bins are contaminated with abnormal data. Such situations occur in various instances of tomography. We propose a new reconstruction algorithm called the Fault-Tolerant reconstruction outlined as follows. The least-squares (L2-norm) error function ||Ax-b||_2^2 used in ordinary iterative reconstructions is sensitive to the existence of abnormal data. The proposed algorithm utilizes the L1-norm error function ||Ax-b||_1^1 instead of the L2-norm, and we develop a row-action-type iterative algorithm using the proximal splitting framework in convex optimization fields. We also propose an improved version of the L1-norm reconstruction called the L1-TV reconstruction, in which a weak Total Variation (TV) penalty is added to the cost function. Simulation results demonstrate that reconstructed images with the L2-norm were severely damaged by the effect of abnormal bins, whereas images with the L1-norm and L1-TV reco...
Improving JWST Coronagraphic Performance with Accurate Image Registration
Van Gorkom, Kyle; Pueyo, Laurent; Lajoie, Charles-Philippe; JWST Coronagraphs Working Group
2016-06-01
The coronagraphs on the James Webb Space Telescope (JWST) will enable high-contrast observations of faint objects at small separations from bright hosts, such as circumstellar disks, exoplanets, and quasar disks. Despite attenuation by the coronagraphic mask, bright speckles in the host’s point spread function (PSF) remain, effectively washing out the signal from the faint companion. Suppression of these bright speckles is typically accomplished by repeating the observation with a star that lacks a faint companion, creating a reference PSF that can be subtracted from the science image to reveal any faint objects. Before this reference PSF can be subtracted, however, the science and reference images must be aligned precisely, typically to 1/20 of a pixel. Here, we present several such algorithms for performing image registration on JWST coronagraphic images. Using both simulated and pre-flight test data (taken in cryovacuum), we assess (1) the accuracy of each algorithm at recovering misaligned scenes and (2) the impact of image registration on achievable contrast. Proper image registration, combined with post-processing techniques such as KLIP or LOCI, will greatly improve the performance of the JWST coronagraphs.
Chvetsov, Alevei V.; Sandison, George A.; Schwartz, Jeffrey L.; Rengan, Ramesh
2015-11-01
The main objective of this article is to improve the stability of reconstruction algorithms for estimation of radiobiological parameters using serial tumor imaging data acquired during radiation therapy. Serial images of tumor response to radiation therapy represent a complex summation of several exponential processes as treatment induced cell inactivation, tumor growth rates, and the rate of cell loss. Accurate assessment of treatment response would require separation of these processes because they define radiobiological determinants of treatment response and, correspondingly, tumor control probability. However, the estimation of radiobiological parameters using imaging data can be considered an inverse ill-posed problem because a sum of several exponentials would produce the Fredholm integral equation of the first kind which is ill posed. Therefore, the stability of reconstruction of radiobiological parameters presents a problem even for the simplest models of tumor response. To study stability of the parameter reconstruction problem, we used a set of serial CT imaging data for head and neck cancer and a simplest case of a two-level cell population model of tumor response. Inverse reconstruction was performed using a simulated annealing algorithm to minimize a least squared objective function. Results show that the reconstructed values of cell surviving fractions and cell doubling time exhibit significant nonphysical fluctuations if no stabilization algorithms are applied. However, after applying a stabilization algorithm based on variational regularization, the reconstruction produces statistical distributions for survival fractions and doubling time that are comparable to published in vitro data. This algorithm is an advance over our previous work where only cell surviving fractions were reconstructed. We conclude that variational regularization allows for an increase in the number of free parameters in our model which enables development of more
Super-Resolution Reconstruction of Image Sequence Using Multiple Motion Estimation Fusion
Institute of Scientific and Technical Information of China (English)
Cheng Wang; Run-Sheng Wang
2004-01-01
Super-resolution reconstruction algorithm produces a high-resolution image from a low-resolution image sequence. The accuracy and the stability of the motion estimation (ME) are essential for the whole restoration. In this paper, a new super-resolution reconstruction algorithm is developed using a robust ME method, which fuses multiple estimated motion vectors within the sequence. The new algorithm has two major improvements compared with the previous research. First, instead of only two frames, the whole sequence is used to obtain a more accurate and stable estimation of the motion vector of each frame; second, the reliability of the ME is quantitatively measured and introduced into the cost function of the reconstruction algorithm. The algorithm is applied to both synthetic and real sequences, and the results are presented in the paper.
Distributed image reconstruction for very large arrays in radio astronomy
Ferrari, André; Flamary, Rémi; Richard, Cédric
2015-01-01
Current and future radio interferometric arrays such as LOFAR and SKA are characterized by a paradox. Their large number of receptors (up to millions) allow theoretically unprecedented high imaging resolution. In the same time, the ultra massive amounts of samples makes the data transfer and computational loads (correlation and calibration) order of magnitudes too high to allow any currently existing image reconstruction algorithm to achieve, or even approach, the theoretical resolution. We investigate here decentralized and distributed image reconstruction strategies which select, transfer and process only a fraction of the total data. The loss in MSE incurred by the proposed approach is evaluated theoretically and numerically on simple test cases.
Accurate measurement of curvilinear shapes by Virtual Image Correlation
Semin, B.; Auradou, H.; François, M. L. M.
2011-10-01
The proposed method allows the detection and the measurement, in the sense of metrology, of smooth elongated curvilinear shapes. Such measurements are required in many fields of physics, for example: mechanical engineering, biology or medicine (deflection of beams, fibers or filaments), fluid mechanics or chemistry (detection of fronts). Contrary to actual methods, the result is given in an analytical form of class C∞ (and not a finite set of locations or pixels) thus curvatures and slopes, often of great interest in science, are given with good confidence. The proposed Virtual Image Correlation (VIC) method uses a virtual beam, an image which consists in a lateral expansion of the curve with a bell-shaped gray level. This figure is deformed until it fits the best the physical image with a method issued from the Digital Image Correlation method in use in solid mechanics. The precision of the identification is studied in a benchmark and successfully compared to two state-of-the-art methods. Three practical examples are given: a bar bending under its own weight, a thin fiber transported by a flow within a fracture and a thermal front. The first allows a comparison with theoretical solution, the second shows the ability of the method to deal with complex shapes and crossings and the third deals with ill-defined image.
Analysis Operator Learning and Its Application to Image Reconstruction
Hawe, Simon; Diepold, Klaus
2012-01-01
Exploiting a priori known structural information lies at the core of many image reconstruction methods that can be stated as inverse problems. The synthesis model, which assumes that images can be decomposed into a linear combination of very few atoms of some dictionary, is now a well established tool for the design of image reconstruction algorithms. An interesting alternative is the analysis model, where the signal is multiplied by an analysis operator and the outcome is assumed to be the sparse. This approach has only recently gained increasing interest. The quality of reconstruction methods based on an analysis model severely depends on the right choice of the suitable operator. In this work, we present an algorithm for learning an analysis operator from training images. Our method is based on an $\\ell_p$-norm minimization on the set of full rank matrices with normalized columns. We carefully introduce the employed conjugate gradient method on manifolds, and explain the underlying geometry of the constrai...
Milani, Simone; Tronca, Enrico
2017-01-01
During the past years, research has focused on the reconstruction of three-dimensional point cloud models from unordered and uncalibrated sets of images. Most of the proposed solutions rely on the structure-from-motion algorithm, and their performances significantly degrade whenever exchangeable image file format information about focal lengths is missing or corrupted. We propose a preprocessing strategy that permits estimating the focal lengths of a camera more accurately. The basic idea is to cluster the input images into separate subsets according to an array of interpolation-related multimedia forensic clues. This operation permits having a more robust estimate and improving the accuracy of the final model.
Sparsity-constrained three-dimensional image reconstruction for C-arm angiography.
Rashed, Essam A; al-Shatouri, Mohammad; Kudo, Hiroyuki
2015-07-01
X-ray C-arm is an important imaging tool in interventional radiology, road-mapping and radiation therapy because it provides accurate descriptions of vascular anatomy and therapeutic end point. In common interventional radiology, the C-arm scanner produces a set of two-dimensional (2D) X-ray projection data obtained with a detector by rotating the scanner gantry around the patient. Unlike conventional fluoroscopic imaging, three-dimensional (3D) C-arm computed tomography (CT) provides more accurate cross-sectional images, which are helpful for therapy planning, guidance and evaluation in interventional radiology. However, 3D vascular imaging using the conventional C-arm fluoroscopy encounters some geometry challenges. Inspired by the theory of compressed sensing, we developed an image reconstruction algorithm for conventional angiography C-arm scanners. The main challenge in this image reconstruction problem is the projection data limitations. We consider a small number of views acquired from a short rotation orbit with offset scan geometry. The proposed method, called sparsity-constrained angiography (SCAN), is developed using the alternating direction method of multipliers, and the results obtained from simulated and real data are encouraging. SCAN algorithm provides a framework to generate 3D vascular images using the conventional C-arm scanners in lower cost than conventional 3D imaging scanners.
Institute of Scientific and Technical Information of China (English)
Zhang Wentao; Li Xiaofeng; Li Zaiming
2001-01-01
The paper first discusses shortcomings of classical adjacent-frame difference. Sec ondly, based on the image energy and high order statistic(HOS) theory, background reconstruction constraints are setup. Under the help of block-processing technology, background is reconstructed quickly. Finally, background difference is used to detect motion regions instead of adjacent frame difference. The DSP based platform tests indicate the background can be recovered losslessly in about one second, and moving regions are not influenced by moving target speeds. The algorithm has important usage both in theory and applications.
Energy Technology Data Exchange (ETDEWEB)
Pino, Francisco [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036, Spain and Servei de Física Mèdica i Protecció Radiològica, Institut Català d’Oncologia, L’Hospitalet de Llobregat 08907 (Spain); Roé, Nuria [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036 (Spain); Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es [Fundación Ramón Domínguez, Complexo Hospitalario Universitario de Santiago de Compostela 15706, Spain and Grupo de Imagen Molecular, Instituto de Investigacións Sanitarias de Santiago de Compostela (IDIS), Galicia 15782 (Spain); Falcon, Carles; Ros, Domènec [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain and CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); Pavía, Javier [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 080836 (Spain); CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); and Servei de Medicina Nuclear, Hospital Clínic, Barcelona 08036 (Spain)
2015-02-15
Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery
Distributed multi-frequency image reconstruction for radio-interferometry
Deguignet, Jérémy; Mary, David; Ferrari, Chiara
2016-01-01
The advent of enhanced technologies in radio interferometry and the perspective of the SKA telescope bring new challenges in image reconstruction. One of these challenges is the spatio-spectral reconstruction of large (Terabytes) data cubes with high fidelity. This contribution proposes an alternative implementation of one such 3D prototype algorithm, MUFFIN (MUlti-Frequency image reconstruction For radio INterferometry), which combines spatial and spectral analysis priors. Using a recently proposed primal dual algorithm, this new version of MUFFIN allows a parallel implementation where computationally intensive steps are split by spectral channels. This parallelization allows to implement computationally demanding translation invariant wavelet transforms (IUWT), as opposed to the union of bases used previously. This alternative implementation is important as it opens the possibility of comparing these efficient dictionaries, and others, in spatio-spectral reconstruction. Numerical results show that the IUWT-...
Probability of correct reconstruction in compressive spectral imaging
Directory of Open Access Journals (Sweden)
Samuel Eduardo Pinilla
2016-08-01
Full Text Available Coded Aperture Snapshot Spectral Imaging (CASSI systems capture the 3-dimensional (3D spatio-spectral information of a scene using a set of 2-dimensional (2D random coded Focal Plane Array (FPA measurements. A compressed sensing reconstruction algorithm is then used to recover the underlying spatio-spectral 3D data cube. The quality of the reconstructed spectral images depends exclusively on the CASSI sensing matrix, which is determined by the statistical structure of the coded apertures. The Restricted Isometry Property (RIP of the CASSI sensing matrix is used to determine the probability of correct image reconstruction and provides guidelines for the minimum number of FPA measurement shots needed for image reconstruction. Further, the RIP can be used to determine the optimal structure of the coded projections in CASSI. This article describes the CASSI optical architecture and develops the RIP for the sensing matrix in this system. Simulations show the higher quality of spectral image reconstructions when the RIP property is satisfied. Simulations also illustrate the higher performance of the optimal structured projections in CASSI.
High resolution image reconstruction with constrained, total-variation minimization
Sidky, Emil Y; Duchin, Yuval; Ullberg, Christer; Pan, Xiaochuan
2011-01-01
This work is concerned with applying iterative image reconstruction, based on constrained total-variation minimization, to low-intensity X-ray CT systems that have a high sampling rate. Such systems pose a challenge for iterative image reconstruction, because a very fine image grid is needed to realize the resolution inherent in such scanners. These image arrays lead to under-determined imaging models whose inversion is unstable and can result in undesirable artifacts and noise patterns. There are many possibilities to stabilize the imaging model, and this work proposes a method which may have an advantage in terms of algorithm efficiency. The proposed method introduces additional constraints in the optimization problem; these constraints set to zero high spatial frequency components which are beyond the sensing capability of the detector. The method is demonstrated with an actual CT data set and compared with another method based on projection up-sampling.
Parallel hyperspectral image reconstruction using random projections
Sevilla, Jorge; Martín, Gabriel; Nascimento, José M. P.
2016-10-01
Spaceborne sensors systems are characterized by scarce onboard computing and storage resources and by communication links with reduced bandwidth. Random projections techniques have been demonstrated as an effective and very light way to reduce the number of measurements in hyperspectral data, thus, the data to be transmitted to the Earth station is reduced. However, the reconstruction of the original data from the random projections may be computationally expensive. SpeCA is a blind hyperspectral reconstruction technique that exploits the fact that hyperspectral vectors often belong to a low dimensional subspace. SpeCA has shown promising results in the task of recovering hyperspectral data from a reduced number of random measurements. In this manuscript we focus on the implementation of the SpeCA algorithm for graphics processing units (GPU) using the compute unified device architecture (CUDA). Experimental results conducted using synthetic and real hyperspectral datasets on the GPU architecture by NVIDIA: GeForce GTX 980, reveal that the use of GPUs can provide real-time reconstruction. The achieved speedup is up to 22 times when compared with the processing time of SpeCA running on one core of the Intel i7-4790K CPU (3.4GHz), with 32 Gbyte memory.
Shape-based image reconstruction using linearized deformations
Öktem, Ozan; Chen, Chong; Onur Domaniç, Nevzat; Ravikumar, Pradeep; Bajaj, Chandrajit
2017-03-01
We introduce a reconstruction framework that can account for shape related prior information in imaging-related inverse problems. It is a variational scheme that uses a shape functional, whose definition is based on deformable template machinery from computational anatomy. We prove existence and, as a proof of concept, we apply the proposed shape-based reconstruction to 2D tomography with very sparse and/or highly noisy measurements.
A FAST CONVERGING SPARSE RECONSTRUCTION ALGORITHM IN GHOST IMAGING
Institute of Scientific and Technical Information of China (English)
Li Enrong; Chen Mingliang; Gong Wenlin; Wang Hui; Han Shensheng
2012-01-01
A fast converging sparse reconstruction algorithm in ghost imaging is presented.It utilizes total variation regularization and its formulation is based on the Karush-Kuhn-Tucker (KKT) theorem in the theory of convex optimization.Tests using experimental data show that,compared with the algorithm of Gradient Projection for Sparse Reconstruction (GPSR),the proposed algorithm yields better results with less computation work.
An adaptive filtered back-projection for photoacoustic image reconstruction
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Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong, E-mail: jingyong.ye@utsa.edu [Department of Biomedical Engineering, University of Texas at San Antonio, San Antonio, Texas 78249 (United States)
2015-05-15
Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing
Jones, Jasmine; Zhang, Rui; Heins, David; Castle, Katherine
In postmastectomy radiotherapy, an increasing number of patients have tissue expanders inserted subpectorally when receiving immediate breast reconstruction. These tissue expanders are composed of silicone and are inflated with saline through an internal metallic port; this serves the purpose of stretching the muscle and skin tissue over time, in order to house a permanent implant. The issue with administering radiation therapy in the presence of a tissue expander is that the port's magnetic core can potentially perturb the dose delivered to the Planning Target Volume, causing significant artifacts in CT images. Several studies have explored this problem, and suggest that density corrections must be accounted for in treatment planning. However, very few studies accurately calibrated commercial TP systems for the high density material used in the port, and no studies employed fusion imaging to yield a more accurate contour of the port in treatment planning. We compared depth dose values in the water phantom between measurement and TPS calculations, and we were able to overcome some of the inhomogeneities presented by the image artifact by fusing the KVCT and MVCT images of the tissue expander together, resulting in a more precise comparison of dose calculations at discrete locations. We expect this method to be pivotal in the quantification of dose distribution in the PTV. Research funded by the LS-AMP Award.
Image reconstruction technique using projection data from neutron tomography system
Directory of Open Access Journals (Sweden)
Waleed Abd el Bar
2015-12-01
Full Text Available Neutron tomography is a very powerful technique for nondestructive evaluation of heavy industrial components as well as for soft hydrogenous materials enclosed in heavy metals which are usually difficult to image using X-rays. Due to the properties of the image acquisition system, the projection images are distorted by several artifacts, and these reduce the quality of the reconstruction. In order to eliminate these harmful effects the projection images should be corrected before reconstruction. This paper gives a description of a filter back projection (FBP technique, which is used for reconstruction of projected data obtained from transmission measurements by neutron tomography system We demonstrated the use of spatial Discrete Fourier Transform (DFT and the 2D Inverse DFT in the formulation of the method, and outlined the theory of reconstruction of a 2D neutron image from a sequence of 1D projections taken at different angles between 0 and π in MATLAB environment. Projections are generated by applying the Radon transform to the original image at different angles.
Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU
Directory of Open Access Journals (Sweden)
Arefan D
2015-06-01
Full Text Available Digital Breast Tomosynthesis (DBT is a technology that creates three dimensional (3D images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU. At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU card and the Graphics Processing Unit (GPU. It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU.
Sparse representation for the ISAR image reconstruction
Hu, Mengqi; Montalbo, John; Li, Shuxia; Sun, Ligang; Qiao, Zhijun G.
2016-05-01
In this paper, a sparse representation of the data for an inverse synthetic aperture radar (ISAR) system is provided in two dimensions. The proposed sparse representation motivates the use a of a Convex Optimization that recovers the image with far less samples, which is required by Nyquist-Shannon sampling theorem to increases the efficiency and decrease the cost of calculation in radar imaging.
Super-resolution reconstruction of hyperspectral images
Elbakary, Mohamed; Alam, Mohammad S.
2007-04-01
Hyperspectral imagery is used for a wide variety of applications, including target detection, tacking, agricultural monitoring and natural resources exploration. The main reason for using hyperspectral imagery is that these images reveal spectral information about the scene that are not available in a single band. Unfortunately, many factors such as sensor noise and atmospheric scattering degrade the spatial quality of these images. Recently, many algorithms are introduced in the literature to improve the resolution of hyperspectral images [7]. In this paper, we propose a new method to produce high resolution bands from low resolution bands that are strongly correlated to the corresponding high resolution panchromatic image. The proposed method is based on using the local correlation instead of using the global correlation to improve the estimated interpolation in order to construct the high resolution image. The utilization of local correlation significantly improved the resolution of high resolution images when compared to the corresponding results obtained using the traditional algorithms. The local correlation is implemented by using predefined small windows across the low resolution image. In addition, numerous experiments are conducted to investigate the effect of the chosen window size in the image quality. Experiments results obtained using real life hyperspectral imagery is presented to verify the effectiveness of the proposed algorithm.
Block Compressed Sensing of Images Using Adaptive Granular Reconstruction
Directory of Open Access Journals (Sweden)
Ran Li
2016-01-01
Full Text Available In the framework of block Compressed Sensing (CS, the reconstruction algorithm based on the Smoothed Projected Landweber (SPL iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.
Flame Reconstruction Using Synthetic Aperture Imaging
Murray, Preston; Tree, Dale; Truscott, Tadd
2011-01-01
Flames can be formed by burning methane (CH4). When oxygen is scarce, carbon particles nucleate into solid particles called soot. These particles emit photons, making the flame yellow. Later, methane is pre-mixed with air forming a blue flame; burning more efficiently, providing less soot and light. Imaging flames and knowing their temperature are vital to maximizing efficiency and validating numerical models. Most temperature probes disrupt the flame and create differences leading to an inaccurate measurement of the flame temperature. We seek to image the flame in three dimensions using synthetic aperture imaging. This technique has already successfully measured velocity fields of a vortex ring [1]. Synthetic aperture imaging is a technique that views one scene from multiple cameras set at different angles, allowing some cameras to view objects that are obscured by others. As the resulting images are overlapped different depths of the scene come into and out of focus, known as focal planes, similar to tomogr...
Murase, Kenya
2016-01-01
The purpose of this study was to present image reconstruction methods for magnetic particle imaging (MPI) with a field-free-line (FFL) encoding scheme and to propose the use of the maximum likelihood-expectation maximization (ML-EM) algorithm for improving the image quality of MPI. The feasibility of these methods was investigated by computer simulations, in which the projection data were generated by summing up the Fourier harmonics obtained from the MPI signals based on the Langevin function. Images were reconstructed from the generated projection data using the filtered backprojection (FBP) method and the ML-EM algorithm. The effects of the gradient of selection magnetic field (SMF), the strength of drive magnetic field (DMF), the diameter of magnetic nanoparticles (MNPs), and the number of projection data on the image quality of the reconstructed images were investigated. The spatial resolution of the reconstructed images became better with increasing gradient of SMF and with increasing diameter of MNPs u...
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Hofmann, Christian [Institute of Medical Physics, Friedrich-Alexander University (FAU), Erlangen 91052 (Germany); Sawall, Stefan; Knaup, Michael [Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg 69120 (Germany); Kachelrieß, Marc, E-mail: marc.kachelriess@dkfz-heidelberg [Institute of Medical Physics, Friedrich-Alexander University (FAU), Erlangen 91052, Germany and Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg 69120 (Germany)
2014-06-15
Purpose: Iterative image reconstruction gains more and more interest in clinical routine, as it promises to reduce image noise (and thereby patient dose), to reduce artifacts, or to improve spatial resolution. Among vendors and researchers, however, there is no consensus of how to best achieve these aims. The general approach is to incorporatea priori knowledge into iterative image reconstruction, for example, by adding additional constraints to the cost function, which penalize variations between neighboring voxels. However, this approach to regularization in general poses a resolution noise trade-off because the stronger the regularization, and thus the noise reduction, the stronger the loss of spatial resolution and thus loss of anatomical detail. The authors propose a method which tries to improve this trade-off. The proposed reconstruction algorithm is called alpha image reconstruction (AIR). One starts with generating basis images, which emphasize certain desired image properties, like high resolution or low noise. The AIR algorithm reconstructs voxel-specific weighting coefficients that are applied to combine the basis images. By combining the desired properties of each basis image, one can generate an image with lower noise and maintained high contrast resolution thus improving the resolution noise trade-off. Methods: All simulations and reconstructions are performed in native fan-beam geometry. A water phantom with resolution bar patterns and low contrast disks is simulated. A filtered backprojection (FBP) reconstruction with a Ram-Lak kernel is used as a reference reconstruction. The results of AIR are compared against the FBP results and against a penalized weighted least squares reconstruction which uses total variation as regularization. The simulations are based on the geometry of the Siemens Somatom Definition Flash scanner. To quantitatively assess image quality, the authors analyze line profiles through resolution patterns to define a contrast
Local fingerprint image reconstruction based on gabor filtering
Bakhtiari, Somayeh; Agaian, Sos S.; Jamshidi, Mo
2012-06-01
In this paper, we propose two solutions for fingerprint local image reconstruction based on Gabor filtering. Gabor filtering is a popular method for fingerprint image enhancement. However, the reliability of the information in the output image suffers, when the input image has a poor quality. This is the result of the spurious estimates of frequency and orientation by classical approaches, particularly in the scratch regions. In both techniques of this paper, the scratch marks are recognized initially using reliability image which is calculated using the gradient images. The first algorithm is based on an inpainting technique and the second method employs two different kernels for the scratch and the non-scratch parts of the image to calculate the gradient images. The simulation results show that both approaches allow the actual information of the image to be preserved while connecting discontinuities correctly by approximating the orientation matrix more genuinely.
Three dimensional reconstruction of conventional stereo optic disc image.
Kong, H J; Kim, S K; Seo, J M; Park, K H; Chung, H; Park, K S; Kim, H C
2004-01-01
Stereo disc photograph was analyzed and reconstructed as 3 dimensional contour image to evaluate the status of the optic nerve head for the early detection of glaucoma and the evaluation of the efficacy of treatment. Stepwise preprocessing was introduced to detect the edge of the optic nerve head and retinal vessels and reduce noises. Paired images were registered by power cepstrum method and zero-mean normalized cross-correlation. After Gaussian blurring, median filter application and disparity pair searching, depth information in the 3 dimensionally reconstructed image was calculated by the simple triangulation formula. Calculated depth maps were smoothed through cubic B-spline interpolation and retinal vessels were visualized more clearly by adding reference image. Resulted 3 dimensional contour image showed optic cups, retinal vessels and the notching of the neural rim of the optic disc clearly and intuitively, helping physicians in understanding and interpreting the stereo disc photograph.
AN IMAGE-BASED TECHNIQUE FOR 3D BUILDING RECONSTRUCTION USING MULTI-VIEW UAV IMAGES
Directory of Open Access Journals (Sweden)
F. Alidoost
2015-12-01
Full Text Available Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.
Blockwise conjugate gradient methods for image reconstruction in volumetric CT.
Qiu, W; Titley-Peloquin, D; Soleimani, M
2012-11-01
Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images.
A methodology to event reconstruction from trace images.
Milliet, Quentin; Delémont, Olivier; Sapin, Eric; Margot, Pierre
2015-03-01
The widespread use of digital imaging devices for surveillance (CCTV) and entertainment (e.g., mobile phones, compact cameras) has increased the number of images recorded and opportunities to consider the images as traces or documentation of criminal activity. The forensic science literature focuses almost exclusively on technical issues and evidence assessment [1]. Earlier steps in the investigation phase have been neglected and must be considered. This article is the first comprehensive description of a methodology to event reconstruction using images. This formal methodology was conceptualised from practical experiences and applied to different contexts and case studies to test and refine it. Based on this practical analysis, we propose a systematic approach that includes a preliminary analysis followed by four main steps. These steps form a sequence for which the results from each step rely on the previous step. However, the methodology is not linear, but it is a cyclic, iterative progression for obtaining knowledge about an event. The preliminary analysis is a pre-evaluation phase, wherein potential relevance of images is assessed. In the first step, images are detected and collected as pertinent trace material; the second step involves organising and assessing their quality and informative potential. The third step includes reconstruction using clues about space, time and actions. Finally, in the fourth step, the images are evaluated and selected as evidence. These steps are described and illustrated using practical examples. The paper outlines how images elicit information about persons, objects, space, time and actions throughout the investigation process to reconstruct an event step by step. We emphasise the hypothetico-deductive reasoning framework, which demonstrates the contribution of images to generating, refining or eliminating propositions or hypotheses. This methodology provides a sound basis for extending image use as evidence and, more generally
Gadgetron: an open source framework for medical image reconstruction.
Hansen, Michael Schacht; Sørensen, Thomas Sangild
2013-06-01
This work presents a new open source framework for medical image reconstruction called the "Gadgetron." The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or "Gadgets" from raw data to reconstructed images. The data processing pipeline is configured dynamically at run-time based on an extensible markup language configuration description. The framework promotes reuse and sharing of reconstruction modules and new Gadgets can be added to the Gadgetron framework through a plugin-like architecture without recompiling the basic framework infrastructure. Gadgets are typically implemented in C/C++, but the framework includes wrapper Gadgets that allow the user to implement new modules in the Python scripting language for rapid prototyping. In addition to the streaming framework infrastructure, the Gadgetron comes with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its application to Cartesian and non-Cartesian parallel magnetic resonance imaging.
Parallel Image Reconstruction for New Vacuum Solar Telescope
Li, Xue-Bao; Wang, Feng; Xiang, Yong Yuan; Zheng, Yan Fang; Liu, Ying Bo; Deng, Hui; Ji, Kai Fan
2014-04-01
Many advanced ground-based solar telescopes improve the spatial resolution of observation images using an adaptive optics (AO) system. As any AO correction remains only partial, it is necessary to use post-processing image reconstruction techniques such as speckle masking or shift-and-add (SAA) to reconstruct a high-spatial-resolution image from atmospherically degraded solar images. In the New Vacuum Solar Telescope (NVST), the spatial resolution in solar images is improved by frame selection and SAA. In order to overcome the burden of massive speckle data processing, we investigate the possibility of using the speckle reconstruction program in a real-time application at the telescope site. The code has been written in the C programming language and optimized for parallel processing in a multi-processor environment. We analyze the scalability of the code to identify possible bottlenecks, and we conclude that the presented code is capable of being run in real-time reconstruction applications at NVST and future large aperture solar telescopes if care is taken that the multi-processor environment has low latencies between the computation nodes.
Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.
Fromm, S A; Sachse, C
2016-01-01
Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method.
Magnetic resonance imaging with nonlinear gradient fields signal encoding and image reconstruction
Schultz, Gerrit
2013-01-01
Within the past few decades magnetic resonance imaging has become one of the most important imaging modalities in medicine. For a reliable diagnosis of pathologies further technological improvements are of primary importance. This text deals with a radically new approach of image encoding: The fundamental principle of gradient linearity is challenged by investigating the possibilities of acquiring anatomical images with the help of nonlinear gradient fields. Besides a thorough theoretical analysis with a focus on signal encoding and image reconstruction, initial hardware implementations are tested using phantom as well as in-vivo measurements. Several applications are presented that give an impression about the implications that this technological advancement may have for future medical diagnostics. Contents n Image Reconstruction in MRI n Nonlinear Gradient Encoding: PatLoc Imaging n Presentation of Initial Hardware Designs n Basics of Signal Encoding and Image Reconstruction in PatLoc Imaging n ...
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Ukwatta, Eranga, E-mail: eukwatt1@jhu.edu; Arevalo, Hermenegild; Pashakhanloo, Farhad; Prakosa, Adityo; Vadakkumpadan, Fijoy [Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland 21205 and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205 (United States); Rajchl, Martin [Department of Computing, Imperial College London, London SW7 2AZ (United Kingdom); White, James [Stephenson Cardiovascular MR Centre, University of Calgary, Calgary, Alberta T2N 2T9 (Canada); Herzka, Daniel A.; McVeigh, Elliot [Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205 (United States); Lardo, Albert C. [Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205 and Division of Cardiology, Johns Hopkins Institute of Medicine, Baltimore, Maryland 21224 (United States); Trayanova, Natalia A. [Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland 21205 (United States); Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205 (United States); Department of Biomedical Engineering, Johns Hopkins Institute of Medicine, Baltimore, Maryland 21205 (United States)
2015-08-15
Purpose: Accurate three-dimensional (3D) reconstruction of myocardial infarct geometry is crucial to patient-specific modeling of the heart aimed at providing therapeutic guidance in ischemic cardiomyopathy. However, myocardial infarct imaging is clinically performed using two-dimensional (2D) late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) techniques, and a method to build accurate 3D infarct reconstructions from the 2D LGE-CMR images has been lacking. The purpose of this study was to address this need. Methods: The authors developed a novel methodology to reconstruct 3D infarct geometry from segmented low-resolution (Lo-res) clinical LGE-CMR images. Their methodology employed the so-called logarithm of odds (LogOdds) function to implicitly represent the shape of the infarct in segmented image slices as LogOdds maps. These 2D maps were then interpolated into a 3D image, and the result transformed via the inverse of LogOdds to a binary image representing the 3D infarct geometry. To assess the efficacy of this method, the authors utilized 39 high-resolution (Hi-res) LGE-CMR images, including 36 in vivo acquisitions of human subjects with prior myocardial infarction and 3 ex vivo scans of canine hearts following coronary ligation to induce infarction. The infarct was manually segmented by trained experts in each slice of the Hi-res images, and the segmented data were downsampled to typical clinical resolution. The proposed method was then used to reconstruct 3D infarct geometry from the downsampled images, and the resulting reconstructions were compared with the manually segmented data. The method was extensively evaluated using metrics based on geometry as well as results of electrophysiological simulations of cardiac sinus rhythm and ventricular tachycardia in individual hearts. Several alternative reconstruction techniques were also implemented and compared with the proposed method. Results: The accuracy of the LogOdds method in reconstructing 3D
Generalized Fourier slice theorem for cone-beam image reconstruction.
Zhao, Shuang-Ren; Jiang, Dazong; Yang, Kevin; Yang, Kang
2015-01-01
The cone-beam reconstruction theory has been proposed by Kirillov in 1961, Tuy in 1983, Feldkamp in 1984, Smith in 1985, Pierre Grangeat in 1990. The Fourier slice theorem is proposed by Bracewell 1956, which leads to the Fourier image reconstruction method for parallel-beam geometry. The Fourier slice theorem is extended to fan-beam geometry by Zhao in 1993 and 1995. By combining the above mentioned cone-beam image reconstruction theory and the above mentioned Fourier slice theory of fan-beam geometry, the Fourier slice theorem in cone-beam geometry is proposed by Zhao 1995 in short conference publication. This article offers the details of the derivation and implementation of this Fourier slice theorem for cone-beam geometry. Especially the problem of the reconstruction from Fourier domain has been overcome, which is that the value of in the origin of Fourier space is 0/0. The 0/0 type of limit is proper handled. As examples, the implementation results for the single circle and two perpendicular circle source orbits are shown. In the cone-beam reconstruction if a interpolation process is considered, the number of the calculations for the generalized Fourier slice theorem algorithm is O(N^4), which is close to the filtered back-projection method, here N is the image size of 1-dimension. However the interpolation process can be avoid, in that case the number of the calculations is O(N5).
Principles of MR image formation and reconstruction.
Duerk, J L
1999-11-01
This article describes a number of concepts that provide insights into the process of MR imaging. The use of shaped, fixed-bandwidth RF pulses and magnetic field gradients is described to provide an understanding of the methods used for slice selection. Variations in the slice-excitation profile are shown as a function of the RF pulse shape used, the truncation method used, and the tip angle. It should be remembered that although the goal is to obtain uniform excitation across the slice, this goal is never achieved in practice, thus necessitating the use of slice gaps in some cases. Excitation, refocusing, and inversion pulses are described. Excitation pulses nutate the spins from the longitudinal axis into the transverse plane, where their magnetization can be detected. Refocusing pulses are used to flip the magnetization through 180 degrees once it is in the transverse plane, so that the influence of magnetic field inhomogeneities is eliminated. Inversion pulses are used to flip the magnetization from the +z to the -z direction in invesrsion-recovery sequences. Radiofrequency pulses can also be used to eliminate either fat or water protons from the images because of the small differences in resonant frequency between these two types of protons. Selective methods based on chemical shift and binomial methods are described. Once the desired magnetization has been tipped into the transverse plane by the slice-selection process, two imaging axes remain to be spatially encoded. One axis is easily encoded by the application of a second magnetic field gradient that establishes a one-to-one mapping between position and frequency during the time that the signal is converted from analog to digital sampling. This frequency-encoding gradient is used in combination with the Fourier transform to determine the location of the precessing magnetization. The second image axis is encoded by a process known as phase encoding. The collected data can be described as the 2D Fourier
Efficient iterative image reconstruction algorithm for dedicated breast CT
Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan
2016-03-01
Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.
Whole Mouse Brain Image Reconstruction from Serial Coronal Sections Using FIJI (ImageJ).
Paletzki, Ronald; Gerfen, Charles R
2015-10-01
Whole-brain reconstruction of the mouse enables comprehensive analysis of the distribution of neurochemical markers, the distribution of anterogradely labeled axonal projections or retrogradely labeled neurons projecting to a specific brain site, or the distribution of neurons displaying activity-related markers in behavioral paradigms. This unit describes a method to produce whole-brain reconstruction image sets from coronal brain sections with up to four fluorescent markers using the freely available image-processing program FIJI (ImageJ).
Progress Update on Iterative Reconstruction of Neutron Tomographic Images
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Hausladen, Paul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gregor, Jens [Univ. of Tennessee, Knoxville, TN (United States)
2016-09-15
This report satisfies the fiscal year 2016 technical deliverable to report on progress in development of fast iterative reconstruction algorithms for project OR16-3DTomography-PD2Jb, "3D Tomography and Image Processing Using Fast Neutrons." This project has two overall goals. The first of these goals is to extend associated-particle fast neutron transmission and, particularly, induced-reaction tomographic imaging algorithms to three dimensions. The second of these goals is to automatically segment the resultant tomographic images into constituent parts, and then extract information about the parts, such as the class of shape and potentially shape parameters. This report addresses of the component of the project concerned with three-dimensional (3D) image reconstruction.
Canning plasmonic microscopy by image reconstruction from the Fourier space
Mollet, O; Drezet, A
2014-01-01
We demonstrate a simple scheme for high-resolution imaging of nanoplasmonic structures that basically removes most of the resolution limiting allowed light usually transmitted to the far field. This is achieved by implementing a Fourier lens in a near-field scanning optical microscope (NSOM) operating in the leakage-radiation microscopy (LRM) mode. The method consists of reconstructing optical images solely from the plasmonic `forbidden' light collected in the Fourier space. It is demonstrated by using a point-like nanodiamond-based tip that illuminates a thin gold film patterned with a sub-wavelength annular slit. The reconstructed image of the slit shows a spatial resolution enhanced by a factor $\\simeq 4$ compared to NSOM images acquired directly in the real space.
