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...... applications. This thesis takes a systematic approach toward establishing quantitative understanding of conditions for sparse reconstruction to work well in CT. A general framework for analyzing sparse reconstruction methods in CT is introduced and two sets of computational tools are proposed: 1...... contributions to a general set of computational characterization tools. Thus, the thesis contributions help advance sparse reconstruction methods toward routine use in...
Proton computed tomography images with algebraic reconstruction
Energy Technology Data Exchange (ETDEWEB)
Bruzzi, M. [Physics and Astronomy Department, University of Florence, Florence (Italy); Civinini, C.; Scaringella, M. [INFN - Florence Division, Florence (Italy); Bonanno, D. [INFN - Catania Division, Catania (Italy); Brianzi, M. [INFN - Florence Division, Florence (Italy); Carpinelli, M. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Cirrone, G.A.P.; Cuttone, G. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Presti, D. Lo [INFN - Catania Division, Catania (Italy); Physics and Astronomy Department, University of Catania, Catania (Italy); Maccioni, G. [INFN – Cagliari Division, Cagliari (Italy); Pallotta, S. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Randazzo, N. [INFN - Catania Division, Catania (Italy); Romano, F. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Sipala, V. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Talamonti, C. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Vanzi, E. [Fisica Sanitaria, Azienda Ospedaliero-Universitaria Senese, Siena (Italy)
2017-02-11
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 <1 mm, achieved within processing times of ~15′ for a 512×512 pixels image prove that this technique will be beneficial if used instead of X-CT in hadron-therapy.
Speeding up image reconstruction in computed tomography
CERN. Geneva
2018-01-01
Computed tomography (CT) is a technique for imaging cross-sections of an object using X-ray measurements taken from different angles. In last decades a significant progress has happened there: today advanced algorithms allow fast image reconstruction and obtaining high-quality images even with missing or dirty data, modern detectors provide high resolution without increasing radiation dose, and high-performance multi-core computing devices are there to help us solving such tasks even faster. I will start with CT basics, then briefly present existing classes of reconstruction algorithms and their differences. After that I will proceed to employing distinctive architectural features of modern multi-core devices (CPUs and GPUs) and popular program interfaces (OpenMP, MPI, CUDA, OpenCL) for developing effective parallel realizations of image reconstruction algorithms. Decreasing full reconstruction time from long hours up to minutes or even seconds has a revolutionary impact in diagnostic medicine and industria...
Image reconstruction. Application to transverse axial tomography
International Nuclear Information System (INIS)
Aubry, Florent.
1977-09-01
A method of computerized tridimensional image reconstruction from their projection, especially in the computerized transverse axial tomography is suggested. First, the different techniques actually developped and presented in the literature are analyzed. Then, the equipment used is briefly described. The reconstruction algorithm developped is presented. This algorithm is based on the convolution method, well adapted to the real conditions of exploitation. It is an extension of SHEPP and LOGAN's algorithm. A correction of the self absorption and of the detector's response is proposed. Finally, the first results obtained which are satisfactory are given. The simplicity of the method which does not need a too long computation time makes possible the implementation of the algorithm on a mini-computer [fr
Simulated annealing image reconstruction for positron emission tomography
Energy Technology Data Exchange (ETDEWEB)
Sundermann, E; Lemahieu, I; Desmedt, P [Department of Electronics and Information Systems, University of Ghent, St. Pietersnieuwstraat 41, B-9000 Ghent, Belgium (Belgium)
1994-12-31
In Positron Emission Tomography (PET) images have to be reconstructed from moisy projection data. The noise on the PET data can be modeled by a Poison distribution. In this paper, we present the results of using the simulated annealing technique to reconstruct PET images. Various parameter settings of the simulated annealing algorithm are discussed and optimized. The reconstructed images are of good quality and high contrast, in comparison to other reconstruction techniques. (authors). 11 refs., 2 figs.
Simulated annealing image reconstruction for positron emission tomography
International Nuclear Information System (INIS)
Sundermann, E.; Lemahieu, I.; Desmedt, P.
1994-01-01
In Positron Emission Tomography (PET) images have to be reconstructed from moisy projection data. The noise on the PET data can be modeled by a Poison distribution. In this paper, we present the results of using the simulated annealing technique to reconstruct PET images. Various parameter settings of the simulated annealing algorithm are discussed and optimized. The reconstructed images are of good quality and high contrast, in comparison to other reconstruction techniques. (authors)
Image reconstruction methods in positron tomography
International Nuclear Information System (INIS)
Townsend, D.W.; Defrise, M.
1993-01-01
In 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-ray but also for studies which explore the functional status of the body using positron-emitting radioisotopes. This report reviews the historical and physical basis of medical imaging techniques using positron-emitting radioisotopes. Mathematical methods which enable three-dimensional distributions of radioisotopes to be reconstructed from projection data (sinograms) acquired by detectors suitably positioned around the patient are discussed. The extension of conventional two-dimensional tomographic reconstruction algorithms to fully three-dimensional reconstruction is described in detail. (orig.)
Bayesian image reconstruction for improving detection performance of muon tomography.
Wang, Guobao; Schultz, Larry J; Qi, Jinyi
2009-05-01
Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.
Image-reconstruction methods in positron tomography
Townsend, David W; CERN. Geneva
1993-01-01
Physics and mathematics for medical imaging In 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...
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 For Bioluminescence Tomography From Partial Measurement
Jiang, M.; Zhou, T.; Cheng, J. T.; Cong, W. X.; Wang, Ge
2007-01-01
The bioluminescence tomography is a novel molecular imaging technology for small animal studies. Known reconstruction methods require the completely measured data on the external surface, although only partially measured data is available in practice. In this work, we formulate a mathematical model for BLT from partial data and generalize our previous results on the solution uniqueness to the partial data case. Then we extend two of our reconstruction methods for BLT to this case. The first m...
Matrix-based image reconstruction methods for tomography
International Nuclear Information System (INIS)
Llacer, J.; Meng, J.D.
1984-10-01
Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures
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.
A neural network image reconstruction technique for electrical impedance tomography
International Nuclear Information System (INIS)
Adler, A.; Guardo, R.
1994-01-01
Reconstruction of Images in Electrical Impedance Tomography requires the solution of a nonlinear inverse problem on noisy data. This problem is typically ill-conditioned and requires either simplifying assumptions or regularization based on a priori knowledge. This paper presents a reconstruction algorithm using neural network techniques which calculates a linear approximation of the inverse problem directly from finite element simulations of the forward problem. This inverse is adapted to the geometry of the medium and the signal-to-noise ratio (SNR) used during network training. Results show good conductivity reconstruction where measurement SNR is similar to the training conditions. The advantages of this method are its conceptual simplicity and ease of implementation, and the ability to control the compromise between the noise performance and resolution of the image reconstruction
Image Reconstruction Algorithm For Electrical Capacitance Tomography (ECT)
International Nuclear Information System (INIS)
Arko
2001-01-01
). Most image reconstruction algorithms for electrical capacitance tomography (ECT) use sensitivity maps as weighting factors. The computation is fast, involving a simple multiply-and- accumulate (MAC) operation, but the resulting image suffers from blurring due to the soft-field effect of the sensor. This paper presents a low cost iterative method employing proportional thresholding, which improves image quality dramatically. The strategy for implementation, computational cost, and achievable speed is examined when using a personal computer (PC) and Digital Signal Processor (DSP). For PC implementation, Watcom C++ 10.6 and Visual C++ 5.0 compilers were used. The experimental results are compared to the images reconstructed by commercially available software. The new algorithm improves the image quality significantly at a cost of a few iterations. This technique can be readily exploited for online applications
Development of Image Reconstruction Algorithms in electrical Capacitance Tomography
International Nuclear Information System (INIS)
Fernandez Marron, J. L.; Alberdi Primicia, J.; Barcala Riveira, J. M.
2007-01-01
The Electrical Capacitance Tomography (ECT) has not obtained a good development in order to be used at industrial level. That is due first to difficulties in the measurement of very little capacitances (in the range of femto farads) and second to the problem of reconstruction on- line of the images. This problem is due also to the small numbers of electrodes (maximum 16), that made the usual algorithms of reconstruction has many errors. In this work it is described a new purely geometrical method that could be used for this purpose. (Author) 4 refs
International Nuclear Information System (INIS)
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
Image reconstruction in computerized tomography using the convolution method
International Nuclear Information System (INIS)
Oliveira Rebelo, A.M. de.
1984-03-01
In the present work an algoritin was derived, using the analytical convolution method (filtered back-projection) for two-dimensional or three-dimensional image reconstruction in computerized tomography applied to non-destructive testing and to the medical use. This mathematical model is based on the analytical Fourier transform method for image reconstruction. This model consists of a discontinuous system formed by an NxN array of cells (pixels). The attenuation in the object under study of a colimated gamma ray beam has been determined for various positions and incidence angles (projections) in terms of the interaction of the beam with the intercepted pixels. The contribution of each pixel to beam attenuation was determined using the weight function W ij which was used for simulated tests. Simulated tests using standard objects with attenuation coefficients in the range of 0,2 to 0,7 cm -1 were carried out using cell arrays of up to 25x25. One application was carried out in the medical area simulating image reconstruction of an arm phantom with attenuation coefficients in the range of 0,2 to 0,5 cm -1 using cell arrays of 41x41. The simulated results show that, in objects with a great number of interfaces and great variations of attenuation coefficients at these interfaces, a good reconstruction is obtained with the number of projections equal to the reconstruction matrix dimension. A good reconstruction is otherwise obtained with fewer projections. (author) [pt
Development of computed tomography system and image reconstruction algorithm
International Nuclear Information System (INIS)
Khairiah Yazid; Mohd Ashhar Khalid; Azaman Ahmad; Khairul Anuar Mohd Salleh; Ab Razak Hamzah
2006-01-01
Computed tomography is one of the most advanced and powerful nondestructive inspection techniques, which is currently used in many different industries. In several CT systems, detection has been by combination of an X-ray image intensifier and charge -coupled device (CCD) camera or by using line array detector. The recent development of X-ray flat panel detector has made fast CT imaging feasible and practical. Therefore this paper explained the arrangement of a new detection system which is using the existing high resolution (127 μm pixel size) flat panel detector in MINT and the image reconstruction technique developed. The aim of the project is to develop a prototype flat panel detector based CT imaging system for NDE. The prototype consisted of an X-ray tube, a flat panel detector system, a rotation table and a computer system to control the sample motion and image acquisition. Hence this project is divided to two major tasks, firstly to develop image reconstruction algorithm and secondly to integrate X-ray imaging components into one CT system. The image reconstruction algorithm using filtered back-projection method is developed and compared to other techniques. The MATLAB program is the tools used for the simulations and computations for this project. (Author)
Image-reconstruction algorithms for positron-emission tomography systems
International Nuclear Information System (INIS)
Cheng, S.N.C.
1982-01-01
The positional uncertainty in the time-of-flight measurement of a positron-emission tomography system is modelled as a Gaussian distributed random variable and the image is assumed to be piecewise constant on a rectilinear lattice. A reconstruction algorithm using maximum-likelihood estimation is derived for the situation in which time-of-flight data are sorted as the most-likely-position array. The algorithm is formulated as a linear system described by a nonseparable, block-banded, Toeplitz matrix, and a sine-transform technique is used to implement this algorithm efficiently. The reconstruction algorithms for both the most-likely-position array and the confidence-weighted array are described by similar equations, hence similar linear systems can be used to described the reconstruction algorithm for a discrete, confidence-weighted array, when the matrix and the entries in the data array are properly identified. It is found that the mean square-error depends on the ratio of the full width at half the maximum of time-of-flight measurement over the size of a pixel. When other parameters are fixed, the larger the pixel size, the smaller is the mean square-error. In the study of resolution, parameters that affect the impulse response of time-of-flight reconstruction algorithms are identified. It is found that the larger the pixel size, the larger is the standard deviation of the impulse response. This shows that small mean square-error and fine resolution are two contradictory requirements
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
Improved proton computed tomography by dual modality image reconstruction
International Nuclear Information System (INIS)
Hansen, David C.; Bassler, Niels; Petersen, Jørgen Breede Baltzer; Sørensen, Thomas Sangild
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 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
Monte-Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography
International Nuclear Information System (INIS)
Gillam, John E.; Rafecas, Magdalena
2016-01-01
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.
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.
First results of genetic algorithm application in ML image reconstruction in emission tomography
International Nuclear Information System (INIS)
Smolik, W.