Joint Image Reconstruction and Segmentation Using the Potts Model
Storath, Martin; Frikel, Jürgen; Unser, Michael
2014-01-01
We propose a new algorithmic approach to the non-smooth and non-convex Potts problem (also called piecewise-constant Mumford-Shah problem) for inverse imaging problems. We derive a suitable splitting into specific subproblems that can all be solved efficiently. Our method does not require a priori knowledge on the gray levels nor on the number of segments of the reconstruction. Further, it avoids anisotropic artifacts such as geometric staircasing. We demonstrate the suitability of our method for joint image reconstruction and segmentation from limited data in x-ray and photoacoustic tomography. For instance, our method is able to reconstruct the Shepp-Logan phantom from $7$ angular views only. We demonstrate the practical applicability in an experiment with real PET data.
Energy Technology Data Exchange (ETDEWEB)
Ortuno, J E; Kontaxakis, G; Rubio, J L; Santos, A [Departamento de Ingenieria Electronica (DIE), Universidad Politecnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain); Guerra, P [Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid (Spain)], E-mail: juanen@die.upm.es
2010-04-07
A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries.
Single Image Super Resolution via Sparse Reconstruction
Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.
2012-01-01
High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms. Limita
Undersampled Hyperspectral Image Reconstruction Based on Surfacelet Transform
Directory of Open Access Journals (Sweden)
Lei Liu
2015-01-01
Full Text Available Hyperspectral imaging is a crucial technique for military and environmental monitoring. However, limited equipment hardware resources severely affect the transmission and storage of a huge amount of data for hyperspectral images. This limitation has the potentials to be solved by compressive sensing (CS, which allows reconstructing images from undersampled measurements with low error. Sparsity and incoherence are two essential requirements for CS. In this paper, we introduce surfacelet, a directional multiresolution transform for 3D data, to sparsify the hyperspectral images. Besides, a Gram-Schmidt orthogonalization is used in CS random encoding matrix, two-dimensional and three-dimensional orthogonal CS random encoding matrixes and a patch-based CS encoding scheme are designed. The proposed surfacelet-based hyperspectral images reconstruction problem is solved by a fast iterative shrinkage-thresholding algorithm. Experiments demonstrate that reconstruction of spectral lines and spatial images is significantly improved using the proposed method than using conventional three-dimensional wavelets, and growing randomness of encoding matrix can further improve the quality of hyperspectral data. Patch-based CS encoding strategy can be used to deal with large data because data in different patches can be independently sampled.
Phase Closure Image Reconstruction for Future VLTI Instrumentation
Filho, Mercedes E; Garcia, Paulo; Duvert, Gilles; Duchene, Gaspard; Thiebaut, Eric; Young, John; Absil, Olivier; Berger, Jean-Phillipe; Beckert, Thomas; Hoenig, Sebastian; Schertl, Dieter; Weigelt, Gerd; Testi, Leonardo; Tatuli, Eric; Borkowski, Virginie; de Becker, Michael; Surdej, Jean; Aringer, Bernard; Hron, Joseph; Lebzelter, Thomas; Chiavassa, Andrea; Corradi, Romano; Harries, Tim
2008-01-01
Classically, optical and near-infrared interferometry have relied on closure phase techniques to produce images. Such techniques allow us to achieve modest dynamic ranges. In order to test the feasibility of next generation optical interferometers in the context of the VLTI-spectro-imager (VSI), we have embarked on a study of image reconstruction and analysis. Our main aim was to test the influence of the number of telescopes, observing nights and distribution of the visibility points on the quality of the reconstructed images. Our results show that observations using six Auxiliary Telescopes (ATs) during one complete night yield the best results in general and is critical in most science cases; the number of telescopes is the determining factor in the image reconstruction outcome. In terms of imaging capabilities, an optical, six telescope VLTI-type configuration and ~200 meter baseline will achieve 4 mas spatial resolution, which is comparable to ALMA and almost 50 times better than JWST will achieve at 2.2...
Projective 3D-reconstruction of Uncalibrated Endoscopic Images
Directory of Open Access Journals (Sweden)
P. Faltin
2010-01-01
Full Text Available The most common medical diagnostic method for urinary bladder cancer is cystoscopy. This inspection of the bladder is performed by a rigid endoscope, which is usually guided close to the bladder wall. This causes a very limited field of view; difficulty of navigation is aggravated by the usage of angled endoscopes. These factors cause difficulties in orientation and visual control. To overcome this problem, the paper presents a method for extracting 3D information from uncalibrated endoscopic image sequences and for reconstructing the scene content. The method uses the SURF-algorithm to extract features from the images and relates the images by advanced matching. To stabilize the matching, the epipolar geometry is extracted for each image pair using a modified RANSAC-algorithm. Afterwards these matched point pairs are used to generate point triplets over three images and to describe the trifocal geometry. The 3D scene points are determined by applying triangulation to the matched image points. Thus, these points are used to generate a projective 3D reconstruction of the scene, and provide the first step for further metric reconstructions.
Three-dimensional reconstruction of functional brain images
Energy Technology Data Exchange (ETDEWEB)
Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao [Kyoto Univ. (Japan)
1999-08-01
We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: routine images by SPM, three-dimensional static images, and three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface
Reconstruction of 3d Digital Image of Weepingforsythia Pollen
Liu, Dongwu; Chen, Zhiwei; Xu, Hongzhi; Liu, Wenqi; Wang, Lina
Confocal microscopy, which is a major advance upon normal light microscopy, has been used in a number of scientific fields. By confocal microscopy techniques, cells and tissues can be visualized deeply, and three-dimensional images created. Compared with conventional microscopes, confocal microscope improves the resolution of images by eliminating out-of-focus light. Moreover, confocal microscope has a higher level of sensitivity due to highly sensitive light detectors and the ability to accumulate images captured over time. In present studies, a series of Weeping Forsythia pollen digital images (35 images in total) were acquired with confocal microscope, and the three-dimensional digital image of the pollen reconstructed with confocal microscope. Our results indicate that it's a very easy job to analysis threedimensional digital image of the pollen with confocal microscope and the probe Acridine orange (AO).
Integrated imaging of neuromagnetic reconstructions and morphological magnetic resonance data.
Kullmann, W H; Fuchs, M
1991-01-01
New neuromagnetic imaging methods provide spatial information about the functional electrical properties of complex current distributions in the human brain. For practical use in medical diagnosis a combination of the abstract neuromagnetic imaging results with magnetic resonance (MR) or computed tomography (CT) images of the morphology is required. The biomagnetic images can be overlayed onto three-dimensional morphological images with spatially arbitrary selectable slices, calculated from conventional 2D data. For the current reconstruction the 3D images furthermore provide a priori information about the conductor geometry. A combination of current source density calculations and linear estimation methods for handling the inverse magnetic problem allows quick imaging of impressed current source density in arbitrary volume conductors.
A novel data processing technique for image reconstruction of penumbral imaging
Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin
2011-06-01
CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.
Mareboyana, Manohar; Le Moigne-Stewart, Jacqueline; Bennett, Jerome
2016-01-01
In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.
Mareboyana, Manohar; Le Moigne, Jacqueline; Bennett, Jerome
2016-05-01
In this paper, we demonstrate simple algorithms that project low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithms are very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. are used in projection. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML) algorithms. The algorithms are robust and are not overly sensitive to the registration inaccuracies.
Huang, Chao; Oraevsky, Alexander A.; Anastasio, Mark A.
2010-08-01
Optoacoustic tomography (OAT) is an emerging ultrasound-mediated biophotonic imaging modality that has exciting potential for many biomedical imaging applications. There is great interest in conducting B-mode ultrasound and OAT imaging studies for breast cancer detection using a common transducer. In this situation, the range of tomographic view angles is limited, which can result in distortions in the reconstructed OAT image if conventional reconstruction algorithms are applied to limited-view measurement data. In this work, we investigate an image reconstruction method that utilizes information regarding target boundaries to improve the quality of the reconstructed OAT images. This is accomplished by developing boundary-constrained image reconstruction algorithm for OAT based on Bayesian image reconstruction theory. The computer-simulation studies demonstrate that the Bayesian approach can effectively reduce the artifact and noise levels and preserve the edges in reconstructed limited-view OAT images as compared to those produced by a conventional OAT reconstruction algorithm.
Constrain static target kinetic iterative image reconstruction for 4D cardiac CT imaging
Alessio, Adam M.; La Riviere, Patrick J.
2011-03-01
Iterative image reconstruction offers improved signal to noise properties for CT imaging. A primary challenge with iterative methods is the substantial computation time. This computation time is even more prohibitive in 4D imaging applications, such as cardiac gated or dynamic acquisition sequences. In this work, we propose only updating the time-varying elements of a 4D image sequence while constraining the static elements to be fixed or slowly varying in time. We test the method with simulations of 4D acquisitions based on measured cardiac patient data from a) a retrospective cardiac-gated CT acquisition and b) a dynamic perfusion CT acquisition. We target the kinetic elements with one of two methods: 1) position a circular ROI on the heart, assuming area outside ROI is essentially static throughout imaging time; and 2) select varying elements from the coefficient of variation image formed from fast analytic reconstruction of all time frames. Targeted kinetic elements are updated with each iteration, while static elements remain fixed at initial image values formed from the reconstruction of data from all time frames. Results confirm that the computation time is proportional to the number of targeted elements; our simulations suggest that 3 times reductions in reconstruction time. The images reconstructed with the proposed method have matched mean square error with full 4D reconstruction. The proposed method is amenable to most optimization algorithms and offers the potential for significant computation improvements, which could be traded off for more sophisticated system models or penalty terms.
Groussin, Mathieu; Hobbs, Joanne K; Szöllősi, Gergely J; Gribaldo, Simonetta; Arcus, Vickery L; Gouy, Manolo
2015-01-01
The resurrection of ancestral proteins provides direct insight into how natural selection has shaped proteins found in nature. By tracing substitutions along a gene phylogeny, ancestral proteins can be reconstructed in silico and subsequently synthesized in vitro. This elegant strategy reveals the complex mechanisms responsible for the evolution of protein functions and structures. However, to date, all protein resurrection studies have used simplistic approaches for ancestral sequence reconstruction (ASR), including the assumption that a single sequence alignment alone is sufficient to accurately reconstruct the history of the gene family. The impact of such shortcuts on conclusions about ancestral functions has not been investigated. Here, we show with simulations that utilizing information on species history using a model that accounts for the duplication, horizontal transfer, and loss (DTL) of genes statistically increases ASR accuracy. This underscores the importance of the tree topology in the inference of putative ancestors. We validate our in silico predictions using in vitro resurrection of the LeuB enzyme for the ancestor of the Firmicutes, a major and ancient bacterial phylum. With this particular protein, our experimental results demonstrate that information on the species phylogeny results in a biochemically more realistic and kinetically more stable ancestral protein. Additional resurrection experiments with different proteins are necessary to statistically quantify the impact of using species tree-aware gene trees on ancestral protein phenotypes. Nonetheless, our results suggest the need for incorporating both sequence and DTL information in future studies of protein resurrections to accurately define the genotype-phenotype space in which proteins diversify.
Polarimetric ISAR: Simulation and image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Chambers, David H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2016-03-21
In polarimetric ISAR the illumination platform, typically airborne, carries a pair of antennas that are directed toward a fixed point on the surface as the platform moves. During platform motion, the antennas maintain their gaze on the point, creating an effective aperture for imaging any targets near that point. The interaction between the transmitted fields and targets (e.g. ships) is complicated since the targets are typically many wavelengths in size. Calculation of the field scattered from the target typically requires solving Maxwell’s equations on a large three-dimensional numerical grid. This is prohibitive to use in any real-world imaging algorithm, so the scattering process is typically simplified by assuming the target consists of a cloud of independent, non-interacting, scattering points (centers). Imaging algorithms based on this scattering model perform well in many applications. Since polarimetric radar is not very common, the scattering model is often derived for a scalar field (single polarization) where the individual scatterers are assumed to be small spheres. However, when polarization is important, we must generalize the model to explicitly account for the vector nature of the electromagnetic fields and its interaction with objects. In this note, we present a scattering model that explicitly includes the vector nature of the fields but retains the assumption that the individual scatterers are small. The response of the scatterers is described by electric and magnetic dipole moments induced by the incident fields. We show that the received voltages in the antennas are linearly related to the transmitting currents through a scattering impedance matrix that depends on the overall geometry of the problem and the nature of the scatterers.
Li, Li; Xiao, Wei; Jian, Weijian
2014-11-20
Three-dimensional (3D) laser imaging combining compressive sensing (CS) has an advantage in lower power consumption and less imaging sensors; however, it brings enormous stress to subsequent calculation devices. In this paper we proposed a fast 3D imaging reconstruction algorithm to deal with time-slice images sampled by single-pixel detectors. The algorithm implements 3D imaging reconstruction before CS recovery, thus it saves plenty of runtime of CS recovery. Several experiments are conducted to verify the performance of the algorithm. Simulation results demonstrated that the proposed algorithm has better performance in terms of efficiency compared to an existing algorithm.
Image Reconstruction for Invasive ERT in Vertical Oil Well Logging
Institute of Scientific and Technical Information of China (English)
周海力; 徐立军; 曹章; 胡金海; 刘兴斌
2012-01-01
An invasive electrical resistance tomographic sensor was proposed for production logging in vertical oil well.The sensor consists of 24 electrodes that are fixed to the logging tool,which can move in the pipeline to acquire data on the conductivity distribution of oil/water mixture flow at different depths.A sensitivity-based algorithm was introduced to reconstruct the cross-sectional images.Analysis on the sensitivity of the sensor to the distribution of oil/water mixture flow was carried out to optimize the position of the imaging cross-section.The imaging results obtained using various boundary conditions at the pipe wall and the logging tool were compared.Eight typical models with various conductivity distributions were created and the measurement data were obtained by solving the forward problem of the sensor system.Image reconstruction was then implemented by using the simulation data for each model.Comparisons between the models and the reconstructed images show that the number and spatial distribution of the oil bubbles can be clearly identified.
Toward 5D image reconstruction for optical interferometry
Baron, Fabien; Kloppenborg, Brian; Monnier, John
2012-07-01
We report on our progress toward a flexible image reconstruction software for optical interferometry capable of "5D imaging" of stellar surfaces. 5D imaging is here defined as the capability to image directly one or several stars in three dimensions, with both the time and wavelength dependencies taken into account during the reconstruction process. Our algorithm makes use of the Healpix (Gorski et al., 2005) sphere partition scheme to tesselate the stellar surface, 3D Open Graphics Language (OpenGL) to model the spheroid geometry, and the Open Compute Language (OpenCL) framework for all other computations. We use the Monte Carlo Markov Chain software SQUEEZE to solve the image reconstruction problem on the surfaces of these stars. Finally, the Compressed Sensing and Bayesian Evidence paradigms are employed to determine the best regularization for spotted stars. Our algorithm makes use of the Healpix (reference needed) sphere partition scheme to tesselate the stellar surface, 3D Open Graphics Language (OpenGL) to model the spheroid, and the Open Compute Language (OpenCL) framework to model the Roche gravitational potential equation.
Proton Computed Tomography: iterative image reconstruction and dose evaluation
Civinini, C.; Bonanno, D.; Brianzi, M.; Carpinelli, M.; Cirrone, G. A. P.; Cuttone, G.; Lo Presti, D.; Maccioni, G.; Pallotta, S.; Randazzo, N.; Scaringella, M.; Romano, F.; Sipala, V.; Talamonti, C.; Vanzi, E.; Bruzzi, M.
2017-01-01
Proton Computed Tomography (pCT) is a medical imaging method with a potential for increasing accuracy of treatment planning and patient positioning in hadron therapy. A pCT system based on a Silicon microstrip tracker and a YAG:Ce crystal calorimeter has been developed within the INFN Prima-RDH collaboration. The prototype has been tested with a 175 MeV proton beam at The Svedberg Laboratory (Uppsala, Sweden) with the aim to reconstruct and characterize a tomographic image. Algebraic iterative reconstruction methods (ART), together with the most likely path formalism, have been used to obtain tomographies of an inhomogeneous phantom to eventually extract density and spatial resolutions. These results will be presented and discussed together with an estimation of the average dose delivered to the phantom and the dependence of the image quality on the dose. Due to the heavy computation load required by the algebraic algorithms the reconstruction programs have been implemented to fully exploit the high calculation parallelism of Graphics Processing Units. An extended field of view pCT system is in an advanced construction stage. This apparatus will be able to reconstruct objects of the size of a human head making possible to characterize this pCT approach in a pre-clinical environment.
3D reconstruction of multiple stained histology images
Directory of Open Access Journals (Sweden)
Yi Song
2013-01-01
Full Text Available Context: Three dimensional (3D tissue reconstructions from the histology images with different stains allows the spatial alignment of structural and functional elements highlighted by different stains for quantitative study of many physiological and pathological phenomena. This has significant potential to improve the understanding of the growth patterns and the spatial arrangement of diseased cells, and enhance the study of biomechanical behavior of the tissue structures towards better treatments (e.g. tissue-engineering applications. Methods: This paper evaluates three strategies for 3D reconstruction from sets of two dimensional (2D histological sections with different stains, by combining methods of 2D multi-stain registration and 3D volumetric reconstruction from same stain sections. Setting and Design: The different strategies have been evaluated on two liver specimens (80 sections in total stained with Hematoxylin and Eosin (H and E, Sirius Red, and Cytokeratin (CK 7. Results and Conclusion: A strategy of using multi-stain registration to align images of a second stain to a volume reconstructed by same-stain registration results in the lowest overall error, although an interlaced image registration approach may be more robust to poor section quality.
3D RECONSTRUCTION FROM MULTI-VIEW MEDICAL X-RAY IMAGES – REVIEW AND EVALUATION OF EXISTING METHODS
Directory of Open Access Journals (Sweden)
S. Hosseinian
2015-12-01
Full Text Available The 3D concept is extremely important in clinical studies of human body. Accurate 3D models of bony structures are currently required in clinical routine for diagnosis, patient follow-up, surgical planning, computer assisted surgery and biomechanical applications. However, 3D conventional medical imaging techniques such as computed tomography (CT scan and magnetic resonance imaging (MRI have serious limitations such as using in non-weight-bearing positions, costs and high radiation dose(for CT. Therefore, 3D reconstruction methods from biplanar X-ray images have been taken into consideration as reliable alternative methods in order to achieve accurate 3D models with low dose radiation in weight-bearing positions. Different methods have been offered for 3D reconstruction from X-ray images using photogrammetry which should be assessed. In this paper, after demonstrating the principles of 3D reconstruction from X-ray images, different existing methods of 3D reconstruction of bony structures from radiographs are classified and evaluated with various metrics and their advantages and disadvantages are mentioned. Finally, a comparison has been done on the presented methods with respect to several metrics such as accuracy, reconstruction time and their applications. With regards to the research, each method has several advantages and disadvantages which should be considered for a specific application.
Last, Carsten
2017-01-01
This book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both of which have their drawbacks. The approach presented uses a local shape prior in each element of the underlying data domain and couples all local shape priors via smoothness constraints. The book provides a sound mathematical foundation in order to embed this new shape prior formulation into the well-known variational image segmentation framework. The new segmentation approach so obtained allows accurate reconstruction of even complex object classes with only a few training shapes at hand.
Fast and accurate generation method of PSF-based system matrix for PET reconstruction
Sun, Xiao-Li; Yun, Ming-Kai; Li, Dao-Wu; Gao, Juan; Li, Mo-Han; Chai, Pei; Tang, Hao-Hui; Zhang, Zhi-Ming; Wei, Long
2016-01-01
Positional single photon incidence response (P-SPIR) theory is researched in this paper to generate more accurate PSF-contained system matrix simply and quickly. The method has been proved highly effective to improve the spatial resolution by applying to the Eplus-260 primate PET designed by the Institute of High Energy Physics of the Chinese Academy of Sciences(IHEP). Simultaneously, to meet the clinical needs, GPU acceleration is put to use. Basically, P-SPIR theory takes both incidence angle and incidence position by crystal subdivision instead of only incidence angle into consideration based on Geant4 Application for Emission Tomography (GATE). The simulation conforms to the actual response distribution and can be completed rapidly within less than 1s. Furthermore,two-block penetration and normalization of the response probability are raised to fit the reality. With PSF obtained, the homogenization model is analyzed to calculate the spread distribution of bins within a few minutes for system matrix genera...
The SRT reconstruction algorithm for semiquantification in PET imaging
Energy Technology Data Exchange (ETDEWEB)
Kastis, George A., E-mail: gkastis@academyofathens.gr [Research Center of Mathematics, Academy of Athens, Athens 11527 (Greece); Gaitanis, Anastasios [Biomedical Research Foundation of the Academy of Athens (BRFAA), Athens 11527 (Greece); Samartzis, Alexandros P. [Nuclear Medicine Department, Evangelismos General Hospital, Athens 10676 (Greece); Fokas, Athanasios S. [Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB30WA, United Kingdom and Research Center of Mathematics, Academy of Athens, Athens 11527 (Greece)
2015-10-15
Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of {sup 18}F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT
LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation
Li, Yusheng; Matej, Samuel; Karp, Joel S.; Metzler, Scott D.
2015-01-01
Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector’s intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanners. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present a LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the non-negative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which
List-mode MLEM Image Reconstruction from 3D ML Position Estimates.
Caucci, Luca; Hunter, William C J; Furenlid, Lars R; Barrett, Harrison H
2010-10-01
Current thick detectors used in medical imaging allow recording many attributes, such as the 3D location of interaction within the scintillation crystal and the amount of energy deposited. An efficient way of dealing with these data is by storing them in list-mode (LM). To reconstruct the data, maximum-likelihood expectation-maximization (MLEM) is efficiently applied to the list-mode data, resulting in the list-mode maximum-likelihood expectation-maximization (LMMLEM) reconstruction algorithm.In this work, we consider a PET system consisting of two thick detectors facing each other. PMT outputs are collected for each coincidence event and are used to perform 3D maximum-likelihood (ML) position estimation of location of interaction. The mathematical properties of the ML estimation allow accurate modeling of the detector blur and provide a theoretical framework for the subsequent estimation step, namely the LMMLEM reconstruction. Indeed, a rigorous statistical model for the detector output can be obtained from calibration data and used in the calculation of the conditional probability density functions for the interaction location estimates.Our implementation of the 3D ML position estimation takes advantage of graphics processing unit (GPU) hardware and permits accurate real-time estimates of position of interaction. The LMMLEM algorithm is then applied to the list of position estimates, and the 3D radiotracer distribution is reconstructed on a voxel grid.
Energy Technology Data Exchange (ETDEWEB)
Min, Jonghwan; Pua, Rizza; Cho, Seungryong, E-mail: scho@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Kim, Insoo; Han, Bumsoo [EB Tech, Co., Ltd., 550 Yongsan-dong, Yuseong-gu, Daejeon 305-500 (Korea, Republic of)
2015-11-15
Purpose: A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. Methods: The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in a circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. Results: The simulation study revealed that the developed reconstruction algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. Conclusions: The authors have successfully demonstrated that the
Light field display and 3D image reconstruction
Iwane, Toru
2016-06-01
Light field optics and its applications become rather popular in these days. With light field optics or light field thesis, real 3D space can be described in 2D plane as 4D data, which we call as light field data. This process can be divided in two procedures. First, real3D scene is optically reduced with imaging lens. Second, this optically reduced 3D image is encoded into light field data. In later procedure we can say that 3D information is encoded onto a plane as 2D data by lens array plate. This transformation is reversible and acquired light field data can be decoded again into 3D image with the arrayed lens plate. "Refocusing" (focusing image on your favorite point after taking a picture), light-field camera's most popular function, is some kind of sectioning process from encoded 3D data (light field data) to 2D image. In this paper at first I show our actual light field camera and our 3D display using acquired and computer-simulated light field data, on which real 3D image is reconstructed. In second I explain our data processing method whose arithmetic operation is performed not in Fourier domain but in real domain. Then our 3D display system is characterized by a few features; reconstructed image is of finer resolutions than density of arrayed lenses and it is not necessary to adjust lens array plate to flat display on which light field data is displayed.
Accuracy of quantitative reconstructions in SPECT/CT imaging
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Shcherbinin, S; Celler, A [Department of Radiology, University of British Columbia, 366-828 West 10th Avenue, Vancouver BC, V5Z 1L8 (Canada); Belhocine, T; Vanderwerf, R; Driedger, A [Department of Nuclear Medicine, London Health Sciences Centre, 375 South Street, PO Box 5375, London ON, N6A 4G5 (Canada)], E-mail: shcher2@interchange.ubc.ca
2008-09-07
The goal of this study was to determine the quantitative accuracy of our OSEM-APDI reconstruction method based on SPECT/CT imaging for Tc-99m, In-111, I-123, and I-131 isotopes. Phantom studies were performed on a SPECT/low-dose multislice CT system (Infinia-Hawkeye-4 slice, GE Healthcare) using clinical acquisition protocols. Two radioactive sources were centrally and peripherally placed inside an anthropometric Thorax phantom filled with non-radioactive water. Corrections for attenuation, scatter, collimator blurring and collimator septal penetration were applied and their contribution to the overall accuracy of the reconstruction was evaluated. Reconstruction with the most comprehensive set of corrections resulted in activity estimation with error levels of 3-5% for all the isotopes.
Holographic images reconstructed from GMR-based fringe pattern
Directory of Open Access Journals (Sweden)
Kikuchi Hiroshi
2013-01-01
Full Text Available We have developed a magneto-optical spatial light modulator (MOSLM using giant magneto-resistance (GMR structures for realizing a holographic three-dimensional (3D display. For practical applications, reconstructed image of hologram consisting of GMR structures should be investigated in order to study the feasibility of the MOSLM. In this study, we fabricated a hologram with GMR based fringe-pattern and demonstrated a reconstructed image. A fringe-pattern convolving a crossshaped image was calculated by a conventional binary computer generated hologram (CGH technique. The CGH-pattern has 2,048 × 2,048 with 5 μm pixel pitch. The GMR stack consists of a Tb-Fe-Co/CoFe pinned layer, a Ag spacer, a Gd-Fe free layer for light modulation, and a Ru capping layer, was deposited by dc-magnetron sputtering. The GMR hologram was formed using photo-lithography and Krion milling processes, followed by the deposition of a Tb-Fe-Co reference layer with large coercivity and the same Kerr-rotation angle compared to the free layer, and a lift-off process. The reconstructed image of the ON-state was clearly observed and successfully distinguished from the OFF-state by switching the magnetization direction of the free-layer with an external magnetic field. These results indicate the possibility of realizing a holographic 3D display by the MOSLM using the GMR structures.
Missing data reconstruction using Gaussian mixture models for fingerprint images
Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary
2016-05-01
Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.
Complications of anterior cruciate ligament reconstruction: MR imaging.
Papakonstantinou, Olympia; Chung, Christine B; Chanchairujira, Kullanuch; Resnick, Donald L
2003-05-01
Arthroscopic reconstruction of the anterior cruciate ligament (ACL) using autografts or allografts is being performed with increasing frequency, particularly in young athletes. Although the procedure is generally well tolerated, with good success rates, early and late complications have been documented. As clinical manifestations of graft complications are often non-specific and plain radiographs cannot directly visualize the graft and the adjacent soft tissues, MR imaging has a definite role in the diagnosis of complications after ACL reconstruction and may direct subsequent therapeutic management. Our purpose is to review the normal MR imaging of the ACL graft and present the MR imaging findings of a wide spectrum of complications after ACL reconstruction, such as graft impingement, graft rupture, cystic degeneration of the graft, postoperative infection of the knee, diffuse and localized (i.e., cyclops lesion) arthrofibrosis, and associated donor site abnormalities. Awareness of the MR imaging findings of complications as well as the normal appearances of the normal ACL graft is essential for correct interpretation.
Complications of anterior cruciate ligament reconstruction: MR imaging
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Papakonstantinou, Olympia; Chung, Christine B.; Chanchairujira, Kullanuch; Resnick, Donald L. [Department of Radiology, Veterans Affairs Medical Center, University of California, 3350 La Jolla Village Dr., San Diego, CA 92161 (United States)
2003-05-01
Arthroscopic reconstruction of the anterior cruciate ligament (ACL) using autografts or allografts is being performed with increasing frequency, particularly in young athletes. Although the procedure is generally well tolerated, with good success rates, early and late complications have been documented. As clinical manifestations of graft complications are often non-specific and plain radiographs cannot directly visualize the graft and the adjacent soft tissues, MR imaging has a definite role in the diagnosis of complications after ACL reconstruction and may direct subsequent therapeutic management. Our purpose is to review the normal MR imaging of the ACL graft and present the MR imaging findings of a wide spectrum of complications after ACL reconstruction, such as graft impingement, graft rupture, cystic degeneration of the graft, postoperative infection of the knee, diffuse and localized (i.e., cyclops lesion) arthrofibrosis, and associated donor site abnormalities. Awareness of the MR imaging findings of complications as well as the normal appearances of the normal ACL graft is essential for correct interpretation. (orig.)
Rapid 3D dynamic arterial spin labeling with a sparse model-based image reconstruction.
Zhao, Li; Fielden, Samuel W; Feng, Xue; Wintermark, Max; Mugler, John P; Meyer, Craig H
2015-11-01
Dynamic arterial spin labeling (ASL) MRI measures the perfusion bolus at multiple observation times and yields accurate estimates of cerebral blood flow in the presence of variations in arterial transit time. ASL has intrinsically low signal-to-noise ratio (SNR) and is sensitive to motion, so that extensive signal averaging is typically required, leading to long scan times for dynamic ASL. The goal of this study was to develop an accelerated dynamic ASL method with improved SNR and robustness to motion using a model-based image reconstruction that exploits the inherent sparsity of dynamic ASL data. The first component of this method is a single-shot 3D turbo spin echo spiral pulse sequence accelerated using a combination of parallel imaging and compressed sensing. This pulse sequence was then incorporated into a dynamic pseudo continuous ASL acquisition acquired at multiple observation times, and the resulting images were jointly reconstructed enforcing a model of potential perfusion time courses. Performance of the technique was verified using a numerical phantom and it was validated on normal volunteers on a 3-Tesla scanner. In simulation, a spatial sparsity constraint improved SNR and reduced estimation errors. Combined with a model-based sparsity constraint, the proposed method further improved SNR, reduced estimation error and suppressed motion artifacts. Experimentally, the proposed method resulted in significant improvements, with scan times as short as 20s per time point. These results suggest that the model-based image reconstruction enables rapid dynamic ASL with improved accuracy and robustness.
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Sharp, J H; Barnard, J S; Midgley, P A [Department of Materials Science, University of Cambridge, Pembroke Street, Cambridge, CB2 3QZ (United Kingdom); Kaneko, K; Higashida, K [Department of Materials Science and Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395 (Japan)], E-mail: jhd28@cam.ac.uk
2008-08-15
After previous work producing a successful 3D tomographic reconstruction of dislocations in GaN from conventional weak-beam dark-field (WBDF) images, we have reconstructed a cascade of dislocations in deformed and annealed silicon to a comparable standard using the more experimentally straightforward technique of STEM annular dark-field imaging (STEM ADF). In this mode, image contrast was much more consistent over the specimen tilt range than in conventional weak-beam dark-field imaging. Automatic acquisition software could thus restore the correct dislocation array to the field of view at each tilt angle, though manual focusing was still required. Reconstruction was carried out by sequential iterative reconstruction technique using FEI's Inspect3D software. Dislocations were distributed non-uniformly along cascades, with sparse areas between denser clumps in which individual dislocations of in-plane image width 24 nm could be distinguished in images and reconstruction. Denser areas showed more complicated stacking-fault contrast, hampering tomographic reconstruction. The general three-dimensional form of the denser areas was reproduced well, showing the dislocation array to be planar and not parallel to the foil surfaces.
An efficient simultaneous reconstruction technique for tomographic particle image velocimetry
Atkinson, Callum; Soria, Julio
2009-10-01
To date, Tomo-PIV has involved the use of the multiplicative algebraic reconstruction technique (MART), where the intensity of each 3D voxel is iteratively corrected to satisfy one recorded projection, or pixel intensity, at a time. This results in reconstruction times of multiple hours for each velocity field and requires considerable computer memory in order to store the associated weighting coefficients and intensity values for each point in the volume. In this paper, a rapid and less memory intensive reconstruction algorithm is presented based on a multiplicative line-of-sight (MLOS) estimation that determines possible particle locations in the volume, followed by simultaneous iterative correction. Reconstructions of simulated images are presented for two simultaneous algorithms (SART and SMART) as well as the now standard MART algorithm, which indicate that the same accuracy as MART can be achieved 5.5 times faster or 77 times faster with 15 times less memory if the processing and storage of the weighting matrix is considered. Application of MLOS-SMART and MART to a turbulent boundary layer at Re θ = 2200 using a 4 camera Tomo-PIV system with a volume of 1,000 × 1,000 × 160 voxels is discussed. Results indicate improvements in reconstruction speed of 15 times that of MART with precalculated weighting matrix, or 65 times if calculation of the weighting matrix is considered. Furthermore the memory needed to store a large weighting matrix and volume intensity is reduced by almost 40 times in this case.
Research on image matching method of big data image of three-dimensional reconstruction
Zhang, Chunsen; Qiu, Zhenguo; Zhu, Shihuan; Wang, Xiqi; Xu, Xiaolei; Zhong, Sidong
2015-12-01
Image matching is the main flow of a three-dimensional reconstruction. With the development of computer processing technology, seeking the image to be matched from the large date image sets which acquired from different image formats, different scales and different locations has put forward a new request for image matching. To establish the three dimensional reconstruction based on image matching from big data images, this paper put forward a new effective matching method based on visual bag of words model. The main technologies include building the bag of words model and image matching. First, extracting the SIFT feature points from images in the database, and clustering the feature points to generate the bag of words model. We established the inverted files based on the bag of words. The inverted files can represent all images corresponding to each visual word. We performed images matching depending on the images under the same word to improve the efficiency of images matching. Finally, we took the three-dimensional model with those images. Experimental results indicate that this method is able to improve the matching efficiency, and is suitable for the requirements of large data reconstruction.
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Arne Vladimir Blackman
2014-07-01
Full Text Available Accurate 3D reconstruction of neurons is vital for applications linking anatomy and physiology. Reconstructions are typically created using Neurolucida after biocytin histology (BH. An alternative inexpensive and fast method is to use freeware such as Neuromantic to reconstruct from fluorescence imaging (FI stacks acquired using 2-photon laser-scanning microscopy during physiological recording. We compare these two methods with respect to morphometry, cell classification, and multicompartmental modeling in the NEURON simulation environment. Quantitative morphological analysis of the same cells reconstructed using both methods reveals that whilst biocytin reconstructions facilitate tracing of more distal collaterals, both methods are comparable in representing the overall morphology: automated clustering of reconstructions from both methods successfully separates neocortical basket cells from pyramidal cells but not BH from FI reconstructions. BH reconstructions suffer more from tissue shrinkage and compression artifacts than FI reconstructions do. FI reconstructions, on the other hand, consistently have larger process diameters. Consequently, significant differences in NEURON modeling of excitatory post-synaptic potential (EPSP forward propagation are seen between the two methods, with FI reconstructions exhibiting smaller depolarizations. Simulated action potential backpropagation (bAP, however, is indistinguishable between reconstructions obtained with the two methods. In our hands, BH reconstructions are necessary for NEURON modeling and detailed morphological tracing, and thus remain state of the art, although they are more labor intensive, more expensive, and suffer from a higher failure rate. However, for a subset of anatomical applications such as cell type identification, FI reconstructions are superior, because of indistinguishable classification performance with greater ease of use, essentially 100% success rate, and lower cost.
Electromagnetic Model and Image Reconstruction Algorithms Based on EIT System
Institute of Scientific and Technical Information of China (English)
CAO Zhang; WANG Huaxiang
2006-01-01
An intuitive 2 D model of circular electrical impedance tomography ( EIT) sensor with small size electrodes is established based on the theory of analytic functions.The validation of the model is proved using the result from the solution of Laplace equation.Suggestions on to electrode optimization and explanation to the ill-condition property of the sensitivity matrix are provided based on the model,which takes electrode distance into account and can be generalized to the sensor with any simple connected region through a conformal transformation.Image reconstruction algorithms based on the model are implemented to show feasibility of the model using experimental data collected from the EIT system developed in Tianjin University.In the simulation with a human chestlike configuration,electrical conductivity distributions are reconstructed using equi-potential backprojection (EBP) and Tikhonov regularization (TR) based on a conformal transformation of the model.The algorithms based on the model are suitable for online image reconstruction and the reconstructed results are good both in size and position.
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Rozario, T; Bereg, S [University of Texas at Dallas, Richardson, TX (United States); Chiu, T; Liu, H; Kearney, V; Jiang, L; Mao, W [UT Southwestern Medical Center, Dallas, TX (United States)
2014-06-01
Purpose: In order to locate lung tumors on projection images without internal markers, digitally reconstructed radiograph (DRR) is created and compared with projection images. Since lung tumors always move and their locations change on projection images while they are static on DRRs, a special DRR (background DRR) is generated based on modified anatomy from which lung tumors are removed. In addition, global discrepancies exist between DRRs and projections due to their different image originations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported. Methods: This method divides global images into a matrix of small tiles and similarities will be evaluated by calculating normalized cross correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) will be automatically optimized to keep the tumor within a single tile which has bad matching with the corresponding DRR tile. A pixel based linear transformation will be determined by linear interpolations of tile transformation results obtained during tile matching. The DRR will be transformed to the projection image level and subtracted from it. The resulting subtracted image now contains only the tumor. A DRR of the tumor is registered to the subtracted image to locate the tumor. Results: This method has been successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (Brainlab) for dynamic tumor tracking on phantom studies. Radiation opaque markers are implanted and used as ground truth for tumor positions. Although, other organs and bony structures introduce strong signals superimposed on tumors at some angles, this method accurately locates tumors on every projection over 12 gantry angles. The maximum error is less than 2.6 mm while the total average error is 1.0 mm. Conclusion: This algorithm is capable of detecting tumor without markers despite strong background signals.
Stokes image reconstruction for two-color microgrid polarization imaging systems.
Lemaster, Daniel A
2011-07-18
The Air Force Research Laboratory has developed a new microgrid polarization imaging system capable of simultaneously reconstructing linear Stokes parameter images in two colors on a single focal plane array. In this paper, an effective method for extracting Stokes images is presented for this type of camera system. It is also shown that correlations between the color bands can be exploited to significantly increase overall spatial resolution. Test data is used to show the advantages of this approach over bilinear interpolation. The bounds (in terms of available reconstruction bandwidth) on image resolution are also provided.
Helou, E. S.; Zibetti, M. V. W.; Miqueles, E. X.
2017-04-01
We propose the superiorization of incremental algorithms for tomographic image reconstruction. The resulting methods follow a better path in its way to finding the optimal solution for the maximum likelihood problem in the sense that they are closer to the Pareto optimal curve than the non-superiorized techniques. A new scaled gradient iteration is proposed and three superiorization schemes are evaluated. Theoretical analysis of the methods as well as computational experiments with both synthetic and real data are provided.
Fan beam image reconstruction with generalized Fourier slice theorem.
Zhao, Shuangren; Yang, Kang; Yang, Kevin
2014-01-01
For parallel beam geometry the Fourier reconstruction works via the Fourier slice theorem (or central slice theorem, projection slice theorem). For fan beam situation, Fourier slice can be extended to a generalized Fourier slice theorem (GFST) for fan-beam image reconstruction. We have briefly introduced this method in a conference. This paper reintroduces the GFST method for fan beam geometry in details. The GFST method can be described as following: the Fourier plane is filled by adding up the contributions from all fanbeam projections individually; thereby the values in the Fourier plane are directly calculated for Cartesian coordinates such avoiding the interpolation from polar to Cartesian coordinates in the Fourier domain; inverse fast Fourier transform is applied to the image in Fourier plane and leads to a reconstructed image in spacial domain. The reconstructed image is compared between the result of the GFST method and the result from the filtered backprojection (FBP) method. The major differences of the GFST and the FBP methods are: (1) The interpolation process are at different data sets. The interpolation of the GFST method is at projection data. The interpolation of the FBP method is at filtered projection data. (2) The filtering process are done in different places. The filtering process of the GFST is at Fourier domain. The filtering process of the FBP method is the ramp filter which is done at projections. The resolution of ramp filter is variable with different location but the filter in the Fourier domain lead to resolution invariable with location. One advantage of the GFST method over the FBP method is in short scan situation, an exact solution can be obtained with the GFST method, but it can not be obtained with the FBP method. The calculation of both the GFST and the FBP methods are at O(N^3), where N is the number of pixel in one dimension.
Computed tomography image reconstruction from only two projections
Mohammad-Djafari, Ali
2007-01-01
English: This paper concerns the image reconstruction from a few projections in Computed Tomography (CT). The main objective of this paper is to show that the problem is so ill posed that no classical method, such as analytical methods based on inverse Radon transform, nor the algebraic methods such as Least squares (LS) or regularization theory can give satisfactory result. As an example, we consider in detail the case of image reconstruction from two horizontal and vertical projections. We then show how a particular composite Markov modeling and the Bayesian estimation framework can possibly propose satisfactory solutions to the problem. For demonstration and educational purpose a set of Matlab programs are given for a live presentation of the results. ----- French: Ce travail, \\`a but p\\'edagogique, pr\\'esente le probl\\`eme inverse de la reconstruction d'image en tomographie X lorsque le nombre des projections est tr\\`es limit\\'e. voir le texte en Anglais et en Fran\\c{c}ais.
Jung, Jae-Hyun; Hong, Keehoon; Park, Gilbae; Chung, Indeok; Park, Jae-Hyeung; Lee, Byoungho
2010-12-06
We proposed a reconstruction method for the occluded region of three-dimensional (3D) object using the depth extraction based on the optical flow and triangular mesh reconstruction in integral imaging. The depth information of sub-images from the acquired elemental image set is extracted using the optical flow with sub-pixel accuracy, which alleviates the depth quantization problem. The extracted depth maps of sub-image array are segmented by the depth threshold from the histogram based segmentation, which is represented as the point clouds. The point clouds are projected to the viewpoint of center sub-image and reconstructed by the triangular mesh reconstruction. The experimental results support the validity of the proposed method with high accuracy of peak signal-to-noise ratio and normalized cross-correlation in 3D image recognition.
Impact of measurement precision and noise on superresolution image reconstruction.
Wood, Sally L; Lee, Shu-Ting; Yang, Gao; Christensen, Marc P; Rajan, Dinesh
2008-04-01
The performance of uniform and nonuniform detector arrays for application to the PANOPTES (processing arrays of Nyquist-limited observations to produce a thin electro-optic sensor) flat camera design is analyzed for measurement noise environments including quantization noise and Gaussian and Poisson processes. Image data acquired from a commercial camera with 8 bit and 14 bit output options are analyzed, and estimated noise levels are computed. Noise variances estimated from the measurement values are used in the optimal linear estimators for superresolution image reconstruction.
Ou-Yang, Mang; Jeng, Wei-De; Wu, Yin-Yi; Dung, Lan-Rong; Wu, Hsien-Ming; Weng, Ping-Kuo; Huang, Ker-Jer; Chiu, Luan-Jiau
2012-05-01
This study investigates image processing using the radial imaging capsule endoscope (RICE) system. First, an experimental environment is established in which a simulated object has a shape that is similar to a cylinder, such that a triaxial platform can be used to push the RICE into the sample and capture radial images. Then four algorithms (mean absolute error, mean square error, Pearson correlation coefficient, and deformation processing) are used to stitch the images together. The Pearson correlation coefficient method is the most effective algorithm because it yields the highest peak signal-to-noise ratio, higher than 80.69 compared to the original image. Furthermore, a living animal experiment is carried out. Finally, the Pearson correlation coefficient method and vector deformation processing are used to stitch the images that were captured in the living animal experiment. This method is very attractive because unlike the other methods, in which two lenses are required to reconstruct the geometrical image, RICE uses only one lens and one mirror.
A study of image reconstruction algorithms for hybrid intensity interferometers
Crabtree, Peter N.; Murray-Krezan, Jeremy; Picard, Richard H.
2011-09-01
Phase retrieval is explored for image reconstruction using outputs from both a simulated intensity interferometer (II) and a hybrid system that combines the II outputs with partially resolved imagery from a traditional imaging telescope. Partially resolved imagery provides an additional constraint for the iterative phase retrieval process, as well as an improved starting point. The benefits of this additional a priori information are explored and include lower residual phase error for SNR values above 0.01, increased sensitivity, and improved image quality. Results are also presented for image reconstruction from II measurements alone, via current state-of-the-art phase retrieval techniques. These results are based on the standard hybrid input-output (HIO) algorithm, as well as a recent enhancement to HIO that optimizes step lengths in addition to step directions. The additional step length optimization yields a reduction in residual phase error, but only for SNR values greater than about 10. Image quality for all algorithms studied is quite good for SNR>=10, but it should be noted that the studied phase-recovery techniques yield useful information even for SNRs that are much lower.
Accurate band-to-band registration of AOTF imaging spectrometer using motion detection technology
Zhou, Pengwei; Zhao, Huijie; Jin, Shangzhong; Li, Ningchuan
2016-05-01
This paper concerns the problem of platform vibration induced band-to-band misregistration with acousto-optic imaging spectrometer in spaceborne application. Registrating images of different bands formed at different time or different position is difficult, especially for hyperspectral images form acousto-optic tunable filter (AOTF) imaging spectrometer. In this study, a motion detection method is presented using the polychromatic undiffracted beam of AOTF. The factors affecting motion detect accuracy are analyzed theoretically, and calculations show that optical distortion is an easily overlooked factor to achieve accurate band-to-band registration. Hence, a reflective dual-path optical system has been proposed for the first time, with reduction of distortion and chromatic aberration, indicating the potential of higher registration accuracy. Consequently, a spectra restoration experiment using additional motion detect channel is presented for the first time, which shows the accurate spectral image registration capability of this technique.
3D CAD model reconstruction of a human femur from MRI images
Directory of Open Access Journals (Sweden)
Benaissa EL FAHIME
2013-05-01
Full Text Available Medical practice and life sciences take full advantage of progress in engineering disciplines, in particular the computer assisted placement technique in hip surgery. This paper describes the three dimensional model reconstruction of human femur from MRI images. The developed program enables to obtain digital shape of 3D femur recognized by all CAD software and allows an accurate placement of the femoral component. This technic provides precise measurement of implant alignment during hip resurfacing or total hip arthroplasty, thereby reducing the risk of component mal-positioning and femoral neck notching.
Hierarchical Bayesian sparse image reconstruction with application to MRFM
Dobigeon, Nicolas; Tourneret, Jean-Yves
2008-01-01
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally sparse image applications as it seamlessly accounts for properties such as sparsity and positivity of the image via appropriate Bayes priors. We propose a prior that is based on a weighted mixture of a positive exponential distribution and a mass at zero. The prior has hyperparameters that are tuned automatically by marginalization over the hierarchical Bayesian model. To overcome the complexity of the posterior distribution, a Gibbs sampling strategy is proposed. The Gibbs samples can be used to estimate the image to be recovered, e.g. by maximizing the estimated posterior distribution. In our fully Bayesian approach the posteriors of all the parameters are available. Thus our algorithm provides more information than other previously proposed sparse reconstr...
Directory of Open Access Journals (Sweden)
Xuemiao Xu
2016-04-01
Full Text Available Exterior orientation parameters’ (EOP estimation using space resection plays an important role in topographic reconstruction for push broom scanners. However, existing models of space resection are highly sensitive to errors in data. Unfortunately, for lunar imagery, the altitude data at the ground control points (GCPs for space resection are error-prone. Thus, existing models fail to produce reliable EOPs. Motivated by a finding that for push broom scanners, angular rotations of EOPs can be estimated independent of the altitude data and only involving the geographic data at the GCPs, which are already provided, hence, we divide the modeling of space resection into two phases. Firstly, we estimate the angular rotations based on the reliable geographic data using our proposed mathematical model. Then, with the accurate angular rotations, the collinear equations for space resection are simplified into a linear problem, and the global optimal solution for the spatial position of EOPs can always be achieved. Moreover, a certainty term is integrated to penalize the unreliable altitude data for increasing the error tolerance. Experimental results evidence that our model can obtain more accurate EOPs and topographic maps not only for the simulated data, but also for the real data from Chang’E-1, compared to the existing space resection model.
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Scheins, J., E-mail: j.scheins@fz-juelich.de [Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425 Jülich (Germany); Ullisch, M.; Tellmann, L.; Weirich, C.; Rota Kops, E.; Herzog, H.; Shah, N.J. [Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425 Jülich (Germany)
2013-02-21
The BrainPET scanner from Siemens, designed as hybrid MR/PET system for simultaneous acquisition of both modalities, provides high-resolution PET images with an optimum resolution of 3 mm. However, significant head motion often compromises the achievable image quality, e.g. in neuroreceptor studies of human brain. This limitation can be omitted when tracking the head motion and accurately correcting measured Lines-of-Response (LORs). For this purpose, we present a novel method, which advantageously combines MR-guided motion tracking with the capabilities of the reconstruction software PRESTO (PET Reconstruction Software Toolkit) to convert motion-corrected LORs into highly accurate generic projection data. In this way, the high-resolution PET images achievable with PRESTO can also be obtained in presence of severe head motion.
Chuang, Ching-Cheng; Tsai, Jui-che; Chen, Chung-Ming; Yu, Zong-Han; Sun, Chia-Wei
2012-04-01
Diffuse optical tomography (DOT) is an emerging technique for functional biological imaging. The imaging quality of DOT depends on the imaging reconstruction algorithm. The SIRT has been widely used for DOT image reconstruction but there is no criterion to truncate based on any kind of residual parameter. The iteration loops will always be decided by experimental rule. This work presents the CR calculation that can be great help for SIRT optimization. In this paper, four inhomogeneities with various shapes of absorption distributions are simulated as imaging targets. The images are reconstructed and analyzed based on the simultaneous iterative reconstruction technique (SIRT) method. For optimization between time consumption and imaging accuracy in reconstruction process, the numbers of iteration loop needed to be optimized with a criterion in algorithm, that is, the root mean square error (RMSE) should be minimized in limited iterations. For clinical applications of DOT, the RMSE cannot be obtained because the measured targets are unknown. Thus, the correlations between the RMSE and the convergence rate (CR) in SIRT algorithm are analyzed in this paper. From the simulation results, the parameter CR reveals the related RMSE value of reconstructed images. The CR calculation offers an optimized criterion of iteration process in SIRT algorithm for DOT imaging. Based on the result, the SIRT can be modified with CR calculation for self-optimization. CR reveals an indicator of SIRT image reconstruction in clinical DOT measurement. Based on the comparison result between RMSE and CR, a threshold value of CR (CRT) can offer an optimized number of iteration steps for DOT image reconstruction. This paper shows the feasibility study by utilizing CR criterion for SIRT in simulation and the clinical application of DOT measurement relies on further investigation.
Almeida, Eduardo DeBrito
2012-01-01
This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL), California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.
Task-driven image acquisition and reconstruction in cone-beam CT.
Gang, Grace J; Stayman, J Webster; Ehtiati, Tina; Siewerdsen, Jeffrey H
2015-04-21
This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ± 30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the tilt
Kainmueller, Dagmar
2014-01-01
? Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author's core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatom
Region-Based 3d Surface Reconstruction Using Images Acquired by Low-Cost Unmanned Aerial Systems
Lari, Z.; Al-Rawabdeh, A.; He, F.; Habib, A.; El-Sheimy, N.
2015-08-01
Accurate 3D surface reconstruction of our environment has become essential for an unlimited number of emerging applications. In the past few years, Unmanned Aerial Systems (UAS) are evolving as low-cost and flexible platforms for geospatial data collection that could meet the needs of aforementioned application and overcome limitations of traditional airborne and terrestrial mobile mapping systems. Due to their payload restrictions, these systems usually include consumer-grade imaging and positioning sensor which will negatively impact the quality of the collected geospatial data and reconstructed surfaces. Therefore, new surface reconstruction surfaces are needed to mitigate the impact of using low-cost sensors on the final products. To date, different approaches have been proposed to for 3D surface construction using overlapping images collected by imaging sensor mounted on moving platforms. In these approaches, 3D surfaces are mainly reconstructed based on dense matching techniques. However, generated 3D point clouds might not accurately represent the scanned surfaces due to point density variations and edge preservation problems. In order to resolve these problems, a new region-based 3D surface renostruction trchnique is introduced in this paper. This approach aims to generate a 3D photo-realistic model of individually scanned surfaces within the captured images. This approach is initiated by a Semi-Global dense Matching procedure is carried out to generate a 3D point cloud from the scanned area within the collected images. The generated point cloud is then segmented to extract individual planar surfaces. Finally, a novel region-based texturing technique is implemented for photorealistic reconstruction of the extracted planar surfaces. Experimental results using images collected by a camera mounted on a low-cost UAS demonstrate the feasibility of the proposed approach for photorealistic 3D surface reconstruction.
REGION-BASED 3D SURFACE RECONSTRUCTION USING IMAGES ACQUIRED BY LOW-COST UNMANNED AERIAL SYSTEMS
Directory of Open Access Journals (Sweden)
Z. Lari
2015-08-01
Full Text Available Accurate 3D surface reconstruction of our environment has become essential for an unlimited number of emerging applications. In the past few years, Unmanned Aerial Systems (UAS are evolving as low-cost and flexible platforms for geospatial data collection that could meet the needs of aforementioned application and overcome limitations of traditional airborne and terrestrial mobile mapping systems. Due to their payload restrictions, these systems usually include consumer-grade imaging and positioning sensor which will negatively impact the quality of the collected geospatial data and reconstructed surfaces. Therefore, new surface reconstruction surfaces are needed to mitigate the impact of using low-cost sensors on the final products. To date, different approaches have been proposed to for 3D surface construction using overlapping images collected by imaging sensor mounted on moving platforms. In these approaches, 3D surfaces are mainly reconstructed based on dense matching techniques. However, generated 3D point clouds might not accurately represent the scanned surfaces due to point density variations and edge preservation problems. In order to resolve these problems, a new region-based 3D surface renostruction trchnique is introduced in this paper. This approach aims to generate a 3D photo-realistic model of individually scanned surfaces within the captured images. This approach is initiated by a Semi-Global dense Matching procedure is carried out to generate a 3D point cloud from the scanned area within the collected images. The generated point cloud is then segmented to extract individual planar surfaces. Finally, a novel region-based texturing technique is implemented for photorealistic reconstruction of the extracted planar surfaces. Experimental results using images collected by a camera mounted on a low-cost UAS demonstrate the feasibility of the proposed approach for photorealistic 3D surface reconstruction.
Superresolution image reconstruction using panchromatic and multispectral image fusion
Elbakary, M. I.; Alam, M. S.
2008-08-01
Hyperspectral imagery is used for a wide variety of applications, including target detection, tacking, agricultural monitoring and natural resources exploration. The main reason for using hyperspectral imagery is that these images reveal spectral information about the scene that is not available in a single band. Unfortunately, many factors such as sensor noise and atmospheric scattering degrade the spatial quality of these images. Recently, many algorithms are introduced in the literature to improve the resolution of hyperspectral images using co-registered high special-resolution imagery such as panchromatic imagery. In this paper, we propose a new algorithm to enhance the spatial resolution of low resolution hyperspectral bands using strongly correlated and co-registered high special-resolution panchromatic imagery. The proposed algorithm constructs the superresolution bands corresponding to the low resolution bands to enhance the resolution using a global correlation enhancement technique. The global enhancement is based on the least square regression and the histogram matching to improve the estimated interpolation of the spatial resolution. The introduced algorithm is considered as an improvement for Priceâ€™s algorithm which uses the global correlation only for the spatial resolution enhancement. Numerous studies are conducted to investigate the effect of the proposed algorithm for achieving the enhancement compared to the traditional algorithm for superresolution enhancement. Experiments results obtained using hyperspectral data derived from airborne imaging sensor are presented to verify the superiority of the proposed algorithm.
Reconstruction of Static Black Hole Images Using Simple Geometric Forms
Benkevitch, Leonid; Lu, Rusen; Doeleman, Shepherd; Fish, Vincent
2016-01-01
General Relativity predicts that the emission close to a black hole must be lensed by its strong gravitational field, illuminating the last photon orbit. This results in a dark circular area known as the black hole 'shadow'. The Event Horizon Telescope (EHT) is a (sub)mm VLBI network capable of Schwarzschild-radius resolution on Sagittarius A* (or Sgr A*), the 4 million solar mass black hole at the Galactic Center. The goals of the Sgr A* observations include resolving and measuring the details of its morphology. However, EHT data are sparse in the visibility domain, complicating reliable detailed image reconstruction. Therefore, direct pixel imaging should be complemented by other approaches. Using simulated EHT data from a black hole emission model we consider an approach to Sgr A* image reconstruction based on a simple and computationally efficient analytical model that produces images similar to the synthetic ones. The model consists of an eccentric ring with a brightness gradient and a two-dimensional Ga...
Simultaneous reconstruction and segmentation for dynamic SPECT imaging
Burger, Martin; Rossmanith, Carolin; Zhang, Xiaoqun
2016-10-01
This work deals with the reconstruction of dynamic images that incorporate characteristic dynamics in certain subregions, as arising for the kinetics of many tracers in emission tomography (SPECT, PET). We make use of a basis function approach for the unknown tracer concentration by assuming that the region of interest can be divided into subregions with spatially constant concentration curves. Applying a regularised variational framework reminiscent of the Chan-Vese model for image segmentation we simultaneously reconstruct both the labelling functions of the subregions as well as the subconcentrations within each region. Our particular focus is on applications in SPECT with the Poisson noise model, resulting in a Kullback-Leibler data fidelity in the variational approach. We present a detailed analysis of the proposed variational model and prove existence of minimisers as well as error estimates. The latter apply to a more general class of problems and generalise existing results in literature since we deal with a nonlinear forward operator and a nonquadratic data fidelity. A computational algorithm based on alternating minimisation and splitting techniques is developed for the solution of the problem and tested on appropriately designed synthetic data sets. For those we compare the results to those of standard EM reconstructions and investigate the effects of Poisson noise in the data.
Energy Technology Data Exchange (ETDEWEB)
Kovarik, Libor; Stevens, Andrew J.; Liyu, Andrey V.; Browning, Nigel D.
2016-10-17
Aberration correction for scanning transmission electron microscopes (STEM) has dramatically increased spatial image resolution for beam-stable materials, but it is the sample stability rather than the microscope that often limits the practical resolution of STEM images. To extract physical information from images of beam sensitive materials it is becoming clear that there is a critical dose/dose-rate below which the images can be interpreted as representative of the pristine material, while above it the observation is dominated by beam effects. Here we describe an experimental approach for sparse sampling in the STEM and in-painting image reconstruction in order to reduce the electron dose/dose-rate to the sample during imaging. By characterizing the induction limited rise-time and hysteresis in scan coils, we show that sparse line-hopping approach to scan randomization can be implemented that optimizes both the speed of the scan and the amount of the sample that needs to be illuminated by the beam. The dose and acquisition time for the sparse sampling is shown to be effectively decreased by factor of 5x relative to conventional acquisition, permitting imaging of beam sensitive materials to be obtained without changing the microscope operating parameters. The use of sparse line-hopping scan to acquire STEM images is demonstrated with atomic resolution aberration corrected Z-contrast images of CaCO3, a material that is traditionally difficult to image by TEM/STEM because of dose issues.
Improved proton computed tomography by dual modality image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Hansen, David C., E-mail: dch@ki.au.dk; Bassler, Niels [Experimental Clinical Oncology, Aarhus University, 8000 Aarhus C (Denmark); Petersen, Jørgen Breede Baltzer [Medical Physics, Aarhus University Hospital, 8000 Aarhus C (Denmark); Sørensen, Thomas Sangild [Computer Science, Aarhus University, 8000 Aarhus C, Denmark and Clinical Medicine, Aarhus University, 8200 Aarhus N (Denmark)
2014-03-15
Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360
Energy Technology Data Exchange (ETDEWEB)
Lauzier, Pascal Theriault; Tang Jie; Speidel, Michael A.; Chen Guanghong [Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705-2275 (United States); Department of Medical Physics and Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin 53705-2275 (United States)
2012-07-15
Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution
System calibration and image reconstruction for a new small-animal SPECT system
Chen, Yi-Chun
A novel small-animal SPECT imager, FastSPECT II, was recently developed at the Center for Gamma-Ray Imaging. FastSPECT II consists of two rings of eight modular scintillation cameras and list-mode data-acquisition electronics that enable stationary and dynamic imaging studies. The instrument is equipped with exchangeable aperture assemblies and adjustable camera positions for selections of magnifications, pinhole sizes, and fields of view (FOVs). The purpose of SPECT imaging is to recover the radiotracer distribution in the object from the measured image data. Accurate knowledge of the imaging system matrix (referred to as H) is essential for image reconstruction. To assure that all of the system physics is contained in the matrix, experimental calibration methods for the individual cameras and the whole imaging system were developed and carefully performed. The average spatial resolution over the FOV of FastSPECT II in its low-magnification (2.4X) configuration is around 2.4 mm, computed from the Fourier crosstalk matrix. The system sensitivity measured with a 99mTc point source at the center of the FOV is about 267 cps/MBq. The system detectability was evaluated by computing the ideal-observer performance on SKE/BKE (signal-known-exactly/background-known-exactly) detection tasks. To reduce the system-calibration time and achieve finer reconstruction grids, two schemes for interpolating H were implemented and compared: these are centroid interpolation with Gaussian fitting and Fourier interpolation. Reconstructed phantom and mouse-cardiac images demonstrated the effectiveness of the H-matrix interpolation. Tomographic reconstruction can be formulated as a linear inverse problem and solved using statistical-estimation techniques. Several iterative reconstruction algorithms were introduced, including maximum-likelihood expectation-maximization (ML-EM) and its ordered-subsets (OS) version, and some least-squares (LS) and weighted-least-squares (WLS) algorithms such
Use of GMM and SCMS for Accurate Road Centerline Extraction from the Classified Image
Directory of Open Access Journals (Sweden)
Zelang Miao
2015-01-01
Full Text Available The extraction of road centerline from the classified image is a fundamental image analysis technology. Common problems encountered in road centerline extraction include low ability for coping with the general case, production of undesired objects, and inefficiency. To tackle these limitations, this paper presents a novel accurate centerline extraction method using Gaussian mixture model (GMM and subspace constraint mean shift (SCMS. The proposed method consists of three main steps. GMM is first used to partition the classified image into several clusters. The major axis of the ellipsoid of each cluster is extracted and deemed to be taken as the initial centerline. Finally, the initial result is adjusted using SCMS to produce precise road centerline. Both simulated and real datasets are used to validate the proposed method. Preliminary results demonstrate that the proposed method provides a comparatively robust solution for accurate centerline extraction from a classified image.
Spectral image reconstruction by a tunable LED illumination
Lin, Meng-Chieh; Tsai, Chen-Wei; Tien, Chung-Hao
2013-09-01
Spectral reflectance estimation of an object via low-dimensional snapshot requires both image acquisition and a post numerical estimation analysis. In this study, we set up a system incorporating a homemade cluster of LEDs with spectral modulation for scene illumination, and a multi-channel CCD to acquire multichannel images by means of fully digital process. Principal component analysis (PCA) and pseudo inverse transformation were used to reconstruct the spectral reflectance in a constrained training set, such as Munsell and Macbeth Color Checker. The average reflectance spectral RMS error from 34 patches of a standard color checker were 0.234. The purpose is to investigate the use of system in conjunction with the imaging analysis for industry or medical inspection in a fast and acceptable accuracy, where the approach was preliminary validated.
A generalized Fourier penalty in prior-image-based reconstruction for cross-platform imaging
Pourmorteza, A.; Siewerdsen, J. H.; Stayman, J. W.
2016-03-01
Sequential CT studies present an excellent opportunity to apply prior-image-based reconstruction (PIBR) methods that leverage high-fidelity prior imaging studies to improve image quality and/or reduce x-ray exposure in subsequent studies. One major obstacle in using PIBR is that the initial and subsequent studies are often performed on different scanners (e.g. diagnostic CT followed by CBCT for interventional guidance); this results in mismatch in attenuation values due to hardware and software differences. While improved artifact correction techniques can potentially mitigate such differences, the correction is often incomplete. Here, we present an alternate strategy where the PIBR itself is used to mitigate these differences. We define a new penalty for the previously introduced PIBR called Reconstruction of Difference (RoD). RoD differs from many other PIBRs in that it reconstructs only changes in the anatomy (vs. reconstructing the current anatomy). Direct regularization of the difference image in RoD provides an opportunity to selectively penalize spatial frequencies of the difference image (e.g. low frequency differences associated with attenuation offsets and shading artifacts) without interfering with the variations in unchanged background image. We leverage this flexibility and introduce a novel regularization strategy using a generalized Fourier penalty within the RoD framework and develop the modified reconstruction algorithm. We evaluate the performance of the new approach in both simulation studies and in physical CBCT test-bench data. We find that generalized Fourier penalty can be highly effective in reducing low-frequency x-ray artifacts through selective suppression of spatial frequencies in the reconstructed difference image.
A hybrid ECT image reconstruction based on Tikhonov regularization theory and SIRT algorithm
Lei, Wang; Xiaotong, Du; Xiaoyin, Shao
2007-07-01
Electrical Capacitance Tomography (ECT) image reconstruction is a key problem that is not well solved due to the influence of soft-field in the ECT system. In this paper, a new hybrid ECT image reconstruction algorithm is proposed by combining Tikhonov regularization theory and Simultaneous Reconstruction Technique (SIRT) algorithm. Tikhonov regularization theory is used to solve ill-posed image reconstruction problem to obtain a stable original reconstructed image in the region of the optimized solution aggregate. Then, SIRT algorithm is used to improve the quality of the final reconstructed image. In order to satisfy the industrial requirement of real-time computation, the proposed algorithm is further been modified to improve the calculation speed. Test results show that the quality of reconstructed image is better than that of the well-known Filter Linear Back Projection (FLBP) algorithm and the time consumption of the new algorithm is less than 0.1 second that satisfies the online requirements.
A hybrid ECT image reconstruction based on Tikhonov regularization theory and SIRT algorithm
Energy Technology Data Exchange (ETDEWEB)
Wang Lei [School of Control Science and Engineering, Shandong University, 250061, Jinan (China); Du Xiaotong [School of Control Science and Engineering, Shandong University, 250061, Jinan (China); Shao Xiaoyin [Department of Manufacture Engineering and Engineering Management, City University of Hong Kong (China)
2007-07-15
Electrical Capacitance Tomography (ECT) image reconstruction is a key problem that is not well solved due to the influence of soft-field in the ECT system. In this paper, a new hybrid ECT image reconstruction algorithm is proposed by combining Tikhonov regularization theory and Simultaneous Reconstruction Technique (SIRT) algorithm. Tikhonov regularization theory is used to solve ill-posed image reconstruction problem to obtain a stable original reconstructed image in the region of the optimized solution aggregate. Then, SIRT algorithm is used to improve the quality of the final reconstructed image. In order to satisfy the industrial requirement of real-time computation, the proposed algorithm is further been modified to improve the calculation speed. Test results show that the quality of reconstructed image is better than that of the well-known Filter Linear Back Projection (FLBP) algorithm and the time consumption of the new algorithm is less than 0.1 second that satisfies the online requirements.
Statistics-based reconstruction method with high random-error tolerance for integral imaging.
Zhang, Juan; Zhou, Liqiu; Jiao, Xiaoxue; Zhang, Lei; Song, Lipei; Zhang, Bo; Zheng, Yi; Zhang, Zan; Zhao, Xing
2015-10-01
A three-dimensional (3D) digital reconstruction method for integral imaging with high random-error tolerance based on statistics is proposed. By statistically analyzing the points reconstructed by triangulation from all corresponding image points in an elemental images array, 3D reconstruction with high random-error tolerance could be realized. To simulate the impacts of random errors, random offsets with different error levels are added to a different number of elemental images in simulation and optical experiments. The results of simulation and optical experiments showed that the proposed statistic-based reconstruction method has relatively stable and better reconstruction accuracy than the conventional reconstruction method. It can be verified that the proposed method can effectively reduce the impacts of random errors on 3D reconstruction of integral imaging. This method is simple and very helpful to the development of integral imaging technology.
Medical Image Watermarking Technique for Accurate Tamper Detection in ROI and Exact Recovery of ROI.
Eswaraiah, R; Sreenivasa Reddy, E
2014-01-01
In telemedicine while transferring medical images tampers may be introduced. Before making any diagnostic decisions, the integrity of region of interest (ROI) of the received medical image must be verified to avoid misdiagnosis. In this paper, we propose a novel fragile block based medical image watermarking technique to avoid embedding distortion inside ROI, verify integrity of ROI, detect accurately the tampered blocks inside ROI, and recover the original ROI with zero loss. In this proposed method, the medical image is segmented into three sets of pixels: ROI pixels, region of noninterest (RONI) pixels, and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on a number of medical images reveal that the proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI with 100% accuracy, and recovers the original ROI without any loss.
LIRA: Low-Count Image Reconstruction and Analysis
Stein, Nathan; van Dyk, David; Connors, Alanna; Siemiginowska, Aneta; Kashyap, Vinay
2009-09-01
LIRA is a new software package for the R statistical computing language. The package is designed for multi-scale non-parametric image analysis for use in high-energy astrophysics. The code implements an MCMC sampler that simultaneously fits the image and the necessary tuning/smoothing parameters in the model (an advance from `EMC2' of Esch et al. 2004). The model-based approach allows for quantification of the standard error of the fitted image and can be used to access the statistical significance of features in the image or to evaluate the goodness-of-fit of a proposed model. The method does not rely on Gaussian approximations, instead modeling image counts as Poisson data, making it suitable for images with extremely low counts. LIRA can include a null (or background) model and fit the departure between the observed data and the null model via a wavelet-like multi-scale component. The technique is therefore suited for problems in which some aspect of an observation is well understood (e.g, a point source), but questions remain about observed departures. To quantitatively test for the presence of diffuse structure unaccounted for by a point source null model, first, the observed image is fit with the null model. Second, multiple simulated images, generated as Poisson realizations of the point source model, are fit using the same null model. MCMC samples from the posterior distributions of the parameters of the fitted models can be compared and can be used to calibrate the misfit between the observed data and the null model. Additionally, output from LIRA includes the MCMC draws of the multi-scale component images, so that the departure of the (simulated or observed) data from the point source null model can be examined visually. To demonstrate LIRA, an example of reconstructing Chandra images of high redshift quasars with jets is presented.
Cardiac motion correction based on partial angle reconstructed images in x-ray CT
Energy Technology Data Exchange (ETDEWEB)
Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr [Department of Electrical Engineering, KAIST, Daejeon 305-701 (Korea, Republic of)
2015-05-15
Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of
DEFF Research Database (Denmark)
Oxvig, Christian Schou; Pedersen, Patrick Steffen; Arildsen, Thomas
2014-01-01
provides researchers in compressed sensing with a selection of algorithms for reconstructing undersampled general images, and offers a consistent and rigorous way to efficiently evaluate the researchers own developed reconstruction algorithms in terms of phase transitions. The package also serves......Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also...
PIVlab – Towards User-friendly, Affordable and Accurate Digital Particle Image Velocimetry in MATLAB
Stamhuis, Eize; Thielicke, William
2014-01-01
Digital particle image velocimetry (DPIV) is a non-intrusive analysis technique that is very popular for mapping flows quantitatively. To get accurate results, in particular in complex flow fields, a number of challenges have to be faced and solved: The quality of the flow measurements is affected b
Local Surface Reconstruction from MER images using Stereo Workstation
Shin, Dongjoe; Muller, Jan-Peter
2010-05-01
The authors present a semi-automatic workflow that reconstructs the 3D shape of the martian surface from local stereo images delivered by PnCam or NavCam on systems such as the NASA Mars Exploration Rover (MER) Mission and in the future the ESA-NASA ExoMars rover PanCam. The process is initiated with manually selected tiepoints on a stereo workstation which is then followed by a tiepoint refinement, stereo-matching using region growing and Levenberg-Marquardt Algorithm (LMA)-based bundle adjustment processing. The stereo workstation, which is being developed by UCL in collaboration with colleagues at the Jet Propulsion Laboratory (JPL) within the EU FP7 ProVisG project, includes a set of practical GUI-based tools that enable an operator to define a visually correct tiepoint via a stereo display. To achieve platform and graphic hardware independence, the stereo application has been implemented using JPL's JADIS graphic library which is written in JAVA and the remaining processing blocks used in the reconstruction workflow have also been developed as a JAVA package to increase the code re-usability, portability and compatibility. Although initial tiepoints from the stereo workstation are reasonably acceptable as true correspondences, it is often required to employ an optional validity check and/or quality enhancing process. To meet this requirement, the workflow has been designed to include a tiepoint refinement process based on the Adaptive Least Square Correlation (ALSC) matching algorithm so that the initial tiepoints can be further enhanced to sub-pixel precision or rejected if they fail to pass the ALSC matching threshold. Apart from the accuracy of reconstruction, it is obvious that the other criterion to assess the quality of reconstruction is the density (or completeness) of reconstruction, which is not attained in the refinement process. Thus, we re-implemented a stereo region growing process, which is a core matching algorithm within the UCL
Maiti, Abhik; Chakravarty, Debashish
2016-01-01
3D reconstruction of geo-objects from their digital images is a time-efficient and convenient way of studying the structural features of the object being modelled. This paper presents a 3D reconstruction methodology which can be used to generate photo-realistic 3D watertight surface of different irregular shaped objects, from digital image sequences of the objects. The 3D reconstruction approach described here is robust, simplistic and can be readily used in reconstructing watertight 3D surface of any object from its digital image sequence. Here, digital images of different objects are used to build sparse, followed by dense 3D point clouds of the objects. These image-obtained point clouds are then used for generation of photo-realistic 3D surfaces, using different surface reconstruction algorithms such as Poisson reconstruction and Ball-pivoting algorithm. Different control parameters of these algorithms are identified, which affect the quality and computation time of the reconstructed 3D surface. The effects of these control parameters in generation of 3D surface from point clouds of different density are studied. It is shown that the reconstructed surface quality of Poisson reconstruction depends on Samples per node (SN) significantly, greater SN values resulting in better quality surfaces. Also, the quality of the 3D surface generated using Ball-Pivoting algorithm is found to be highly depend upon Clustering radius and Angle threshold values. The results obtained from this study give the readers of the article a valuable insight into the effects of different control parameters on determining the reconstructed surface quality.
Reconstructing the open-field magnetic geometry of solar corona using coronagraph images
Uritsky, Vadim M.; Davila, Joseph M.; Jones, Shaela; Burkepile, Joan
2015-04-01
The upcoming Solar Probe Plus and Solar Orbiter missions will provide an new insight into the inner heliosphere magnetically connected with the topologically complex and eruptive solar corona. Physical interpretation of these observations will be dependent on the accurate reconstruction of the large-scale coronal magnetic field. We argue that such reconstruction can be performed using photospheric extrapolation codes constrained by white-light coronagraph images. The field extrapolation component of this project is featured in a related presentation by S. Jones et al. Here, we focus on our image-processing algorithms conducting an automated segmentation of coronal loop structures. In contrast to the previously proposed segmentation codes designed for detecting small-scale closed loops in the vicinity of active regions, our technique focuses on the large-scale geometry of the open-field coronal features observed at significant radial distances from the solar surface. Coronagraph images are transformed into a polar coordinate system and undergo radial detrending and initial noise reduction followed by an adaptive angular differentiation. An adjustable threshold is applied to identify candidate coronagraph features associated with the large-scale coronal field. A blob detection algorithm is used to identify valid features against a noisy background. The extracted coronal features are used to derive empirical directional constraints for magnetic field extrapolation procedures based on photospheric magnetograms. Two versions of the method optimized for processing ground-based (Mauna Loa Solar Observatory) and satellite-based (STEREO Cor1 and Cor2) coronagraph images are being developed.