1999-01-01
This paper concerns application of genetic algorithm in maximum likelihood image reconstruction in emission tomography. The example of genetic algorithm for image reconstruction is presented. The genetic algorithm was based on the typical genetic scheme modified due to the nature of solved problem. The convergence of algorithm was examined. The different adaption functions, selection and crossover methods were verified. The algorithm was tested on simulated SPECT data. The obtained results of image reconstruction are discussed. (author)
Directory of Open Access Journals (Sweden)
Chen Deyun
2013-01-01
Full Text Available According to the image reconstruction accuracy influenced by the “soft field” nature and ill-conditioned problems in electrical capacitance tomography, a superresolution image reconstruction algorithm based on Landweber is proposed in the paper, which is based on the working principle of the electrical capacitance tomography system. The method uses the algorithm which is derived by regularization of solutions derived and derives closed solution by fast Fourier transform of the convolution kernel. So, it ensures the certainty of the solution and improves the stability and quality of image reconstruction results. Simulation results show that the imaging precision and real-time imaging of the algorithm are better than Landweber algorithm, and this algorithm proposes a new method for the electrical capacitance tomography image reconstruction algorithm.
Monte Carlo simulation of gamma ray tomography for image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Guedes, Karlos A.N.; Moura, Alex; Dantas, Carlos; Melo, Silvio; Lima, Emerson, E-mail: karlosguedes@hotmail.com [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil); Meric, Ilker [University of Bergen (Norway)
2015-07-01
The Monte Carlo simulations of known density and shape object was validate with Gamma Ray Tomography in static experiments. An aluminum half-moon piece placed inside a steel pipe was the MC simulation test object that was also measured by means of gamma ray transmission. Wall effect of the steel pipe due to irradiation geometry in a single pair source-detector tomography was evaluated by comparison with theoretical data. MCNPX code requires a defined geometry to each photon trajectory which practically prevents this usage for tomography reconstruction simulation. The solution was found by writing a program in Delphi language to create input files automation code. Simulations of tomography data by automated MNCPX code were carried out and validated by experimental data. Working in this sequence the produced data needed a databank to be stored. Experimental setup used a Cesium-137 isotopic radioactive source (7.4 × 109 Bq), and NaI(Tl) scintillation detector of (51 × 51) × 10−3 m crystal size coupled to a multichannel analyzer. A stainless steel tubes of 0,154 m internal diameter, 0.014 m thickness wall. The results show that the MCNPX simulation code adapted to automated input file is useful for generating a matrix data M(θ,t), of a computerized gamma ray tomography for any known density and regular shape object. Experimental validation used RMSE from gamma ray paths and from attenuation coefficient data. (author)
SU-E-I-73: Clinical Evaluation of CT Image Reconstructed Using Interior Tomography
International Nuclear Information System (INIS)
Zhang, J; Ge, G; Winkler, M; Cong, W; Wang, G
2014-01-01
Purpose: Radiation dose reduction has been a long standing challenge in CT imaging of obese patients. Recent advances in interior tomography (reconstruction of an interior region of interest (ROI) from line integrals associated with only paths through the ROI) promise to achieve significant radiation dose reduction without compromising image quality. This study is to investigate the application of this technique in CT imaging through evaluating imaging quality reconstructed from patient data. Methods: Projection data were directly obtained from patients who had CT examinations in a Dual Source CT scanner (DSCT). Two detectors in a DSCT acquired projection data simultaneously. One detector provided projection data for full field of view (FOV, 50 cm) while another detectors provided truncated projection data for a FOV of 26 cm. Full FOV CT images were reconstructed using both filtered back projection and iterative algorithm; while interior tomography algorithm was implemented to reconstruct ROI images. For comparison reason, FBP was also used to reconstruct ROI images. Reconstructed CT images were evaluated by radiologists and compared with images from CT scanner. Results: The results show that the reconstructed ROI image was in excellent agreement with the truth inside the ROI, obtained from images from CT scanner, and the detailed features in the ROI were quantitatively accurate. Radiologists evaluation shows that CT images reconstructed with interior tomography met diagnosis requirements. Radiation dose may be reduced up to 50% using interior tomography, depending on patient size. Conclusion: This study shows that interior tomography can be readily employed in CT imaging for radiation dose reduction. It may be especially useful in imaging obese patients, whose subcutaneous tissue is less clinically relevant but may significantly increase radiation dose
Freyer, Marcus; Ale, Angelique; Schulz, Ralf B; Zientkowska, Marta; Ntziachristos, Vasilis; Englmeier, Karl-Hans
2010-01-01
The recent development of hybrid imaging scanners that integrate fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) allows the utilization of x-ray information as image priors for improving optical tomography reconstruction. To fully capitalize on this capacity, we consider a framework for the automatic and fast detection of different anatomic structures in murine XCT images. To accurately differentiate between different structures such as bone, lung, and heart, a combination of image processing steps including thresholding, seed growing, and signal detection are found to offer optimal segmentation performance. The algorithm and its utilization in an inverse FMT scheme that uses priors is demonstrated on mouse images.
Image Reconstruction of Metal Pipe in Electrical Resistance Tomography
Directory of Open Access Journals (Sweden)
Suzanna RIDZUAN AW
2017-02-01
Full Text Available This paper demonstrates a Linear Back Projection (LBP algorithm based on the reconstruction of conductivity distributions to identify different sizes and locations of bubble phantoms in a metal pipe. Both forward and inverse problems are discussed. Reconstructed images of the phantoms under test conditions are presented. From the results, it was justified that the sensitivity maps of the conducting boundary strategy can be applied successfully in identifying the location for the phantom of interest using LBP algorithm. Additionally, the number and spatial distribution of the bubble phantoms can be clearly distinguished at any location in the pipeline. It was also shown that the reconstructed images agree well with the bubble phantoms.
Bindu, G; Semenov, S
2013-01-01
This paper describes an efficient two-dimensional fused image reconstruction approach for Microwave Tomography (MWT). Finite Difference Time Domain (FDTD) models were created for a viable MWT experimental system having the transceivers modelled using thin wire approximation with resistive voltage sources. Born Iterative and Distorted Born Iterative methods have been employed for image reconstruction with the extremity imaging being done using a differential imaging technique. The forward solver in the imaging algorithm employs the FDTD method of solving the time domain Maxwell's equations with the regularisation parameter computed using a stochastic approach. The algorithm is tested with 10% noise inclusion and successful image reconstruction has been shown implying its robustness.
Wang, Kun; Huang, Chao; Kao, Yu-Jiun; Chou, Cheng-Ying; Oraevsky, Alexander A; Anastasio, Mark A
2013-02-01
Optoacoustic tomography (OAT) is inherently a three-dimensional (3D) inverse problem. However, most studies of OAT image reconstruction still employ two-dimensional 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. 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 graphics 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 accuracy of the developed algorithms. The GPU implementations improve the computational efficiency by factors of 1000, 125, and 250 for the FBP algorithm and the two pairs of projection/backprojection operators, respectively. Accurate images are reconstructed by use of the FBP and iterative image reconstruction algorithms from both computer-simulated and experimental data. Parallelization strategies for 3D OAT image reconstruction are proposed for the first time. These GPU-based implementations significantly reduce the computational time for 3D image reconstruction, complementing our earlier work on 3D OAT iterative image reconstruction.
Image reconstruction from projections and its application in emission computer tomography
International Nuclear Information System (INIS)
Kuba, Attila; Csernay, Laszlo
1989-01-01
Computer tomography is an imaging technique for producing cross sectional images by reconstruction from projections. Its two main branches are called transmission and emission computer tomography, TCT and ECT, resp. After an overview of the theory and practice of TCT and ECT, the first Hungarian ECT type MB 9300 SPECT consisting of a gamma camera and Ketronic Medax N computer is described, and its applications to radiological patient observations are discussed briefly. (R.P.) 28 refs.; 4 figs
Principles of image reconstruction in X-ray computer tomography
International Nuclear Information System (INIS)
Schwierz, G.; Haerer, W.; Ruehrnschopf, E.P.
1978-01-01
The presented geometrical interpretation elucidates the convergence behavior of the classical iteration technique in X-ray computer tomography. The filter techniques nowadays used in preference are derived from a concept of linear system theory which excels due to its particular clarity. The one-dimensional form of the filtering is of decisive importance for immediate image reproduction as realized by both Siemens systems, the SIRETOM 2000 head scanner and the SOMATOM whole-body machine, as such unique to date for whole-body machines. The equivalence of discrete and continuous filtering when dealing with frequency-band-limited projections is proved. (orig.) [de
Novel image reconstruction algorithm for multi-phase flow tomography system using γ ray method
International Nuclear Information System (INIS)
Hao Kuihong; Wang Huaxiang; Gao Mei
2007-01-01
After analyzing the reason of image reconstructed algorithm by using the conventional back projection (IBP) is prone to produce spurious line, and considering the characteristic of multi-phase flow tomography, a novel image reconstruction algorithm is proposed, which carries out the intersection calculation using back projection data. This algorithm can obtain a perfect system point spread function, and can eliminate spurious line better. Simulating results show that the algorithm is effective for identifying multi-phase flow pattern. (authors)
International Nuclear Information System (INIS)
Song, Xizi; Xu, Yanbin; Dong, Feng
2017-01-01
Electrical resistance tomography (ERT) is a promising measurement technique with important industrial and clinical applications. However, with limited effective measurements, it suffers from poor spatial resolution due to the ill-posedness of the inverse problem. Recently, there has been an increasing research interest in hybrid imaging techniques, utilizing couplings of physical modalities, because these techniques obtain much more effective measurement information and promise high resolution. Ultrasound modulated electrical impedance tomography (UMEIT) is one of the newly developed hybrid imaging techniques, which combines electric and acoustic modalities. A linearized image reconstruction method based on power density is proposed for UMEIT. The interior data, power density distribution, is adopted to reconstruct the conductivity distribution with the proposed image reconstruction method. At the same time, relating the power density change to the change in conductivity, the Jacobian matrix is employed to make the nonlinear problem into a linear one. The analytic formulation of this Jacobian matrix is derived and its effectiveness is also verified. In addition, different excitation patterns are tested and analyzed, and opposite excitation provides the best performance with the proposed method. Also, multiple power density distributions are combined to implement image reconstruction. Finally, image reconstruction is implemented with the linear back-projection (LBP) algorithm. Compared with ERT, with the proposed image reconstruction method, UMEIT can produce reconstructed images with higher quality and better quantitative evaluation results. (paper)
Guan, Huifeng; Anastasio, Mark A.
2017-03-01
It is well-known that properly designed image reconstruction methods can facilitate reductions in imaging doses and data-acquisition times in tomographic imaging. The ability to do so is particularly important for emerging modalities such as differential X-ray phase-contrast tomography (D-XPCT), which are currently limited by these factors. An important application of D-XPCT is high-resolution imaging of biomedical samples. However, reconstructing high-resolution images from few-view tomographic measurements remains a challenging task. In this work, a two-step sub-space reconstruction strategy is proposed and investigated for use in few-view D-XPCT image reconstruction. It is demonstrated that the resulting iterative algorithm can mitigate the high-frequency information loss caused by data incompleteness and produce images that have better preserved high spatial frequency content than those produced by use of a conventional penalized least squares (PLS) estimator.
Research on Image Reconstruction Algorithms for Tuber Electrical Resistance Tomography System
Directory of Open Access Journals (Sweden)
Jiang Zili
2016-01-01
Full Text Available The application of electrical resistance tomography (ERT technology has been expanded to the field of agriculture, and the concept of TERT (Tuber Electrical Resistance Tomography is proposed. On the basis of the research on the forward and the inverse problems of the TERT system, a hybrid algorithm based on genetic algorithm is proposed, which can be used in TERT system to monitor the growth status of the plant tubers. The image reconstruction of TERT system is different from the conventional ERT system for two phase-flow measurement. Imaging of TERT needs more precision measurement and the conventional ERT cares more about the image reconstruction speed. A variety of algorithms are analyzed and optimized for the purpose of making them suitable for TERT system. For example: linear back projection, modified Newton-Raphson and genetic algorithm. Experimental results showed that the novel hybrid algorithm is superior to other algorithm and it can effectively improve the image reconstruction quality.
Directory of Open Access Journals (Sweden)
Jing Wang
2013-01-01
Full Text Available The image reconstruction for electrical impedance tomography (EIT mathematically is a typed nonlinear ill-posed inverse problem. In this paper, a novel iteration regularization scheme based on the homotopy perturbation technique, namely, homotopy perturbation inversion method, is applied to investigate the EIT image reconstruction problem. To verify the feasibility and effectiveness, simulations of image reconstruction have been performed in terms of considering different locations, sizes, and numbers of the inclusions, as well as robustness to data noise. Numerical results indicate that this method can overcome the numerical instability and is robust to data noise in the EIT image reconstruction. Moreover, compared with the classical Landweber iteration method, our approach improves the convergence rate. The results are promising.
Electro-optical system for the high speed reconstruction of computed tomography images
International Nuclear Information System (INIS)
Tresp, V.
1989-01-01
An electro-optical system for the high-speed reconstruction of computed tomography (CT) images has been built and studied. The system is capable of reconstructing high-contrast and high-resolution images at video rate (30 images per second), which is more than two orders of magnitude faster than the reconstruction rate achieved by special purpose digital computers used in commercial CT systems. The filtered back-projection algorithm which was implemented in the reconstruction system requires the filtering of all projections with a prescribed filter function. A space-integrating acousto-optical convolver, a surface acoustic wave filter and a digital finite-impulse response filter were used for this purpose and their performances were compared. The second part of the reconstruction, the back projection of the filtered projections, is computationally very expensive. An optical back projector has been built which maps the filtered projections onto the two-dimensional image space using an anamorphic lens system and a prism image rotator. The reconstructed image is viewed by a video camera, routed through a real-time image-enhancement system, and displayed on a TV monitor. The system reconstructs parallel-beam projection data, and in a modified version, is also capable of reconstructing fan-beam projection data. This extension is important since the latter are the kind of projection data actually acquired in high-speed X-ray CT scanners. The reconstruction system was tested by reconstructing precomputed projection data of phantom images. These were stored in a special purpose projection memory and transmitted to the reconstruction system as an electronic signal. In this way, a projection measurement system that acquires projections sequentially was simulated
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...
Image alignment for tomography reconstruction from synchrotron X-ray microscopic images.
Directory of Open Access Journals (Sweden)
Chang-Chieh Cheng
Full Text Available A synchrotron X-ray microscope is a powerful imaging apparatus for taking high-resolution and high-contrast X-ray images of nanoscale objects. A sufficient number of X-ray projection images from different angles is required for constructing 3D volume images of an object. Because a synchrotron light source is immobile, a rotational object holder is required for tomography. At a resolution of 10 nm per pixel, the vibration of the holder caused by rotating the object cannot be disregarded if tomographic images are to be reconstructed accurately. This paper presents a computer method to compensate for the vibration of the rotational holder by aligning neighboring X-ray images. This alignment process involves two steps. The first step is to match the "projected feature points" in the sequence of images. The matched projected feature points in the x-θ plane should form a set of sine-shaped loci. The second step is to fit the loci to a set of sine waves to compute the parameters required for alignment. The experimental results show that the proposed method outperforms two previously proposed methods, Xradia and SPIDER. The developed software system can be downloaded from the URL, http://www.cs.nctu.edu.tw/~chengchc/SCTA or http://goo.gl/s4AMx.
Image alignment for tomography reconstruction from synchrotron X-ray microscopic images.
Cheng, Chang-Chieh; Chien, Chia-Chi; Chen, Hsiang-Hsin; Hwu, Yeukuang; Ching, Yu-Tai
2014-01-01
A synchrotron X-ray microscope is a powerful imaging apparatus for taking high-resolution and high-contrast X-ray images of nanoscale objects. A sufficient number of X-ray projection images from different angles is required for constructing 3D volume images of an object. Because a synchrotron light source is immobile, a rotational object holder is required for tomography. At a resolution of 10 nm per pixel, the vibration of the holder caused by rotating the object cannot be disregarded if tomographic images are to be reconstructed accurately. This paper presents a computer method to compensate for the vibration of the rotational holder by aligning neighboring X-ray images. This alignment process involves two steps. The first step is to match the "projected feature points" in the sequence of images. The matched projected feature points in the x-θ plane should form a set of sine-shaped loci. The second step is to fit the loci to a set of sine waves to compute the parameters required for alignment. The experimental results show that the proposed method outperforms two previously proposed methods, Xradia and SPIDER. The developed software system can be downloaded from the URL, http://www.cs.nctu.edu.tw/~chengchc/SCTA or http://goo.gl/s4AMx.
Image reconstruction with an adaptive threshold technique in electrical resistance tomography
International Nuclear Information System (INIS)
Kim, Bong Seok; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn
2011-01-01
In electrical resistance tomography, electrical currents are injected through the electrodes placed on the surface of a domain and the corresponding voltages are measured. Based on these currents and voltage data, the cross-sectional resistivity distribution is reconstructed. Electrical resistance tomography shows high temporal resolution for monitoring fast transient processes, but it still remains a challenging problem to improve the spatial resolution of the reconstructed images. In this paper, a novel image reconstruction technique is proposed to improve the spatial resolution by employing an adaptive threshold method to the iterative Gauss–Newton method. Numerical simulations and phantom experiments have been performed to illustrate the superior performance of the proposed scheme in the sense of spatial resolution
An ART iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging
International Nuclear Information System (INIS)
Wang Zhentian; Zhang Li; Huang Zhifeng; Kang Kejun; Chen Zhiqiang; Fang Qiaoguang; Zhu Peiping
2009-01-01
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). (authors)
International Nuclear Information System (INIS)
Zhou, Weifeng; Cai, Jian-Feng; Gao, Hao
2013-01-01
A popular approach for medical image reconstruction has been through the sparsity regularization, assuming the targeted image can be well approximated by sparse coefficients under some properly designed system. The wavelet tight frame is such a widely used system due to its capability for sparsely approximating piecewise-smooth functions, such as medical images. However, using a fixed system may not always be optimal for reconstructing a variety of diversified images. Recently, the method based on the adaptive over-complete dictionary that is specific to structures of the targeted images has demonstrated its superiority for image processing. This work is to develop the adaptive wavelet tight frame method image reconstruction. The proposed scheme first constructs the adaptive wavelet tight frame that is task specific, and then reconstructs the image of interest by solving an l 1 -regularized minimization problem using the constructed adaptive tight frame system. The proof-of-concept study is performed for computed tomography (CT), and the simulation results suggest that the adaptive tight frame method improves the reconstructed CT image quality from the traditional tight frame method. (paper)
Liang, Zhiting; Guan, Yong; Liu, Gang; Chen, Xiangyu; Li, Fahu; Guo, Pengfei; Tian, Yangchao
2016-03-01
The `missing wedge', which is due to a restricted rotation range, is a major challenge for quantitative analysis of an object using tomography. With prior knowledge of the grey levels, the discrete algebraic reconstruction technique (DART) is able to reconstruct objects accurately with projections in a limited angle range. However, the quality of the reconstructions declines as the number of grey levels increases. In this paper, a modified DART (MDART) was proposed, in which each independent region of homogeneous material was chosen as a research object, instead of the grey values. The grey values of each discrete region were estimated according to the solution of the linear projection equations. The iterative process of boundary pixels updating and correcting the grey values of each region was executed alternately. Simulation experiments of binary phantoms as well as multiple grey phantoms show that MDART is capable of achieving high-quality reconstructions with projections in a limited angle range. The interesting advancement of MDART is that neither prior knowledge of the grey values nor the number of grey levels is necessary.
Model-based respiratory motion compensation for emission tomography image reconstruction
International Nuclear Information System (INIS)
Reyes, M; Malandain, G; Koulibaly, P M; Gonzalez-Ballester, M A; Darcourt, J
2007-01-01
In emission tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations, imprecise diagnosis, impairing of fusion with other modalities, etc. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested, which lead to improvements over the spatial activity distribution in lungs lesions, but which have the disadvantages of requiring additional instrumentation or the need of discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion compensation directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the maximum likelihood expectation maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data
International Nuclear Information System (INIS)
Chen, Shuhang; Liu, Huafeng; Shi, Pengcheng; Chen, Yunmei
2015-01-01
Accurate and robust reconstruction of the radioactivity concentration is of great importance in positron emission tomography (PET) imaging. Given the Poisson nature of photo-counting measurements, we present a reconstruction framework that integrates sparsity penalty on a dictionary into a maximum likelihood estimator. Patch-sparsity on a dictionary provides the regularization for our effort, and iterative procedures are used to solve the maximum likelihood function formulated on Poisson statistics. Specifically, in our formulation, a dictionary could be trained on CT images, to provide intrinsic anatomical structures for the reconstructed images, or adaptively learned from the noisy measurements of PET. Accuracy of the strategy with very promising application results from Monte-Carlo simulations, and real data are demonstrated. (paper)
ℓ0 Gradient Minimization Based Image Reconstruction for Limited-Angle Computed Tomography.
Directory of Open Access Journals (Sweden)
Wei Yu
Full Text Available In medical and industrial applications of computed tomography (CT imaging, limited by the scanning environment and the risk of excessive X-ray radiation exposure imposed to the patients, reconstructing high quality CT images from limited projection data has become a hot topic. X-ray imaging in limited scanning angular range is an effective imaging modality to reduce the radiation dose to the patients. As the projection data available in this modality are incomplete, limited-angle CT image reconstruction is actually an ill-posed inverse problem. To solve the problem, image reconstructed by conventional filtered back projection (FBP algorithm frequently results in conspicuous streak artifacts and gradual changed artifacts nearby edges. Image reconstruction based on total variation minimization (TVM can significantly reduce streak artifacts in few-view CT, but it suffers from the gradual changed artifacts nearby edges in limited-angle CT. To suppress this kind of artifacts, we develop an image reconstruction algorithm based on ℓ0 gradient minimization for limited-angle CT in this paper. The ℓ0-norm of the image gradient is taken as the regularization function in the framework of developed reconstruction model. We transformed the optimization problem into a few optimization sub-problems and then, solved these sub-problems in the manner of alternating iteration. Numerical experiments are performed to validate the efficiency and the feasibility of the developed algorithm. From the statistical analysis results of the performance evaluations peak signal-to-noise ratio (PSNR and normalized root mean square distance (NRMSD, it shows that there are significant statistical differences between different algorithms from different scanning angular ranges (p<0.0001. From the experimental results, it also indicates that the developed algorithm outperforms classical reconstruction algorithms in suppressing the streak artifacts and the gradual changed
International Nuclear Information System (INIS)
Niki, Noboru; Mizutani, Toshio; Takahashi, Yoshizo; Inouye, Tamon.
1983-01-01
The nescessity for developing real-time computerized tomography (CT) aiming at the dynamic observation of organs such as hearts has lately been advocated. It is necessary for its realization to reconstruct the images which are markedly faster than present CTs. Although various reconstructing methods have been proposed so far, the method practically employed at present is the filtered backprojection (FBP) method only, which can give high quality image reconstruction, but takes much computing time. In the past, the two-dimensional Fourier transform (TFT) method was regarded as unsuitable to practical use because the quality of images obtained was not good, in spite of the promising method for high speed reconstruction because of its less computing time. However, since it was revealed that the image quality by TFT method depended greatly on interpolation accuracy in two-dimensional Fourier space, the authors have developed a high-speed calculation algorithm that can obtain high quality images by pursuing the relationship between the image quality and the interpolation method. In this case, radial data sampling points in Fourier space are increased to β-th power of 2 times, and the linear or spline interpolation is used. Comparison of this method with the present FBP method resulted in the conclusion that the image quality is almost the same in practical image matrix, the computational time by TFT method becomes about 1/10 of FBP method, and the memory capacity also reduces by about 20 %. (Wakatsuki, Y.)