Deformable Surface 3D Reconstruction from Monocular Images
Salzmann, Matthieu
2010-01-01
Being able to recover the shape of 3D deformable surfaces from a single video stream would make it possible to field reconstruction systems that run on widely available hardware without requiring specialized devices. However, because many different 3D shapes can have virtually the same projection, such monocular shape recovery is inherently ambiguous. In this survey, we will review the two main classes of techniques that have proved most effective so far: The template-based methods that rely on establishing correspondences with a reference image in which the shape is already known, and non-rig
Improved proton computed tomography by dual modality image reconstruction
DEFF Research Database (Denmark)
Hansen, David Christoffer; Bassler, Niels; Petersen, Jørgen B.B.;
2014-01-01
Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full...... nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully...
Data reconstructed of ultraviolet spatially modulated imaging spectrometer
Yuan, Xiaochun; Yu, Chunchao; Yang, Zhixiong; Yan, Min; Zeng, Yi
2016-10-01
With the advantages of fluorescence excitation and environmental adaptability simultaneously, Ultraviolet Image Spectroscopy has shown irreplaceable features in the field of latent target detection and become a current research focus. A design of Large Aperture Ultraviolet Spatially Modulated Imaging Spectrometer (LAUV-SMIS) based on image plane interferometer and offner system was first proposed in this paper. The data processing technology of time-spatial modulation FTIS in UV band has been studied. The latent fingerprint could be recognized clearly from the image since which is capable to meet the need of latent target detection. The spectral curve of the target could distinguish the emission peak at 253.7nm and 365nm when the low pressure and high pressure mercury lamp were used as the illuminator. Accurate spectral data of the target can be collected on the short and long wave ends of the working band.
Transaxial system models for jPET-D4 image reconstruction
Yamaya, Taiga; Hagiwara, Naoki; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki; Kitamura, Keishi; Hasegawa, Tomoyuki; Haneishi, Hideaki; Yoshida, Eiji; Inadama, Naoko; Murayama, Hideo
2005-11-01
A high-performance brain PET scanner, jPET-D4, which provides four-layer depth-of-interaction (DOI) information, is being developed to achieve not only high spatial resolution, but also high scanner sensitivity. One technical issue to be dealt with is the data dimensions which increase in proportion to the square of the number of DOI layers. It is, therefore, difficult to apply algebraic or statistical image reconstruction methods directly to DOI-PET, though they improve image quality through accurate system modelling. The process that requires the most computational time and storage space is the calculation of the huge number of system matrix elements. The DOI compression (DOIC) method, which we have previously proposed, reduces data dimensions by a factor of 1/5. In this paper, we propose a transaxial imaging system model optimized for jPET-D4 with the DOIC method. The proposed model assumes that detector response functions (DRFs) are uniform along line-of-responses (LORs). Then each element of the system matrix is calculated as the summed intersection lengths between a pixel and sub-LORs weighted by a value from the DRF look-up-table. 2D numerical simulation results showed that the proposed model cut the calculation time by a factor of several hundred while keeping image quality, compared with the accurate system model. A 3D image reconstruction with the on-the-fly calculation of the system matrix is within the practical limitations by incorporating the proposed model and the DOIC method with one-pass accelerated iterative methods.
Zhang, Xuezhu; Zhou, Jian; Cherry, Simon R; Badawi, Ramsey D; Qi, Jinyi
2017-03-21
The EXPLORER project aims to build a 2 meter long total-body PET scanner, which will provide extremely high sensitivity for imaging the entire human body. It will possess a range of capabilities currently unavailable to state-of-the-art clinical PET scanners with a limited axial field-of-view. The huge number of lines-of-response (LORs) of the EXPLORER poses a challenge to the data handling and image reconstruction. The objective of this study is to develop a quantitative image reconstruction method for the EXPLORER and compare its performance with current whole-body scanners. Fully 3D image reconstruction was performed using time-of-flight list-mode data with parallel computation. To recover the resolution loss caused by the parallax error between crystal pairs at a large axial ring difference or transaxial radial offset, we applied an image domain resolution model estimated from point source data. To evaluate the image quality, we conducted computer simulations using the SimSET Monte-Carlo toolkit and XCAT 2.0 anthropomorphic phantom to mimic a 20 min whole-body PET scan with an injection of 25 MBq (18)F-FDG. We compare the performance of the EXPLORER with a current clinical scanner that has an axial FOV of 22 cm. The comparison results demonstrated superior image quality from the EXPLORER with a 6.9-fold reduction in noise standard deviation comparing with multi-bed imaging using the clinical scanner.
Holographic microscopy reconstruction in both object and image half spaces with undistorted 3D grid
Verrier, Nicolas; Tessier, Gilles; Gross, Michel
2015-01-01
We propose a holographic microscopy reconstruction method, which propagates the hologram, in the object half space, in the vicinity of the object. The calibration yields reconstructions with an undistorted reconstruction grid i.e. with orthogonal x, y and z axis and constant pixels pitch. The method is validated with an USAF target imaged by a x60 microscope objective, whose holograms are recorded and reconstructed for different USAF locations along the longitudinal axis:-75 to +75 {\\mu}m. Since the reconstruction numerical phase mask, the reference phase curvature and MO form an afocal device, the reconstruction can be interpreted as occurring equivalently in the object or in image half space.
Reconstruction algorithm medical imaging DRR; Algoritmo de construccion de imagenes medicas DRR
Energy Technology Data Exchange (ETDEWEB)
Estrada Espinosa, J. C.
2013-07-01
The method of reconstruction for digital radiographic Imaging (DRR), is based on two orthogonal images, on the dorsal and lateral decubitus position of the simulation. DRR images are reconstructed with an algorithm that simulates running a conventional X-ray, a single rendition team, beam emitted is not divergent, in this case, the rays are considered to be parallel in the image reconstruction DRR, for this purpose, it is necessary to use all the values of the units (HU) hounsfield of each voxel in all axial cuts that form the study TC, finally obtaining the reconstructed image DRR performing a transformation from 3D to 2D. (Author)
Energy Technology Data Exchange (ETDEWEB)
Cui, Xiaoming, E-mail: mmayzy2008@126.com; Li, Tao, E-mail: litaofeivip@163.com; Li, Xin, E-mail: lx0803@sina.com.cn; Zhou, Weihua, E-mail: wangxue0606@gmail.com
2015-05-15
Highlights: • High-resolution scan mode is appropriate for imaging coronary stent. • HD-detail reconstruction algorithm is stent-dedicated kernel. • The intrastent lumen visibility also depends on stent diameter and material. - Abstract: Objective: The aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Materials and methods: Thirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. Results: The stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0 ± 8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. Conclusions: Compared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement.
Directory of Open Access Journals (Sweden)
Gui-Song Xia
2015-11-01
Full Text Available It is a challenging problem to efficiently interpret the large volumes of remotely sensed image data being collected in the current age of remote sensing “big data”. Although human visual interpretation can yield accurate annotation of remote sensing images, it demands considerable expert knowledge and is always time-consuming, which strongly hinders its efficiency. Alternatively, intelligent approaches (e.g., supervised classification and unsupervised clustering can speed up the annotation process through the application of advanced image analysis and data mining technologies. However, high-quality expert-annotated samples are still a prerequisite for intelligent approaches to achieve accurate results. Thus, how to efficiently annotate remote sensing images with little expert knowledge is an important and inevitable problem. To address this issue, this paper introduces a novel active clustering method for the annotation of high-resolution remote sensing images. More precisely, given a set of remote sensing images, we first build a graph based on these images and then gradually optimize the structure of the graph using a cut-collect process, which relies on a graph-based spectral clustering algorithm and pairwise constraints that are incrementally added via active learning. The pairwise constraints are simply similarity/dissimilarity relationships between the most uncertain pairwise nodes on the graph, which can be easily determined by non-expert human oracles. Furthermore, we also propose a strategy to adaptively update the number of classes in the clustering algorithm. In contrast with existing methods, our approach can achieve high accuracy in the task of remote sensing image annotation with relatively little expert knowledge, thereby greatly lightening the workload burden and reducing the requirements regarding expert knowledge. Experiments on several datasets of remote sensing images show that our algorithm achieves state
Image reconstruction with acoustic radiation force induced shear waves
McAleavey, Stephen A.; Nightingale, Kathryn R.; Stutz, Deborah L.; Hsu, Stephen J.; Trahey, Gregg E.
2003-05-01
Acoustic radiation force may be used to induce localized displacements within tissue. This phenomenon is used in Acoustic Radiation Force Impulse Imaging (ARFI), where short bursts of ultrasound deliver an impulsive force to a small region. The application of this transient force launches shear waves which propagate normally to the ultrasound beam axis. Measurements of the displacements induced by the propagating shear wave allow reconstruction of the local shear modulus, by wave tracking and inversion techniques. Here we present in vitro, ex vivo and in vivo measurements and images of shear modulus. Data were obtained with a single transducer, a conventional ultrasound scanner and specialized pulse sequences. Young's modulus values of 4 kPa, 13 kPa and 14 kPa were observed for fat, breast fibroadenoma, and skin. Shear modulus anisotropy in beef muscle was observed.
Reconstruction of mechanically recorded sound by image processing
Energy Technology Data Exchange (ETDEWEB)
Fadeyev, Vitaliy; Haber, Carl
2003-03-26
Audio information stored in the undulations of grooves in a medium such as a phonograph record may be reconstructed, with no or minimal contact, by measuring the groove shape using precision metrology methods and digital image processing. The effects of damage, wear, and contamination may be compensated, in many cases, through image processing and analysis methods. The speed and data handling capacity of available computing hardware make this approach practical. Various aspects of this approach are discussed. A feasibility test is reported which used a general purpose optical metrology system to study a 50 year old 78 r.p.m. phonograph record. Comparisons are presented with stylus playback of the record and with a digitally re-mastered version of the original magnetic recording. A more extensive implementation of this approach, with dedicated hardware and software, is considered.
3D reconstruction of concave surfaces using polarisation imaging
Sohaib, A.; Farooq, A. R.; Ahmed, J.; Smith, L. N.; Smith, M. L.
2015-06-01
This paper presents a novel algorithm for improved shape recovery using polarisation-based photometric stereo. The majority of previous research using photometric stereo involves 3D reconstruction using both the diffuse and specular components of light; however, this paper suggests the use of the specular component only as it is the only form of light that comes directly off the surface without subsurface scattering or interreflections. Experiments were carried out on both real and synthetic surfaces. Real images were obtained using a polarisation-based photometric stereo device while synthetic images were generated using PovRay® software. The results clearly demonstrate that the proposed method can extract three-dimensional (3D) surface information effectively even for concave surfaces with complex texture and surface reflectance.
Multiple View Reconstruction of Calibrated Images using Singular Value Decomposition
Chaudhury, Ayan; Manna, Sumita; Mukherjee, Subhadeep; Chakrabarti, Amlan
2010-01-01
Calibration in a multi camera network has widely been studied for over several years starting from the earlier days of photogrammetry. Many authors have presented several calibration algorithms with their relative advantages and disadvantages. In a stereovision system, multiple view reconstruction is a challenging task. However, the total computational procedure in detail has not been presented before. Here in this work, we are dealing with the problem that, when a world coordinate point is fixed in space, image coordinates of that 3D point vary for different camera positions and orientations. In computer vision aspect, this situation is undesirable. That is, the system has to be designed in such a way that image coordinate of the world coordinate point will be fixed irrespective of the position & orientation of the cameras. We have done it in an elegant fashion. Firstly, camera parameters are calculated in its local coordinate system. Then, we use global coordinate data to transfer all local coordinate d...
Energy Technology Data Exchange (ETDEWEB)
Guo, En-Yu [Key Laboratory for Advanced Materials Processing Technology, School of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Materials Science and Engineering, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 (United States); Chawla, Nikhilesh [Materials Science and Engineering, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 (United States); Jing, Tao [Key Laboratory for Advanced Materials Processing Technology, School of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Torquato, Salvatore [Department of Chemistry, Princeton University, Princeton, NJ 08544 (United States); Department of Physics, Princeton University, Princeton, NJ 08544 (United States); Princeton Institute for the Science and Technology of Materials, Princeton University, Princeton, NJ 08544 (United States); Program in Applied and Computational Mathematics, Princeton University, Princeton, NJ 08544 (United States); Jiao, Yang, E-mail: yang.jiao.2@asu.edu [Materials Science and Engineering, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 (United States)
2014-03-01
Heterogeneous materials are ubiquitous in nature and synthetic situations and have a wide range of important engineering applications. Accurate modeling and reconstructing three-dimensional (3D) microstructure of topologically complex materials from limited morphological information such as a two-dimensional (2D) micrograph is crucial to the assessment and prediction of effective material properties and performance under extreme conditions. Here, we extend a recently developed dilation–erosion method and employ the Yeong–Torquato stochastic reconstruction procedure to model and generate 3D austenitic–ferritic cast duplex stainless steel microstructure containing percolating filamentary ferrite phase from 2D optical micrographs of the material sample. Specifically, the ferrite phase is dilated to produce a modified target 2D microstructure and the resulting 3D reconstruction is eroded to recover the percolating ferrite filaments. The dilation–erosion reconstruction is compared with the actual 3D microstructure, obtained from serial sectioning (polishing), as well as the standard stochastic reconstructions incorporating topological connectedness information. The fact that the former can achieve the same level of accuracy as the latter suggests that the dilation–erosion procedure is tantamount to incorporating appreciably more topological and geometrical information into the reconstruction while being much more computationally efficient. - Highlights: • Spatial correlation functions used to characterize filamentary ferrite phase • Clustering information assessed from 3D experimental structure via serial sectioning • Stochastic reconstruction used to generate 3D virtual structure 2D micrograph • Dilation–erosion method to improve accuracy of 3D reconstruction.
Institute of Scientific and Technical Information of China (English)
钟志威
2016-01-01
针对稀疏角度投影数据CT图像重建问题,TV-ART算法将图像的梯度稀疏先验知识引入代数重建法( ART)中,对分段平滑的图像具有较好的重建效果。但是,该算法在边界重建时会产生阶梯效应,影响重建质量。因此,本文提出自适应核回归函数结合代数重建法的重建算法( LAKR-ART),不仅在边界重建时不会产生阶梯效应,而且对细节纹理重建具有更好的重建效果。最后对shepp-logan标准CT图像和实际CT头颅图像进行仿真实验,并与ART、TV-ART算法进行比较,实验结果表明本文算法有效。%To the problem of sparse angular projection data of CT image reconstruction, TV-ART algorithm introduces the gradient sparse prior knowledge of image to algebraic reconstruction, and the local smooth image gets a better reconstruction effect. How-ever, the algorithm generates step effect when the borders are reconstructed, affecting the quality of the reconstruction. Therefore, this paper proposes an adaptive kernel regression function combined with Algebraic Reconstruction Technique reconstruction algo-rithm ( LAKR-ART) , it does not produce the step effect on the border reconstruction, and has a better effect to detail reconstruc-tion. Finally we use the shepp-logan CT image and the actual CT image to make the simulation experiment, and compare with ART and TV-ART algorithm. The experimental results show the algorithm is of effectiveness.
An Optimized Method for Terrain Reconstruction Based on Descent Images
Directory of Open Access Journals (Sweden)
Xu Xinchao
2016-02-01
Full Text Available An optimization method is proposed to perform high-accuracy terrain reconstruction of the landing area of Chang’e III. First, feature matching is conducted using geometric model constraints. Then, the initial terrain is obtained and the initial normal vector of each point is solved on the basis of the initial terrain. By changing the vector around the initial normal vector in small steps a set of new vectors is obtained. By combining these vectors with the direction of light and camera, the functions are set up on the basis of a surface reflection model. Then, a series of gray values is derived by solving the equations. The new optimized vector is recorded when the obtained gray value is closest to the corresponding pixel. Finally, the optimized terrain is obtained after iteration of the vector field. Experiments were conducted using the laboratory images and descent images of Chang’e III. The results showed that the performance of the proposed method was better than that of the classical feature matching method. It can provide a reference for terrain reconstruction of the landing area in subsequent moon exploration missions.
Robust Compressive Phase Retrieval via L1 Minimization With Application to Image Reconstruction
Yang, Zai; Xie, Lihua
2013-01-01
Phase retrieval refers to a classical nonconvex problem of recovering a signal from its Fourier magnitude measurements. Inspired by the compressed sensing technique, signal sparsity is exploited in recent studies of phase retrieval to reduce the required number of measurements, known as compressive phase retrieval (CPR). In this paper, l1 minimization problems are formulated for CPR to exploit the signal sparsity and alternating direction algorithms are presented for problem solving. For real-valued, nonnegative image reconstruction, the image of interest is shown to be an optimal solution of the formulated l1 minimization in the noise free case. Numerical simulations demonstrate that the proposed approach is fast, accurate and robust to measurements noises.
3D Image Reconstruction from X-Ray Measurements with Overlap
Klodt, Maria
2016-01-01
3D image reconstruction from a set of X-ray projections is an important image reconstruction problem, with applications in medical imaging, industrial inspection and airport security. The innovation of X-ray emitter arrays allows for a novel type of X-ray scanners with multiple simultaneously emitting sources. However, two or more sources emitting at the same time can yield measurements from overlapping rays, imposing a new type of image reconstruction problem based on nonlinear constraints. Using traditional linear reconstruction methods, respective scanner geometries have to be implemented such that no rays overlap, which severely restricts the scanner design. We derive a new type of 3D image reconstruction model with nonlinear constraints, based on measurements with overlapping X-rays. Further, we show that the arising optimization problem is partially convex, and present an algorithm to solve it. Experiments show highly improved image reconstruction results from both simulated and real-world measurements.
3D Dose reconstruction: Banding artefacts in cine mode EPID images during VMAT delivery
Woodruff, H. C.; Greer, P. B.
2013-06-01
Cine (continuous) mode images obtained during VMAT delivery are heavily degraded by banding artefacts. We have developed a method to reconstruct the pulse sequence (and hence dose deposited) from open field images. For clinical VMAT fields we have devised a frame averaging strategy that greatly improves image quality and dosimetric information for three-dimensional dose reconstruction.
High-resolution Image Reconstruction by Neural Network and Its Application in Infrared Imaging
Institute of Scientific and Technical Information of China (English)
ZHANG Nan; JIN Wei-qi; SU Bing-hua
2005-01-01
As digital image techniques have been widely used, the requirements for high-resolution images become increasingly stringent. Traditional single-frame interpolation techniques cannot add new high frequency information to the expanded images, and cannot improve resolution in deed. Multiframe-based techniques are effective ways for high-resolution image reconstruction, but their computation complexities and the difficulties in achieving image sequences limit their applications. An original method using an artificial neural network is proposed in this paper. Using the inherent merits in neural network, we can establish the mapping between high frequency components in low-resolution images and high-resolution images. Example applications and their results demonstrated the images reconstructed by our method are aesthetically and quantitatively (using the criteria of MSE and MAE) superior to the images acquired by common methods. Even for infrared images this method can give satisfactory results with high definition. In addition, a single-layer linear neural network is used in this paper, the computational complexity is very low, and this method can be realized in real time.
Energy Technology Data Exchange (ETDEWEB)
Das, Marco; Muehlenbruch, Georg; Mahnken, Andreas Horst; Guenther, Rolf W.; Wildberger, Joachim Ernst [University Hospital, University of Technology (RWTH), Department of Diagnostic Radiology, Aachen (Germany); Weiss, Claudia [RWTH Aachen, Institute of Medical Statistics, Aachen (Germany); Schoepf, U. Joseph [Medical University of South Carolina, Department of Radiology, Charleston, SC (United States); Leidecker, Christianne [Institute of Medical Physics, University of Erlangen, Erlangen (Germany)
2006-02-01
The aims of this study were to optimize image quality for indirect CT venography (sequential versus spiral), and to evaluate different image reconstruction parameters for patients with suspected deep venous thrombosis (DVT). Fifty-one patients (26/25 with/without DVT) were prospectively evaluated for pulmonary embolism (PE) with standard multidetector-row computed tomography (MDCT) protocols. Retrospective image reconstruction was done with different slice thicknesses and reconstruction increments in sequential and spiral modes. All reconstructions were read for depiction of DVT and to evaluate best reconstruction parameters in comparison with the thinnest reconstruction (''gold standard''). Image noise and venous enhancement were measured as objective criteria for image quality. Subjective image quality was rated on a four-point scale. Effective dose was estimated for all reconstructions. In sequential 10/50 reconstruction DVT was completely detected in 13/26 cases, partially in 10/26 cases and was not detected at all in 3/26 cases, and 15/26, 9/26 and 2/26 cases for the 10/20 reconstruction, respectively. DVT was completely detected in all spiral reconstructions. Image noise ranged between 14.8-29.1 HU. Median image quality was 2. Estimated effective dose ranged between 2.3 mSv and 11.8 mSv. Gaps in sequential protocols may lead to false negative results. Therefore, spiral scanning protocols for complete depiction of DVT are mandatory. (orig.)
Directory of Open Access Journals (Sweden)
Luís F Seoane
2015-04-01
Full Text Available We provide a proof of concept for an EEG-based reconstruction of a visual image which is on a user's mind. Our approach is based on the Rapid Serial Visual Presentation (RSVP of polygon primitives and Brain-Computer Interface (BCI technology. In an experimental setup, subjects were presented bursts of polygons: some of them contributed to building a target image (because they matched the shape and/or color of the target while some of them did not. The presentation of the contributing polygons triggered attention-related EEG patterns. These Event Related Potentials (ERPs could be determined using BCI classification and could be matched to the stimuli that elicited them. These stimuli (i.e. the ERP-correlated polygons were accumulated in the display until a satisfactory reconstruction of the target image was reached. As more polygons were accumulated, finer visual details were attained resulting in more challenging classification tasks. In our experiments, we observe an average classification accuracy of around 75%. An in-depth investigation suggests that many of the misclassifications were not misinterpretations of the BCI concerning the users' intent, but rather caused by ambiguous polygons that could contribute to reconstruct several different images. When we put our BCI-image reconstruction in perspective with other RSVP BCI paradigms, there is large room for improvement both in speed and accuracy. These results invite us to be optimistic. They open a plethora of possibilities to explore non-invasive BCIs for image reconstruction both in healthy and impaired subjects and, accordingly, suggest interesting recreational and clinical applications.
Institute of Scientific and Technical Information of China (English)
GUO Qiang; YANG Xin
2006-01-01
A statistical algorithm for the reconstruction from time sequence echocardiographic images is proposed in this paper.The ability to jointly restore the images and reconstruct the 3D images without blurring the boundary is the main innovation of this algorithm. First, a Bayesian model based on MAP-MRF is used to reconstruct 3D volume, and extended to deal with the images acquired by rotation scanning method. Then, the spatiotemporal nature of ultrasound images is taken into account for the parameter of energy function, which makes this statistical model anisotropic. Hence not only can this method reconstruct 3D ultrasound images, but also remove the speckle noise anisotropically. Finally, we illustrate the experiments of our method on the synthetic and medical images and compare it with the isotropic reconstruction method.
Chen, Jianlin; Wang, Linyuan; Yan, Bin; Zhang, Hanming; Cheng, Genyang
2015-01-01
Iterative reconstruction algorithms for computed tomography (CT) through total variation regularization based on piecewise constant assumption can produce accurate, robust, and stable results. Nonetheless, this approach is often subject to staircase artefacts and the loss of fine details. To overcome these shortcomings, we introduce a family of novel image regularization penalties called total generalized variation (TGV) for the effective production of high-quality images from incomplete or noisy projection data for 3D reconstruction. We propose a new, fast alternating direction minimization algorithm to solve CT image reconstruction problems through TGV regularization. Based on the theory of sparse-view image reconstruction and the framework of augmented Lagrange function method, the TGV regularization term has been introduced in the computed tomography and is transformed into three independent variables of the optimization problem by introducing auxiliary variables. This new algorithm applies a local linearization and proximity technique to make the FFT-based calculation of the analytical solutions in the frequency domain feasible, thereby significantly reducing the complexity of the algorithm. Experiments with various 3D datasets corresponding to incomplete projection data demonstrate the advantage of our proposed algorithm in terms of preserving fine details and overcoming the staircase effect. The computation cost also suggests that the proposed algorithm is applicable to and is effective for CBCT imaging. Theoretical and technical optimization should be investigated carefully in terms of both computation efficiency and high resolution of this algorithm in application-oriented research.
A Layered Approach for Robust Spatial Virtual Human Pose Reconstruction Using a Still Image
Directory of Open Access Journals (Sweden)
Chengyu Guo
2016-02-01
Full Text Available Pedestrian detection and human pose estimation are instructive for reconstructing a three-dimensional scenario and for robot navigation, particularly when large amounts of vision data are captured using various data-recording techniques. Using an unrestricted capture scheme, which produces occlusions or breezing, the information describing each part of a human body and the relationship between each part or even different pedestrians must be present in a still image. Using this framework, a multi-layered, spatial, virtual, human pose reconstruction framework is presented in this study to recover any deficient information in planar images. In this framework, a hierarchical parts-based deep model is used to detect body parts by using the available restricted information in a still image and is then combined with spatial Markov random fields to re-estimate the accurate joint positions in the deep network. Then, the planar estimation results are mapped onto a virtual three-dimensional space using multiple constraints to recover any deficient spatial information. The proposed approach can be viewed as a general pre-processing method to guide the generation of continuous, three-dimensional motion data. The experiment results of this study are used to describe the effectiveness and usability of the proposed approach.
O'Halloran, M.; Lohfeld, S.; Ruvio, G.; Browne, J.; Krewer, F.; Ribeiro, C. O.; Inacio Pita, V. C.; Conceicao, R. C.; Jones, E.; Glavin, M.
2014-05-01
Breast cancer is one of the most common cancers in women. In the United States alone, it accounts for 31% of new cancer cases, and is second only to lung cancer as the leading cause of deaths in American women. More than 184,000 new cases of breast cancer are diagnosed each year resulting in approximately 41,000 deaths. Early detection and intervention is one of the most significant factors in improving the survival rates and quality of life experienced by breast cancer sufferers, since this is the time when treatment is most effective. One of the most promising breast imaging modalities is microwave imaging. The physical basis of active microwave imaging is the dielectric contrast between normal and malignant breast tissue that exists at microwave frequencies. The dielectric contrast is mainly due to the increased water content present in the cancerous tissue. Microwave imaging is non-ionizing, does not require breast compression, is less invasive than X-ray mammography, and is potentially low cost. While several prototype microwave breast imaging systems are currently in various stages of development, the design and fabrication of anatomically and dielectrically representative breast phantoms to evaluate these systems is often problematic. While some existing phantoms are composed of dielectrically representative materials, they rarely accurately represent the shape and size of a typical breast. Conversely, several phantoms have been developed to accurately model the shape of the human breast, but have inappropriate dielectric properties. This study will brie y review existing phantoms before describing the development of a more accurate and practical breast phantom for the evaluation of microwave breast imaging systems.
Electron Trajectory Reconstruction for Advanced Compton Imaging of Gamma Rays
Plimley, Brian Christopher
Gamma-ray imaging is useful for detecting, characterizing, and localizing sources in a variety of fields, including nuclear physics, security, nuclear accident response, nuclear medicine, and astronomy. Compton imaging in particular provides sensitivity to weak sources and good angular resolution in a large field of view. However, the photon origin in a single event sequence is normally only limited to the surface of a cone. If the initial direction of the Compton-scattered electron can be measured, the cone can be reduced to a cone segment with width depending on the uncertainty in the direction measurement, providing a corresponding increase in imaging sensitivity. Measurement of the electron's initial direction in an efficient detection material requires very fine position resolution due to the electron's short range and tortuous path. A thick (650 mum), fully-depleted charge-coupled device (CCD) developed for infrared astronomy has 10.5-mum position resolution in two dimensions, enabling the initial trajectory measurement of electrons of energy as low as 100 keV. This is the first time the initial trajectories of electrons of such low energies have been measured in a solid material. In this work, the CCD's efficacy as a gamma-ray detector is demonstrated experimentally, using a reconstruction algorithm to measure the initial electron direction from the CCD track image. In addition, models of fast electron interaction physics, charge transport and readout were used to generate modeled tracks with known initial direction. These modeled tracks allowed the development and refinement of the reconstruction algorithm. The angular sensitivity of the reconstruction algorithm is evaluated extensively with models for tracks below 480 keV, showing a FWHM as low as 20° in the pixel plane, and 30° RMS sensitivity to the magnitude of the out-of-plane angle. The measurement of the trajectories of electrons with energies as low as 100 keV have the potential to make electron
Directory of Open Access Journals (Sweden)
Reza Saadat Mostafavi
2010-05-01
Full Text Available Background/Objective: The presence of liver volume has a great effect on diagnosis and management of different diseases such as lymphoproliferative conditions. "nPatients and Methods: Abdominal CT scan of 100 patients without any findings for liver disease (in history and imaging was subjected to volumetry and reconstruction. Along with the liver volume, in axial series, the AP diameter of the left lobe (in midline and right lobe (mid-clavicular and lateral maximum diameter of the liver in the mid-axiliary line and maximum diameter to IVC were calculated. In the coronal mid-axillary and sagittal mid-clavicular plane, maximum superior-inferior dimensions were calculated with their various combinations (multiplying. Regression analysis between dimensions and volume were performed. "nResults: The most accurate combination was the superior inferior sagittal dimension multiplied by AP diameter of the right lobe (R squared 0.78, P-value<0.001 and the most solitary dimension was the lateral dimension to IVC in the axial plane (R squared 0.57, P-value<0.001 with an interval of 9-11cm for 68% of normal. "nConclusion: We recommend the lateral maximum diameter of liver from surface to IVC in the axial plane in ultrasound for liver volume prediction with an interval of 9-11cm for 68% of normal. Out of this range is regarded as abnormal.
Information extraction and CT reconstruction of liver images based on diffraction enhanced imaging
Institute of Scientific and Technical Information of China (English)
Chunhong Hu; Tao Zhao; Lu Zhang; Hui Li; Xinyan Zhao; Shuqian Luo
2009-01-01
X-ray phase-contrast imaging (PCI) is a new emerging imaging technique that generates a high spatial resolution and high contrast of biological soft tissues compared to conventional radiography. Herein a biomedical application of diffraction enhanced imaging (DEI) is presented. As one of the PCI methods, DEI derives contrast from many different kinds of sample information, such as the sample's X-ray absorption, refraction gradient and ultra-small-angle X-ray scattering (USAXS) properties, and the sample information is expressed by three parametric images. Combined with computed tomography (CT), DEI-CT can produce 3D volumetric images of the sample and can be used for investigating micro-structures of biomedical samples. Our DEI experiments for fiver samples were implemented at the topog-raphy station of Beijing Synchrotron Radiation Facility (BSRF). The results show that by using our provided information extraction method and DEI-CT reconstruction approach, the obtained parametric images clearly display the inner structures of liver tissues and the morphology of blood vessels. Furthermore, the reconstructed 3D view of the fiver blood vessels exhibits the micro blood vessels whose minimum diameter is on the order of about tens of microns, much better than its conventional CT reconstruction at a millimeter resolution.In conclusion, both the information extraction method and DEI-CT have the potential for use in biomedical micro-structures analysis.
Patch-based image reconstruction for PET using prior-image derived dictionaries
Tahaei, Marzieh S.; Reader, Andrew J.
2016-09-01
In PET image reconstruction, regularization is often needed to reduce the noise in the resulting images. Patch-based image processing techniques have recently been successfully used for regularization in medical image reconstruction through a penalized likelihood framework. Re-parameterization within reconstruction is another powerful regularization technique in which the object in the scanner is re-parameterized using coefficients for spatially-extensive basis vectors. In this work, a method for extracting patch-based basis vectors from the subject’s MR image is proposed. The coefficients for these basis vectors are then estimated using the conventional MLEM algorithm. Furthermore, using the alternating direction method of multipliers, an algorithm for optimizing the Poisson log-likelihood while imposing sparsity on the parameters is also proposed. This novel method is then utilized to find sparse coefficients for the patch-based basis vectors extracted from the MR image. The results indicate the superiority of the proposed methods to patch-based regularization using the penalized likelihood framework.
Energy Technology Data Exchange (ETDEWEB)
Pesavento, J B; Morgan, D; Bermingham, R; Zamora, D; Chromy, B; Segelke, B; Coleman, M; Xing, L; Cheng, H; Bench, G; Hoeprich, P
2007-06-07
Nanolipoprotein particles (NLPs) are small 10-20 nm diameter assemblies of apolipoproteins and lipids. At Lawrence Livermore National Laboratory (LLNL), they have constructed multiple variants of these assemblies. NLPs have been generated from a variety of lipoproteins, including apolipoprotein Al, apolipophorin III, apolipoprotein E4 22K, and MSP1T2 (nanodisc, Inc.). Lipids used included DMPC (bulk of the bilayer material), DMPE (in various amounts), and DPPC. NLPs were made in either the absence or presence of the detergent cholate. They have collected electron microscopy data as a part of the characterization component of this research. Although purified by size exclusion chromatography (SEC), samples are somewhat heterogeneous when analyzed at the nanoscale by negative stained cryo-EM. Images reveal a broad range of shape heterogeneity, suggesting variability in conformational flexibility, in fact, modeling studies point to dynamics of inter-helical loop regions within apolipoproteins as being a possible source for observed variation in NLP size. Initial attempts at three-dimensional reconstructions have proven to be challenging due to this size and shape disparity. They are pursuing a strategy of computational size exclusion to group particles into subpopulations based on average particle diameter. They show here results from their ongoing efforts at statistically and computationally subdividing NLP populations to realize greater homogeneity and then generate 3D reconstructions.
PIVlab – Towards User-friendly, Affordable and Accurate Digital Particle Image Velocimetry in MATLAB
Directory of Open Access Journals (Sweden)
William Thielicke
2014-10-01
Full Text Available Digital particle image velocimetry (DPIV is a non-intrusive analysis technique that is very popular for mapping flows quantitatively. To get accurate results, in particular in complex flow fields, a number of challenges have to be faced and solved: The quality of the flow measurements is affected by computational details such as image pre-conditioning, sub-pixel peak estimators, data validation procedures, interpolation algorithms and smoothing methods. The accuracy of several algorithms was determined and the best performing methods were implemented in a user-friendly open-source tool for performing DPIV flow analysis in Matlab.
Accurate color synthesis of three-dimensional objects in an image
Xin, John H.; Shen, Hui-Liang
2004-05-01
Our study deals with color synthesis of a three-dimensional object in an image; i.e., given a single image, a target color can be accurately mapped onto the object such that the color appearance of the synthesized object closely resembles that of the actual one. As it is almost impossible to acquire the complete geometric description of the surfaces of an object in an image, this study attempted to recover the implicit description of geometry for the color synthesis. The description was obtained from either a series of spectral reflectances or the RGB signals at different surface positions on the basis of the dichromatic reflection model. The experimental results showed that this implicit image-based representation is related to the object geometry and is sufficient for accurate color synthesis of three-dimensional objects in an image. The method established is applicable to the color synthesis of both rigid and deformable objects and should contribute to color fidelity in virtual design, manufacturing, and retailing.
Je, U. K.; Cho, H. M.; Cho, H. S.; Park, Y. O.; Park, C. K.; Lim, H. W.; Kim, K. S.; Kim, G. A.; Park, S. Y.; Woo, T. H.; Choi, S. I.
2016-02-01
In this paper, we propose a new/next-generation type of CT examinations, the so-called Interior Computed Tomography (ICT), which may presumably lead to dose reduction to the patient outside the target region-of-interest (ROI), in dental x-ray imaging. Here an x-ray beam from each projection position covers only a relatively small ROI containing a target of diagnosis from the examined structure, leading to imaging benefits such as decreasing scatters and system cost as well as reducing imaging dose. We considered the compressed-sensing (CS) framework, rather than common filtered-backprojection (FBP)-based algorithms, for more accurate ICT reconstruction. We implemented a CS-based ICT algorithm and performed a systematic simulation to investigate the imaging characteristics. Simulation conditions of two ROI ratios of 0.28 and 0.14 between the target and the whole phantom sizes and four projection numbers of 360, 180, 90, and 45 were tested. We successfully reconstructed ICT images of substantially high image quality by using the CS framework even with few-view projection data, still preserving sharp edges in the images.