An Lq–Lp optimization framework for image reconstruction of electrical resistance tomography
International Nuclear Information System (INIS)
Zhao, Jia; Xu, Yanbin; Dong, Feng
2014-01-01
Image reconstruction in electrical resistance tomography (ERT) is an ill-posed and nonlinear problem, which is easily affected by measurement noise. The regularization method with L 2 constraint term or L 1 constraint term is often used to solve the inverse problem of ERT. It shows that the reconstruction method with L 2 regularization puts smoothness to obtain stability in the image reconstruction process, which is blurry at the interface of different conductivities. The regularization method with L 1 norm is powerful at dealing with the over-smoothing effects, which is beneficial in obtaining a sharp transaction in conductivity distribution. To find the reason for these effects, an L q –L p optimization framework (1 ⩽ q ⩽ 2, 1 ⩽ p ⩽ 2) for the image reconstruction of ERT is presented in this paper. The L q –L p optimization framework is solved based on an approximation handling with Gauss–Newton iteration algorithm. The optimization framework is tested for image reconstruction of ERT with different models and the effects of the L p regularization term on the quality of the reconstructed images are discussed with both simulation and experiment. By comparing the reconstructed results with different p in the regularization term, it is found that a large penalty is implemented on small data in the solution when p is small and a lesser penalty is implemented on small data in the solution when p is larger. It also makes the reconstructed images smoother and more easily affected by noise when p is larger. (paper)
International Nuclear Information System (INIS)
Watanabe, Shuichi; Kudo, Hiroyuki; Saito, Tsuneo
1993-01-01
In this paper, we propose a new reconstruction algorithm based on MAP (maximum a posteriori probability) estimation principle for emission tomography. To improve noise suppression properties of the conventional ML-EM (maximum likelihood expectation maximization) algorithm, direct three-dimensional reconstruction that utilizes intensity correlations between adjacent transaxial slices is introduced. Moreover, to avoid oversmoothing of edges, a priori knowledge of RI (radioisotope) distribution is represented by using a doubly-stochastic image model called the compound Gauss-Markov random field. The a posteriori probability is maximized by using the iterative GEM (generalized EM) algorithm. Computer simulation results are shown to demonstrate validity of the proposed algorithm. (author)
A comparison framework for temporal image reconstructions in electrical impedance tomography
International Nuclear Information System (INIS)
Gagnon, Hervé; Adler, Andy; Grychtol, Bartłomiej
2015-01-01
Electrical impedance tomography (EIT) provides low-resolution images of internal conductivity distributions, but is able to achieve relatively high temporal resolutions. Most EIT image reconstruction algorithms do not explicitly account for the temporal constraints on the measurements or physiological processes under investigation. Instead, algorithms typically assume both that the conductivity distribution does not change during the acquisition of each EIT data frame, and that frames can be reconstructed independently, without consideration of the correlation between images. A failure to account for these temporal effects will result in aliasing-related artefacts in images. Several methods have been proposed to compensate for these effects, including interpolation of raw data, and reconstruction algorithms using Kalman and temporal filtering. However, no systematic work has been performed to understand the severity of the temporal artefacts nor the extent to which algorithms can account for them. We seek to address this need by developing a temporal comparison framework and figures of merit to assess the ability of reconstruction algorithms to account for temporal effects. Using this approach, we compare combinations of three reconstruction algorithms using three EIT data frame types: perfect, realistic and interpolated. The results show that, without accounting for temporal effects, artefacts are present in images for dynamic conductivity contrasts at frequencies 10–20 times slower than the frame rate. The proposed methods show some improvements in reducing these artefacts. (paper)
Huang, Hsuan-Ming; Hsiao, Ing-Tsung
2017-01-01
Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.
Full field image reconstruction is suitable for high-pitch dual-source computed tomography.
Mahnken, Andreas H; Allmendinger, Thomas; Sedlmair, Martin; Tamm, Miriam; Reinartz, Sebastian D; Flohr, Thomas
2012-11-01
The field of view (FOV) in high-pitch dual-source computed tomography (DSCT) is limited by the size of the second detector. The goal of this study was to develop and evaluate a full FOV image reconstruction technique for high-pitch DSCT. For reconstruction beyond the FOV of the second detector, raw data of the second system were extended to the full dimensions of the first system, using the partly existing data of the first system in combination with a very smooth transition weight function. During the weighted filtered backprojection, the data of the second system were applied with an additional weighting factor. This method was tested for different pitch values from 1.5 to 3.5 on a simulated phantom and on 25 high-pitch DSCT data sets acquired at pitch values of 1.6, 2.0, 2.5, 2.8, and 3.0. Images were reconstructed with FOV sizes of 260 × 260 and 500 × 500 mm. Image quality was assessed by 2 radiologists using a 5-point Likert scale and analyzed with repeated-measure analysis of variance. In phantom and patient data, full FOV image quality depended on pitch. Where complete projection data from both tube-detector systems were available, image quality was unaffected by pitch changes. Full FOV image quality was not compromised at pitch values of 1.6 and remained fully diagnostic up to a pitch of 2.0. At higher pitch values, there was an increasing difference in image quality between limited and full FOV images (P = 0.0097). With this new image reconstruction technique, full FOV image reconstruction can be used up to a pitch of 2.0.
Cai, Ailong; Li, Lei; Zheng, Zhizhong; Zhang, Hanming; Wang, Linyuan; Hu, Guoen; Yan, Bin
2018-02-01
In medical imaging many conventional regularization methods, such as total variation or total generalized variation, impose strong prior assumptions which can only account for very limited classes of images. A more reasonable sparse representation frame for images is still badly needed. Visually understandable images contain meaningful patterns, and combinations or collections of these patterns can be utilized to form some sparse and redundant representations which promise to facilitate image reconstructions. In this work, we propose and study block matching sparsity regularization (BMSR) and devise an optimization program using BMSR for computed tomography (CT) image reconstruction for an incomplete projection set. The program is built as a constrained optimization, minimizing the L1-norm of the coefficients of the image in the transformed domain subject to data observation and positivity of the image itself. To solve the program efficiently, a practical method based on the proximal point algorithm is developed and analyzed. In order to accelerate the convergence rate, a practical strategy for tuning the BMSR parameter is proposed and applied. The experimental results for various settings, including real CT scanning, have verified the proposed reconstruction method showing promising capabilities over conventional regularization.
Energy Technology Data Exchange (ETDEWEB)
Velo, Alexandre F.; Carvalho, Diego V.; Alvarez, Alexandre G.; Hamada, Margarida M.; Mesquita, Carlos H., E-mail: afvelo@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2017-07-01
The greatest impact of the tomography technology currently occurs in medicine. The success is due to the human body presents standardized dimensions with well-established composition. These conditions are not found in industrial objects. In industry, there is much interest in using the tomography in order to know the inner of (1) the manufactured industrial objects or (2) the machines and their means of production. In these cases, the purpose of the tomography is to (a) control the quality of the final product and (b) to optimize production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. This scan system is a non-destructive, efficient and fast method for providing sectional images of industrial objects and is able to show the dynamic processes and the dispersion of the materials structures within these objects. In this context, it is important that the reconstructed image presents a great spatial resolution with a satisfactory temporal resolution. Thus the algorithm to reconstruct the images has to meet these requirements. This work consists in the analysis of three different iterative algorithm methods, such Maximum Likelihood Estimation Method (MLEM), Maximum Likelihood Transmitted Method (MLTR) and Simultaneous Iterative Reconstruction Method (SIRT. The analysis consists on measurement of the contrast to noise ratio (CNR), the root mean square error (RMSE) and the Modulation Transfer Function (MTF), to know which algorithm fits better the conditions in order to optimize system. The algorithms and the image quality analysis were performed by the Matlab® 2013b. (author)
International Nuclear Information System (INIS)
Velo, Alexandre F.; Carvalho, Diego V.; Alvarez, Alexandre G.; Hamada, Margarida M.; Mesquita, Carlos H.
2017-01-01
The greatest impact of the tomography technology currently occurs in medicine. The success is due to the human body presents standardized dimensions with well-established composition. These conditions are not found in industrial objects. In industry, there is much interest in using the tomography in order to know the inner of (1) the manufactured industrial objects or (2) the machines and their means of production. In these cases, the purpose of the tomography is to (a) control the quality of the final product and (b) to optimize production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. This scan system is a non-destructive, efficient and fast method for providing sectional images of industrial objects and is able to show the dynamic processes and the dispersion of the materials structures within these objects. In this context, it is important that the reconstructed image presents a great spatial resolution with a satisfactory temporal resolution. Thus the algorithm to reconstruct the images has to meet these requirements. This work consists in the analysis of three different iterative algorithm methods, such Maximum Likelihood Estimation Method (MLEM), Maximum Likelihood Transmitted Method (MLTR) and Simultaneous Iterative Reconstruction Method (SIRT. The analysis consists on measurement of the contrast to noise ratio (CNR), the root mean square error (RMSE) and the Modulation Transfer Function (MTF), to know which algorithm fits better the conditions in order to optimize system. The algorithms and the image quality analysis were performed by the Matlab® 2013b. (author)
Precht, Helle; Thygesen, Jesper; Gerke, Oke; Egstrup, Kenneth; Waaler, Dag; Lambrechtsen, Jess
2016-12-01
Coronary computed tomography angiography (CCTA) requires high spatial and temporal resolution, increased low contrast resolution for the assessment of coronary artery stenosis, plaque detection, and/or non-coronary pathology. Therefore, new reconstruction algorithms, particularly iterative reconstruction (IR) techniques, have been developed in an attempt to improve image quality with no cost in radiation exposure. To evaluate whether adaptive statistical iterative reconstruction (ASIR) enhances perceived image quality in CCTA compared to filtered back projection (FBP). Thirty patients underwent CCTA due to suspected coronary artery disease. Images were reconstructed using FBP, 30% ASIR, and 60% ASIR. Ninety image sets were evaluated by five observers using the subjective visual grading analysis (VGA) and assessed by proportional odds modeling. Objective quality assessment (contrast, noise, and the contrast-to-noise ratio [CNR]) was analyzed with linear mixed effects modeling on log-transformed data. The need for ethical approval was waived by the local ethics committee as the study only involved anonymously collected clinical data. VGA showed significant improvements in sharpness by comparing FBP with ASIR, resulting in odds ratios of 1.54 for 30% ASIR and 1.89 for 60% ASIR ( P = 0.004). The objective measures showed significant differences between FBP and 60% ASIR ( P < 0.0001) for noise, with an estimated ratio of 0.82, and for CNR, with an estimated ratio of 1.26. ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR.
International Nuclear Information System (INIS)
Dong, Xiangyuan; Guo, Shuqing
2008-01-01
In this paper, a novel image reconstruction method for electrical capacitance tomography (ECT) based on the combined series and parallel model is presented. A regularization technique is used to obtain a stabilized solution of the inverse problem. Also, the adaptive coefficient of the combined model is deduced by numerical optimization. Simulation results indicate that it can produce higher quality images when compared to the algorithm based on the parallel or series models for the cases tested in this paper. It provides a new algorithm for ECT application
Model-based image reconstruction in X-ray computed tomography
Zbijewski, Wojciech Bartosz
2006-01-01
The thesis investigates the applications of iterative, statistical reconstruction (SR) algorithms in X-ray Computed Tomography. Emphasis is put on various aspects of system modeling in statistical reconstruction. Fundamental issues such as effects of object discretization and algorithm
Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method
Baikejiang, Reheman; Zhao, Yue; Fite, Brett Z.; Ferrara, Katherine W.; Li, Changqing
2017-01-01
Abstract. Fluorescence molecular tomography (FMT) is an important in vivo imaging modality to visualize physiological and pathological processes in small animals. However, FMT reconstruction is ill-posed and ill-conditioned due to strong optical scattering in deep tissues, which results in poor spatial resolution. It is well known that FMT image quality can be improved substantially by applying the structural guidance in the FMT reconstruction. An approach to introducing anatomical information into the FMT reconstruction is presented using the kernel method. In contrast to conventional methods that incorporate anatomical information with a Laplacian-type regularization matrix, the proposed method introduces the anatomical guidance into the projection model of FMT. The primary advantage of the proposed method is that it does not require segmentation of targets in the anatomical images. Numerical simulations and phantom experiments have been performed to demonstrate the proposed approach’s feasibility. Numerical simulation results indicate that the proposed kernel method can separate two FMT targets with an edge-to-edge distance of 1 mm and is robust to false-positive guidance and inhomogeneity in the anatomical image. For the phantom experiments with two FMT targets, the kernel method has reconstructed both targets successfully, which further validates the proposed kernel method. PMID:28464120
International Nuclear Information System (INIS)
Michel, Eric; Hernandez, Daniel; Cho, Min Hyoung; Lee, Soo Yeol
2014-01-01
Purpose: To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B 1 + maps in electrical properties tomography (EPT). Methods: In EPT, electrical property images are computed by taking Laplacian of the B 1 + maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B 1 + maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finite-difference time-domain models. They evaluated the EPT images comparing them with the ones obtained by previous EPT reconstruction methods. Results: In both the EPT simulations and experiments, the nonlinear filtering greatly improved the EPT image quality when evaluated in terms of the mean and standard deviation of the electrical property values at the regions of interest. The proposed method also improved the overall similarity between the reconstructed conductivity images and the true shapes of the conductivity distribution. Conclusions: The nonlinear denoising enabled us to obtain better-quality EPT images of the phantoms and the human brain at 3 T
Mezgebo, Biniyam; Nagib, Karim; Fernando, Namal; Kordi, Behzad; Sherif, Sherif
2018-02-01
Swept Source optical coherence tomography (SS-OCT) is an important imaging modality for both medical and industrial diagnostic applications. A cross-sectional SS-OCT image is obtained by applying an inverse discrete Fourier transform (DFT) to axial interferograms measured in the frequency domain (k-space). This inverse DFT is typically implemented as a fast Fourier transform (FFT) that requires the data samples to be equidistant in k-space. As the frequency of light produced by a typical wavelength-swept laser is nonlinear in time, the recorded interferogram samples will not be uniformly spaced in k-space. Many image reconstruction methods have been proposed to overcome this problem. Most such methods rely on oversampling the measured interferogram then use either hardware, e.g., Mach-Zhender interferometer as a frequency clock module, or software, e.g., interpolation in k-space, to obtain equally spaced samples that are suitable for the FFT. To overcome the problem of nonuniform sampling in k-space without any need for interferogram oversampling, an earlier method demonstrated the use of the nonuniform discrete Fourier transform (NDFT) for image reconstruction in SS-OCT. In this paper, we present a more accurate method for SS-OCT image reconstruction from nonuniform samples in k-space using a scaled nonuniform Fourier transform. The result is demonstrated using SS-OCT images of Axolotl salamander eggs.
International Nuclear Information System (INIS)
Sato, Jiro; Akahane, Masaaki; Inano, Sachiko; Terasaki, Mariko; Akai, Hiroyuki; Katsura, Masaki; Matsuda, Izuru; Kunimatsu, Akira; Ohtomo, Kuni
2012-01-01
The purpose of this study was to assess the effects of dose and adaptive statistical iterative reconstruction (ASIR) on image quality of pulmonary computed tomography (CT). Inflated and fixed porcine lungs were scanned with a 64-slice CT system at 10, 20, 40 and 400 mAs. Using automatic exposure control, 40 mAs was chosen as standard dose. Scan data were reconstructed with filtered back projection (FBP) and ASIR. Image pairs were obtained by factorial combination of images at a selected level. Using a 21-point scale, three experienced radiologists independently rated differences in quality between adjacently displayed paired images for image noise, image sharpness and conspicuity of tiny nodules. A subjective quality score (SQS) for each image was computed based on Anderson's functional measurement theory. The standard deviation was recorded as a quantitative noise measurement. At all doses examined, SQSs improved with ASIR for all evaluation items. No significant differences were noted between the SQSs for 40%-ASIR images obtained at 20 mAs and those for FBP images at 40 mAs. Compared to the FBP algorithm, ASIR for lung CT can enable an approximately 50% dose reduction from the standard dose while preserving visualization of small structures. (author)
Barca, Patrizio; Giannelli, Marco; Fantacci, Maria Evelina; Caramella, Davide
2018-06-01
Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.
Bai, Bing
2012-03-01
There has been a lot of work on total variation (TV) regularized tomographic image reconstruction recently. Many of them use gradient-based optimization algorithms with a differentiable approximation of the TV functional. In this paper we apply TV regularization in Positron Emission Tomography (PET) image reconstruction. We reconstruct the PET image in a Bayesian framework, using Poisson noise model and TV prior functional. The original optimization problem is transformed to an equivalent problem with inequality constraints by adding auxiliary variables. Then we use an interior point method with logarithmic barrier functions to solve the constrained optimization problem. In this method, a series of points approaching the solution from inside the feasible region are found by solving a sequence of subproblems characterized by an increasing positive parameter. We use preconditioned conjugate gradient (PCG) algorithm to solve the subproblems directly. The nonnegativity constraint is enforced by bend line search. The exact expression of the TV functional is used in our calculations. Simulation results show that the algorithm converges fast and the convergence is insensitive to the values of the regularization and reconstruction parameters.
Correia, Teresa; Koch, Maximilian; Ale, Angelique; Ntziachristos, Vasilis; Arridge, Simon
2016-02-21
Fluorescence diffuse optical tomography (fDOT) provides 3D images of fluorescence distributions in biological tissue, which represent molecular and cellular processes. The image reconstruction problem is highly ill-posed and requires regularisation techniques to stabilise and find meaningful solutions. Quadratic regularisation tends to either oversmooth or generate very noisy reconstructions, depending on the regularisation strength. Edge preserving methods, such as anisotropic diffusion regularisation (AD), can preserve important features in the fluorescence image and smooth out noise. However, AD has limited ability to distinguish an edge from noise. We propose a patch-based anisotropic diffusion regularisation (PAD), where regularisation strength is determined by a weighted average according to the similarity between patches around voxels within a search window, instead of a simple local neighbourhood strategy. However, this method has higher computational complexity and, hence, we wavelet compress the patches (PAD-WT) to speed it up, while simultaneously taking advantage of the denoising properties of wavelet thresholding. Furthermore, structural information can be incorporated into the image reconstruction with PAD-WT to improve image quality and resolution. In this case, the weights used to average voxels in the image are calculated using the structural image, instead of the fluorescence image. The regularisation strength depends on both structural and fluorescence images, which guarantees that the method can preserve fluorescence information even when it is not structurally visible in the anatomical images. In part 1, we tested the method using a denoising problem. Here, we use simulated and in vivo mouse fDOT data to assess the algorithm performance. Our results show that the proposed PAD-WT method provides high quality and noise free images, superior to those obtained using AD.
Effect of The Measuring Parameters on The Reconstructed Images by Computerized Tomography
International Nuclear Information System (INIS)
Ali, A.M.; Ali, A.M.; Megahid, R.M.
2011-01-01
In this paper, the potential of computerized tomography by neutrons and gamma rays as a main precise technique for nondestructive assay of materials and components of prime importance in nuclear and general industries are given and discussed. Both Fast Fourier Transform (FFT) and convolution techniques are introduced. Shepp and Logan human head phantom is used for theoretical testing and studying the effect of translation value for both techniques. Moreover, the effect of the projection number discussed. Comparison between the two reconstruction techniques wasper formed for the examined object. In addition, some of the experimentally scanned images using slit beam of gamma rays emitt ed from the ETRR- 1 reactor are presented and discussed.
Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T
The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P ASIR 80% had the best and worst spatial resolution, respectively. Adaptive statistical iterative reconstruction-V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.
International Nuclear Information System (INIS)
Matsuda, Izuru; Hanaoka, Shohei; Akahane, Masaaki
2010-01-01
Adaptive statistical iterative reconstruction (ASIR) is a reconstruction technique for computed tomography (CT) that reduces image noise. The purpose of our study was to investigate whether ASIR improves the quality of volume-rendered (VR) CT portovenography. Institutional review board approval, with waived consent, was obtained. A total of 19 patients (12 men, 7 women; mean age 69.0 years; range 25-82 years) suspected of having liver lesions underwent three-phase enhanced CT. VR image sets were prepared with both the conventional method and ASIR. The required time to make VR images was recorded. Two radiologists performed independent qualitative evaluations of the image sets. The Wilcoxon signed-rank test was used for statistical analysis. Contrast-noise ratios (CNRs) of the portal and hepatic vein were also evaluated. Overall image quality was significantly improved by ASIR (P<0.0001 and P=0.0155 for each radiologist). ASIR enhanced CNRs of the portal and hepatic vein significantly (P<0.0001). The time required to create VR images was significantly shorter with ASIR (84.7 vs. 117.1 s; P=0.014). ASIR enhances CNRs and improves image quality in VR CT portovenography. It also shortens the time required to create liver VR CT portovenographs. (author)
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Wang Jiajun
2010-05-01
Full Text Available Abstract Background The inverse problem of fluorescent molecular tomography (FMT often involves complex large-scale matrix operations, which may lead to unacceptable computational errors and complexity. In this research, a tree structured Schur complement decomposition strategy is proposed to accelerate the reconstruction process and reduce the computational complexity. Additionally, an adaptive regularization scheme is developed to improve the ill-posedness of the inverse problem. Methods The global system is decomposed level by level with the Schur complement system along two paths in the tree structure. The resultant subsystems are solved in combination with the biconjugate gradient method. The mesh for the inverse problem is generated incorporating the prior information. During the reconstruction, the regularization parameters are adaptive not only to the spatial variations but also to the variations of the objective function to tackle the ill-posed nature of the inverse problem. Results Simulation results demonstrate that the strategy of the tree structured Schur complement decomposition obviously outperforms the previous methods, such as the conventional Conjugate-Gradient (CG and the Schur CG methods, in both reconstruction accuracy and speed. As compared with the Tikhonov regularization method, the adaptive regularization scheme can significantly improve ill-posedness of the inverse problem. Conclusions The methods proposed in this paper can significantly improve the reconstructed image quality of FMT and accelerate the reconstruction process.
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Helle Precht
2016-12-01
Full Text Available Background Coronary computed tomography angiography (CCTA requires high spatial and temporal resolution, increased low contrast resolution for the assessment of coronary artery stenosis, plaque detection, and/or non-coronary pathology. Therefore, new reconstruction algorithms, particularly iterative reconstruction (IR techniques, have been developed in an attempt to improve image quality with no cost in radiation exposure. Purpose To evaluate whether adaptive statistical iterative reconstruction (ASIR enhances perceived image quality in CCTA compared to filtered back projection (FBP. Material and Methods Thirty patients underwent CCTA due to suspected coronary artery disease. Images were reconstructed using FBP, 30% ASIR, and 60% ASIR. Ninety image sets were evaluated by five observers using the subjective visual grading analysis (VGA and assessed by proportional odds modeling. Objective quality assessment (contrast, noise, and the contrast-to-noise ratio [CNR] was analyzed with linear mixed effects modeling on log-transformed data. The need for ethical approval was waived by the local ethics committee as the study only involved anonymously collected clinical data. Results VGA showed significant improvements in sharpness by comparing FBP with ASIR, resulting in odds ratios of 1.54 for 30% ASIR and 1.89 for 60% ASIR (P = 0.004. The objective measures showed significant differences between FBP and 60% ASIR (P < 0.0001 for noise, with an estimated ratio of 0.82, and for CNR, with an estimated ratio of 1.26. Conclusion ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR.
Wang, Qi; Wang, Huaxiang; Cui, Ziqiang; Yang, Chengyi
2012-11-01
Electrical impedance tomography (EIT) calculates the internal conductivity distribution within a body using electrical contact measurements. The image reconstruction for EIT is an inverse problem, which is both non-linear and ill-posed. The traditional regularization method cannot avoid introducing negative values in the solution. The negativity of the solution produces artifacts in reconstructed images in presence of noise. A statistical method, namely, the expectation maximization (EM) method, is used to solve the inverse problem for EIT in this paper. The mathematical model of EIT is transformed to the non-negatively constrained likelihood minimization problem. The solution is obtained by the gradient projection-reduced Newton (GPRN) iteration method. This paper also discusses the strategies of choosing parameters. Simulation and experimental results indicate that the reconstructed images with higher quality can be obtained by the EM method, compared with the traditional Tikhonov and conjugate gradient (CG) methods, even with non-negative processing. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography
Sidky, Emil Y.; Kraemer, David N.; Roth, Erin G.; Ullberg, Christer; Reiser, Ingrid S.; Pan, Xiaochuan
2014-01-01
Abstract. One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data. PMID:25685824
Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography.
Sidky, Emil Y; Kraemer, David N; Roth, Erin G; Ullberg, Christer; Reiser, Ingrid S; Pan, Xiaochuan
2014-10-03
One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data.
International Nuclear Information System (INIS)
Qi Zhihua; Chen Guanghong
2007-01-01
Recently, x-ray differential phase contrast computed tomography (DPC-CT) has been experimentally implemented using a conventional source combined with several gratings. Images were reconstructed using a parallel-beam reconstruction formula. However, parallel-beam reconstruction formulae are not directly applicable for a large image object where the parallel-beam approximation fails. In this note, we present a new image reconstruction formula for fan-beam DPC-CT. There are two major features in this algorithm: (1) it enables the reconstruction of a local region of interest (ROI) using data acquired from an angular interval shorter than 180 0 + fan angle and (2) it still preserves the filtered backprojection structure. Numerical simulations have been conducted to validate the image reconstruction algorithm. (note)
International Nuclear Information System (INIS)
Rampado, O.; Bossi, L.; Garabello, D.; Davini, O.; Ropolo, R.