Energy Technology Data Exchange (ETDEWEB)
Hu, E; Lasio, G; Lee, M; Chen, S; Yi, B [Univ. of Maryland School Of Medicine, Baltimore, MD (United States)
2015-06-15
Purpose: Only a part of a treatment couch is reconstructed in CBCT due to the limited field of view (FOV). This often generates inaccurate results in the delivered dose evaluation with CBCT and more noise in the CBCT reconstruction. Full reconstruction of the couch at treatment setup can be used for more accurate exit beam dosimetry. The goal of this study is to develop a method to reconstruct a full treatment couch using a pre-scanned couch image and rigid registration. Methods: A full couch (Exact Couch, Varian) model image was reconstructed by rigidly registering and combining two sets of partial CBCT images. The full couch model includes three parts: two side rails and a couch top. A patient CBCT was reconstructed with reconstruction grid size larger than the physical field of view to include the full couch. The image quality of the couch is not good due to data truncation, but good enough to allow rigid registration of the couch. A composite CBCT image of the patient plus couch has been generated from the original reconstruction by replacing couch portion with the pre-acquired model couch, rigidly registered to the original scan. We evaluated the clinical usefulness of this method by comparing treatment plans generated on the original and on the modified scans. Results: The full couch model could be attached to a patient CBCT image set via rigid image registration. Plan DVHs showed 1∼2% difference between plans with and without full couch modeling. Conclusion: The proposed method generated a full treatment couch CBCT model, which can be successfully registered to the original patient image. This method was also shown to be useful in generating more accurate dose distributions, by lowering 1∼2% dose in PTV and a few other critical organs. Part of this study is supported by NIH R01CA133539.
Image reconstruction for a Positron Emission Tomograph optimized for breast cancer imaging
Energy Technology Data Exchange (ETDEWEB)
Virador, Patrick R.G.
2000-04-01
The author performs image reconstruction for a novel Positron Emission Tomography camera that is optimized for breast cancer imaging. This work addresses for the first time, the problem of fully-3D, tomographic reconstruction using a septa-less, stationary, (i.e. no rotation or linear motion), and rectangular camera whose Field of View (FOV) encompasses the entire volume enclosed by detector modules capable of measuring Depth of Interaction (DOI) information. The camera is rectangular in shape in order to accommodate breasts of varying sizes while allowing for soft compression of the breast during the scan. This non-standard geometry of the camera exacerbates two problems: (a) radial elongation due to crystal penetration and (b) reconstructing images from irregularly sampled data. Packing considerations also give rise to regions in projection space that are not sampled which lead to missing information. The author presents new Fourier Methods based image reconstruction algorithms that incorporate DOI information and accommodate the irregular sampling of the camera in a consistent manner by defining lines of responses (LORs) between the measured interaction points instead of rebinning the events into predefined crystal face LORs which is the only other method to handle DOI information proposed thus far. The new procedures maximize the use of the increased sampling provided by the DOI while minimizing interpolation in the data. The new algorithms use fixed-width evenly spaced radial bins in order to take advantage of the speed of the Fast Fourier Transform (FFT), which necessitates the use of irregular angular sampling in order to minimize the number of unnormalizable Zero-Efficiency Bins (ZEBs). In order to address the persisting ZEBs and the issue of missing information originating from packing considerations, the algorithms (a) perform nearest neighbor smoothing in 2D in the radial bins (b) employ a semi-iterative procedure in order to estimate the unsampled data
Image reconstruction for a Positron Emission Tomograph optimized for breast cancer imaging
Energy Technology Data Exchange (ETDEWEB)
Virador, Patrick R.G. [Univ. of California, Berkeley, CA (United States)
2000-04-01
The author performs image reconstruction for a novel Positron Emission Tomography camera that is optimized for breast cancer imaging. This work addresses for the first time, the problem of fully-3D, tomographic reconstruction using a septa-less, stationary, (i.e. no rotation or linear motion), and rectangular camera whose Field of View (FOV) encompasses the entire volume enclosed by detector modules capable of measuring Depth of Interaction (DOI) information. The camera is rectangular in shape in order to accommodate breasts of varying sizes while allowing for soft compression of the breast during the scan. This non-standard geometry of the camera exacerbates two problems: (a) radial elongation due to crystal penetration and (b) reconstructing images from irregularly sampled data. Packing considerations also give rise to regions in projection space that are not sampled which lead to missing information. The author presents new Fourier Methods based image reconstruction algorithms that incorporate DOI information and accommodate the irregular sampling of the camera in a consistent manner by defining lines of responses (LORs) between the measured interaction points instead of rebinning the events into predefined crystal face LORs which is the only other method to handle DOI information proposed thus far. The new procedures maximize the use of the increased sampling provided by the DOI while minimizing interpolation in the data. The new algorithms use fixed-width evenly spaced radial bins in order to take advantage of the speed of the Fast Fourier Transform (FFT), which necessitates the use of irregular angular sampling in order to minimize the number of unnormalizable Zero-Efficiency Bins (ZEBs). In order to address the persisting ZEBs and the issue of missing information originating from packing considerations, the algorithms (a) perform nearest neighbor smoothing in 2D in the radial bins (b) employ a semi-iterative procedure in order to estimate the unsampled data
Zhang, Hao; Ma, Jianhua; Lu, Hongbing; Liang, Zhengrong
2014-01-01
Statistical image reconstruction (SIR) methods have shown potential to substantially improve the image quality of low-dose X-ray computed tomography (CT) as compared to the conventional filtered back-projection (FBP) method for various clinical tasks. According to the maximum a posterior (MAP) estimation, the SIR methods can be typically formulated by an objective function consisting of two terms: (1) data-fidelity (or equivalently, data-fitting or data-mismatch) term modeling the statistics of projection measurements, and (2) regularization (or equivalently, prior or penalty) term reflecting prior knowledge or expectation on the characteristics of the image to be reconstructed. Existing SIR methods for low-dose CT can be divided into two groups: (1) those that use calibrated transmitted photon counts (before log-transform) with penalized maximum likelihood (pML) criterion, and (2) those that use calibrated line-integrals (after log-transform) with penalized weighted least-squares (PWLS) criterion. Accurate s...
Xin, Fan; Ming-Kai, Yun; Xiao-Li, Sun; Xue-Xiang, Cao; Shuang-Quanm, Liu; Pei, Chai; Dao-Wu, Li; Long, Wei
2014-01-01
In positron emission tomography (PET) imaging, statistical iterative reconstruction (IR) techniques appear particularly promising since they can provide accurate physical model and geometric system description. The reconstructed image quality mainly depends on the system matrix model which describes the relationship between image space and projection space for the IR method. The system matrix can contain some physics factors of detection such as geometrical component and blurring component. Point spread function (PSF) is generally used to describe the blurring component. This paper proposes an IR method based on the PSF system matrix, which is derived from the single photon incidence response function. More specifically, the gamma photon incidence on a crystal array is simulated by the Monte Carlo (MC) simulation, and then the single photon incidence response functions are obtained. Subsequently, using the single photon incidence response functions, the coincidence blurring factor is acquired according to the...
A tensor-based dictionary learning approach to tomographic image reconstruction
DEFF Research Database (Denmark)
Soltani, Sara; Kilmer, Misha E.; Hansen, Per Christian
2016-01-01
We consider tomographic reconstruction using priors in the form of a dictionary learned from training images. The reconstruction has two stages: first we construct a tensor dictionary prior from our training data, and then we pose the reconstruction problem in terms of recovering the expansion co...
Investigation of optimization-based reconstruction with an image-total-variation constraint in PET
Zhang, Zheng; Ye, Jinghan; Chen, Buxin; Perkins, Amy E.; Rose, Sean; Sidky, Emil Y.; Kao, Chien-Min; Xia, Dan; Tung, Chi-Hua; Pan, Xiaochuan
2016-08-01
Interest remains in reconstruction-algorithm research and development for possible improvement of image quality in current PET imaging and for enabling innovative PET systems to enhance existing, and facilitate new, preclinical and clinical applications. Optimization-based image reconstruction has been demonstrated in recent years of potential utility for CT imaging applications. In this work, we investigate tailoring the optimization-based techniques to image reconstruction for PET systems with standard and non-standard scan configurations. Specifically, given an image-total-variation (TV) constraint, we investigated how the selection of different data divergences and associated parameters impacts the optimization-based reconstruction of PET images. The reconstruction robustness was explored also with respect to different data conditions and activity up-takes of practical relevance. A study was conducted particularly for image reconstruction from data collected by use of a PET configuration with sparsely populated detectors. Overall, the study demonstrates the robustness of the TV-constrained, optimization-based reconstruction for considerably different data conditions in PET imaging, as well as its potential to enable PET configurations with reduced numbers of detectors. Insights gained in the study may be exploited for developing algorithms for PET-image reconstruction and for enabling PET-configuration design of practical usefulness in preclinical and clinical applications.
Su, Hai; Xing, Fuyong; Yang, Lin
2016-06-01
Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96.
Efficient DPCA SAR imaging with fast iterative spectrum reconstruction method
Institute of Scientific and Technical Information of China (English)
FANG Jian; ZENG JinShan; XU ZongBen; ZHAO Yao
2012-01-01
The displaced phase center antenna (DPCA) technique is an effective strategy to achieve wide-swath synthetic aperture radar (SAR) imaging with high azimuth resolution.However,traditionally,it requires strict limitation of the pulse repetition frequency (PRF） to avoid non-uniform sampling.Otherwise,any deviation could bring serious ambiguity if the data are directly processed using a matched filter.To break this limitation,a recently proposed spectrum reconstruction method is capable of recovering the true spectrum from the nonuniform samples. However,the performance is sensitive to the selection of the PRF.Sparse regularization based imaging may provide a way to overcome this sensitivity. The existing time-domain method,however,requires a large-scale observation matrix to be built,which brings a high computational cost.In this paper,we propose a frequency domain method,called the iterative spectrum reconstruction method,through integration of the sparse regularization technique with spectrum analysis of the DPCA signal.By approximately expressing the observation in the frequency domain,which is realized via a series of decoupled linear operations,the method performs SAR imaging which is then not directly based on the observation matrix,which reduces the computational cost from O(N2) to O(NlogN) (where N is the number of range cells),and is therefore more efficient than the time domain method. The sparse regularization scheme,realized via a fast thresholding iteration,has been adopted in this method,which brings the robustness of the imaging process to the PRF selection.We provide a series of simulations and ground based experiments to demonstrate the high efficiency and robustness of the method.The simulations show that the new method is almost as fast as the traditional mono-channel algorithm,and works well almost independently of the PRF selection.Consequently,the suggested method can be accepted as a practical and efficient wide-swath SAR imaging technique.
[Research on maize multispectral image accurate segmentation and chlorophyll index estimation].
Wu, Qian; Sun, Hong; Li, Min-zan; Song, Yuan-yuan; Zhang, Yan-e
2015-01-01
In order to rapidly acquire maize growing information in the field, a non-destructive method of maize chlorophyll content index measurement was conducted based on multi-spectral imaging technique and imaging processing technology. The experiment was conducted at Yangling in Shaanxi province of China and the crop was Zheng-dan 958 planted in about 1 000 m X 600 m experiment field. Firstly, a 2-CCD multi-spectral image monitoring system was available to acquire the canopy images. The system was based on a dichroic prism, allowing precise separation of the visible (Blue (B), Green (G), Red (R): 400-700 nm) and near-infrared (NIR, 760-1 000 nm) band. The multispectral images were output as RGB and NIR images via the system vertically fixed to the ground with vertical distance of 2 m and angular field of 50°. SPAD index of each sample was'measured synchronously to show the chlorophyll content index. Secondly, after the image smoothing using adaptive smooth filtering algorithm, the NIR maize image was selected to segment the maize leaves from background, because there was a big difference showed in gray histogram between plant and soil background. The NIR image segmentation algorithm was conducted following steps of preliminary and accuracy segmentation: (1) The results of OTSU image segmentation method and the variable threshold algorithm were discussed. It was revealed that the latter was better one in corn plant and weed segmentation. As a result, the variable threshold algorithm based on local statistics was selected for the preliminary image segmentation. The expansion and corrosion were used to optimize the segmented image. (2) The region labeling algorithm was used to segment corn plants from soil and weed background with an accuracy of 95. 59 %. And then, the multi-spectral image of maize canopy was accurately segmented in R, G and B band separately. Thirdly, the image parameters were abstracted based on the segmented visible and NIR images. The average gray
Accurate Image Search using Local Descriptors into a Compact Image Representation
Directory of Open Access Journals (Sweden)
Soumia Benkrama
2013-01-01
Full Text Available Progress in image retrieval by using low-level features, such as colors, textures and shapes, the performance is still unsatisfied as there are existing gaps between low-level features and high-level semantic concepts. In this work, we present an improved implementation for the bag of visual words approach. We propose a image retrieval system based on bag-of-features (BoF model by using scale invariant feature transform (SIFT and speeded up robust features (SURF. In literature SIFT and SURF give of good results. Based on this observation, we decide to use a bag-of-features approach over quaternion zernike moments (QZM. We compare the results of SIFT and SURF with those of QZM. We propose an indexing method for content based search task that aims to retrieve collection of images and returns a ranked list of objects in response to a query image. Experimental results with the Coil-100 and corel-1000 image database, demonstrate that QZM produces a better performance than known representations (SIFT and SURF.
Quantitative thermo-acoustic imaging: An exact reconstruction formula
Ammari, Habib; Jing, Wenjia; Nguyen, Loc
2012-01-01
The quantitative thermo-acoustic imaging is considered in this paper. Given several data sets of electromagnetic data, we first establish an exact formula for the absorption coefficient, which involves derivatives of the given data up to the third order. However, because of the dependence of such derivatives, this formula is unstable in the sense that small measurement noises may cause large errors. Hence, with the presence of noise, the obtained formula, together with noise regularization, provides an initial guess for the true absorption coefficient. We next correct the errors by deriving a reconstruction formula based on the least square solution of an optimal control problem and show that this optimization step reduces the errors occurring.
A Fast Super-Resolution Reconstruction from Image Sequence
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Based on the mechanism of imagery, a novel method called the delaminating combining template method, used for the problem of super-resolution reconstruction from image sequence, is described in this paper. The combining template method contains two steps: a delaminating strategy and a combining template algorithm. The delaminating strategy divides the original problem into several sub-problems;each of them is only connected to one degrading factor. The combining template algorithm is suggested to resolve each sub-problem. In addition, to verify the valid of the method, a new index called oriental entropy is presented. The results from the theoretical analysis and experiments illustrate that this method to be promising and efficient.
Iterative reconstruction of images from incomplete spectral data
Rhebergen, Jan B.; van den Berg, Peter M.; Habashy, Tarek M.
1997-06-01
In various branches of engineering and science, one is confronted with measurements resulting in incomplete spectral data. The problem of the reconstruction of an image from such a data set can be formulated in terms of an integral equation of the first kind. Consequently, this equation can be converted into an equivalent integral equation of the second kind which can be solved by a Neumann-type iterative method. It is shown that this Neumann expansion is an error-reducing method and that it is equivalent to the Papoulis - Gerchberg algorithm for band-limited signal extrapolation. The integral equation can also be solved by employing a conjugate gradient iterative scheme. Again, convergence of this scheme is demonstrated. Finally a number of illustrative numerical examples are presented and discussed.
Curvelet-based sampling for accurate and efficient multimodal image registration
Safran, M. N.; Freiman, M.; Werman, M.; Joskowicz, L.
2009-02-01
We present a new non-uniform adaptive sampling method for the estimation of mutual information in multi-modal image registration. The method uses the Fast Discrete Curvelet Transform to identify regions along anatomical curves on which the mutual information is computed. Its main advantages of over other non-uniform sampling schemes are that it captures the most informative regions, that it is invariant to feature shapes, orientations, and sizes, that it is efficient, and that it yields accurate results. Extensive evaluation on 20 validated clinical brain CT images to Proton Density (PD) and T1 and T2-weighted MRI images from the public RIRE database show the effectiveness of our method. Rigid registration accuracy measured at 10 clinical targets and compared to ground truth measurements yield a mean target registration error of 0.68mm(std=0.4mm) for CT-PD and 0.82mm(std=0.43mm) for CT-T2. This is 0.3mm (1mm) more accurate in the average (worst) case than five existing sampling methods. Our method has the lowest registration errors recorded to date for the registration of CT-PD and CT-T2 images in the RIRE website when compared to methods that were tested on at least three patient datasets.
Scheins, J J; Herzog, H; Shah, N J
2011-03-01
For iterative, fully 3D positron emission tomography (PET) image reconstruction intrinsic symmetries can be used to significantly reduce the size of the system matrix. The precalculation and beneficial memory-resident storage of all nonzero system matrix elements is possible where sufficient compression exists. Thus, reconstruction times can be minimized independently of the used projector and more elaborate weighting schemes, e.g., volume-of-intersection (VOI), are applicable. A novel organization of scanner-independent, adaptive 3D projection data is presented which can be advantageously combined with highly rotation-symmetric voxel assemblies. In this way, significant system matrix compression is achieved. Applications taking into account all physical lines-of-response (LORs) with individual VOI projectors are presented for the Siemens ECAT HR+ whole-body scanner and the Siemens BrainPET, the PET component of a novel hybrid-MR/PET imaging system. Measured and simulated data were reconstructed using the new method with ordered-subset-expectation-maximization (OSEM). Results are compared to those obtained by the sinogram-based OSEM reconstruction provided by the manufacturer. The higher computational effort due to the more accurate image space sampling provides significantly improved images in terms of resolution and noise.
Geng, Hua; Todd, Naomi M; Devlin-Mullin, Aine; Poologasundarampillai, Gowsihan; Kim, Taek Bo; Madi, Kamel; Cartmell, Sarah; Mitchell, Christopher A; Jones, Julian R; Lee, Peter D
2016-06-01
A correlative imaging methodology was developed to accurately quantify bone formation in the complex lattice structure of additive manufactured implants. Micro computed tomography (μCT) and histomorphometry were combined, integrating the best features from both, while demonstrating the limitations of each imaging modality. This semi-automatic methodology registered each modality using a coarse graining technique to speed the registration of 2D histology sections to high resolution 3D μCT datasets. Once registered, histomorphometric qualitative and quantitative bone descriptors were directly correlated to 3D quantitative bone descriptors, such as bone ingrowth and bone contact. The correlative imaging allowed the significant volumetric shrinkage of histology sections to be quantified for the first time (~15 %). This technique demonstrated the importance of location of the histological section, demonstrating that up to a 30 % offset can be introduced. The results were used to quantitatively demonstrate the effectiveness of 3D printed titanium lattice implants.
Lemoigne, Yves
2008-01-01
This volume collects the lectures presented at the ninth ESI School held at Archamps (FR) in November 2006 and is dedicated to nuclear physics applications in molecular imaging. The lectures focus on the multiple facets of image reconstruction processing and management and illustrate the role of digital imaging in clinical practice. Medical computing and image reconstruction are introduced by analysing the underlying physics principles and their implementation, relevant quality aspects, clinical performance and recent advancements in the field. Several stages of the imaging process are specifically addressed, e.g. optimisation of data acquisition and storage, distributed computing, physiology and detector modelling, computer algorithms for image reconstruction and measurement in tomography applications, for both clinical and biomedical research applications. All topics are presented with didactical language and style, making this book an appropriate reference for students and professionals seeking a comprehen...
Optimization-based image reconstruction with artifact reduction in C-arm CBCT
Xia, Dan; Langan, David A.; Solomon, Stephen B.; Zhang, Zheng; Chen, Buxin; Lai, Hao; Sidky, Emil Y.; Pan, Xiaochuan
2016-10-01
We investigate an optimization-based reconstruction, with an emphasis on image-artifact reduction, from data collected in C-arm cone-beam computed tomography (CBCT) employed in image-guided interventional procedures. In the study, an image to be reconstructed is formulated as a solution to a convex optimization program in which a weighted data divergence is minimized subject to a constraint on the image total variation (TV); a data-derivative fidelity is introduced in the program specifically for effectively suppressing dominant, low-frequency data artifact caused by, e.g. data truncation; and the Chambolle-Pock (CP) algorithm is tailored to reconstruct an image through solving the program. Like any other reconstructions, the optimization-based reconstruction considered depends upon numerous parameters. We elucidate the parameters, illustrate their determination, and demonstrate their impact on the reconstruction. The optimization-based reconstruction, when applied to data collected from swine and patient subjects, yields images with visibly reduced artifacts in contrast to the reference reconstruction, and it also appears to exhibit a high degree of robustness against distinctively different anatomies of imaged subjects and scanning conditions of clinical significance. Knowledge and insights gained in the study may be exploited for aiding in the design of practical reconstructions of truly clinical-application utility.
Sakellarios, Antonis I; Stefanou, Kostas; Siogkas, Panagiotis; Tsakanikas, Vasilis D; Bourantas, Christos V; Athanasiou, Lambros; Exarchos, Themis P; Fotiou, Evangelos; Naka, Katerina K; Papafaklis, Michail I; Patterson, Andrew J; Young, Victoria E L; Gillard, Jonathan H; Michalis, Lampros K; Fotiadis, Dimitrios I
2012-10-01
In this study, we present a novel methodology that allows reliable segmentation of the magnetic resonance images (MRIs) for accurate fully automated three-dimensional (3D) reconstruction of the carotid arteries and semiautomated characterization of plaque type. Our approach uses active contours to detect the luminal borders in the time-of-flight images and the outer vessel wall borders in the T(1)-weighted images. The methodology incorporates the connecting components theory for the automated identification of the bifurcation region and a knowledge-based algorithm for the accurate characterization of the plaque components. The proposed segmentation method was validated in randomly selected MRI frames analyzed offline by two expert observers. The interobserver variability of the method for the lumen and outer vessel wall was -1.60%±6.70% and 0.56%±6.28%, respectively, while the Williams Index for all metrics was close to unity. The methodology implemented to identify the composition of the plaque was also validated in 591 images acquired from 24 patients. The obtained Cohen's k was 0.68 (0.60-0.76) for lipid plaques, while the time needed to process an MRI sequence for 3D reconstruction was only 30 s. The obtained results indicate that the proposed methodology allows reliable and automated detection of the luminal and vessel wall borders and fast and accurate characterization of plaque type in carotid MRI sequences. These features render the currently presented methodology a useful tool in the clinical and research arena.
Photoacoustic image reconstruction from ultrasound post-beamformed B-mode image
Zhang, Haichong K.; Guo, Xiaoyu; Kang, Hyun Jae; Boctor, Emad M.
2016-03-01
A requirement to reconstruct photoacoustic (PA) image is to have a synchronized channel data acquisition with laser firing. Unfortunately, most clinical ultrasound (US) systems don't offer an interface to obtain synchronized channel data. To broaden the impact of clinical PA imaging, we propose a PA image reconstruction algorithm utilizing US B-mode image, which is readily available from clinical scanners. US B-mode image involves a series of signal processing including beamforming, followed by envelope detection, and end with log compression. Yet, it will be defocused when PA signals are input due to incorrect delay function. Our approach is to reverse the order of image processing steps and recover the original US post-beamformed radio-frequency (RF) data, in which a synthetic aperture based PA rebeamforming algorithm can be further applied. Taking B-mode image as the input, we firstly recovered US postbeamformed RF data by applying log decompression and convoluting an acoustic impulse response to combine carrier frequency information. Then, the US post-beamformed RF data is utilized as pre-beamformed RF data for the adaptive PA beamforming algorithm, and the new delay function is applied by taking into account that the focus depth in US beamforming is at the half depth of the PA case. The feasibility of the proposed method was validated through simulation, and was experimentally demonstrated using an acoustic point source. The point source was successfully beamformed from a US B-mode image, and the full with at the half maximum of the point improved 3.97 times. Comparing this result to the ground-truth reconstruction using channel data, the FWHM was slightly degraded with 1.28 times caused by information loss during envelope detection and convolution of the RF information.
Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter
2016-05-01
At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts
Real-time maximum a-posteriori image reconstruction for fluorescence microscopy
Directory of Open Access Journals (Sweden)
Anwar A. Jabbar
2015-08-01
Full Text Available Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU based real-time maximum a-posteriori (MAP image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA efficiently execute the iterative image reconstruction algorithm that is ≈200-fold faster (for large dataset when compared to existing CPU based systems.
Real-time maximum a-posteriori image reconstruction for fluorescence microscopy
Jabbar, Anwar A.; Dilipkumar, Shilpa; C K, Rasmi; Rajan, K.; Mondal, Partha P.
2015-08-01
Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is ≈200-fold faster (for large dataset) when compared to existing CPU based systems.
Noise-free accurate count of microbial colonies by time-lapse shadow image analysis.
Ogawa, Hiroyuki; Nasu, Senshi; Takeshige, Motomu; Funabashi, Hisakage; Saito, Mikako; Matsuoka, Hideaki
2012-12-01
Microbial colonies in food matrices could be counted accurately by a novel noise-free method based on time-lapse shadow image analysis. An agar plate containing many clusters of microbial colonies and/or meat fragments was trans-illuminated to project their 2-dimensional (2D) shadow images on a color CCD camera. The 2D shadow images of every cluster distributed within a 3-mm thick agar layer were captured in focus simultaneously by means of a multiple focusing system, and were then converted to 3-dimensional (3D) shadow images. By time-lapse analysis of the 3D shadow images, it was determined whether each cluster comprised single or multiple colonies or a meat fragment. The analytical precision was high enough to be able to distinguish a microbial colony from a meat fragment, to recognize an oval image as two colonies contacting each other, and to detect microbial colonies hidden under a food fragment. The detection of hidden colonies is its outstanding performance in comparison with other systems. The present system attained accuracy for counting fewer than 5 colonies and is therefore of practical importance.
A MATLAB package for the EIDORS project to reconstruct two-dimensional EIT images.
Vauhkonen, M; Lionheart, W R; Heikkinen, L M; Vauhkonen, P J; Kaipio, J P
2001-02-01
The EIDORS (electrical impedance and diffuse optical reconstruction software) project aims to produce a software system for reconstructing images from electrical or diffuse optical data. MATLAB is a software that is used in the EIDORS project for rapid prototyping, graphical user interface construction and image display. We have written a MATLAB package (http://venda.uku.fi/ vauhkon/) which can be used for two-dimensional mesh generation, solving the forward problem and reconstructing and displaying the reconstructed images (resistivity or admittivity). In this paper we briefly describe the mathematical theory on which the codes are based on and also give some examples of the capabilities of the package.
Fast and Accurate Semiautomatic Segmentation of Individual Teeth from Dental CT Images.
Kang, Ho Chul; Choi, Chankyu; Shin, Juneseuk; Lee, Jeongjin; Shin, Yeong-Gil
2015-01-01
In this paper, we propose a fast and accurate semiautomatic method to effectively distinguish individual teeth from the sockets of teeth in dental CT images. Parameter values of thresholding and shapes of the teeth are propagated to the neighboring slice, based on the separated teeth from reference images. After the propagation of threshold values and shapes of the teeth, the histogram of the current slice was analyzed. The individual teeth are automatically separated and segmented by using seeded region growing. Then, the newly generated separation information is iteratively propagated to the neighboring slice. Our method was validated by ten sets of dental CT scans, and the results were compared with the manually segmented result and conventional methods. The average error of absolute value of volume measurement was 2.29 ± 0.56%, which was more accurate than conventional methods. Boosting up the speed with the multicore processors was shown to be 2.4 times faster than a single core processor. The proposed method identified the individual teeth accurately, demonstrating that it can give dentists substantial assistance during dental surgery.
Fast and Accurate Semiautomatic Segmentation of Individual Teeth from Dental CT Images
Directory of Open Access Journals (Sweden)
Ho Chul Kang
2015-01-01
Full Text Available DIn this paper, we propose a fast and accurate semiautomatic method to effectively distinguish individual teeth from the sockets of teeth in dental CT images. Parameter values of thresholding and shapes of the teeth are propagated to the neighboring slice, based on the separated teeth from reference images. After the propagation of threshold values and shapes of the teeth, the histogram of the current slice was analyzed. The individual teeth are automatically separated and segmented by using seeded region growing. Then, the newly generated separation information is iteratively propagated to the neighboring slice. Our method was validated by ten sets of dental CT scans, and the results were compared with the manually segmented result and conventional methods. The average error of absolute value of volume measurement was 2.29±0.56%, which was more accurate than conventional methods. Boosting up the speed with the multicore processors was shown to be 2.4 times faster than a single core processor. The proposed method identified the individual teeth accurately, demonstrating that it can give dentists substantial assistance during dental surgery.
An accurate and practical method for inference of weak gravitational lensing from galaxy images
Bernstein, Gary M.; Armstrong, Robert; Krawiec, Christina; March, Marisa C.
2016-07-01
We demonstrate highly accurate recovery of weak gravitational lensing shear using an implementation of the Bayesian Fourier Domain (BFD) method proposed by Bernstein & Armstrong, extended to correct for selection biases. The BFD formalism is rigorously correct for Nyquist-sampled, background-limited, uncrowded images of background galaxies. BFD does not assign shapes to galaxies, instead compressing the pixel data D into a vector of moments M, such that we have an analytic expression for the probability P(M|g) of obtaining the observations with gravitational lensing distortion g along the line of sight. We implement an algorithm for conducting BFD's integrations over the population of unlensed source galaxies which measures ≈10 galaxies s-1 core-1 with good scaling properties. Initial tests of this code on ≈109 simulated lensed galaxy images recover the simulated shear to a fractional accuracy of m = (2.1 ± 0.4) × 10-3, substantially more accurate than has been demonstrated previously for any generally applicable method. Deep sky exposures generate a sufficiently accurate approximation to the noiseless, unlensed galaxy population distribution assumed as input to BFD. Potential extensions of the method include simultaneous measurement of magnification and shear; multiple-exposure, multiband observations; and joint inference of photometric redshifts and lensing tomography.
Energy Technology Data Exchange (ETDEWEB)
Sajib, Saurav Z. K.; Kim, Ji Eun; Jeong, Woo Chul; Kim, Hyung Joong; Woo, Eung Je [Department of Biomedical Engineering, Kyung Hee University, Yongin, Gyeonggi (Korea, Republic of); Kwon, Oh In, E-mail: oikwon@konkuk.ac.kr [Department of Mathematics, Konkuk University, Seoul (Korea, Republic of)
2015-03-14
Magnetic resonance electrical impedance tomography visualizes current density and/or conductivity distributions inside an electrically conductive object. Injecting currents into the imaging object along at least two different directions, induced magnetic flux density data can be measured using a magnetic resonance imaging scanner. Without rotating the object inside the scanner, we can measure only one component of the magnetic flux density denoted as B{sub z}. Since the biological tissues such as skeletal muscle and brain white matter show strong anisotropic properties, the reconstruction of anisotropic conductivity tensor is indispensable for the accurate observations in the biological systems. In this paper, we propose a direct method to reconstruct an axial apparent orthotropic conductivity tensor by using multiple B{sub z} data subject to multiple injection currents. To investigate the anisotropic conductivity properties, we first recover the internal current density from the measured B{sub z} data. From the recovered internal current density and the curl-free condition of the electric field, we derive an over-determined matrix system for determining the internal absolute orthotropic conductivity tensor. The over-determined matrix system is designed to use a combination of two loops around each pixel. Numerical simulations and phantom experimental results demonstrate that the proposed algorithm stably determines the orthotropic conductivity tensor.
Energy Technology Data Exchange (ETDEWEB)
Converse, Matthew I., E-mail: mconverse85@yahoo.com; Fullwood, David T.
2013-09-15
Current methods of image segmentation and reconstructions from scanning electron micrographs can be inadequate for resolving nanoscale gaps in composite materials (1–20 nm). Such information is critical to both accurate material characterizations and models of piezoresistive response. The current work proposes the use of crystallographic orientation data and machine learning for enhancing this process. It is first shown how a machine learning algorithm can be used to predict the connectivity of nanoscale grains in a Nickel nanostrand/epoxy composite. This results in 71.9% accuracy for a 2D algorithm and 62.4% accuracy in 3D. Finally, it is demonstrated how these algorithms can be used to predict the location of gaps between distinct nanostrands — gaps which would otherwise not be detected with the sole use of a scanning electron microscope. - Highlights: • A method is proposed for enhancing the segmentation/reconstruction of SEM images. • 3D crystallographic orientation data from a nickel nanocomposite is collected. • A machine learning algorithm is used to detect trends in adjacent grains. • This algorithm is then applied to predict likely regions of nanoscale gaps. • These gaps would otherwise be unresolved with the sole use of an SEM.
Energy Technology Data Exchange (ETDEWEB)
Reinartz, S.D.; Diefenbach, B.S.; Kuhl, C.K.; Mahnken, A.H. [University Hospital, RWTH Aachen University, Department of Diagnostic and Interventional Radiology, Aachen (Germany); Allmendinger, T. [Siemens Healthcare Sector, Department of Computed Tomography, Forchheim (Germany)
2012-12-15
To compare image quality in coronary artery computed tomography angiography (cCTA) using reconstructions with automated phase detection and Reconstructions computed with Identical Filling of the heart (RIF). Seventy-four patients underwent ECG-gated dual source CT (DSCT) between November 2009 and July 2010 for suspected coronary heart disease (n = 35), planning of transcatheter aortic valve replacement (n = 34) or evaluation of ventricular function (n = 5). Image data sets by the RIF formula and automated phase detection were computed and evaluated with the AHA 15-segment model and a 5-grade Likert scale (1: poor, 5: excellent quality). Subgroups regarding rhythm (sinus rhythm = SR; arrhythmia = ARR) and potential premedication were evaluated by a per-segment, per-vessel and per-patient analysis. RIF significantly improved image quality in 10 of 15 coronary segments (P < 0.05). More diagnostic segments were provided by RIF regarding the entire cohort (n = 693 vs. 590, P < 0.001) and all of the subgroups (e.g. ARR: n = 143 vs. 72, P < 0.001). In arrhythmic patients (n = 19), more diagnostic vessels (e.g. LAD: n = 10 vs. 3; P < 0.014) and complete data sets (n = 7 vs. 1; P < 0.001) were produced. RIF reconstruction is superior to automatic diastolic non-edited reconstructions, especially in arrhythmic patients. RIF theory provides a physiological approach for determining the optimal image reconstruction point in ECG-gated CT angiography. (orig.)
Dang, H.; Wang, A. S.; Sussman, Marc S.; Siewerdsen, J. H.; Stayman, J. W.
2014-09-01
Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration, and
Influence of iterative image reconstruction on CT-based calcium score measurements
van Osch, Jochen A. C.; Mouden, Mohamed; van Dalen, Jorn A.; Timmer, Jorik R.; Reiffers, Stoffer; Knollema, Siert; Greuter, Marcel J. W.; Ottervanger, Jan Paul; Jager, Piet L.
2014-01-01
Iterative reconstruction techniques for coronary CT angiography have been introduced as an alternative for traditional filter back projection (FBP) to reduce image noise, allowing improved image quality and a potential for dose reduction. However, the impact of iterative reconstruction on the corona
Rapid Non-Cartesian Parallel Imaging Reconstruction on Commodity Graphics Hardware
DEFF Research Database (Denmark)
Sørensen, Thomas Sangild; Atkinson, David; Boubertakh, Redha;
2008-01-01
time per frame is now below the acquisition time providing non-Cartesian reconstruction with only minimal delay between acquisition and subsequent display of images. This is demonstrated by four-fold and eight-fold undersampled real-time radial imaging reconstructed in 25 ms to 55 ms per frame....
Energy Technology Data Exchange (ETDEWEB)
Arinilhaq,; Widita, Rena [Department of Physics, Nuclear Physics and Biophysics Research Group, Institut Teknologi Bandung (Indonesia)
2014-09-30
Optical Coherence Tomography is often used in medical image acquisition to diagnose that change due easy to use and low price. Unfortunately, this type of examination produces a two-dimensional retinal image of the point of acquisition. Therefore, this study developed a method that combines and reconstruct 2-dimensional retinal images into three-dimensional images to display volumetric macular accurately. The system is built with three main stages: data acquisition, data extraction and 3-dimensional reconstruction. At data acquisition step, Optical Coherence Tomography produced six *.jpg images of each patient were further extracted with MATLAB 2010a software into six one-dimensional arrays. The six arrays are combined into a 3-dimensional matrix using a kriging interpolation method with SURFER9 resulting 3-dimensional graphics of macula. Finally, system provides three-dimensional color graphs based on the data distribution normal macula. The reconstruction system which has been designed produces three-dimensional images with size of 481 × 481 × h (retinal thickness) pixels.
Institute of Scientific and Technical Information of China (English)
Divya Udayan J; HyungSeok KIM; Jee-In KIM
2015-01-01
The objective of this research is the rapid reconstruction of ancient buildings of historical importance using a single image. The key idea of our approach is to reduce the infi nite solutions that might otherwise arise when recovering a 3D geometry from 2D photographs. The main outcome of our research shows that the proposed methodology can be used to reconstruct ancient monuments for use as proxies for digital effects in applications such as tourism, games, and entertainment, which do not require very accurate modeling. In this article, we consider the reconstruction of ancient Mughal architecture including the Taj Mahal. We propose a modeling pipeline that makes an easy reconstruction possible using a single photograph taken from a single view, without the need to create complex point clouds from multiple images or the use of laser scanners. First, an initial model is automatically reconstructed using locally fi tted planar primitives along with their boundary polygons and the adjacency relation among parts of the polygons. This approach is faster and more accurate than creating a model from scratch because the initial reconstruction phase provides a set of structural information together with the adjacency relation, which makes it possible to estimate the approximate depth of the entire structural monument. Next, we use manual extrapolation and editing techniques with modeling software to assemble and adjust different 3D components of the model. Thus, this research opens up the opportunity for the present generation to experience remote sites of architectural and cultural importance through virtual worlds and real-time mobile applications. Variations of a recreated 3D monument to represent an amalgam of various cultures are targeted for future work.
Multiframe image point matching and 3-d surface reconstruction.
Tsai, R Y
1983-02-01
This paper presents two new methods, the Joint Moment Method (JMM) and the Window Variance Method (WVM), for image matching and 3-D object surface reconstruction using multiple perspective views. The viewing positions and orientations for these perspective views are known a priori, as is usually the case for such applications as robotics and industrial vision as well as close range photogrammetry. Like the conventional two-frame correlation method, the JMM and WVM require finding the extrema of 1-D curves, which are proved to theoretically approach a delta function exponentially as the number of frames increases for the JMM and are much sharper than the two-frame correlation function for both the JMM and the WVM, even when the image point to be matched cannot be easily distinguished from some of the other points. The theoretical findings have been supported by simulations. It is also proved that JMM and WVM are not sensitive to certain radiometric effects. If the same window size is used, the computational complexity for the proposed methods is about n - 1 times that for the two-frame method where n is the number of frames. Simulation results show that the JMM and WVM require smaller windows than the two-frame correlation method with better accuracy, and therefore may even be more computationally feasible than the latter since the computational complexity increases quadratically as a function of the window size.