2012-01-01
Objective: This study aims to investigate the consequences on dose and image quality of the choices of different combinations of NI and adaptive statistical iterative reconstruction (ASIR) percentage, the image quality parameters of GE CT equipment. Methods: An anthropomorphic phantom was used to simulate the chest and upper abdomen of a standard weight patient. Images were acquired with tube current modulation and different values of noise index, in the range 10–22 for a slice thickness of 5 mm and a tube voltage of 120 kV. For each selected noise index, several image series were reconstructed using different percentages of ASIR (0, 40, 50, 60, 70, 100). Quantitative noise was assessed at different phantom locations. Computed tomography dose index (CTDI) and dose length products (DLP) were recorded. Three radiologists reviewed the images in a blinded and randomized manner and assessed the subjective image quality by comparing the image series with the one acquired with the reference protocol (noise index 14, ASIR 40%). The perceived noise, contrast, edge sharpness and overall quality were graded on a scale from −2 (much worse) to +2 (much better). Results: A repeatable trend of noise reduction versus the percentage of ASIR was observed for different noise levels and phantom locations. The different combinations of noise index and percentage of ASIR to obtain a desired dose reduction were assessed. The subjective image quality evaluation evidenced a possible dose reduction between 24 and 40% as a consequence of an increment of ASIR percentage to 50 or 70%, respectively. Conclusion: These results highlighted that the same patient dose reduction can be obtained with several combinations of noise index and percentages of ASIR, providing a model with which to choose these acquisition parameters in future optimization studies, with the aim of reducing patient dose by maintaining image quality in diagnostic levels.
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Rampado, O., E-mail: orampado@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Bossi, L., E-mail: laura-bossi@hotmail.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Garabello, D., E-mail: dgarabello@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Davini, O., E-mail: odavini@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Ropolo, R., E-mail: rropolo@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy)
2012-11-15
Objective: This study aims to investigate the consequences on dose and image quality of the choices of different combinations of NI and adaptive statistical iterative reconstruction (ASIR) percentage, the image quality parameters of GE CT equipment. Methods: An anthropomorphic phantom was used to simulate the chest and upper abdomen of a standard weight patient. Images were acquired with tube current modulation and different values of noise index, in the range 10-22 for a slice thickness of 5 mm and a tube voltage of 120 kV. For each selected noise index, several image series were reconstructed using different percentages of ASIR (0, 40, 50, 60, 70, 100). Quantitative noise was assessed at different phantom locations. Computed tomography dose index (CTDI) and dose length products (DLP) were recorded. Three radiologists reviewed the images in a blinded and randomized manner and assessed the subjective image quality by comparing the image series with the one acquired with the reference protocol (noise index 14, ASIR 40%). The perceived noise, contrast, edge sharpness and overall quality were graded on a scale from -2 (much worse) to +2 (much better). Results: A repeatable trend of noise reduction versus the percentage of ASIR was observed for different noise levels and phantom locations. The different combinations of noise index and percentage of ASIR to obtain a desired dose reduction were assessed. The subjective image quality evaluation evidenced a possible dose reduction between 24 and 40% as a consequence of an increment of ASIR percentage to 50 or 70%, respectively. Conclusion: These results highlighted that the same patient dose reduction can be obtained with several combinations of noise index and percentages of ASIR, providing a model with which to choose these acquisition parameters in future optimization studies, with the aim of reducing patient dose by maintaining image quality in diagnostic levels.
Improved iterative image reconstruction algorithm for the exterior problem of computed tomography
International Nuclear Information System (INIS)
Guo, Yumeng; Zeng, Li
2017-01-01
In industrial applications that are limited by the angle of a fan-beam and the length of a detector, the exterior problem of computed tomography (CT) uses only the projection data that correspond to the external annulus of the objects to reconstruct an image. Because the reconstructions are not affected by the projection data that correspond to the interior of the objects, the exterior problem is widely applied to detect cracks in the outer wall of large-sized objects, such as in-service pipelines. However, image reconstruction in the exterior problem is still a challenging problem due to truncated projection data and beam-hardening, both of which can lead to distortions and artifacts. Thus, developing an effective algorithm and adopting a scanning trajectory suited for the exterior problem may be valuable. In this study, an improved iterative algorithm that combines total variation minimization (TVM) with a region scalable fitting (RSF) model was developed for a unilateral off-centered scanning trajectory and can be utilized to inspect large-sized objects for defects. Experiments involving simulated phantoms and real projection data were conducted to validate the practicality of our algorithm. Furthermore, comparative experiments show that our algorithm outperforms others in suppressing the artifacts caused by truncated projection data and beam-hardening.
Improved iterative image reconstruction algorithm for the exterior problem of computed tomography
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Guo, Yumeng [Chongqing University, College of Mathematics and Statistics, Chongqing 401331 (China); Chongqing University, ICT Research Center, Key Laboratory of Optoelectronic Technology and System of the Education Ministry of China, Chongqing 400044 (China); Zeng, Li, E-mail: drlizeng@cqu.edu.cn [Chongqing University, College of Mathematics and Statistics, Chongqing 401331 (China); Chongqing University, ICT Research Center, Key Laboratory of Optoelectronic Technology and System of the Education Ministry of China, Chongqing 400044 (China)
2017-01-11
In industrial applications that are limited by the angle of a fan-beam and the length of a detector, the exterior problem of computed tomography (CT) uses only the projection data that correspond to the external annulus of the objects to reconstruct an image. Because the reconstructions are not affected by the projection data that correspond to the interior of the objects, the exterior problem is widely applied to detect cracks in the outer wall of large-sized objects, such as in-service pipelines. However, image reconstruction in the exterior problem is still a challenging problem due to truncated projection data and beam-hardening, both of which can lead to distortions and artifacts. Thus, developing an effective algorithm and adopting a scanning trajectory suited for the exterior problem may be valuable. In this study, an improved iterative algorithm that combines total variation minimization (TVM) with a region scalable fitting (RSF) model was developed for a unilateral off-centered scanning trajectory and can be utilized to inspect large-sized objects for defects. Experiments involving simulated phantoms and real projection data were conducted to validate the practicality of our algorithm. Furthermore, comparative experiments show that our algorithm outperforms others in suppressing the artifacts caused by truncated projection data and beam-hardening.
Statistical image reconstruction for transmission tomography using relaxed ordered subset algorithms
International Nuclear Information System (INIS)
Kole, J S
2005-01-01
Statistical reconstruction methods offer possibilities for improving image quality as compared to analytical methods, but current reconstruction times prohibit routine clinical applications in x-ray computed tomography (CT). To reduce reconstruction times, we have applied (under) relaxation to ordered subset algorithms. This enables us to use subsets consisting of only single projection angle, effectively increasing the number of image updates within an entire iteration. A second advantage of applying relaxation is that it can help improve convergence by removing the limit cycle behaviour of ordered subset algorithms, which normally do not converge to an optimal solution but rather a suboptimal limit cycle consisting of as many points as there are subsets. Relaxation suppresses the limit cycle behaviour by decreasing the stepsize for approaching the solution. A simulation study for a 2D mathematical phantom and three different ordered subset algorithms shows that all three algorithms benefit from relaxation: equal noise-to-resolution trade-off can be achieved using fewer iterations than the conventional algorithms, while a lower minimal normalized mean square error (NMSE) clearly indicates a better convergence. Two different schemes for setting the relaxation parameter are studied, and both schemes yield approximately the same minimal NMSE
Okuda, Kyohei; Sakimoto, Shota; Fujii, Susumu; Ida, Tomonobu; Moriyama, Shigeru
The frame-of-reference using computed-tomography (CT) coordinate system on single-photon emission computed tomography (SPECT) reconstruction is one of the advanced characteristics of the xSPECT reconstruction system. The aim of this study was to reveal the influence of the high-resolution frame-of-reference on the xSPECT reconstruction. 99m Tc line-source phantom and National Electrical Manufacturers Association (NEMA) image quality phantom were scanned using the SPECT/CT system. xSPECT reconstructions were performed with the reference CT images in different sizes of the display field-of-view (DFOV) and pixel. The pixel sizes of the reconstructed xSPECT images were close to 2.4 mm, which is acquired as originally projection data, even if the reference CT resolution was varied. The full width at half maximum (FWHM) of the line-source, absolute recovery coefficient, and background variability of image quality phantom were independent on the sizes of DFOV in the reference CT images. The results of this study revealed that the image quality of the reconstructed xSPECT images is not influenced by the resolution of frame-of-reference on SPECT reconstruction.
Zhang, Hua; Huang, Jing; Ma, Jianhua; Bian, Zhaoying; Feng, Qianjin; Lu, Hongbing; Liang, Zhengrong; Chen, Wufan
2014-09-01
Repeated X-ray computed tomography (CT) scans are often required in several specific applications such as perfusion imaging, image-guided biopsy needle, image-guided intervention, and radiotherapy with noticeable benefits. However, the associated cumulative radiation dose significantly increases as comparison with that used in the conventional CT scan, which has raised major concerns in patients. In this study, to realize radiation dose reduction by reducing the X-ray tube current and exposure time (mAs) in repeated CT scans, we propose a prior-image induced nonlocal (PINL) regularization for statistical iterative reconstruction via the penalized weighted least-squares (PWLS) criteria, which we refer to as "PWLS-PINL". Specifically, the PINL regularization utilizes the redundant information in the prior image and the weighted least-squares term considers a data-dependent variance estimation, aiming to improve current low-dose image quality. Subsequently, a modified iterative successive overrelaxation algorithm is adopted to optimize the associative objective function. Experimental results on both phantom and patient data show that the present PWLS-PINL method can achieve promising gains over the other existing methods in terms of the noise reduction, low-contrast object detection, and edge detail preservation.
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Thomas Weidinger
2016-01-01
Full Text Available This work proposes a dedicated statistical algorithm to perform a direct reconstruction of material-decomposed images from data acquired with photon-counting detectors (PCDs in computed tomography. It is based on local approximations (surrogates of the negative logarithmic Poisson probability function. Exploiting the convexity of this function allows for parallel updates of all image pixels. Parallel updates can compensate for the rather slow convergence that is intrinsic to statistical algorithms. We investigate the accuracy of the algorithm for ideal photon-counting detectors. Complementarily, we apply the algorithm to simulation data of a realistic PCD with its spectral resolution limited by K-escape, charge sharing, and pulse-pileup. For data from both an ideal and realistic PCD, the proposed algorithm is able to correct beam-hardening artifacts and quantitatively determine the material fractions of the chosen basis materials. Via regularization we were able to achieve a reduction of image noise for the realistic PCD that is up to 90% lower compared to material images form a linear, image-based material decomposition using FBP images. Additionally, we find a dependence of the algorithms convergence speed on the threshold selection within the PCD.
International Nuclear Information System (INIS)
Liang, Z.
1994-01-01
A mathematical method was studied to model the detector response of high spatial-resolution positron emission tomography systems consisting of close-packed small crystals, and to restore the resolution deteriorated due to crystal penetration and/or nonuniform sampling across the field-of-view (FOV). The simulated detector system had 600 bismuth germanate crystals of 3.14 mm width and 30 mm length packed on a single ring of 60 cm diameter. The space between crystal was filled up with lead. Each crystal was in coincidence with 200 opposite crystals so that the FOV had a radius of 30 cm. The detector response was modeled based on the attenuating properties of the crystals and the septa, as well as the geometry of the detector system. The modeled detector-response function was used to restore the projections from the sinogram of the ring-detector system. The restored projections had a uniform sampling of 1.57 mm across the FOV. The crystal penetration and/or the nonuniform sampling were compensated in the projections. A penalized maximum-likelihood algorithm was employed to accomplish the restoration. The restored projections were then filtered and backprojected to reconstruct the image. A chest phantom with a few small circular ''cold'' objects located at the center and near the periphery of FOV was computer generated and used to test the restoration. The reconstructed images from the restored projections demonstrated resolution improvement off the FOV center, while preserving the resolution near the center
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Pua, Rizza; Park, Miran; Wi, Sunhee; Cho, Seungryong, E-mail: scho@kaist.ac.kr
2016-12-21
We propose a hybrid metal artifact reduction (MAR) approach for computed tomography (CT) that is computationally more efficient than a fully iterative reconstruction method, but at the same time achieves superior image quality to the interpolation-based in-painting techniques. Our proposed MAR method, an image-based artifact subtraction approach, utilizes an intermediate prior image reconstructed via PDART to recover the background information underlying the high density objects. For comparison, prior images generated by total-variation minimization (TVM) algorithm, as a realization of fully iterative approach, were also utilized as intermediate images. From the simulation and real experimental results, it has been shown that PDART drastically accelerates the reconstruction to an acceptable quality of prior images. Incorporating PDART-reconstructed prior images in the proposed MAR scheme achieved higher quality images than those by a conventional in-painting method. Furthermore, the results were comparable to the fully iterative MAR that uses high-quality TVM prior images. - Highlights: • An accelerated reconstruction method, PDART, is proposed for exterior problems. • With a few iterations, soft prior image was reconstructed from the exterior data. • PDART framework has enabled an efficient hybrid metal artifact reduction in CT.
Deng, Bin; Lundqvist, Mats; Fang, Qianqian; Carp, Stefan A
2018-03-01
Near-infrared diffuse optical tomography (NIR-DOT) is an emerging technology that offers hemoglobin based, functional imaging tumor biomarkers for breast cancer management. The most promising clinical translation opportunities are in the differential diagnosis of malignant vs. benign lesions, and in early response assessment and guidance for neoadjuvant chemotherapy. Accurate quantification of the tissue oxy- and deoxy-hemoglobin concentration across the field of view, as well as repeatability during longitudinal imaging in the context of therapy guidance, are essential for the successful translation of NIR-DOT to clinical practice. The ill-posed and ill-condition nature of the DOT inverse problem makes this technique particularly susceptible to model errors that may occur, for example, when the experimental conditions do not fully match the assumptions built into the image reconstruction process. To evaluate the susceptibility of DOT images to experimental errors that might be encountered in practice for a parallel-plate NIR-DOT system, we simulated 7 different types of errors, each with a range of magnitudes. We generated simulated data by using digital breast phantoms derived from five actual mammograms of healthy female volunteers, to which we added a 1-cm tumor. After applying each of the experimental error types and magnitudes to the simulated measurements, we reconstructed optical images with and without structural prior guidance and assessed the overall error in the total hemoglobin concentrations (HbT) and in the HbT contrast between the lesion and surrounding area vs. the best-case scenarios. It is found that slight in-plane probe misalignment and plate rotation did not result in large quantification errors. However, any out-of-plane probe tilting could result in significant deterioration in lesion contrast. Among the error types investigated in this work, optical images were the least likely to be impacted by breast shape inaccuracies but suffered the
Luo, Shouhua; Shen, Tao; Sun, Yi; Li, Jing; Li, Guang; Tang, Xiangyang
2018-04-01
In high resolution (microscopic) CT applications, the scan field of view should cover the entire specimen or sample to allow complete data acquisition and image reconstruction. However, truncation may occur in projection data and results in artifacts in reconstructed images. In this study, we propose a low resolution image constrained reconstruction algorithm (LRICR) for interior tomography in microscopic CT at high resolution. In general, the multi-resolution acquisition based methods can be employed to solve the data truncation problem if the project data acquired at low resolution are utilized to fill up the truncated projection data acquired at high resolution. However, most existing methods place quite strict restrictions on the data acquisition geometry, which greatly limits their utility in practice. In the proposed LRICR algorithm, full and partial data acquisition (scan) at low and high resolutions, respectively, are carried out. Using the image reconstructed from sparse projection data acquired at low resolution as the prior, a microscopic image at high resolution is reconstructed from the truncated projection data acquired at high resolution. Two synthesized digital phantoms, a raw bamboo culm and a specimen of mouse femur, were utilized to evaluate and verify performance of the proposed LRICR algorithm. Compared with the conventional TV minimization based algorithm and the multi-resolution scout-reconstruction algorithm, the proposed LRICR algorithm shows significant improvement in reduction of the artifacts caused by data truncation, providing a practical solution for high quality and reliable interior tomography in microscopic CT applications. The proposed LRICR algorithm outperforms the multi-resolution scout-reconstruction method and the TV minimization based reconstruction for interior tomography in microscopic CT.
International Nuclear Information System (INIS)
Zvolsky, Milan
2017-12-01
In the scope of the EndoTOFPET-US project, a novel multimodal device for ultrasound (US) endoscopy and positron emission tomography (PET) is being developed. The project aims at detecting and quantifying morphologic and functional biomarkers and developing new biomarkers for pancreas and prostate oncology. The detector system comprises a small detector probe mounted on an ultrasound endoscope and an external detector plate. The detection of the gamma rays is realised by scintillator crystals with Silicon Photomultiplier (SiPM) read-out. For the characterisation of over 4000 SiPMs for the external plate, an automatised measurement and data analysis procedure is established. The key properties of the SiPMs like breakdown voltage and dark count rate (DCR) are extracted. This knowledge is needed both as a quality assurance as well as for the calibration of the detector. The spread between minimum and maximum breakdown voltage within a SiPM array of 4 x 4 is at maximum 0.43 V with a mean of 0.15 V and an RMS of 0.06 V. This assures the optimal biasing of each SiPM at its individual operating voltage. The mean DCR amounts to 1.49 MHz with an RMS of 0.54 MHz and is thus well below the acceptable threshold of 3 MHz. Two spare modules from the external plate are re-measured and analysed several years after the module assembly, revealing a potential alteration of the SiPM noise properties over time. For the characterisation of SiPMs from different vendors, a software framework for the automatic extraction of performance parameters from pulseheight spectra, including a t of the entire spectrum, is developed and tested. In order to facilitate the modelling of the response of the EndoTOFPET-US detector, a framework is developed which is built around the Geant4-based simulation toolkit GAMOS, to simulate and reconstruct realistic imaging scenarios with this asymmetric PET detector. The simulation studies are used to compare different possible detector designs, guide the
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Zvolsky, Milan
2017-12-15
In the scope of the EndoTOFPET-US project, a novel multimodal device for ultrasound (US) endoscopy and positron emission tomography (PET) is being developed. The project aims at detecting and quantifying morphologic and functional biomarkers and developing new biomarkers for pancreas and prostate oncology. The detector system comprises a small detector probe mounted on an ultrasound endoscope and an external detector plate. The detection of the gamma rays is realised by scintillator crystals with Silicon Photomultiplier (SiPM) read-out. For the characterisation of over 4000 SiPMs for the external plate, an automatised measurement and data analysis procedure is established. The key properties of the SiPMs like breakdown voltage and dark count rate (DCR) are extracted. This knowledge is needed both as a quality assurance as well as for the calibration of the detector. The spread between minimum and maximum breakdown voltage within a SiPM array of 4 x 4 is at maximum 0.43 V with a mean of 0.15 V and an RMS of 0.06 V. This assures the optimal biasing of each SiPM at its individual operating voltage. The mean DCR amounts to 1.49 MHz with an RMS of 0.54 MHz and is thus well below the acceptable threshold of 3 MHz. Two spare modules from the external plate are re-measured and analysed several years after the module assembly, revealing a potential alteration of the SiPM noise properties over time. For the characterisation of SiPMs from different vendors, a software framework for the automatic extraction of performance parameters from pulseheight spectra, including a t of the entire spectrum, is developed and tested. In order to facilitate the modelling of the response of the EndoTOFPET-US detector, a framework is developed which is built around the Geant4-based simulation toolkit GAMOS, to simulate and reconstruct realistic imaging scenarios with this asymmetric PET detector. The simulation studies are used to compare different possible detector designs, guide the
Image reconstruction in electrostatic tomography using a priori knowledge from ECT
International Nuclear Information System (INIS)
Zhou Bin; Zhang Jianyong; Xu Chuanlong; Wang Shimin
2011-01-01
Research highlights: → A dual-mode sensor technique based on ECT and EST is proposed. → The interference of the charged particles to ECT can be eliminated. → A priori knowledge from ECT improves the inversion accuracy. - Abstract: In gas-solid two-phase flow, the charge distribution is a very important process parameter which is useful to the study of electrostatic adhesion. Electrostatic tomography (EST) is a relatively new non-intrusive technique which can be used to acquire charge distribution. However, due to limited measurements, the quality of image reconstruction is poor. In this paper, a dual-mode sensor technique based on electrical capacitance tomography (ECT) and EST is proposed. The theoretical analysis and the numerical simulation results reveal that the permittivity distribution obtained from ECT can provide a priori knowledge for the inversion calculation of EST, so that the accuracy of spatial sensitivity calculation in EST can be improved. This proposed technique is expected to be prospective in industrial applications and will also be beneficial to the research on the fluid dynamics of gas-solid two-phase flow.
Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo
The aim of this study was to evaluate the impact on dose reduction and image quality of the new iterative reconstruction technique: adaptive statistical iterative reconstruction (ASIR-V). Fifty consecutive oncologic patients acted as case controls undergoing during their follow-up a computed tomography scan both with ASIR and ASIR-V. Each study was analyzed in a double-blinded fashion by 2 radiologists. Both quantitative and qualitative analyses of image quality were conducted. Computed tomography scanner radiation output was 38% (29%-45%) lower (P ASIR-V examinations than for the ASIR ones. The quantitative image noise was significantly lower (P ASIR-V. Adaptive statistical iterative reconstruction-V had a higher performance for the subjective image noise (P = 0.01 for 5 mm and P = 0.009 for 1.25 mm), the other parameters (image sharpness, diagnostic acceptability, and overall image quality) being similar (P > 0.05). Adaptive statistical iterative reconstruction-V is a new iterative reconstruction technique that has the potential to provide image quality equal to or greater than ASIR, with a dose reduction around 40%.
Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou
2017-07-01
In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.
Hussain, Fahad Ahmed; Mail, Noor; Shamy, Abdulrahman M; Suliman, Alghamdi; Saoudi, Abdelhamid
2016-05-08
Image quality is a key issue in radiology, particularly in a clinical setting where it is important to achieve accurate diagnoses while minimizing radiation dose. Some computed tomography (CT) manufacturers have introduced algorithms that claim significant dose reduction. In this study, we assessed CT image quality produced by two reconstruction algorithms provided with GE Healthcare's Discovery 690 Elite positron emission tomography (PET) CT scanner. Image quality was measured for images obtained at various doses with both conventional filtered back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR) algorithms. A stan-dard CT dose index (CTDI) phantom and a pencil ionization chamber were used to measure the CT dose at 120 kVp and an exposure of 260 mAs. Image quality was assessed using two phantoms. CT images of both phantoms were acquired at tube voltage (kV) of 120 with exposures ranging from 25 mAs to 400 mAs. Images were reconstructed using FBP and ASIR ranging from 10% to 100%, then analyzed for noise, low-contrast detectability, contrast-to-noise ratio (CNR), and modulation transfer function (MTF). Noise was 4.6 HU in water phantom images acquired at 260 mAs/FBP 120 kV and 130 mAs/50% ASIR 120 kV. The large objects (fre-quency ASIR, compared to 260 mAs/FBP. The application of ASIR for small objects (frequency >7 lp/cm) showed poor visibility compared to FBP at 260 mAs and even worse for images acquired at less than 130 mAs. ASIR blending more than 50% at low dose tends to reduce contrast of small objects (frequency >7 lp/cm). We concluded that dose reduction and ASIR should be applied with close attention if the objects to be detected or diagnosed are small (frequency > 7 lp/cm). Further investigations are required to correlate the small objects (frequency > 7 lp/cm) to patient anatomy and clinical diagnosis.
International Nuclear Information System (INIS)
Tereshchenko, Sergei A; Potapov, D A; Podgaetskii, Vitalii M; Smirnov, A V
2002-01-01
A distorting influence of light refraction at the boundaries of scattering media on the results of tomographic reconstruction of images of radially symmetric objects is investigated. The methods for the correction of such refraction-caused distortions are described. The results of the image reconstruction for two model cylindrical objects are presented.
Overview of image reconstruction
International Nuclear Information System (INIS)
Marr, R.B.
1980-04-01
Image reconstruction (or computerized tomography, etc.) is any process whereby a function, f, on R/sup n/ is estimated from empirical data pertaining to its integrals, ∫f(x) dx, for some collection of hyperplanes of dimension k < n. The paper begins with background information on how image reconstruction problems have arisen in practice, and describes some of the application areas of past or current interest; these include radioastronomy, optics, radiology and nuclear medicine, electron microscopy, acoustical imaging, geophysical tomography, nondestructive testing, and NMR zeugmatography. Then the various reconstruction algorithms are discussed in five classes: summation, or simple back-projection; convolution, or filtered back-projection; Fourier and other functional transforms; orthogonal function series expansion; and iterative methods. Certain more technical mathematical aspects of image reconstruction are considered from the standpoint of uniqueness, consistency, and stability of solution. The paper concludes by presenting certain open problems. 73 references
International Nuclear Information System (INIS)
Viana, R.S.; Yoriyaz, H.; Santos, A.
2011-01-01
The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)
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Viana, R.S.; Yoriyaz, H.; Santos, A., E-mail: rodrigossviana@gmail.com, E-mail: hyoriyaz@ipen.br, E-mail: asantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2011-07-01
The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)
International Nuclear Information System (INIS)
Mangat, J.; Morgan, J.; Benson, E.; Baath, M.; Lewis, M.; Reilly, A.