Directory of Open Access Journals (Sweden)
Saumya Tiwari
Full Text Available Rejection is a common problem after cardiac transplants leading to significant number of adverse events and deaths, particularly in the first year of transplantation. The gold standard to identify rejection is endomyocardial biopsy. This technique is complex, cumbersome and requires a lot of expertise in the correct interpretation of stained biopsy sections. Traditional histopathology cannot be used actively or quickly during cardiac interventions or surgery. Our objective was to develop a stain-less approach using an emerging technology, Fourier transform infrared (FT-IR spectroscopic imaging to identify different components of cardiac tissue by their chemical and molecular basis aided by computer recognition, rather than by visual examination using optical microscopy. We studied this technique in assessment of cardiac transplant rejection to evaluate efficacy in an example of complex cardiovascular pathology. We recorded data from human cardiac transplant patients' biopsies, used a Bayesian classification protocol and developed a visualization scheme to observe chemical differences without the need of stains or human supervision. Using receiver operating characteristic curves, we observed probabilities of detection greater than 95% for four out of five histological classes at 10% probability of false alarm at the cellular level while correctly identifying samples with the hallmarks of the immune response in all cases. The efficacy of manual examination can be significantly increased by observing the inherent biochemical changes in tissues, which enables us to achieve greater diagnostic confidence in an automated, label-free manner. We developed a computational pathology system that gives high contrast images and seems superior to traditional staining procedures. This study is a prelude to the development of real time in situ imaging systems, which can assist interventionists and surgeons actively during procedures.
A Compton scattering image reconstruction algorithm based on total variation minimization
Institute of Scientific and Technical Information of China (English)
Li Shou-Peng; Wang Lin-Yuan; Yan Bin; Li Lei; Liu Yong-Jun
2012-01-01
Compton scattering imaging is a novel radiation imaging method using scattered photons.Its main characteristics are detectors that do not have to be on the opposite side of the source,so avoiding the rotation process.The reconstruction problem of Compton scattering imaging is the inverse problem to solve electron densities from nonlinear equations,which is ill-posed.This means the solution exhibits instability and sensitivity to noise or erroneous measurements.Using the theory for reconstruction of sparse images,a reconstruction algorithm based on total variation minimization is proposed.The reconstruction problem is described as an optimization problem with nonlinear data-consistency constraint.The simulated results show that the proposed algorithm could reduce reconstruction error and improve image quality,especially when there are not enough measurements.
High Resolution Image Reconstruction Method for a Double-plane PET System with Changeable Spacing
Gu, Xiao-Yue; Li, Lin; Yin, Peng-Fei; Shang, Lei-Min; Yun, Ming-Kai; Lu, Zhen-Rui; Huang, Xian-Chao; Wei, Long
2015-01-01
Positron Emission Mammography (PEM) imaging systems with the ability in detection of millimeter-sized tumors were developed in recent years. And some of them have been well used in clinical applications. In consideration of biopsy application, a double-plane detector configuration is practical for the convenience of breast immobilization. However, the serious blurring effect in the double-plane system with changeable spacing for different breast size should be studied. Methods: We study a high resolution reconstruction method applicable for a double-plane PET system with a changeable detector spacing. Geometric and blurring components should be calculated at real time for different detector distance. Accurate geometric sensitivity is obtained with a tube area model. Resolution recovery is achieved by estimating blurring effects derived from simulated single gamma response information. Results: The results show that the new geometric modeling gives a more finite and smooth sensitivity weight in double-plane sy...
Singh, Gurmeet; Raj, Ashish; Kressler, Bryan; Nguyen, Thanh D.; Spincemaille, Pascal; Zabih, Ramin; Wang, Yi
2010-01-01
Among recent parallel MR imaging reconstruction advances, a Bayesian method called Edge-preserving Parallel Imaging with GRAph cut Minimization (EPIGRAM) has been demonstrated to significantly improve signal to noise ratio (SNR) compared to conventional regularized sensitivity encoding (SENSE) method. However, EPIGRAM requires a large number of iterations in proportion to the number of intensity labels in the image, making it computationally expensive for high dynamic range images. The objective of this study is to develop a Fast EPIGRAM reconstruction based on the efficient binary jump move algorithm that provides a logarithmic reduction in reconstruction time while maintaining image quality. Preliminary in vivo validation of the proposed algorithm is presented for 2D cardiac cine MR imaging and 3D coronary MR angiography at acceleration factors of 2-4. Fast EPIGRAM was found to provide similar image quality to EPIGRAM and maintain the previously reported SNR improvement over regularized SENSE, while reducing EPIGRAM reconstruction time by 25-50 times. PMID:20939095
Müller, K; Maier, A K; Schwemmer, C; Lauritsch, G; De Buck, S; Wielandts, J-Y; Hornegger, J; Fahrig, R
2014-06-21
The acquisition of data for cardiac imaging using a C-arm computed tomography system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable three-dimensional (3D)/3D registration performed on initial 3D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3D images. In this paper, the sensitivity of the 3D/3D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing combined with the improved total variation algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical
Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification
Zhu, Xiaofeng
2015-05-28
This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple visual features, the MMKR first maps them into a high-dimensional space, e.g., a reproducing kernel Hilbert space (RKHS), where test images are then linearly reconstructed by some representative training images, rather than all of them. Furthermore a classification rule is proposed to classify test images. Experimental results on real datasets show the effectiveness of the proposed MMKR while comparing to state-of-the-art algorithms.
Rahmat, Mohd Fua'ad; Isa, Mohd Daud; Rahim, Ruzairi Abdul; Hussin, Tengku Ahmad Raja
2009-01-01
Electrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image of materials being conveyed based on data measured by an electrodynamics sensor installed around the pipe. Image reconstruction in electrical charge tomography is vital and has not been widely studied before. Three methods have been introduced before, namely the linear back projection method, the filtered back projection method and the least square method. These methods normally face ill-posed problems and their solutions are unstable and inaccurate. In order to ensure the stability and accuracy, a special solution should be applied to obtain a meaningful image reconstruction result. In this paper, a new image reconstruction method - Least squares with regularization (LSR) will be introduced to reconstruct the image of material in a gravity mode conveyor pipeline for electrical charge tomography. Numerical analysis results based on simulation data indicated that this algorithm efficiently overcomes the numerical instability. The results show that the accuracy of the reconstruction images obtained using the proposed algorithm was enhanced and similar to the image captured by a CCD Camera. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.
High resolution image reconstruction method for a double-plane PET system with changeable spacing
Gu, Xiao-Yue; Zhou, Wei; Li, Lin; Wei, Long; Yin, Peng-Fei; Shang, Lei-Min; Yun, Ming-Kai; Lu, Zhen-Rui; Huang, Xian-Chao
2016-05-01
Breast-dedicated positron emission tomography (PET) imaging techniques have been developed in recent years. Their capacities to detect millimeter-sized breast tumors have been the subject of many studies. Some of them have been confirmed with good results in clinical applications. With regard to biopsy application, a double-plane detector arrangement is practicable, as it offers the convenience of breast immobilization. However, the serious blurring effect of the double-plane PET, with changeable spacing for different breast sizes, should be studied. We investigated a high resolution reconstruction method applicable for a double-plane PET. The distance between the detector planes is changeable. Geometric and blurring components were calculated in real-time for different detector distances, and accurate geometric sensitivity was obtained with a new tube area model. Resolution recovery was achieved by estimating blurring effects derived from simulated single gamma response information. The results showed that the new geometric modeling gave a more finite and smooth sensitivity weight in the double-plane PET. The blurring component yielded contrast recovery levels that could not be reached without blurring modeling, and improved visual recovery of the smallest spheres and better delineation of the structures in the reconstructed images were achieved with the blurring component. Statistical noise had lower variance at the voxel level with blurring modeling at matched resolution, compared to without blurring modeling. In distance-changeable double-plane PET, finite resolution modeling during reconstruction achieved resolution recovery, without noise amplification. Supported by Knowledge Innovation Project of The Chinese Academy of Sciences (KJCX2-EW-N06)
The research of Digital Holographic Object Wave Field Reconstruction in Image and Object Space
Institute of Scientific and Technical Information of China (English)
LI Jun-Chang; PENG Zu-Jie; FU Yun-Chang
2011-01-01
@@ For conveniently detecting objects of different sizes using digital holography, usual measurements employ the object wave transformed by an optical system with different magnifications to fit charge coupled devices (CCDs), then the object field reconstruction involves the diffraction calculation of the optic wave passing through the optical system.We propose two methods to reconstruct the object field.The one is that, when the object is imaging in an image space in which we reconstruct the image of the object field, the object field can be expressed according to the object-image relationship.The other is that, when the object field reaching CCD is imaged in an object space in which we reconstruct the object field, the optical system is described by introducing matrix optics in this paper.The reconstruction formulae which easily use classic diffraction integral are derived.Finally, experimental verifications are also accomplished.%For conveniently detecting objects of different sizes using digital holography, usual measurements employ the object wave transformed by an optical system with different magnifications to fit charge coupled devices (CCDs), then the object Reid reconstruction involves the diffraction calculation of the optic wave passing through the optical system. We propose two methods to reconstruct the object field. The one is that, when the object is imaging in an image space in which we reconstruct the image of the object field, the object field can be expressed according to the object-image relationship. The other is that, when the object field reaching CCD is imaged in an object space in which we reconstruct the object field, the optical system is described by introducing matrix optics in this paper. The reconstruction formulae which easily use classic diffraction integral are derived. Finally, experimental verifications are also accomplished.
Jeong, Youngmo; Kim, Jonghyun; Yeom, Jiwoon; Lee, Chang-Kun; Lee, Byoungho
2015-12-10
In this paper, we develop a real-time depth controllable integral imaging system. With a high-frame-rate camera and a focus controllable lens, light fields from various depth ranges can be captured. According to the image plane of the light field camera, the objects in virtual and real space are recorded simultaneously. The captured light field information is converted to the elemental image in real time without pseudoscopic problems. In addition, we derive characteristics and limitations of the light field camera as a 3D broadcasting capturing device with precise geometry optics. With further analysis, the implemented system provides more accurate light fields than existing devices without depth distortion. We adapt an f-number matching method at the capture and display stage to record a more exact light field and solve depth distortion, respectively. The algorithm allows the users to adjust the pixel mapping structure of the reconstructed 3D image in real time. The proposed method presents a possibility of a handheld real-time 3D broadcasting system in a cheaper and more applicable way as compared to the previous methods.
Color image super-resolution reconstruction based on POCS with edge preserving
Wang, Rui; Liang, Ying; Liang, Yu
2015-10-01
A color image super-resolution (SR) reconstruction based on an improved Projection onto Convex Sets (POCS) in YCbCr space is proposed. Compared with other methods, the POCS method is more intuitive and generally simple to implement. However, conventional POCS algorithm is strict to the accuracy of movement estimation and it is not conducive to the resumption of the edge and details of images. Addressed to these two problems, we on one hand improve the LOG operator to detect edges with the directions of +/-0°, +/-45°, +/-90°, +/-135° in order to inhibit the edge degradation. Then, by using the edge information, we proposed a self-adaptive edge-directed interpolation and a modified adaptive direction PSF to construct a reference image as well as to reduce the edge oscillation when revising the reference respectively. On the other hand, instead of block-matching, the Speeded up Robust Feature (SURF) matching algorithm, which can accurately extract the feature points with invariant to affine transform, rotation, scale, illumination changes, are utilized to improve the robustness and real-time in motion estimation. The performance of the proposed approach has been tested on several images and the obtained results demonstrate that it is competitive or rather better in quality and efficiency in comparison with the traditional POCS.
On multigrid methods for image reconstruction from projections
Energy Technology Data Exchange (ETDEWEB)
Henson, V.E.; Robinson, B.T. [Naval Postgraduate School, Monterey, CA (United States); Limber, M. [Simon Fraser Univ., Burnaby, British Columbia (Canada)
1994-12-31
The sampled Radon transform of a 2D function can be represented as a continuous linear map R : L{sup 1} {yields} R{sup N}. The image reconstruction problem is: given a vector b {element_of} R{sup N}, find an image (or density function) u(x, y) such that Ru = b. Since in general there are infinitely many solutions, the authors pick the solution with minimal 2-norm. Numerous proposals have been made regarding how best to discretize this problem. One can, for example, select a set of functions {phi}{sub j} that span a particular subspace {Omega} {contained_in} L{sup 1}, and model R : {Omega} {yields} R{sup N}. The subspace {Omega} may be chosen as a member of a sequence of subspaces whose limit is dense in L{sup 1}. One approach to the choice of {Omega} gives rise to a natural pixel discretization of the image space. Two possible choices of the set {phi}{sub j} are the set of characteristic functions of finite-width `strips` representing energy transmission paths and the set of intersections of such strips. The authors have studied the eigenstructure of the matrices B resulting from these choices and the effect of applying a Gauss-Seidel iteration to the problem Bw = b. There exists a near null space into which the error vectors migrate with iteration, after which Gauss-Seidel iteration stalls. The authors attempt to accelerate convergence via a multilevel scheme, based on the principles of McCormick`s Multilevel Projection Method (PML). Coarsening is achieved by thickening the rays which results in a much smaller discretization of an optimal grid, and a halving of the number of variables. This approach satisfies all the requirements of the PML scheme. They have observed that a multilevel approach based on this idea accelerates convergence at least to the point where noise in the data dominates.
The Performance Evaluation of Multi-Image 3d Reconstruction Software with Different Sensors
Mousavi, V.; Khosravi, M.; Ahmadi, M.; Noori, N.; Naveh, A. Hosseini; Varshosaz, M.
2015-12-01
Today, multi-image 3D reconstruction is an active research field and generating three dimensional model of the objects is one the most discussed issues in Photogrammetry and Computer Vision that can be accomplished using range-based or image-based methods. Very accurate and dense point clouds generated by range-based methods such as structured light systems and laser scanners has introduced them as reliable tools in the industry. Image-based 3D digitization methodologies offer the option of reconstructing an object by a set of unordered images that depict it from different viewpoints. As their hardware requirements are narrowed down to a digital camera and a computer system, they compose an attractive 3D digitization approach, consequently, although range-based methods are generally very accurate, image-based methods are low-cost and can be easily used by non-professional users. One of the factors affecting the accuracy of the obtained model in image-based methods is the software and algorithm used to generate three dimensional model. These algorithms are provided in the form of commercial software, open source and web-based services. Another important factor in the accuracy of the obtained model is the type of sensor used. Due to availability of mobile sensors to the public, popularity of professional sensors and the advent of stereo sensors, a comparison of these three sensors plays an effective role in evaluating and finding the optimized method to generate three-dimensional models. Lots of research has been accomplished to identify a suitable software and algorithm to achieve an accurate and complete model, however little attention is paid to the type of sensors used and its effects on the quality of the final model. The purpose of this paper is deliberation and the introduction of an appropriate combination of a sensor and software to provide a complete model with the highest accuracy. To do this, different software, used in previous studies, were compared and
Directory of Open Access Journals (Sweden)
Christian Schou Oxvig
2014-10-01
Full Text Available Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also provides researchers in compressed sensing with a selection of algorithms for reconstructing undersampled general images, and offers a consistent and rigorous way to efficiently evaluate the researchers own developed reconstruction algorithms in terms of phase transitions. The package also serves as a convenient platform for researchers in compressed sensing aiming at obtaining a high degree of reproducibility of their research.
Energy Technology Data Exchange (ETDEWEB)
Izumi, N; Turner, R; Barbee, T; Koch, J; Welser, L; Mansini, R
2004-04-15
We have developed a software package for image reconstruction of a multiple monochromatic x-ray imaging diagnostics (MMI) for diagnostic of inertial conferment fusion capsules. The MMI consists of a pinhole array, a multi-layer Bragg mirror, and a charge injection device image detector (CID). The pinhole array projects {approx}500 sub-images onto the CID after reflection off the multi-layer Bragg mirror. The obtained raw images have continuum spectral dispersion on its vertical axis. For systematic analysis, a computer-aided reconstruction of the quasi-monochromatic image is essential.
Benincasa, Anne B.; Clements, Logan W.; Herrell, S. Duke; Galloway, Robert L.
2008-01-01
A notable complication of applying current image-guided surgery techniques of soft tissue to kidney resections (nephrectomies) is the limited field of view of the intraoperative kidney surface. This limited view constrains the ability to obtain a sufficiently geometrically descriptive surface for accurate surface-based registrations. The authors examined the effects of the limited view by using two orientations of a kidney phantom to model typical laparoscopic and open partial nephrectomy views. Point-based registrations, using either rigidly attached markers or anatomical landmarks as fiducials, served as initial alignments for surface-based registrations. Laser range scanner (LRS) obtained surfaces were registered to the phantom’s image surface using a rigid iterative closest point algorithm. Subsets of each orientation’s LRS surface were used in a robustness test to determine which parts of the surface yield the most accurate registrations. Results suggest that obtaining accurate registrations is a function of the percentage of the total surface and of geometric surface properties, such as curvature. Approximately 28% of the total surface is required regardless of the location of that surface subset. However, that percentage decreases when the surface subset contains information from opposite ends of the surface and∕or unique anatomical features, such as the renal artery and vein. PMID:18841875
A nonlinear fuzzy assisted image reconstruction algorithm for electrical capacitance tomography.
Deabes, W A; Abdelrahman, M A
2010-01-01
A nonlinear method based on a Fuzzy Inference System (FIS) to improve the images obtained from Electrical Capacitance Tomography (ECT) is proposed. Estimation of the molten metal characteristic in the Lost Foam Casting (LFC) process is a novel application in the area of the tomography process. The convergence rate of iterative image reconstruction techniques is dependent on the accuracy of the first image. The possibility of the existence of metal in the first image is computed by the proposed fuzzy system. This first image is passed to an iterative image reconstruction technique to get more precise images and to speed up the convergence rate. The proposed technique is able to detect the position of the metal on the periphery of the imaging area by using just eight capacitive sensors. The final results demonstrate the advantage of using the FIS compared to the performance of the iterative back projection image reconstruction technique.
Iterative reconstruction in image space (IRIS) in cardiac computed tomography: initial experience.
Bittencourt, Márcio Sommer; Schmidt, Bernhard; Seltmann, Martin; Muschiol, Gerd; Ropers, Dieter; Daniel, Werner Günther; Achenbach, Stephan
2011-10-01
Improvements in image quality in cardiac computed tomography may be achieved through iterative image reconstruction techniques. We evaluated the ability of "Iterative Reconstruction in Image Space" (IRIS) reconstruction to reduce image noise and improve subjective image quality. 55 consecutive patients undergoing coronary CT angiography to rule out coronary artery stenosis were included. A dual source CT system and standard protocols were used. Images were reconstructed using standard filtered back projection and IRIS. Image noise, attenuation within the coronary arteries, contrast, signal to noise and contrast to noise parameters as well as subjective classification of image quality (using a scale with four categories) were evaluated and compared between the two image reconstruction protocols. Subjective image quality (2.8 ± 0.4 in filtered back projection and 2.8 ± 0.4 in iterative reconstruction) and the number of "evaluable" segments per patient 14.0 ± 1.2 in filtered back projection and 14.1 ± 1.1 in iterative reconstruction) were not significant different between the two methods. However iterative reconstruction had a lower image noise (22.6 ± 4.5 HU vs. 28.6 ± 5.1 HU) and higher signal to noise and image to noise ratios in the proximal coronary arteries. IRIS reduces image noise and contrast-to-noise ratio in coronary CT angiography, thus providing potential for reducing radiation exposure.
Sato, T; Norton, S J; Linzer, M; Ikeda, O; Hirama, M
1981-02-01
An iterative technique is proposed for improving the quality of reconstructions from projections when the number of projections is small or the angular range of projections is limited. The technique consists of transforming repeatedly between image and transform spaces and applying a priori object information at each iteration. The approach is a generalization of the Gerchberg-Papoulis algorithm, a technique for extrapolating in the Fourier domain by imposing a space-limiting constraint on the object in the spatial domain. A priori object data that may be applied, in addition to truncating the image beyond the known boundaries of the object, include limiting the maximum range of variation of the physical parameter being imaged. The results of computer simulations show clearly how the process of forcing the image to conform to a priori object data reduces artifacts arising from limited data available in the Fourier domain.
Ning, Nannan; Tian, Jie; Liu, Xia; Deng, Kexin; Wu, Ping; Wang, Bo; Wang, Kun; Ma, Xibo
2014-02-01
In mathematics, optical molecular imaging including bioluminescence tomography (BLT), fluorescence tomography (FMT) and Cerenkov luminescence tomography (CLT) are concerned with a similar inverse source problem. They all involve the reconstruction of the 3D location of a single/multiple internal luminescent/fluorescent sources based on 3D surface flux distribution. To achieve that, an accurate fusion between 2D luminescent/fluorescent images and 3D structural images that may be acquired form micro-CT, MRI or beam scanning is extremely critical. However, the absence of a universal method that can effectively convert 2D optical information into 3D makes the accurate fusion challengeable. In this study, to improve the fusion accuracy, a new fusion method for dual-modality tomography (luminescence/fluorescence and micro-CT) based on natural light surface reconstruction (NLSR) and iterated closest point (ICP) was presented. It consisted of Octree structure, exact visual hull from marching cubes and ICP. Different from conventional limited projection methods, it is 360° free-space registration, and utilizes more luminescence/fluorescence distribution information from unlimited multi-orientation 2D optical images. A mouse mimicking phantom (one XPM-2 Phantom Light Source, XENOGEN Corporation) and an in-vivo BALB/C mouse with implanted one luminescent light source were used to evaluate the performance of the new fusion method. Compared with conventional fusion methods, the average error of preset markers was improved by 0.3 and 0.2 pixels from the new method, respectively. After running the same 3D internal light source reconstruction algorithm of the BALB/C mouse, the distance error between the actual and reconstructed internal source was decreased by 0.19 mm.
Institute of Scientific and Technical Information of China (English)
Zhiliang Zhou; Yan Yuan; Xiangli Bin; Qian Wang
2011-01-01
@@ Synthetic aperture integral imaging provides the ability to reconstruct partially occluded objects from multi-view images.However, the reconstructed images suffer from degraded contrast due to the super-imposition of foreground defocus blur.We propose an algorithm to remove foreground occlusions before reconstructing backgrounds.Occlusions are identified by estimating the color variance on elemental im-ages and then deleting it in the final synthetic image.We demonstrate the superiority of our method by presenting experimental results as well as comparing our method with other approaches.%Synthetic aperture integral imaging provides the ability to reconstruct partially occluded objects from multi-view images. However, the reconstructed images suffer from degraded contrast due to the superimposition of foreground defocus blur. We propose an algorithm to remove foreground occlusions before reconstructing backgrounds. Occlusions are identified by estimating the color variance on elemental images and then deleting it in the final synthetic image. We demonstrate the superiority of our method by presenting experimental results as well as comparing our method with other approaches.
Wang, Kun; Kao, Yu-Jiun; Chou, Cheng-Ying; Oraevsky, Alexander A; Anastasio, Mark A; 10.1118/1.4774361
2013-01-01
Purpose: Optoacoustic tomography (OAT) is inherently a three-dimensional (3D) inverse problem. However, most studies of OAT image reconstruction still employ two-dimensional (2D) imaging models. One important reason is because 3D image reconstruction is computationally burdensome. The aim of this work is to accelerate existing image reconstruction algorithms for 3D OAT by use of parallel programming techniques. Methods: Parallelization strategies are proposed to accelerate a filtered backprojection (FBP) algorithm and two different pairs of projection/backprojection operations that correspond to two different numerical imaging models. The algorithms are designed to fully exploit the parallel computing power of graphic processing units (GPUs). In order to evaluate the parallelization strategies for the projection/backprojection pairs, an iterative image reconstruction algorithm is implemented. Computer-simulation and experimental studies are conducted to investigate the computational efficiency and numerical a...
Choi, Jong-ryul; Kim, Donghyun
2012-10-01
We investigate improved image reconstruction of structured light illumination for high-resolution imaging of three-dimensional (3D) cell-based assays. For proof of concept, an in situ fluorescence optical detection system was built with a digital micromirror device as a spatial light modulator, for which phase and tilting angle in a grid pattern were varied to implement specific image reconstruction schemes. Subtractive reconstruction algorithms based on structured light illumination were used to acquire images of fluorescent microbeads deposited as a two-dimensional monolayer or in 3D alginate matrix. We have confirmed that an optical subtraction algorithm improves axial and lateral resolution by effectively removing out-of-focus fluorescence. The results suggest that subtractive image reconstruction can be useful for structured illumination microscopy of broad types of cell-based assays with high image resolution.
Li, Lei; Wang, Linyuan; Yan, Bin; Zhang, Hanming; Zheng, Zhizhong; Zhang, Wenkun; Lu, Wanli; Hu, Guoen
2016-01-01
Dual-energy computed tomography (DECT) has shown great potential and promising applications in advanced imaging fields for its capabilities of material decomposition. However, image reconstructions and decompositions under sparse views dataset suffers severely from multi factors, such as insufficiencies of data, appearances of noise, and inconsistencies of observations. Under sparse views, conventional filtered back-projection type reconstruction methods fails to provide CT images with satisfying quality. Moreover, direct image decomposition is unstable and meet with noise boost even with full views dataset. This paper proposes an iterative image reconstruction algorithm and a practical image domain decomposition method for DECT. On one hand, the reconstruction algorithm is formulated as an optimization problem, which containing total variation regularization term and data fidelity term. The alternating direction method is utilized to design the corresponding algorithm which shows faster convergence speed com...
Robust framework for PET image reconstruction incorporating system and measurement uncertainties.
Directory of Open Access Journals (Sweden)
Huafeng Liu
Full Text Available In Positron Emission Tomography (PET, an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts.
Ham, Woonchul; Song, Chulgyu; Lee, Kangsan; Roh, Seungkuk
2016-05-01
In this paper, we propose a new image reconstruction algorithm considering the geometric information of acoustic sources and senor detector and review the two-step reconstruction algorithm which was previously proposed based on the geometrical information of ROI(region of interest) considering the finite size of acoustic sensor element. In a new image reconstruction algorithm, not only mathematical analysis is very simple but also its software implementation is very easy because we don't need to use the FFT. We verify the effectiveness of the proposed reconstruction algorithm by showing the simulation results by using Matlab k-wave toolkit.
Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan
2016-06-01
Lens-free holographic microscopy can achieve wide-field imaging in a cost-effective and field-portable setup, making it a promising technique for point-of-care and telepathology applications. However, due to relatively narrow-band sources used in holographic microscopy, conventional colorization methods that use images reconstructed at discrete wavelengths, corresponding to e.g., red (R), green (G) and blue (B) channels, are subject to color artifacts. Furthermore, these existing RGB colorization methods do not match the chromatic perception of human vision. Here we present a high-color-fidelity and high-resolution imaging method, termed “digital color fusion microscopy” (DCFM), which fuses a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform-based colorization method. We demonstrate accurate color reproduction of DCFM by imaging stained tissue sections. In particular we show that a lens-free holographic microscope in combination with a cost-effective mobile-phone-based microscope can generate color images of specimens, performing very close to a high numerical-aperture (NA) benchtop microscope that is corrected for color distortions and chromatic aberrations, also matching the chromatic response of human vision. This method can be useful for wide-field imaging needs in telepathology applications and in resource-limited settings, where whole-slide scanning microscopy systems are not available.
Large-Scale Multi-Resolution Representations for Accurate Interactive Image and Volume Operations
Sicat, Ronell B.
2015-11-25
and voxel footprints in input images and volumes. We show that the continuous pdfs encoded in the sparse pdf map representation enable accurate multi-resolution non-linear image operations on gigapixel images. Similarly, we show that sparse pdf volumes enable more consistent multi-resolution volume rendering compared to standard approaches, on both artificial and real world large-scale volumes. The supplementary videos demonstrate our results. In the standard approach, users heavily rely on panning and zooming interactions to navigate the data within the limits of their display devices. However, panning across the whole spatial domain and zooming across all resolution levels of large-scale images to search for interesting regions is not practical. Assisted exploration techniques allow users to quickly narrow down millions to billions of possible regions to a more manageable number for further inspection. However, existing approaches are not fully user-driven because they typically already prescribe what being of interest means. To address this, we introduce the patch sets representation for large-scale images. Patches inside a patch set are grouped and encoded according to similarity via a permutohedral lattice (p-lattice) in a user-defined feature space. Fast set operations on p-lattices facilitate patch set queries that enable users to describe what is interesting. In addition, we introduce an exploration framework—GigaPatchExplorer—for patch set-based image exploration. We show that patch sets in our framework are useful for a variety of user-driven exploration tasks in gigapixel images and whole collections thereof.
Chou, C. S.; Tang, Y. P.; Chu, F. S.; Huang, W. C.; Liu, R. G.; Gau, T. S.
2012-03-01
Calibration of mask images on wafer becomes more important as features shrink. Two major types of metrology have been commonly adopted. One is to measure the mask image with scanning electron microscope (SEM) to obtain the contours on mask and then simulate the wafer image with optical simulator. The other is to use an optical imaging tool Aerial Image Measurement System (AIMSTM) to emulate the image on wafer. However, the SEM method is indirect. It just gathers planar contours on a mask with no consideration of optical characteristics such as 3D topography structures. Hence, the image on wafer is not predicted precisely. Though the AIMSTM method can be used to directly measure the intensity at the near field of a mask but the image measured this way is not quite the same as that on the wafer due to reflections and refractions in the films on wafer. Here, a new approach is proposed to emulate the image on wafer more precisely. The behavior of plane waves with different oblique angles is well known inside and between planar film stacks. In an optical microscope imaging system, plane waves can be extracted from the pupil plane with a coherent point source of illumination. Once plane waves with a specific coherent illumination are analyzed, the partially coherent component of waves could be reconstructed with a proper transfer function, which includes lens aberration, polarization, reflection and refraction in films. It is a new method that we can transfer near light field of a mask into an image on wafer without the disadvantages of indirect SEM measurement such as neglecting effects of mask topography, reflections and refractions in the wafer film stacks. Furthermore, with this precise latent image, a separated resist model also becomes more achievable.
3-D Reconstruction From 2-D Radiographic Images and Its Application to Clinical Veterinary Medicine
Hamamoto, Kazuhiko; Sato, Motoyoshi
3D imaging technique is very important and indispensable in diagnosis. The main stream of the technique is one in which 3D image is reconstructed from a set of slice images, such as X-ray CT and MRI. However, these systems require large space and high costs. On the other hand, a low cost and small size 3D imaging system is needed in clinical veterinary medicine, for example, in the case of diagnosis in X-ray car or pasture area. We propose a novel 3D imaging technique using 2-D X-ray radiographic images. This system can be realized by cheaper system than X-ray CT and enables to get 3D image in X-ray car or portable X-ray equipment. In this paper, a 3D visualization technique from 2-D radiographic images is proposed and several reconstructions are shown. These reconstructions are evaluated by veterinarians.
Zooming in: high resolution 3D reconstruction of differently stained histological whole slide images
Lotz, Johannes; Berger, Judith; Müller, Benedikt; Breuhahn, Kai; Grabe, Niels; Heldmann, Stefan; Homeyer, André; Lahrmann, Bernd; Laue, Hendrik; Olesch, Janine; Schwier, Michael; Sedlaczek, Oliver; Warth, Arne
2014-03-01
Much insight into metabolic interactions, tissue growth, and tissue organization can be gained by analyzing differently stained histological serial sections. One opportunity unavailable to classic histology is three-dimensional (3D) examination and computer aided analysis of tissue samples. In this case, registration is needed to reestablish spatial correspondence between adjacent slides that is lost during the sectioning process. Furthermore, the sectioning introduces various distortions like cuts, folding, tearing, and local deformations to the tissue, which need to be corrected in order to exploit the additional information arising from the analysis of neighboring slide images. In this paper we present a novel image registration based method for reconstructing a 3D tissue block implementing a zooming strategy around a user-defined point of interest. We efficiently align consecutive slides at increasingly fine resolution up to cell level. We use a two-step approach, where after a macroscopic, coarse alignment of the slides as preprocessing, a nonlinear, elastic registration is performed to correct local, non-uniform deformations. Being driven by the optimization of the normalized gradient field (NGF) distance measure, our method is suitable for differently stained and thus multi-modal slides. We applied our method to ultra thin serial sections (2 μm) of a human lung tumor. In total 170 slides, stained alternately with four different stains, have been registered. Thorough visual inspection of virtual cuts through the reconstructed block perpendicular to the cutting plane shows accurate alignment of vessels and other tissue structures. This observation is confirmed by a quantitative analysis. Using nonlinear image registration, our method is able to correct locally varying deformations in tissue structures and exceeds the limitations of globally linear transformations.
Thériault Lauzier, Pascal; Tang, Jie; Chen, Guang-Hong
2012-03-01
Myocardial perfusion scans are an important tool in the assessment of myocardial viability following an infarction. Cardiac perfusion analysis using CT datasets is limited by the presence of so-called partial scan artifacts. These artifacts are due to variations in beam hardening and scatter between different short-scan angular ranges. In this research, another angular range dependent effect is investigated: non-uniform noise spatial distribution. Images reconstructed using filtered backprojection (FBP) are subject to this effect. Statistical image reconstruction (SIR) is proposed as a potential solution. A numerical phantom with added Poisson noise was simulated and two swines were scanned in vivo to study the effect of FBP and SIR on the spatial uniformity of the noise distribution. It was demonstrated that images reconstructed using FBP often show variations in noise on the order of 50% between different time frames. This variation is mitigated to about 10% using SIR. The noise level is also reduced by a factor of 2 in SIR images. Finally, it is demonstrated that the measurement of quantitative perfusion metrics are generally more accurate when SIR is used instead of FBP.
Song, Xizi; Xu, Yanbin; Dong, Feng
2016-11-01
A new image reconstruction framework based on boundary voltages is presented for ultrasound modulated electrical impedance tomography (UMEIT). Combining the electric and acoustic modalities, UMEIT reconstructs the conductivity distribution with more measurements with position information. The proposed image reconstruction framework begins with approximately constructing the sensitivity matrix of the imaging object with inclusion. Then the conductivity is recovered from the boundary voltages of the imaging object. To solve the nonlinear inverse problem, an optimization method is adopted and the iterative method is tested. Compared with that for electrical resistance tomography (ERT), the newly constructed sensitivity matrix is more sensitive to the inclusion, even in the center of the imaging object, and it contains more effective information about the inclusions. Finally, image reconstruction is carried out by the conjugate gradient algorithm, and results show that reconstructed images with higher quality can be obtained for UMEIT with a faster convergence rate. Both theory and image reconstruction results validate the feasibility of the proposed framework for UMEIT and confirm that UMEIT is a potential imaging technique.
Dahlke, D.; Linkiewicz, M.
2016-06-01
This paper compares two generic approaches for the reconstruction of buildings. Synthesized and real oblique and vertical aerial imagery is transformed on the one hand into a dense photogrammetric 3D point cloud and on the other hand into photogrammetric 2.5D surface models depicting a scene from different cardinal directions. One approach evaluates the 3D point cloud statistically in order to extract the hull of structures, while the other approach makes use of salient line segments in 2.5D surface models, so that the hull of 3D structures can be recovered. With orders of magnitudes more analyzed 3D points, the point cloud based approach is an order of magnitude more accurate for the synthetic dataset compared to the lower dimensioned, but therefor orders of magnitude faster, image processing based approach. For real world data the difference in accuracy between both approaches is not significant anymore. In both cases the reconstructed polyhedra supply information about their inherent semantic and can be used for subsequent and more differentiated semantic annotations through exploitation of texture information.
Identifying same-cell contours in image stacks: a key step in making 3D reconstructions.
Leung, Tony Kin Shun; Veldhuis, Jim H; Krens, S F Gabby; Heisenberg, C P; Brodland, G Wayne
2011-02-01
Identification of contours belonging to the same cell is a crucial step in the analysis of confocal stacks and other image sets in which cell outlines are visible, and it is central to the making of 3D cell reconstructions. When the cells are close packed, the contour grouping problem is more complex than that found in medical imaging, for example, because there are multiple regions of interest, the regions are not separable from each other by an identifiable background and regions cannot be distinguished by intensity differences. Here, we present an algorithm that uses three primary metrics-overlap of contour areas in adjacent images, co-linearity of the centroids of these areas across three images in a stack, and cell taper-to assign cells to groups. Decreasing thresholds are used to successively assign contours whose membership is less obvious. In a final step, remaining contours are assigned to existing groups by setting all thresholds to zero and groups having strong hour-glass shapes are partitioned. When applied to synthetic data from isotropic model aggregates, a curved model epithelium in which the long axes of the cells lie at all possible angles to the transection plane, and a confocal image stack, algorithm assignments were between 97 and 100% accurate in sets having at least four contours per cell. The algorithm is not particularly sensitive to the thresholds used, and a single set of parameters was used for all of the tests. The algorithm, which could be extended to time-lapse data, solves a key problem in the translation of image data into cell information.
Lan, Fei; Jiang, Minlin; Tao, Quan; Wei, Fanan; Li, Guangyong
2017-03-01
A Kelvin probe force microscopy (KPFM) image is sometimes difficult to interpret because it is a blurred representation of the true surface potential (SP) distribution of the materials under test. The reason for the blurring is that KPFM relies on the detection of electrostatic force, which is a long-range force compared to other surface forces. Usually, KPFM imaging model is described as the convolution of the true SP distribution of the sample with an intrinsic point spread function (PSF) of the measurement system. To restore the true SP signals from the blurred ones, the intrinsic PSF of the system is needed. In this work, we present a way to experimentally calibrate the PSF of the KPFM system. Taking the actual probe shape and experimental parameters into consideration, this calibration method leads to a more accurate PSF than the ones obtained from simulations. Moreover, a nonlinear reconstruction algorithm based on total variation (TV) regularization is applied to KPFM measurement to reverse the blurring caused by PSF during KPFM imaging process; as a result, noises are reduced and the fidelity of SP signals is improved.
SPARCO : a semi-parametric approach for image reconstruction of chromatic objects
Kluska, J; Berger, J -P; Baron, F; Lazareff, B; Bouquin, J -B Le; Monnier, J D; Soulez, F; Thiébaut, E
2014-01-01
The emergence of optical interferometers with three and more telescopes allows image reconstruction of astronomical objects at the milliarcsecond scale. However, some objects contain components with very different spectral energy distributions (SED; i.e. different temperatures), which produces strong chromatic effects on the interferograms that have to be managed with care by image reconstruction algorithms. For example, the gray approximation for the image reconstruction process results in a degraded image if the total (u, v)-coverage given by the spectral supersynthesis is used. The relative flux contribution of the central object and an extended structure changes with wavelength for different temperatures. For young stellar objects, the known characteristics of the central object (i.e., stellar SED), or even the fit of the spectral index and the relative flux ratio, can be used to model the central star while reconstructing the image of the extended structure separately. Methods. We present a new method, c...
Wu, Jiao; Liu, Fang; Jiao, L C; Wang, Xiaodong; Hou, Biao
2011-12-01
Most wavelet-based reconstruction methods of compressive sensing (CS) are developed under the independence assumption of the wavelet coefficients. However, the wavelet coefficients of images have significant statistical dependencies. Lots of multivariate prior models for the wavelet coefficients of images have been proposed and successfully applied to the image estimation problems. In this paper, the statistical structures of the wavelet coefficients are considered for CS reconstruction of images that are sparse or compressive in wavelet domain. A multivariate pursuit algorithm (MPA) based on the multivariate models is developed. Several multivariate scale mixture models are used as the prior distributions of MPA. Our method reconstructs the images by means of modeling the statistical dependencies of the wavelet coefficients in a neighborhood. The proposed algorithm based on these scale mixture models provides superior performance compared with many state-of-the-art compressive sensing reconstruction algorithms.
Efficient content-based low-altitude images correlated network and strips reconstruction
He, Haiqing; You, Qi; Chen, Xiaoyong
2017-01-01
The manual intervention method is widely used to reconstruct strips for further aerial triangulation in low-altitude photogrammetry. Clearly the method for fully automatic photogrammetric data processing is not an expected way. In this paper, we explore a content-based approach without manual intervention or external information for strips reconstruction. Feature descriptors in the local spatial patterns are extracted by SIFT to construct vocabulary tree, in which these features are encoded in terms of TF-IDF numerical statistical algorithm to generate new representation for each low-altitude image. Then images correlated network is reconstructed by similarity measure, image matching and geometric graph theory. Finally, strips are reconstructed automatically by tracing straight lines and growing adjacent images gradually. Experimental results show that the proposed approach is highly effective in automatically rearranging strips of lowaltitude images and can provide rough relative orientation for further aerial triangulation.
ADAPTIVE RECONSTRUCTION TECHNIQUE FOR THE LOST INFORMATION OF THE RECTANGULAR IMAGE AREA
Institute of Scientific and Technical Information of China (English)
Shi Rong; Li Xiaofeng; Li Zaiming
2004-01-01
The adaptive reconstruction for the lost information of the rectangular image area is very important for the robust transmission and restoration of the image. In this paper, a new reconstruction method based on the Discrete Cosine Transform (DCT) domain has been put forward. According to the low pass character of the human visual system and the energy distribution of the DCT coefficients on the rectangular boundary, the DCT coefficients of the rectangular image area are adaptively selected and recovered. After the Inverse Discrete Cosine Transform (IDCT), the lost information of the rectangular image area can be reconstructed. The experiments have demonstrated that the subjective and objective qualities of the reconstructed images are enhanced greatly than before.
Filters involving derivatives with application to reconstruction from scanned halftone images
DEFF Research Database (Denmark)
Forchhammer, Søren; Jensen, Kim S.
1995-01-01
filters are developed and applied to the problem of gray value image reconstruction from bilevel (scanned) clustered-dot halftone images, which is an application useful in the graphic arts. Reconstruction results are given, showing that reconstruction with higher resolution than the halftone grid......This paper presents a method for designing finite impulse response (FIR) filters for samples of a 2-D signal, e.g., an image, and its gradient. The filters, which are called blended filters, are decomposable in three filters, each separable in 1-D filters on subsets of the data set. Optimality...
Three-dimensional reconstruction of far and large objects using synthetic aperture integral imaging
Piao, Yongri; Xing, Luyan; Zhang, Miao; Lee, Byung-Gook
2017-01-01
In this paper, we present a three-dimensional reconstruction of far and large objects in a synthetic aperture integral imaging system. In the proposed method, the far and large size objects are recorded as a set of elemental images by using an additional Plano-concave lens in the synthetic aperture integral imaging system. Due to the use of the Plano-concave lens, the reconstruction distance can be significantly reduced. This enables us to computationally reconstruct the objects in the far-field region. Experimental results are carried out, and the feasibility of the proposed method is verified.
Noise Equivalent Counts Based Emission Image Reconstruction Algorithm of Tomographic Gamma Scanning
Wang, Ke; Feng, Wei; Han, Dong
2014-01-01
Tomographic Gamma Scanning (TGS) is a technique used to assay the nuclide distribution and radioactivity in nuclear waste drums. Both transmission and emission scans are performed in TGS and the transmission image is used for the attenuation correction in emission reconstructions. The error of the transmission image, which is not considered by the existing reconstruction algorithms, negatively affects the final results. An emission reconstruction method based on Noise Equivalent Counts (NEC) is presented. Noises from the attenuation image are concentrated to the projection data to apply the NEC Maximum-Likelihood Expectation-Maximization algorithm. Experiments are performed to verify the effectiveness of the proposed method.
Energy Technology Data Exchange (ETDEWEB)
Vaegler, Sven; Sauer, Otto [Wuerzburg Univ. (Germany). Dept. of Radiation Oncology; Stsepankou, Dzmitry; Hesser, Juergen [University Medical Center Mannheim, Mannheim (Germany). Dept. of Experimental Radiation Oncology
2015-07-01
The reduction of dose in cone beam computer tomography (CBCT) arises from the decrease of the tube current for each projection as well as from the reduction of the number of projections. In order to maintain good image quality, sophisticated image reconstruction techniques are required. The Prior Image Constrained Compressed Sensing (PICCS) incorporates prior images into the reconstruction algorithm and outperforms the widespread used Feldkamp-Davis-Kress-algorithm (FDK) when the number of projections is reduced. However, prior images that contain major variations are not appropriately considered so far in PICCS. We therefore propose the partial-PICCS (pPICCS) algorithm. This framework is a problem-specific extension of PICCS and enables the incorporation of the reliability of the prior images additionally. We assumed that the prior images are composed of areas with large and small deviations. Accordingly, a weighting matrix considered the assigned areas in the objective function. We applied our algorithm to the problem of image reconstruction from few views by simulations with a computer phantom as well as on clinical CBCT projections from a head-and-neck case. All prior images contained large local variations. The reconstructed images were compared to the reconstruction results by the FDK-algorithm, by Compressed Sensing (CS) and by PICCS. To show the gain of image quality we compared image details with the reference image and used quantitative metrics (root-mean-square error (RMSE), contrast-to-noise-ratio (CNR)). The pPICCS reconstruction framework yield images with substantially improved quality even when the number of projections was very small. The images contained less streaking, blurring and inaccurately reconstructed structures compared to the images reconstructed by FDK, CS and conventional PICCS. The increased image quality is also reflected in large RMSE differences. We proposed a modification of the original PICCS algorithm. The pPICCS algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Seung-Wan; Lee, Chang-Lae; Cho, Hyo-Min; Park, Hye-Suk; Kim, Dae-Hong; Choi, Yu-Na; Kim, Hee-Joung [Yonsei University, Wonju (Korea, Republic of)
2011-10-15
CBCT (cone-beam computed tomography) is a promising modality in many medical applications due to the properties of fast volume coverage, lower radiation dose, easy hardware implementation, and higher spatial resolution. Recently, attention is being paid to the noise and resolution relationship for CBCT. In a CBCT system, image noise and spatial resolution play very important roles in image quality. However, there have not been many works to evaluate the relationship between the image noise and the spatial resolution in CBCT. In this study, we evaluated the effects of reconstruction parameters, such as the characteristics of the filter, the number of projections, and the voxel size, on the image noise and the spatial resolution in a CBCT system. The simulated projection data of a Catphan 600 phantom were reconstructed using the FDK (Feldkamp) algorithm. To evaluate the image noise and the spatial resolution, we calculated the COV (coefficient of variation) of the attenuation coefficient and the MTF (modulation transfer function) in axial images. Five reconstruction filters, Ram-Lak, Shepp-Logan, Cosine, Hamming, and Hann, were used to reconstruct the images. Different numbers of projections for a circular scan of 360 degrees and different voxel sizes were used to reconstruct the images to evaluate their effect on image noise and spatial resolution. The image noise given by the Hann filter was the lowest and the spatial resolution given by the Ram-Lak filter was the highest. The image noise was decreased as functions of the number of projections and the voxel size. The spatial resolution was increased as a function of the number of projections and decreased as a function of the voxel size. The results of this study show the relationship between the image noise and the spatial resolution in a CBCT system and the characteristics of the reconstruction factors for trade-off between the image noise and the spatial resolution. It can also provide information of the image
Toward accurate tooth segmentation from computed tomography images using a hybrid level set model
Energy Technology Data Exchange (ETDEWEB)
Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)
2015-01-15
Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0
Yang, Alice C; Kretzler, Madison; Sudarski, Sonja; Gulani, Vikas; Seiberlich, Nicole
2016-06-01
The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.
Optimal reconstruction of natural images by small sets of Gabor filters
Van Deemter, JH; Cristobal, G
1998-01-01
Images can be reconstructed after being filtered by a Gaussian and a few Gabor filters. Several search methods for the filter parameters for a (near) optimal reconstruction are examined. At first, the search is performed on a 1-D signal which satisfies the radial spectrum of the average of natural i
Energy Technology Data Exchange (ETDEWEB)
Vidal Gimeno, V.
2012-07-01
The algebraic reconstruction methods are based on solving a system of linear equations. In a previous study, was used and showed as the PETSc library, was and is a scientific computing tool, which facilitates and enables the optimal use of a computer system in the image reconstruction process.
Benincasa, Anne B.; Clements, Logan W.; Herrell, S. Duke; Chang, Sam S.; Cookson, Michael S.; Galloway, Robert L.
2006-03-01
Currently, the removal of kidney tumor masses uses only direct or laparoscopic visualizations, resulting in prolonged procedure and recovery times and reduced clear margin. Applying current image guided surgery (IGS) techniques, as those used in liver cases, to kidney resections (nephrectomies) presents a number of complications. Most notably is the limited field of view of the intraoperative kidney surface, which constrains the ability to obtain a surface delineation that is geometrically descriptive enough to drive a surface-based registration. Two different phantom orientations were used to model the laparoscopic and traditional partial nephrectomy views. For the laparoscopic view, fiducial point sets were compiled from a CT image volume using anatomical features such as the renal artery and vein. For the traditional view, markers attached to the phantom set-up were used for fiducials and targets. The fiducial points were used to perform a point-based registration, which then served as a guide for the surface-based registration. Laser range scanner (LRS) obtained surfaces were registered to each phantom surface using a rigid iterative closest point algorithm. Subsets of each phantom's LRS surface were used in a robustness test to determine the predictability of their registrations to transform the entire surface. Results from both orientations suggest that about half of the kidney's surface needs to be obtained intraoperatively for accurate registrations between the image surface and the LRS surface, suggesting the obtained kidney surfaces were geometrically descriptive enough to perform accurate registrations. This preliminary work paves the way for further development of kidney IGS systems.
Matheoud, Roberta; Della Monica, Patrizia; Loi, Gianfranco; Vigna, Luca; Krengli, Marco; Inglese, Eugenio; Brambilla, Marco
2011-01-30
The purpose of this study was to analyze the behavior of a contouring algorithm for PET images based on adaptive thresholding depending on lesions size and target-to-background (TB) ratio under different conditions of image reconstruction parameters. Based on this analysis, the image reconstruction scheme able to maximize the goodness of fit of the thresholding algorithm has been selected. A phantom study employing spherical targets was designed to determine slice-specific threshold (TS) levels which produce accurate cross-sectional areas. A wide range of TB ratio was investigated. Multiple regression methods were used to fit the data and to construct algorithms depending both on target cross-sectional area and TB ratio, using various reconstruction schemes employing a wide range of iteration number and amount of postfiltering Gaussian smoothing. Analysis of covariance was used to test the influence of iteration number and smoothing on threshold determination. The degree of convergence of ordered-subset expectation maximization (OSEM) algorithms does not influence TS determination. Among these approaches, the OSEM at two iterations and eight subsets with a 6-8 mm post-reconstruction Gaussian three-dimensional filter provided the best fit with a coefficient of determination R² = 0.90 for cross-sectional areas ≤ 133 mm² and R² = 0.95 for cross-sectional areas > 133 mm². The amount of post-reconstruction smoothing has been directly incorporated in the adaptive thresholding algorithms. The feasibility of the method was tested in two patients with lymph node FDG accumulation and in five patients using the bladder to mimic an anatomical structure of large size and uniform uptake, with satisfactory results. Slice-specific adaptive thresholding algorithms look promising as a reproducible method for delineating PET target volumes with good accuracy.
Energy Technology Data Exchange (ETDEWEB)
Park, Yeonok; Cho, Heemoon; Je, Uikyu; Cho, Hyosung, E-mail: hscho1@yonsei.ac.kr; Park, Chulkyu; Lim, Hyunwoo; Kim, Kyuseok; Kim, Guna; Park, Soyoung; Woo, Taeho; Choi, Sungil
2015-12-21
In this work, we have developed a prototype digital breast tomosynthesis (DBT) system which mainly consists of an x-ray generator (28 kV{sub p}, 7 mA s), a CMOS-type flat-panel detector (70-μm pixel size, 230.5×339 mm{sup 2} active area), and a rotational arm to move the x-ray generator in an arc. We employed a compressed-sensing (CS)-based reconstruction algorithm, rather than a common filtered-backprojection (FBP) one, for more accurate DBT reconstruction. Here the CS is a state-of-the-art mathematical theory for solving the inverse problems, which exploits the sparsity of the image with substantially high accuracy. We evaluated the reconstruction quality in terms of the detectability, the contrast-to-noise ratio (CNR), and the slice-sensitive profile (SSP) by using the mammographic accreditation phantom (Model 015, CIRS Inc.) and compared it to the FBP-based quality. The CS-based algorithm yielded much better image quality, preserving superior image homogeneity, edge sharpening, and cross-plane resolution, compared to the FBP-based one. - Highlights: • A prototype digital breast tomosynthesis (DBT) system is developed. • Compressed-sensing (CS) based reconstruction framework is employed. • We reconstructed high-quality DBT images by using the proposed reconstruction framework.
Hosani, E. Al; Zhang, M.; Abascal, J. F. P. J.; Soleimani, M.
2016-11-01
Electrical capacitance tomography (ECT) is an imaging technology used to reconstruct the permittivity distribution within the sensing region. So far, ECT has been primarily used to image non-conductive media only, since if the conductivity of the imaged object is high, the capacitance measuring circuit will be almost shortened by the conductivity path and a clear image cannot be produced using the standard image reconstruction approaches. This paper tackles the problem of imaging metallic samples using conventional ECT systems by investigating the two main aspects of image reconstruction algorithms, namely the forward problem and the inverse problem. For the forward problem, two different methods to model the region of high conductivity in ECT is presented. On the other hand, for the inverse problem, three different algorithms to reconstruct the high contrast images are examined. The first two methods are the linear single step Tikhonov method and the iterative total variation regularization method, and use two sets of ECT data to reconstruct the image in time difference mode. The third method, namely the level set method, uses absolute ECT measurements and was developed using a metallic forward model. The results indicate that the applications of conventional ECT systems can be extended to metal samples using the suggested algorithms and forward model, especially using a level set algorithm to find the boundary of the metal.
Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.
Li, Liang; Wang, Bigong; Wang, Ge
2016-01-01
In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.
Deep subwavelength nanometric image reconstruction using Fourier domain optical normalization
Institute of Scientific and Technical Information of China (English)
Jing Qin; Richard M Silver; Bryan M Barnes; Hui Zhou; Ronald G Dixson; Mark-Alexander Henn
2016-01-01
Quantitative optical measurements of deep subwavelength,three-dimensional (3D),nanometric structures with sensitivity to sub-nanometer details address a ubiquitous measurement challenge.A Fourier domain normalization approach is used in the Fourier optical imaging code to simulate the full 3D scattered light field of nominally 15 nm-sized structures,accurately replicating the light field as a function of the focus position.Using the full 3D light field,nanometer scale details such as a 2 nm thin conformal oxide and nanometer topography are rigorously fitted for features less than one-thirtiethof the wavelength in size.The densely packed structures are positioned nearly an order of magnitude closer than the conventional Rayleigh resolution limit and can be measured with sub-nanometer parametric uncertainties.This approach enables a practical measurement sensitivity to size variations of only a few atoms in size using a high-throughput optical configuration with broad application in measuring nanometric structures and nanoelectronic devices.
Quantitative study of undersampled recoverability for sparse images in computed tomography
DEFF Research Database (Denmark)
Jørgensen, Jakob Heide; Sidky, Emil Y.; Hansen, Per Christian
2012-01-01
Image reconstruction methods based on exploiting image sparsity, motivated by compressed sensing (CS), allow reconstruction from a significantly reduced number of projections in X-ray computed tomography (CT). However, CS provides neither theoretical guarantees of accurate CT reconstruction, nor...
Zhang, Tiankui; Hu, Huasi; Jia, Qinggang; Zhang, Fengna; Chen, Da; Li, Zhenghong; Wu, Yuelei; Liu, Zhihua; Hu, Guang; Guo, Wei
2012-11-01
Monte-Carlo simulation of neutron coded imaging based on encoding aperture for Z-pinch of large field-of-view with 5 mm radius has been investigated, and then the coded image has been obtained. Reconstruction method of source image based on genetic algorithms (GA) has been established. "Residual watermark," which emerges unavoidably in reconstructed image, while the peak normalization is employed in GA fitness calculation because of its statistical fluctuation amplification, has been discovered and studied. Residual watermark is primarily related to the shape and other parameters of the encoding aperture cross section. The properties and essential causes of the residual watermark were analyzed, while the identification on equivalent radius of aperture was provided. By using the equivalent radius, the reconstruction can also be accomplished without knowing the point spread function (PSF) of actual aperture. The reconstruction result is close to that by using PSF of the actual aperture.
DEFF Research Database (Denmark)
Jørgensen, Jakob Heide; Sidky, Emil Y.; Pan, Xiaochuan
2013-01-01
Iterative image reconstruction with sparsity-exploiting methods, such as total variation (TV) minimization, investigated in compressive sensing claim potentially large reductions in sampling requirements. Quantifying this claim for computed tomography (CT) is nontrivial, because both full sampling...
Barron, M R; Roch, A M; Waters, J A; Parikh, J A; DeWitt, J M; Al-Haddad, M A; Ceppa, E P; House, M G; Zyromski, N J; Nakeeb, A; Pitt, H A; Schmidt, C Max
2014-03-01
Main pancreatic duct (MPD) involvement is a well-demonstrated risk factor for malignancy in intraductal papillary mucinous neoplasm (IPMN). Preoperative radiographic determination of IPMN type is heavily relied upon in oncologic risk stratification. We hypothesized that radiographic assessment of MPD involvement in IPMN is an accurate predictor of pathological MPD involvement. Data regarding all patients undergoing resection for IPMN at a single academic institution between 1992 and 2012 were gathered prospectively. Retrospective analysis of imaging and pathologic data was undertaken. Preoperative classification of IPMN type was based on cross-sectional imaging (MRI/magnetic resonance cholangiopancreatography (MRCP) and/or CT). Three hundred sixty-two patients underwent resection for IPMN. Of these, 334 had complete data for analysis. Of 164 suspected branch duct (BD) IPMN, 34 (20.7%) demonstrated MPD involvement on final pathology. Of 170 patients with suspicion of MPD involvement, 50 (29.4%) demonstrated no MPD involvement. Of 34 patients with suspected BD-IPMN who were found to have MPD involvement on pathology, 10 (29.4%) had invasive carcinoma. Alternatively, 2/50 (4%) of the patients with suspected MPD involvement who ultimately had isolated BD-IPMN demonstrated invasive carcinoma. Preoperative radiographic IPMN type did not correlate with final pathology in 25% of the patients. In addition, risk of invasive carcinoma correlates with pathologic presence of MPD involvement.
Model-free reconstruction of excitatory neuronal connectivity from calcium imaging signals.
Directory of Open Access Journals (Sweden)
Olav Stetter
Full Text Available A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting. Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections
Directory of Open Access Journals (Sweden)
Qingsong Yang
Full Text Available The purpose of this paper is to develop an algorithm for hybrid spectral computed tomography (CT which combines energy-integrating and photon-counting detectors. While the energy-integrating scan is global, the photon-counting scan can have a local field of view (FOV. The algorithm synthesizes both spectral data and energy-integrating data. Low rank and sparsity prior is used for spectral CT reconstruction. An initial estimation is obtained from the projection data based on physical principles of x-ray interaction with the matter, which provides a more accurate Taylor expansion than previous work and can guarantee the convergence of the algorithm. Numerical simulation with clinical CT images are performed. The proposed algorithm produces very good spectral features outside the FOV when no K-edge material exists. Exterior reconstruction of K-edge material can be partially achieved.
Yang, Qingsong; Cong, Wenxiang; Xi, Yan; Wang, Ge
2016-01-01
The purpose of this paper is to develop an algorithm for hybrid spectral computed tomography (CT) which combines energy-integrating and photon-counting detectors. While the energy-integrating scan is global, the photon-counting scan can have a local field of view (FOV). The algorithm synthesizes both spectral data and energy-integrating data. Low rank and sparsity prior is used for spectral CT reconstruction. An initial estimation is obtained from the projection data based on physical principles of x-ray interaction with the matter, which provides a more accurate Taylor expansion than previous work and can guarantee the convergence of the algorithm. Numerical simulation with clinical CT images are performed. The proposed algorithm produces very good spectral features outside the FOV when no K-edge material exists. Exterior reconstruction of K-edge material can be partially achieved.
Gront, Dominik; Kmiecik, Sebastian; Kolinski, Andrzej
2007-07-15
In this contribution, we present an algorithm for protein backbone reconstruction that comprises very high computational efficiency with high accuracy. Reconstruction of the main chain atomic coordinates from the alpha carbon trace is a common task in protein modeling, including de novo structure prediction, comparative modeling, and processing experimental data. The method employed in this work follows the main idea of some earlier approaches to the problem. The details and careful design of the present approach are new and lead to the algorithm that outperforms all commonly used earlier applications. BBQ (Backbone Building from Quadrilaterals) program has been extensively tested both on native structures as well as on near-native decoy models and compared with the different available existing methods. Obtained results provide a comprehensive benchmark of existing tools and evaluate their applicability to a large scale modeling using a reduced representation of protein conformational space. The BBQ package is available for downloading from our website at http://biocomp.chem.uw.edu.pl/services/BBQ/. This webpage also provides a user manual that describes BBQ functions in detail.
Ma, Jianhua; Zhang, Hua; Gao, Yang; Huang, Jing; Liang, Zhengrong; Feng, Qianjing; Chen, Wufan
2012-11-01
Cerebral perfusion x-ray computed tomography (PCT) imaging, which detects and characterizes the ischemic penumbra, and assesses blood-brain barrier permeability with acute stroke or chronic cerebrovascular diseases, has been developed extensively over the past decades. However, due to its sequential scan protocol, the associated radiation dose has raised significant concerns to patients. Therefore, in this study we developed an iterative image reconstruction algorithm based on the maximum a posterior (MAP) principle to yield a clinically acceptable cerebral PCT image with lower milliampere-seconds (mA s). To preserve the edges of the reconstructed image, an edge-preserving prior was designed using a normal-dose pre-contrast unenhanced scan. For simplicity, the present algorithm was termed as ‘MAP-ndiNLM’. Evaluations with the digital phantom and the simulated low-dose clinical brain PCT datasets clearly demonstrate that the MAP-ndiNLM method can achieve more significant gains than the existing FBP and MAP-Huber algorithms with better image noise reduction, low-contrast object detection and resolution preservation. More importantly, the MAP-ndiNLM method can yield more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps than the MAP-Huber method.
CT x-ray tube voltage optimisation and image reconstruction evaluation using visual grading analysis
Zheng, Xiaoming; Kim, Ted M.; Davidson, Rob; Lee, Seongju; Shin, Cheongil; Yang, Sook
2014-03-01
The purposes of this work were to find an optimal x-ray voltage for CT imaging and to determine the diagnostic effectiveness of image reconstruction techniques by using the visual grading analysis (VGA). Images of the PH-5 CT abdomen phantom (Kagaku Co, Kyoto) were acquired by the Toshiba Aquillion One 320 slices CT system with various exposures (from 10 to 580 mAs) under different tube peak voltages (80, 100 and 120 kVp). The images were reconstructed by employing the FBP and the AIDR 3D iterative reconstructions with Mild, Standard and Strong FBP blending. Image quality was assessed by measuring noise, contrast to noise ratio and human observer's VGA scores. The CT dose index CTDIv was obtained from the values displayed on the images. The best fit for the curves of the image quality VGA vs dose CTDIv is a logistic function from the SPSS estimation. A threshold dose Dt is defined as the CTDIv at the just acceptable for diagnostic image quality and a figure of merit (FOM) is defined as the slope of the standardised logistic function. The Dt and FOM were found to be 5.4, 8.1 and 9.1 mGy and 0.47, 0.51 and 0.38 under the tube voltages of 80, 100 and 120 kVp, respectively, from images reconstructed by the FBP technique. The Dt and FOM values were lower from the images reconstructed by the AIDR 3D in comparison with the FBP technique. The optimal xray peak voltage for the imaging of the PH-5 abdomen phantom by the Aquillion One CT system was found to be at 100 kVp. The images reconstructed by the FBP are more diagnostically effective than that by the AIDR 3D but with a higher dose Dt to the patients.
Three-dimensional reconstruction of Roman coins from photometric image sets
MacDonald, Lindsay; Moitinho de Almeida, Vera; Hess, Mona
2017-01-01
A method is presented for increasing the spatial resolution of the three-dimensional (3-D) digital representation of coins by combining fine photometric detail derived from a set of photographic images with accurate geometric data from a 3-D laser scanner. 3-D reconstructions were made of the obverse and reverse sides of two ancient Roman denarii by processing sets of images captured under directional lighting in an illumination dome. Surface normal vectors were calculated by a "bounded regression" technique, excluding both shadow and specular components of reflection from the metallic surface. Because of the known difficulty in achieving geometric accuracy when integrating photometric normals to produce a digital elevation model, the low spatial frequencies were replaced by those derived from the point cloud produced by a 3-D laser scanner. The two datasets were scaled and registered by matching the outlines and correlating the surface gradients. The final result was a realistic rendering of the coins at a spatial resolution of 75 pixels/mm (13-μm spacing), in which the fine detail modulated the underlying geometric form of the surface relief. The method opens the way to obtain high quality 3-D representations of coins in collections to enable interactive online viewing.
Dictionary-based image reconstruction for superresolution in integrated circuit imaging.
Cilingiroglu, T Berkin; Uyar, Aydan; Tuysuzoglu, Ahmet; Karl, W Clem; Konrad, Janusz; Goldberg, Bennett B; Ünlü, M Selim
2015-06-01
Resolution improvement through signal processing techniques for integrated circuit imaging is becoming more crucial as the rapid decrease in integrated circuit dimensions continues. Although there is a significant effort to push the limits of optical resolution for backside fault analysis through the use of solid immersion lenses, higher order laser beams, and beam apodization, signal processing techniques are required for additional improvement. In this work, we propose a sparse image reconstruction framework which couples overcomplete dictionary-based representation with a physics-based forward model to improve resolution and localization accuracy in high numerical aperture confocal microscopy systems for backside optical integrated circuit analysis. The effectiveness of the framework is demonstrated on experimental data.
Bilateral bad pixel and Stokes image reconstruction for microgrid polarimetric imagers
LeMaster, Daniel A.; Ratliff, Bradley M.
2015-09-01
Uncorrected or poorly corrected bad pixels reduce the effectiveness of polarimetric clutter suppression. In conventional microgrid processing, bad pixel correction is accomplished as a separate step from Stokes image reconstruction. Here, these two steps are combined to speed processing and provide better estimates of the entire image, including missing samples. A variation on the bilateral filter enables both edge preservation in the Stokes imagery and bad pixel suppression. Understanding the newly presented filter requires two key insights. First, the adaptive nature of the bilateral filter is extended to correct for bad pixels by simply incorporating a bad pixel mask. Second, the bilateral filter for Stokes estimation is the sum of the normalized bilateral filters for estimating each analyzer channel individually. This paper describes the new approach and compares it to our legacy method using simulated imagery.
Sample based 3D face reconstruction from a single frontal image by adaptive locally linear embedding
Institute of Scientific and Technical Information of China (English)
ZHANG Jian; ZHUANG Yue-ting
2007-01-01
In this paper, we propose a highly automatic approach for 3D photorealistic face reconstruction from a single frontal image. The key point of our work is the implementation of adaptive manifold learning approach. Beforehand, an active appearance model (AAM) is trained for automatic feature extraction and adaptive locally linear embedding (ALLE) algorithm is utilized to reduce the dimensionality of the 3D database. Then, given an input frontal face image, the corresponding weights between 3D samples and the image are synthesized adaptively according to the AAM selected facial features. Finally, geometry reconstruction is achieved by linear weighted combination of adaptively selected samples. Radial basis function (RBF) is adopted to map facial texture from the frontal image to the reconstructed face geometry. The texture of invisible regions between the face and the ears is interpolated by sampling from the frontal image. This approach has several advantages: (1) Only a single frontal face image is needed for highly automatic face reconstruction; (2) Compared with former works, our reconstruction approach provides higher accuracy; (3) Constraint based RBF texture mapping provides natural appearance for reconstructed face.
Acceleration of the direct reconstruction of linear parametric images using nested algorithms.
Wang, Guobao; Qi, Jinyi
2010-03-01
Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.
A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.
Directory of Open Access Journals (Sweden)
Justin J Konkle
Full Text Available Magnetic Particle Imaging (mpi is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.
Ahmad, Munir; Shahzad, Tasawar; Masood, Khalid; Rashid, Khalid; Tanveer, Muhammad; Iqbal, Rabail; Hussain, Nasir; Shahid, Abubakar; Fazal-E-Aleem
2016-06-01
Emission tomographic image reconstruction is an ill-posed problem due to limited and noisy data and various image-degrading effects affecting the data and leads to noisy reconstructions. Explicit regularization, through iterative reconstruction methods, is considered better to compensate for reconstruction-based noise. Local smoothing and edge-preserving regularization methods can reduce reconstruction-based noise. However, these methods produce overly smoothed images or blocky artefacts in the final image because they can only exploit local image properties. Recently, non-local regularization techniques have been introduced, to overcome these problems, by incorporating geometrical global continuity and connectivity present in the objective image. These techniques can overcome drawbacks of local regularization methods; however, they also have certain limitations, such as choice of the regularization function, neighbourhood size or calibration of several empirical parameters involved. This work compares different local and non-local regularization techniques used in emission tomographic imaging in general and emission computed tomography in specific for improved quality of the resultant images.
Kole, J. S.; Beekman, F. J.
2006-02-01
Statistical reconstruction methods offer possibilities to improve image quality as compared with analytical methods, but current reconstruction times prohibit routine application in clinical and micro-CT. In particular, for cone-beam x-ray CT, the use of graphics hardware has been proposed to accelerate the forward and back-projection operations, in order to reduce reconstruction times. In the past, wide application of this texture hardware mapping approach was hampered owing to limited intrinsic accuracy. Recently, however, floating point precision has become available in the latest generation commodity graphics cards. In this paper, we utilize this feature to construct a graphics hardware accelerated version of the ordered subset convex reconstruction algorithm. The aims of this paper are (i) to study the impact of using graphics hardware acceleration for statistical reconstruction on the reconstructed image accuracy and (ii) to measure the speed increase one can obtain by using graphics hardware acceleration. We compare the unaccelerated algorithm with the graphics hardware accelerated version, and for the latter we consider two different interpolation techniques. A simulation study of a micro-CT scanner with a mathematical phantom shows that at almost preserved reconstructed image accuracy, speed-ups of a factor 40 to 222 can be achieved, compared with the unaccelerated algorithm, and depending on the phantom and detector sizes. Reconstruction from physical phantom data reconfirms the usability of the accelerated algorithm for practical cases.
Energy Technology Data Exchange (ETDEWEB)
Kole, J S; Beekman, F J [Image Sciences Institute, Department of Nuclear Medicine and Department of Pharmacology and Anatomy, Rudolf Magnus Institute of Neuroscience, UMC Utrecht, Universiteitsweg 100, STR5.203, 3584 CG Utrecht (Netherlands)
2006-02-21
Statistical reconstruction methods offer possibilities to improve image quality as compared with analytical methods, but current reconstruction times prohibit routine application in clinical and micro-CT. In particular, for cone-beam x-ray CT, the use of graphics hardware has been proposed to accelerate the forward and back-projection operations, in order to reduce reconstruction times. In the past, wide application of this texture hardware mapping approach was hampered owing to limited intrinsic accuracy. Recently, however, floating point precision has become available in the latest generation commodity graphics cards. In this paper, we utilize this feature to construct a graphics hardware accelerated version of the ordered subset convex reconstruction algorithm. The aims of this paper are (i) to study the impact of using graphics hardware acceleration for statistical reconstruction on the reconstructed image accuracy and (ii) to measure the speed increase one can obtain by using graphics hardware acceleration. We compare the unaccelerated algorithm with the graphics hardware accelerated version, and for the latter we consider two different interpolation techniques. A simulation study of a micro-CT scanner with a mathematical phantom shows that at almost preserved reconstructed image accuracy, speed-ups of a factor 40 to 222 can be achieved, compared with the unaccelerated algorithm, and depending on the phantom and detector sizes. Reconstruction from physical phantom data reconfirms the usability of the accelerated algorithm for practical cases.
Tunnel Effect in CNNs: Image Reconstruction From Max-Switch Locations
DEFF Research Database (Denmark)
de La Roche Saint Andre, Matthieu; Rieger, Laura; Hannemose, Morten;
2016-01-01
In this paper, we show that reconstruction of an image passed through a neural network is possible, using only the locations of the max pool activations. This was demonstrated with an architecture consisting of an encoder and a decoder. The decoder is a mirrored version of the encoder, where...... convolutions are replaced with deconvolutions and poolings are replaced with unpooling layers. The locations of the max pool switches are transmitted to the corresponding unpooling layer. The reconstruction is computed only from these switches without the use of feature values. Using only the max switch...... location information of the pool layers, a surprisingly good image reconstruction can be achieved. We examine this effect in various architectures, as well as how the quality of the reconstruction is affected by the number of features. We also compare the reconstruction with an encoder with randomly...
Smith, M R; Nichols, S T; Constable, R T; Henkelman, R M
1991-05-01
The resolution of magnetic resonance images reconstructed using the discrete Fourier transform (DFT) algorithm is limited by the effective window generated by the finite data length. The transient error reconstruction approach (TERA) is an alternative reconstruction method based on autoregressive moving average (ARMA) modeling techniques. Quantitative measurements comparing the truncation artifacts present during DFT and TERA image reconstruction show that the modeling method substantially reduces these artifacts on "full" (256 X 256), "truncated" (256 X 192), and "severely truncated" (256 X 128) data sets without introducing the global amplitude distortion found in other modeling techniques. Two global measures for determining the success of modeling are suggested. Problem areas for one-dimensional modeling are examined and reasons for considering two-dimensional modeling discussed. Analysis of both medical and phantom data reconstructions are presented.
Image Capture with Synchronized Multiple-Cameras for Extraction of Accurate Geometries
Koehl, M.; Delacourt, T.; Boutry, C.
2016-06-01
This paper presents a project of recording and modelling tunnels, traffic circles and roads from multiple sensors. The aim is the representation and the accurate 3D modelling of a selection of road infrastructures as dense point clouds in order to extract profiles and metrics from it. Indeed, these models will be used for the sizing of infrastructures in order to simulate exceptional convoy truck routes. The objective is to extract directly from the point clouds the heights, widths and lengths of bridges and tunnels, the diameter of gyrating and to highlight potential obstacles for a convoy. Light, mobile and fast acquisition approaches based on images and videos from a set of synchronized sensors have been tested in order to obtain useable point clouds. The presented solution is based on a combination of multiple low-cost cameras designed on an on-boarded device allowing dynamic captures. The experimental device containing GoPro Hero4 cameras has been set up and used for tests in static or mobile acquisitions. That way, various configurations have been tested by using multiple synchronized cameras. These configurations are discussed in order to highlight the best operational configuration according to the shape of the acquired objects. As the precise calibration of each sensor and its optics are major factors in the process of creation of accurate dense point clouds, and in order to reach the best quality available from such cameras, the estimation of the internal parameters of fisheye lenses of the cameras has been processed. Reference measures were also realized by using a 3D TLS (Faro Focus 3D) to allow the accuracy assessment.
Wang, Qi; Lian, Zhijie; Wang, Jianming; Chen, Qingliang; Sun, Yukuan; Li, Xiuyan; Duan, Xiaojie; Cui, Ziqiang; Wang, Huaxiang
2016-11-01
Electrical impedance tomography (EIT) reconstruction is a nonlinear and ill-posed problem. Exact reconstruction of an EIT image inverts a high dimensional mathematical model to calculate the conductivity field, which causes significant problems regarding that the computational complexity will reduce the achievable frame rate, which is considered as a major advantage of EIT imaging. The single-step method, state estimation method, and projection method were always used to accelerate reconstruction process. The basic principle of these methods is to reduce computational complexity. However, maintaining high resolution in space together with not much cost is still challenging, especially for complex conductivity distribution. This study proposes an idea to accelerate image reconstruction of EIT based on compressive sensing (CS) theory, namely, CSEIT method. The novel CSEIT method reduces the sampling rate through minimizing redundancy in measurements, so that detailed information of reconstruction is not lost. In order to obtain sparse solution, which is the prior condition of signal recovery required by CS theory, a novel image reconstruction algorithm based on patch-based sparse representation is proposed. By applying the new framework of CSEIT, the data acquisition time, or the sampling rate, is reduced by more than two times, while the accuracy of reconstruction is significantly improved.
GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume
Directory of Open Access Journals (Sweden)
Xing Zhao
2009-01-01
Full Text Available Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation.
Reconstruction of 3D images from a series of 2D images has been restricted by the limited capacity to decrease the opacity of surrounding tissue. Commercial software that allows color-keying and manipulation of 2D images in true 3D space allowed us to produce 3D reconstructions from pixel based imag...
Assessing 3D tunnel position in ACL reconstruction using a novel single image 3D-2D registration
Kang, X.; Yau, W. P.; Otake, Y.; Cheung, P. Y. S.; Hu, Y.; Taylor, R. H.
2012-02-01
The routinely used procedure for evaluating tunnel positions following anterior cruciate ligament (ACL) reconstructions based on standard X-ray images is known to pose difficulties in terms of obtaining accurate measures, especially in providing three-dimensional tunnel positions. This is largely due to the variability in individual knee joint pose relative to X-ray plates. Accurate results were reported using postoperative CT. However, its extensive usage in clinical routine is hampered by its major requirement of having CT scans of individual patients, which is not available for most ACL reconstructions. These difficulties are addressed through the proposed method, which aligns a knee model to X-ray images using our novel single-image 3D-2D registration method and then estimates the 3D tunnel position. In the proposed method, the alignment is achieved by using a novel contour-based 3D-2D registration method wherein image contours are treated as a set of oriented points. However, instead of using some form of orientation weighting function and multiplying it with a distance function, we formulate the 3D-2D registration as a probability density estimation using a mixture of von Mises-Fisher-Gaussian (vMFG) distributions and solve it through an expectation maximization (EM) algorithm. Compared with the ground-truth established from postoperative CT, our registration method in an experiment using a plastic phantom showed accurate results with errors of (-0.43°+/-1.19°, 0.45°+/-2.17°, 0.23°+/-1.05°) and (0.03+/-0.55, -0.03+/-0.54, -2.73+/-1.64) mm. As for the entry point of the ACL tunnel, one of the key measurements, it was obtained with high accuracy of 0.53+/-0.30 mm distance errors.
Digital reconstructed radiography with multiple color image overlay for image-guided radiotherapy.
Yoshino, Shinichi; Miki, Kentaro; Sakata, Kozo; Nakayama, Yuko; Shibayama, Kouichi; Mori, Shinichiro
2015-05-01
Registration of patient anatomical structures to the reference position is a basic part of the patient set-up procedure. Registration of anatomical structures between the site of beam entrance on the patient surface and the distal target position is particularly important. Here, to improve patient positional accuracy during set-up for particle beam treatment, we propose a new visualization methodology using digitally reconstructed radiographs (DRRs), overlaid DRRs, and evaluation of overlaid DRR images in clinical cases. The overlaid method overlays two DRR images in different colors by dividing the CT image into two CT sections at the distal edge of the target along the treatment beam direction. Since our hospital uses fixed beam ports, the treatment beam angles for this study were set at 0 and 90 degrees. The DRR calculation direction was from the X-ray tube to the imaging device, and set to 180/270 degrees and 135/225 degrees, based on the installation of our X-ray imaging system. Original and overlaid DRRs were calculated using CT data for two patients, one with a parotid gland tumor and the other with prostate cancer. The original and overlaid DRR images were compared. Since the overlaid DRR image was completely separated into two regions when the DRR calculation angle was the same as the treatment beam angle, the overlaid DRR visualization technique was able to provide rich information for aiding recognition of the relationship between anatomical structures and the target position. This method will also be useful in patient set-up procedures for fixed irradiation ports.
Institute of Scientific and Technical Information of China (English)
XIE Hong-Lan; CHEN Jian-Wen; GAO Hong-Yi; ZHU Hua-Feng; LI Ru-Xin; XU Zhi-Zhan
2004-01-01
X-ray fluorescence holography (XFH) is a novel method for three-dimensional (3D) imaging of atomic structure. Theoretically, in an XFH experiment, one has to measure the fluorescence energy on a spherical surface to get well-resolved 3D images of atoms. But in practice, the experimental system arrangement does not allow the measurement of the fluorescent intensity oscillations in the full sphere. The holographic information losses because of the limited sampling range (less than 4π) will directly result in defective reconstructed atomic images. In this work, the atomic image of a Fe single crystal (001) was reconstructed by numerically simulating X-ray fluorescence holograms of the crystal at different recording angle's ranges and step lengths. Influences of the ranges of azimuth angles and polar angles and the step length of polar angles on the reconstructed atomic images were discussed.
Total variation regularization in measurement and image space for PET reconstruction
Burger, M
2014-09-18
© 2014 IOP Publishing Ltd. The aim of this paper is to test and analyse a novel technique for image reconstruction in positron emission tomography, which is based on (total variation) regularization on both the image space and the projection space. We formulate our variational problem considering both total variation penalty terms on the image and on an idealized sinogram to be reconstructed from a given Poisson distributed noisy sinogram. We prove existence, uniqueness and stability results for the proposed model and provide some analytical insight into the structures favoured by joint regularization. For the numerical solution of the corresponding discretized problem we employ the split Bregman algorithm and extensively test the approach in comparison to standard total variation regularization on the image. The numerical results show that an additional penalty on the sinogram performs better on reconstructing images with thin structures.
Improved Reconstruction of Radio Holographic Signal for Forward Scatter Radar Imaging.
Hu, Cheng; Liu, Changjiang; Wang, Rui; Zeng, Tao
2016-05-07
Forward scatter radar (FSR), as a specially configured bistatic radar, is provided with the capabilities of target recognition and classification by the Shadow Inverse Synthetic Aperture Radar (SISAR) imaging technology. This paper mainly discusses the reconstruction of radio holographic signal (RHS), which is an important procedure in the signal processing of FSR SISAR imaging. Based on the analysis of signal characteristics, the method for RHS reconstruction is improved in two parts: the segmental Hilbert transformation and the reconstruction of mainlobe RHS. In addition, a quantitative analysis of the method's applicability is presented by distinguishing between the near field and far field in forward scattering. Simulation results validated the method's advantages in improving the accuracy of RHS reconstruction and imaging.
Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Mueller-Lisse, Ullrich; Moeller, Knut
2016-06-01
Electrical impedance tomography (EIT) reconstructs the conductivity distribution of a domain using electrical data on its boundary. This is an ill-posed inverse problem usually solved on a finite element mesh. For this article, a special regularization method incorporating structural information of the targeted domain is proposed and evaluated. Structural information was obtained either from computed tomography images or from preliminary EIT reconstructions by a modified k-means clustering. The proposed regularization method integrates this structural information into the reconstruction as a soft constraint preferring sparsity in group level. A first evaluation with Monte Carlo simulations indicated that the proposed solver is more robust to noise and the resulting images show fewer artifacts. This finding is supported by real data analysis. The structure based regularization has the potential to balance structural a priori information with data driven reconstruction. It is robust to noise, reduces artifacts and produces images that reflect anatomy and are thus easier to interpret for physicians.
Wang, Zhen-Tian; Zhang, Li; Huang, Zhi-Feng; Kang, Ke-Jun; Chen, Zhi-Qiang; Fang, Qiao-Guang; Zhu, Pei-Ping
2009-11-01
X-ray diffraction enhanced imaging (DEI) has extremely high sensitivity for weakly absorbing low-Z samples in medical and biological fields. In this paper, we propose an Algebra Reconstruction Technique (ART) iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging (DEI-CT). An Ordered Subsets (OS) technique is used to accelerate the ART reconstruction. Few-view reconstruction is also studied, and a partial differential equation (PDE) type filter which has the ability of edge-preserving and denoising is used to improve the image quality and eliminate the artifacts. The proposed algorithm is validated with both the numerical simulations and the experiment at the Beijing synchrotron radiation facility (BSRF).
Multiscale vision model for event detection and reconstruction in two-photon imaging data
DEFF Research Database (Denmark)
Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke;
2014-01-01
Reliable detection of calcium waves in multiphoton imaging data is challenging because of the low signal-to-noise ratio and because of the unpredictability of the time and location of these spontaneous events. This paper describes our approach to calcium wave detection and reconstruction based...... on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... in the context of detection and reconstruction of intercellular glial calcium waves. We extend the framework by a different decomposition algorithm and iterative reconstruction of the detected objects. Comparison with several popular state-of-the-art image denoising methods shows that performance...
Improved Reconstruction of Radio Holographic Signal for Forward Scatter Radar Imaging
Directory of Open Access Journals (Sweden)
Cheng Hu
2016-05-01
Full Text Available Forward scatter radar (FSR, as a specially configured bistatic radar, is provided with the capabilities of target recognition and classification by the Shadow Inverse Synthetic Aperture Radar (SISAR imaging technology. This paper mainly discusses the reconstruction of radio holographic signal (RHS, which is an important procedure in the signal processing of FSR SISAR imaging. Based on the analysis of signal characteristics, the method for RHS reconstruction is improved in two parts: the segmental Hilbert transformation and the reconstruction of mainlobe RHS. In addition, a quantitative analysis of the method’s applicability is presented by distinguishing between the near field and far field in forward scattering. Simulation results validated the method’s advantages in improving the accuracy of RHS reconstruction and imaging.
DEFF Research Database (Denmark)
Hellebust, Taran Paulsen; Tanderup, Kari; Bergstrand, Eva Stabell;
2007-01-01
The purpose of this study is to investigate whether the method of applicator reconstruction and/or the applicator orientation influence the dose calculation to points around the applicator for brachytherapy of cervical cancer with CT-based treatment planning. A phantom, containing a fixed ring...
Multicolor 3D super-resolution imaging by quantum dot stochastic optical reconstruction microscopy.
Xu, Jianquan; Tehrani, Kayvan F; Kner, Peter
2015-03-24
We demonstrate multicolor three-dimensional super-resolution imaging with quantum dots (QSTORM). By combining quantum dot asynchronous spectral blueing with stochastic optical reconstruction microscopy and adaptive optics, we achieve three-dimensional imaging with 24 nm lateral and 37 nm axial resolution. By pairing two short-pass filters with two appropriate quantum dots, we are able to image single blueing quantum dots on two channels simultaneously, enabling multicolor imaging with high photon counts.
Pachon, Jan H.; Yadava, Girijesh; Pal, Debashish; Hsieh, Jiang
2012-03-01
Non-linear iterative reconstruction (IR) algorithms have shown promising improvements in image quality at reduced dose levels. However, IR images sometimes may be perceived as having different image noise texture than traditional filtered back projection (FBP) reconstruction. Standard linear-systems-based image quality evaluation metrics are limited in characterizing such textural differences and non-linear image-quality vs. dose trade-off behavior, hence limited in predicting potential impact of such texture differences in diagnostic task. In an attempt to objectively characterize and measure dose dependent image noise texture and statistical properties of IR and FBP images, we have investigated higher order moments and Haralicks Gray Level Co-occurrence Matrices (GLCM) based texture features on phantom images reconstructed by an iterative and a traditional FBP method. In this study, the first 4 central order moments, and multiple texture features from Haralick GLCM in 4 directions at 6 different ROI sizes and four dose levels were computed. For resolution, noise and texture trade-off analysis, spatial frequency domain NPS and contrastdependent MTF were also computed. Preliminary results of the study indicate that higher order moments, along with spatial domain measures of energy, contrast, correlation, homogeneity, and entropy consistently capture the textural differences between FBP and IR as dose changes. These metrics may be useful in describing the perceptual differences in randomness, coarseness, contrast, and smoothness of images reconstructed by non-linear algorithms.
Image reconstruction of simulated specimens using convolution back projection
Directory of Open Access Journals (Sweden)
Mohd. Farhan Manzoor
2001-04-01
Full Text Available This paper reports about the reconstruction of cross-sections of composite structures. The convolution back projection (CBP algorithm has been used to capture the attenuation field over the specimen. Five different test cases have been taken up for evaluation. These cases represent varying degrees of complexity. In addition, the role of filters on the nature of the reconstruction errors has also been discussed. Numerical results obtained in the study reveal that CBP algorithm is a useful tool for qualitative as well as quantitative assessment of composite regions encountered in engineering applications.
Accurate inference of shoot biomass from high-throughput images of cereal plants
Directory of Open Access Journals (Sweden)
Tester Mark
2011-02-01
Full Text Available Abstract With the establishment of advanced technology facilities for high throughput plant phenotyping, the problem of estimating plant biomass of individual plants from their two dimensional images is becoming increasingly important. The approach predominantly cited in literature is to estimate the biomass of a plant as a linear function of the projected shoot area of plants in the images. However, the estimation error from this model, which is solely a function of projected shoot area, is large, prohibiting accurate estimation of the biomass of plants, particularly for the salt-stressed plants. In this paper, we propose a method based on plant specific weight for improving the accuracy of the linear model and reducing the estimation bias (the difference between actual shoot dry weight and the value of the shoot dry weight estimated with a predictive model. For the proposed method in this study, we modeled the plant shoot dry weight as a function of plant area and plant age. The data used for developing our model and comparing the results with the linear model were collected from a completely randomized block design experiment. A total of 320 plants from two bread wheat varieties were grown in a supported hydroponics system in a greenhouse. The plants were exposed to two levels of hydroponic salt treatments (NaCl at 0 and 100 mM for 6 weeks. Five harvests were carried out. Each time 64 randomly selected plants were imaged and then harvested to measure the shoot fresh weight and shoot dry weight. The results of statistical analysis showed that with our proposed method, most of the observed variance can be explained, and moreover only a small difference between actual and estimated shoot dry weight was obtained. The low estimation bias indicates that our proposed method can be used to estimate biomass of individual plants regardless of what variety the plant is and what salt treatment has been applied. We validated this model on an independent
Impact of reconstruction parameters on quantitative I-131 SPECT
van Gils, C A J; Beijst, C; van Rooij, R; de Jong, H W A M
2016-01-01
Radioiodine therapy using I-131 is widely used for treatment of thyroid disease or neuroendocrine tumors. Monitoring treatment by accurate dosimetry requires quantitative imaging. The high energy photons however render quantitative SPECT reconstruction challenging, potentially requiring accurate cor
Mikhaylova, E.; Kolstein, M.; De Lorenzo, G.; Chmeissani, M.
2014-07-01
A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project [1]. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head [2]. With unprecedented high channel density (450 channels/cm3) image reconstruction is a challenge. Therefore optimization is needed to find the best algorithm in order to exploit correctly the promising detector potential. The following reconstruction algorithms are evaluated: 2-D Filtered Backprojection (FBP), Ordered Subset Expectation Maximization (OSEM), List-Mode OSEM (LM-OSEM), and the Origin Ensemble (OE) algorithm. The evaluation is based on the comparison of a true image phantom with a set of reconstructed images obtained by each algorithm. This is achieved by calculation of image quality merit parameters such as the bias, the variance and the mean square error (MSE). A systematic optimization of each algorithm is performed by varying the reconstruction parameters, such as the cutoff frequency of the noise filters and the number of iterations. The region of interest (ROI) analysis of the reconstructed phantom is also performed for each algorithm and the results are compared. Additionally, the performance of the image reconstruction methods is compared by calculating the modulation transfer function (MTF). The reconstruction time is also taken into account to choose the optimal algorithm. The analysis is based on GAMOS [3] simulation including the expected CdTe and electronic specifics.
Optimal image reconstruction intervals for non-invasive coronary angiography with 64-slice CT
Energy Technology Data Exchange (ETDEWEB)
Leschka, Sebastian; Husmann, Lars; Desbiolles, Lotus M.; Boehm, Thomas; Marincek, Borut; Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic Radiology, Zurich (Switzerland); Gaemperli, Oliver; Schepis, Tiziano; Koepfli, Pascal [University Hospital Zurich, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiovascular Center, Zurich (Switzerland); University of Zurich, Center for Integrative Human Physiology, Zurich (Switzerland)
2006-09-15
The reconstruction intervals providing best image quality for non-invasive coronary angiography with 64-slice computed tomography (CT) were evaluated. Contrast-enhanced, retrospectively electrocardiography (ECG)-gated 64-slice CT coronary angiography was performed in 80 patients (47 male, 33 female; mean age 62.1{+-}10.6 years). Thirteen data sets were reconstructed in 5% increments from 20 to 80% of the R-R interval. Depending on the average heart rate during scanning, patients were grouped as <65 bpm (n=49) and {>=}65 bpm (n=31). Two blinded and independent readers assessed the image quality of each coronary segment with a diameter {>=}1.5 mm using the following scores: 1, no motion artifacts; 2, minor artifacts; 3, moderate artifacts; 4, severe artifacts; and 5, not evaluative. The average heart rate was 63.3{+-}13.1 bpm (range 38-102). Acceptable image quality (scores 1-3) was achieved in 99.1% of all coronary segments (1,162/1,172; mean image quality score 1.55{+-}0.77) in the best reconstruction interval. Best image quality was found at 60% and 65% of the R-R interval for all patients and for each heart rate subgroup, whereas motion artifacts occurred significantly more often (P<0.01) at other reconstruction intervals. At heart rates <65 bpm, acceptable image quality was found in all coronary segments at 60%. At heart rates {>=}65 bpm, the whole coronary artery tree could be visualized with acceptable image quality in 87% (27/31) of the patients at 60%, while ten segments in four patients were rated as non-diagnostic (scores 4-5) at any reconstruction interval. In conclusion, 64-slice CT coronary angiography provides best overall image quality in mid-diastole. At heart rates <65 bpm, diagnostic image quality of all coronary segments can be obtained at a single reconstruction interval of 60%. (orig.)
An active contour method for bone cement reconstruction from C-arm x-ray images.
Lucas, Blake C; Otake, Yoshito; Armand, Mehran; Taylor, Russell H
2012-04-01
A novel algorithm is presented to segment and reconstruct injected bone cement from a sparse set of X-ray images acquired at arbitrary poses. The sparse X-ray multi-view active contour (SxMAC-pronounced "smack") can 1) reconstruct objects for which the background partially occludes the object in X-ray images, 2) use X-ray images acquired on a noncircular trajectory, and 3) incorporate prior computed tomography (CT) information. The algorithm's inputs are preprocessed X-ray images, their associated pose information, and prior CT, if available. The algorithm initiates automated reconstruction using visual hull computation from a sparse number of X-ray images. It then improves the accuracy of the reconstruction by optimizing a geodesic active contour. Experiments with mathematical phantoms demonstrate improvements over a conventional silhouette based approach, and a cadaver experiment demonstrates SxMAC's ability to reconstruct high contrast bone cement that has been injected into a femur and achieve sub-millimeter accuracy with four images.
Research and Realization of Medical Image Fusion Based on Three-Dimensional Reconstruction
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A new medical image fusion technique is presented. The method is based on three-dimensional reconstruction. After reconstruction, the three-dimensional volume data is normalized by three-dimensional coordinate conversion in the same way and intercepted through setting up cutting plane including anatomical structure, as a result two images in entire registration on space and geometry are obtained and the images are fused at last.Compared with traditional two-dimensional fusion technique, three-dimensional fusion technique can not only resolve the different problems existed in the two kinds of images, but also avoid the registration error of the two kinds of images when they have different scan and imaging parameter. The research proves this fusion technique is more exact and has no registration, so it is more adapt to arbitrary medical image fusion with different equipments.
Gadgetron: An Open Source Framework for Medical Image Reconstruction
DEFF Research Database (Denmark)
Hansen, Michael Schacht; Sørensen, Thomas Sangild
2013-01-01
. The data processing pipeline is configured dynamically at run-time based on an extensible markup language configuration description. The framework promotes reuse and sharing of reconstruction modules and new Gadgets can be added to the Gadgetron framework through a plugin-like architecture without...
Reconstruction-Free Action Inference from Compressive Imagers.
Kulkarni, Kuldeep; Turaga, Pavan
2016-04-01
Persistent surveillance from camera networks, such as at parking lots, UAVs, etc., often results in large amounts of video data, resulting in significant challenges for inference in terms of storage, communication and computation. Compressive cameras have emerged as a potential solution to deal with the data deluge issues in such applications. However, inference tasks such as action recognition require high quality features which implies reconstructing the original video data. Much work in compressive sensing (CS) theory is geared towards solving the reconstruction problem, where state-of-the-art methods are computationally intensive and provide low-quality results at high compression rates. Thus, reconstruction-free methods for inference are much desired. In this paper, we propose reconstruction-free methods for action recognition from compressive cameras at high compression ratios of 100 and above. Recognizing actions directly from CS measurements requires features which are mostly nonlinear and thus not easily applicable. This leads us to search for such properties that are preserved in compressive measurements. To this end, we propose the use of spatio-temporal smashed filters, which are compressive domain versions of pixel-domain matched filters. We conduct experiments on publicly available databases and show that one can obtain recognition rates that are comparable to the oracle method in uncompressed setup, even for high compression ratios.
Institute of Scientific and Technical Information of China (English)
ZHANG Shu-xu; ZHOU Ling-hong; CHEN Guang-jie; LIN Sheng-qu; YE Yu-sheng; ZHANG Hai-nan
2008-01-01
Objective:To investigate the feasibility of a 4D-CT reconstruction method based on the similarity principle of spatial adjacent images and mutual information measure. Methods:A motor driven sinusoidal motion platform made in house was used to create one-dimensional periodical motion that was along the longitudinal axis of the CT couch. The amplitude of sinusoidal motion was set to an amplitude of ±1 cm. The period of the motion was adjustable and set to 3.5 s. Phantom objects of two eggs were placed in a Styrofoam block, which in turn were placed on the motion platform. These objects were used to simulate volumes of interest undergoing ideal periodic motion. CT data of static phantom were acquired using a multi-slice general electric (GE) LightSpeed 16-slice CT scanner in an axial mode. And the CT data of periodical motion phantom were acquired in an axial and cine-mode scan. A software program was developed by using VC++ and VTK software tools to resort the CT data and reconstruct the 4D-CT. Then all of the CT data with same phase were sorted by the program into the same series based on the similarity principle of spatial adjacent images and mutual information measure among them, and 3D reconstruction of different phase CT data were completed by using the software. Results:All of the CT data were sorted accurately into different series based on the similarity principle of spatial adjacent images and mutual information measures among them. Compared with the unsorted CT data, the motion artifacts in the 3D reconstruction of sorted CT data were reduced significantly, and all of the sorted CT series result in a 4D-CT that reflected the characteristic of the periodical motion phantom. Conclusion:Time-resolved 4D-CT reconstruction can be implemented with any general multi-slice CT scanners based on the similarity principle of spatial adjacent images and mutual information measure.The process of the 4D-CT data acquisition and reconstruction were not restricted to the
Directory of Open Access Journals (Sweden)
Stefano Zurrida
2011-01-01
Full Text Available Breast cancer is the most common cancer in women. Primary treatment is surgery, with mastectomy as the main treatment for most of the twentieth century. However, over that time, the extent of the procedure varied, and less extensive mastectomies are employed today compared to those used in the past, as excessively mutilating procedures did not improve survival. Today, many women receive breast-conserving surgery, usually with radiotherapy to the residual breast, instead of mastectomy, as it has been shown to be as effective as mastectomy in early disease. The relatively new skin-sparing mastectomy, often with immediate breast reconstruction, improves aesthetic outcomes and is oncologically safe. Nipple-sparing mastectomy is newer and used increasingly, with better acceptance by patients, and again appears to be oncologically safe. Breast reconstruction is an important adjunct to mastectomy, as it has a positive psychological impact on the patient, contributing to improved quality of life.
Müller, Marcel; Mönkemöller, Viola; Hennig, Simon; Hübner, Wolfgang; Huser, Thomas
2016-03-01
Super-resolved structured illumination microscopy (SR-SIM) is an important tool for fluorescence microscopy. SR-SIM microscopes perform multiple image acquisitions with varying illumination patterns, and reconstruct them to a super-resolved image. In its most frequent, linear implementation, SR-SIM doubles the spatial resolution. The reconstruction is performed numerically on the acquired wide-field image data, and thus relies on a software implementation of specific SR-SIM image reconstruction algorithms. We present fairSIM, an easy-to-use plugin that provides SR-SIM reconstructions for a wide range of SR-SIM platforms directly within ImageJ. For research groups developing their own implementations of super-resolution structured illumination microscopy, fairSIM takes away the hurdle of generating yet another implementation of the reconstruction algorithm. For users of commercial microscopes, it offers an additional, in-depth analysis option for their data independent of specific operating systems. As a modular, open-source solution, fairSIM can easily be adapted, automated and extended as the field of SR-SIM progresses.
Automatic lung segmentation in CT images with accurate handling of the hilar region.
De Nunzio, Giorgio; Tommasi, Eleonora; Agrusti, Antonella; Cataldo, Rosella; De Mitri, Ivan; Favetta, Marco; Maglio, Silvio; Massafra, Andrea; Quarta, Maurizio; Torsello, Massimo; Zecca, Ilaria; Bellotti, Roberto; Tangaro, Sabina; Calvini, Piero; Camarlinghi, Niccolò; Falaschi, Fabio; Cerello, Piergiorgio; Oliva, Piernicola
2011-02-01
A fully automated and three-dimensional (3D) segmentation method for the identification of the pulmonary parenchyma in thorax X-ray computed tomography (CT) datasets is proposed. It is meant to be used as pre-processing step in the computer-assisted detection (CAD) system for malignant lung nodule detection that is being developed by the Medical Applications in a Grid Infrastructure Connection (MAGIC-5) Project. In this new approach the segmentation of the external airways (trachea and bronchi), is obtained by 3D region growing with wavefront simulation and suitable stop conditions, thus allowing an accurate handling of the hilar region, notoriously difficult to be segmented. Particular attention was also devoted to checking and solving the problem of the apparent 'fusion' between the lungs, caused by partial-volume effects, while 3D morphology operations ensure the accurate inclusion of all the nodules (internal, pleural, and vascular) in the segmented volume. The new algorithm was initially developed and tested on a dataset of 130 CT scans from the Italung-CT trial, and was then applied to the ANODE09-competition images (55 scans) and to the LIDC database (84 scans), giving very satisfactory results. In particular, the lung contour was adequately located in 96% of the CT scans, with incorrect segmentation of the external airways in the remaining cases. Segmentation metrics were calculated that quantitatively express the consistency between automatic and manual segmentations: the mean overlap degree of the segmentation masks is 0.96 ± 0.02, and the mean and the maximum distance between the mask borders (averaged on the whole dataset) are 0.74 ± 0.05 and 4.5 ± 1.5, respectively, which confirms that the automatic segmentations quite correctly reproduce the borders traced by the radiologist. Moreover, no tissue containing internal and pleural nodules was removed in the segmentation process, so that this method proved to be fit for the use in the
Region-Based 4D Tomographic Image Reconstruction: Application to Cardiac X-ray CT
Eyndhoven, G. Van; Batenburg, K.J.; Sijbers, J.
2015-01-01
X-ray computed tomography (CT) is a powerful tool for noninvasive cardiac imaging. However, radiation dose is a major issue. In this paper, we propose an iterative reconstruction method that reduces the radiation dose without compromising image quality. This is achieved by exploiting prior knowledge
Statistical image reconstruction for low-dose CT using nonlocal means-based regularization.
Zhang, Hao; Ma, Jianhua; Wang, Jing; Liu, Yan; Lu, Hongbing; Liang, Zhengrong
2014-09-01
Low-dose computed tomography (CT) imaging without sacrifice of clinical tasks is desirable due to the growing concerns about excessive radiation exposure to the patients. One common strategy to achieve low-dose CT imaging is to lower the milliampere-second (mAs) setting in data scanning protocol. However, the reconstructed CT images by the conventional filtered back-projection (FBP) method from the low-mAs acquisitions may be severely degraded due to the excessive noise. Statistical image reconstruction (SIR) methods have shown potentials to significantly improve the reconstructed image quality from the low-mAs acquisitions, wherein the regularization plays a critical role and an established family of regularizations is based on the Markov random field (MRF) model. Inspired by the success of nonlocal means (NLM) in image processing applications, in this work, we propose to explore the NLM-based regularization for SIR to reconstruct low-dose CT images from low-mAs acquisitions. Experimental results with both digital and physical phantoms consistently demonstrated that SIR with the NLM-based regularization can achieve more gains than SIR with the well-known Gaussian MRF regularization or the generalized Gaussian MRF regularization and the conventional FBP method, in terms of image noise reduction and resolution preservation.
Algorithms and software for total variation image reconstruction via first-order methods
DEFF Research Database (Denmark)
Dahl, Joahim; Hansen, Per Christian; Jensen, Søren Holdt
2010-01-01
This paper describes new algorithms and related software for total variation (TV) image reconstruction, more specifically: denoising, inpainting, and deblurring. The algorithms are based on one of Nesterov's first-order methods, tailored to the image processing applications in such a way that...
Penalized likelihood PET image reconstruction using patch-based edge-preserving regularization.
Wang, Guobao; Qi, Jinyi
2012-12-01
Iterative image reconstruction for positron emission tomography (PET) can improve image quality by using spatial regularization that penalizes image intensity difference between neighboring pixels. The most commonly used quadratic penalty often oversmoothes edges and fine features in reconstructed images. Nonquadratic penalties can preserve edges but often introduce piece-wise constant blocky artifacts and the results are also sensitive to the hyper-parameter that controls the shape of the penalty function. This paper presents a patch-based regularization for iterative image reconstruction that uses neighborhood patches instead of individual pixels in computing the nonquadratic penalty. The new regularization is more robust than the conventional pixel-based regularization in differentiating sharp edges from random fluctuations due to noise. An optimization transfer algorithm is developed for the penalized maximum likelihood estimation. Each iteration of the algorithm can be implemented in three simple steps: an EM-like image update, an image smoothing and a pixel-by-pixel image fusion. Computer simulations show that the proposed patch-based regularization can achieve higher contrast recovery for small objects without increasing background variation compared with the quadratic regularization. The reconstruction is also more robust to the hyper-parameter than conventional pixel-based nonquadratic regularizations. The proposed regularization method has been applied to real 3-D PET data.
Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging
Energy Technology Data Exchange (ETDEWEB)
Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL
2016-01-01
Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.
Wang, Qi; Wang, Huaxiang; Zhang, Ronghua; Wang, Jinhai; Zheng, Yu; Cui, Ziqiang; Yang, Chengyi
2012-10-01
Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction in EIT is a nonlinear and ill-posed inverse problem. The Tikhonov method with L(2) regularization is always used to solve the EIT problem. However, the L(2) method always smoothes the sharp changes or discontinue areas of the reconstruction. Image reconstruction using the L(1) regularization allows addressing this difficulty. In this paper, a sum of absolute values is substituted for the sum of squares used in the L(2) regularization to form the L(1) regularization, the solution is obtained by the barrier method. However, the L(1) method often involves repeatedly solving large-dimensional matrix equations, which are computationally expensive. In this paper, the projection method is combined with the L(1) regularization method to reduce the computational cost. The L(1) problem is mainly solved in the coarse subspace. This paper also discusses the strategies of choosing parameters. Both simulation and experimental results of the L(1) regularization method were compared with the L(2) regularization method, indicating that the L(1) regularization method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages. Furthermore, the projected L(1) method can also effectively reduce the computational time without affecting the quality of reconstructed images.
Development of acoustic model-based iterative reconstruction technique for thick-concrete imaging
Almansouri, Hani; Clayton, Dwight; Kisner, Roger; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector
2016-02-01
Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.1
Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging
Energy Technology Data Exchange (ETDEWEB)
Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL
2015-01-01
Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well s health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.
Energy Technology Data Exchange (ETDEWEB)
Haubenreisser, Holger; Fink, Christian; Nance, John W. [Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University (Germany); Sedlmair, Martin; Schmidt, Bernhard [Siemens Healthcare, Division CT, Forchheim (Germany); Schoenberg, Stefan O. [Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University (Germany); Henzler, Thomas, E-mail: thomas.henzler@medma.uni-heidelberg.de [Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University (Germany)
2014-06-15
Purpose: To prospectively compare image quality of cranial computed tomography (CCT) examinations with varying slice widths using traditional filtered back projection (FBP) versus sinogram-affirmed iterative image reconstruction (SAFIRE). Materials and methods: 29 consecutive patients (14 men, mean age: 72 ± 17 years) referred for a total of 40 CCT studies were prospectively included. Each CCT raw data set was reconstructed with FBP and SAFIRE at 5 slice widths (1–5 mm; 1 mm increments). Objective image quality was assessed in three predefined regions of the brain (white matter, thalamus, cerebellum) using identical regions of interest (ROIs). Subjective image quality was assessed by 2 experienced radiologists. Objective and subjective image quality parameters were statistically compared between FBP and SAFIRE reconstructions. Results: SAFIRE reconstructions resulted in mean noise reductions of 43.8% in the white matter, 45.6% in the thalamus and 42.0% in the cerebellum (p < 0.01) compared to FBP on non contrast-enhanced 1 mm slice width images. Corresponding mean noise reductions on 1 mm contrast-enhanced studies were 45.7%, 47.3%, and 45.0% in the white matter, thalamus, and cerebellum, respectively (p < 0.01). There was no significant difference in mean attenuation of any region or slice width between the two reconstruction methods (all p > 0.05). Subjective image quality of IR images was mostly rated higher than that of the FBP images. Conclusion: Compared to FBP, SAFIRE provides significant reductions in image noise while increasing subjective image in CCT, particularly when thinner slices are used. Therefore, SAFIRE may allow utilization of thinner slices in CCT, potentially reducing partial volume effects and improving diagnostic accuracy.
Three dimensional image reconstruction based on a wide-field optical coherence tomography system
Feng, Yinqi; Feng, Shengtong; Zhang, Min; Hao, Junjun
2014-07-01
Wide-field optical coherence tomography has a promising application for its high scanning rate and resolution. The principle of a wide-field optical coherence tomography system is described, and 2D images of glass slides are reconstructed using eight-stepped phase-shifting method in the system. Using VC6.0 and OpenGL programming, 3D images are reconstructed based on the Marching Cube algorithm with 2D image sequences. The experimental results show that the depth detection and three-dimensional tomography for translucent materials could be implemented efficiently in the WFOCT system.
Xu, Daguang; Huang, Yong; Kang, Jin U
2014-09-01
In this work, we propose a novel dispersion compensation method that enables real-time compressive sensing (CS) spectral domain optical coherence tomography (SD OCT) image reconstruction. We show that dispersion compensation can be incorporated into CS SD OCT by multiplying the dispersion-correcting terms by the undersampled spectral data before CS reconstruction. High-quality SD OCT imaging with dispersion compensation was demonstrated at a speed in excess of 70 frames per s using 40% of the spectral measurements required by the well-known Shannon/Nyquist theory. The data processing and image display were performed on a conventional workstation having three graphics processing units.
DEFF Research Database (Denmark)
Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan
2012-01-01
The primal–dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1–26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems...... for the purpose of designing iterative image reconstruction algorithms for CT. The primal–dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application...... modeling breast CT with low-intensity x-ray illumination is presented....
Ahn, Kang-Hyun; Halpern, Howard J
2007-03-01
Spectral-spatial images reconstructed from a small number of projections suffer from streak artifacts that are seen as noise, particularly in the spectral dimension. Interpolation in projection space can reduce artifacts in the reconstructed images. The reduction of background artifacts improves lineshape fitting. In this work, we compared the performances of angular interpolation implemented using linear, cubic B-spline, and sinc methods. Line width maps were extracted from 4-D EPR images of phantoms using spectral fitting to evaluate each interpolation method and its robustness to noise. Results from experiment and simulation showed that the cubic B-spline, angular interpolation was preferable to either sinc or linear interpolation methods.
Noise-Compensating Algebraic Reconstruction for a Rotational Modulation Gamma-Ray Imager
Budden, B; Cherry, M L
2010-01-01
Imaging in the hard X-ray/gamma ray spectrum requires techniques which involve the spatial or temporal modulation of incident photons. A deconvolution of the observed data is then implemented to reconstruct an image of the object scene. In practice, noise in the data contributes to poor quality in the reconstructed image. The use of statistical deconvolution techniques is a common practice in astronomical and medical physics applications to compensate for this noise. In the case of the Rotational Modulator (RM), however, an algebraic technique is required to achieve "super-resolution". We present the RM and the advantages it offers over more traditional approaches, and describe an image reconstruction technique based on an algebraic solution with compensation for noise.