2016-01-01
The recent reintroduction of iterative reconstruction in computed tomography has facilitated the realisation of major dose saving. The aim of this article was to investigate the possibility of achieving further savings at a site with well-established Adaptive Statistical iterative Reconstruction (ASiR TM ) (GE Healthcare) brain protocols. An adult patient study was conducted with observers making visual grading assessments using image quality criteria, which were compared with the frequency domain metrics, noise power spectrum and modulation transfer function. Subjective image quality equivalency was found in the 40-70% ASiR TM range, leading to the proposal of ranges for the objective metrics defining acceptable image quality. Based on the findings of both the patient-based and objective studies of the ASiR TM /tube-current combinations tested, 60%/305 mA was found to fall within all, but one, of these ranges. Therefore, it is recommended that an ASiR TM level of 60%, with a noise index of 12.20, is a viable alternative to the currently used protocol featuring a 40% ASiR TM level and a noise index of 11.20, potentially representing a 16% dose saving. (authors)
Jamaludin, Juliza; Rahim, Ruzairi Abdul; Fazul Rahiman, Mohd Hafiz; Mohd Rohani, Jemmy
2018-04-01
Optical tomography (OPT) is a method to capture a cross-sectional image based on the data obtained by sensors, distributed around the periphery of the analyzed system. This system is based on the measurement of the final light attenuation or absorption of radiation after crossing the measured objects. The number of sensor views will affect the results of image reconstruction, where the high number of sensor views per projection will give a high image quality. This research presents an application of charge-coupled device linear sensor and laser diode in an OPT system. Experiments in detecting solid and transparent objects in crystal clear water were conducted. Two numbers of sensors views, 160 and 320 views are evaluated in this research in reconstructing the images. The image reconstruction algorithms used were filtered images of linear back projection algorithms. Analysis on comparing the simulation and experiments image results shows that, with 320 image views giving less area error than 160 views. This suggests that high image view resulted in the high resolution of image reconstruction.
International Nuclear Information System (INIS)
Park, Justin C.; Kim, Jin Sung; Park, Sung Ho; Liu, Zhaowei; Song, Bongyong; Song, William Y.
2013-01-01
Purpose: Utilization of respiratory correlated four-dimensional cone-beam computed tomography (4DCBCT) has enabled verification of internal target motion and volume immediately prior to treatment. However, with current standard CBCT scan, 4DCBCT poses challenge for reconstruction due to the fact that multiple phase binning leads to insufficient number of projection data to reconstruct and thus cause streaking artifacts. The purpose of this study is to develop a novel 4DCBCT reconstruction algorithm framework called motion-map constrained image reconstruction (MCIR), that allows reconstruction of high quality and high phase resolution 4DCBCT images with no more than the imaging dose as well as projections used in a standard free breathing 3DCBCT (FB-3DCBCT) scan.Methods: The unknown 4DCBCT volume at each phase was mathematically modeled as a combination of FB-3DCBCT and phase-specific update vector which has an associated motion-map matrix. The motion-map matrix, which is the key innovation of the MCIR algorithm, was defined as the matrix that distinguishes voxels that are moving from stationary ones. This 4DCBCT model was then reconstructed with compressed sensing (CS) reconstruction framework such that the voxels with high motion would be aggressively updated by the phase-wise sorted projections and the voxels with less motion would be minimally updated to preserve the FB-3DCBCT. To evaluate the performance of our proposed MCIR algorithm, we evaluated both numerical phantoms and a lung cancer patient. The results were then compared with the (1) clinical FB-3DCBCT reconstructed using the FDK, (2) 4DCBCT reconstructed using the FDK, and (3) 4DCBCT reconstructed using the well-known prior image constrained compressed sensing (PICCS).Results: Examination of the MCIR algorithm showed that high phase-resolved 4DCBCT with sets of up to 20 phases using a typical FB-3DCBCT scan could be reconstructed without compromising the image quality. Moreover, in comparison with
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Park, Justin C. [Center for Advanced Radiotherapy Technologies and Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 and Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093 (United States); Kim, Jin Sung [Department of Radiation Oncology, Samsung Medical Center, Seoul 135-710 (Korea, Republic of); Park, Sung Ho [Department of Medical Physics, Asan Medical Center, College of Medicine, University of Ulsan, Seoul 138-736 (Korea, Republic of); Liu, Zhaowei [Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093 (United States); Song, Bongyong; Song, William Y. [Center for Advanced Radiotherapy Technologies and Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States)
2013-12-15
Purpose: Utilization of respiratory correlated four-dimensional cone-beam computed tomography (4DCBCT) has enabled verification of internal target motion and volume immediately prior to treatment. However, with current standard CBCT scan, 4DCBCT poses challenge for reconstruction due to the fact that multiple phase binning leads to insufficient number of projection data to reconstruct and thus cause streaking artifacts. The purpose of this study is to develop a novel 4DCBCT reconstruction algorithm framework called motion-map constrained image reconstruction (MCIR), that allows reconstruction of high quality and high phase resolution 4DCBCT images with no more than the imaging dose as well as projections used in a standard free breathing 3DCBCT (FB-3DCBCT) scan.Methods: The unknown 4DCBCT volume at each phase was mathematically modeled as a combination of FB-3DCBCT and phase-specific update vector which has an associated motion-map matrix. The motion-map matrix, which is the key innovation of the MCIR algorithm, was defined as the matrix that distinguishes voxels that are moving from stationary ones. This 4DCBCT model was then reconstructed with compressed sensing (CS) reconstruction framework such that the voxels with high motion would be aggressively updated by the phase-wise sorted projections and the voxels with less motion would be minimally updated to preserve the FB-3DCBCT. To evaluate the performance of our proposed MCIR algorithm, we evaluated both numerical phantoms and a lung cancer patient. The results were then compared with the (1) clinical FB-3DCBCT reconstructed using the FDK, (2) 4DCBCT reconstructed using the FDK, and (3) 4DCBCT reconstructed using the well-known prior image constrained compressed sensing (PICCS).Results: Examination of the MCIR algorithm showed that high phase-resolved 4DCBCT with sets of up to 20 phases using a typical FB-3DCBCT scan could be reconstructed without compromising the image quality. Moreover, in comparison with
International Nuclear Information System (INIS)
Nagatani, Yukihiro; Takahashi, Masashi; Takazakura, Ryutaro; Nitta, Norihisa; Murata, Kiyoshi; Ushio, Noritoshi; Matsuo, Shinro; Yamamoto, Takashi; Horie, Minoru
2007-01-01
The purpose of this study was to optimize the image reconstruction phase of multidetector-row computed tomography (MDCT) coronary angiography according to the heart rate is crucial. Scan data were reconstructed for 10 different phases in 58 sequential patients who under went 8-row cardiac MDCT. The obtained images were scored and compared in terms of motion artifacts and visibility of the vessels, and moreover, electrocardiogram (ECG) record-based evaluations were added for clarification of the temporal relationships among these 10 phases. In the cases with lower heart rates ( 65 beats/mm), they were obtained in the late systolic period. As the heart rate increased, the optimal image reconstruction phase changed from mid diastole to late systole. However, it is recommended to try to decrease the heart rate of patients before data acquisition. (author)
International Nuclear Information System (INIS)
Kaneko, Takeshi; Takagi, Masachika; Kato, Ryohei; Anno, Hirofumi; Kobayashi, Masanao; Yoshimi, Satoshi; Sanda, Yoshihiro; Katada, Kazuhiro
2012-01-01
The purpose of this study was to design and construct a phantom for using motion artifact in the electrocardiogram (ECG)-gated reconstruction image. In addition, the temporal resolution under various conditions was estimated. A stepping motor was used to move the phantom over an arc in a reciprocating manner. The program for controlling the stepping motor permitted the stationary period and the heart rate to be adjusted as desired. Images of the phantom were obtained using a 320-row area-detector computed tomography (ADCT) system under various conditions using the ECG-gated reconstruction method. For estimation, the reconstruction phase was continuously changed and the motion artifacts were quantitatively assessed. The temporal resolution was calculated from the number of motion-free images. Changes in the temporal resolution according to heart rate, rotation time, the number of reconstruction segments and acquisition position in z-axis were also investigated. The measured temporal resolution of ECG-gated half reconstruction is 180 ms, which is in good agreement with the nominal temporal resolution of 175 ms. The measured temporal resolution of ECG-gated segmental reconstruction is in good agreement with the nominal temporal resolution in most cases. The estimated temporal resolution improved to approach the nominal temporal resolution as the number of reconstruction segments was increased. Temporal resolution in changing acquisition position is equal. This study shows that we could design a new phantom for estimating temporal resolution. (author)
Image Reconstruction for Diffuse Optical Tomography Based on Radiative Transfer Equation
Directory of Open Access Journals (Sweden)
Bo Bi
2015-01-01
L2 regularization. Results also show the competitive performance of the split Bregman algorithm for the DOT image reconstruction with sparsity regularization compared with other existing L1 algorithms.
Guo, J.; Bücherl, T.; Zou, Y.; Guo, Z.
2011-09-01
Investigations on the fast neutron beam geometry for the NECTAR facility are presented. The results of MCNP simulations and experimental measurements of the beam distributions at NECTAR are compared. Boltzmann functions are used to describe the beam profile in the detection plane assuming the area source to be set up of large number of single neutron point sources. An iterative algebraic reconstruction algorithm is developed, realized and verified by both simulated and measured projection data. The feasibility for improved reconstruction in fast neutron computerized tomography at the NECTAR facility is demonstrated.
International Nuclear Information System (INIS)
Guo, J.; Buecherl, T.; Zou, Y.; Guo, Z.
2011-01-01
Investigations on the fast neutron beam geometry for the NECTAR facility are presented. The results of MCNP simulations and experimental measurements of the beam distributions at NECTAR are compared. Boltzmann functions are used to describe the beam profile in the detection plane assuming the area source to be set up of large number of single neutron point sources. An iterative algebraic reconstruction algorithm is developed, realized and verified by both simulated and measured projection data. The feasibility for improved reconstruction in fast neutron computerized tomography at the NECTAR facility is demonstrated.
Energy Technology Data Exchange (ETDEWEB)
Guo, J. [State Key Laboratory of Nuclear Physics and Technology and School of Physics, Peking University, 5 Yiheyuan Lu, Beijing 100871 (China); Lehrstuhl fuer Radiochemie, Technische Universitaet Muenchen, Garching 80748 (Germany); Buecherl, T. [Lehrstuhl fuer Radiochemie, Technische Universitaet Muenchen, Garching 80748 (Germany); Zou, Y., E-mail: zouyubin@pku.edu.cn [State Key Laboratory of Nuclear Physics and Technology and School of Physics, Peking University, 5 Yiheyuan Lu, Beijing 100871 (China); Guo, Z. [State Key Laboratory of Nuclear Physics and Technology and School of Physics, Peking University, 5 Yiheyuan Lu, Beijing 100871 (China)
2011-09-21
Investigations on the fast neutron beam geometry for the NECTAR facility are presented. The results of MCNP simulations and experimental measurements of the beam distributions at NECTAR are compared. Boltzmann functions are used to describe the beam profile in the detection plane assuming the area source to be set up of large number of single neutron point sources. An iterative algebraic reconstruction algorithm is developed, realized and verified by both simulated and measured projection data. The feasibility for improved reconstruction in fast neutron computerized tomography at the NECTAR facility is demonstrated.
May, Matthias S; Wüst, Wolfgang; Brand, Michael; Stahl, Christian; Allmendinger, Thomas; Schmidt, Bernhard; Uder, Michael; Lell, Michael M
2011-07-01
We sought to evaluate the image quality of iterative reconstruction in image space (IRIS) in half-dose (HD) datasets compared with full-dose (FD) and HD filtered back projection (FBP) reconstruction in abdominal computed tomography (CT). To acquire data with FD and HD simultaneously, contrast-enhanced abdominal CT was performed with a dual-source CT system, both tubes operating at 120 kV, 100 ref.mAs, and pitch 0.8. Three different image datasets were reconstructed from the raw data: Standard FD images applying FBP which served as reference, HD images applying FBP and HD images applying IRIS. For the HD data sets, only data from 1 tube detector-system was used. Quantitative image quality analysis was performed by measuring image noise in tissue and air. Qualitative image quality was evaluated according to the European Guidelines on Quality criteria for CT. Additional assessment of artifacts, lesion conspicuity, and edge sharpness was performed. : Image noise in soft tissue was substantially decreased in HD-IRIS (-3.4 HU, -22%) and increased in HD-FBP (+6.2 HU, +39%) images when compared with the reference (mean noise, 15.9 HU). No significant differences between the FD-FBP and HD-IRIS images were found for the visually sharp anatomic reproduction, overall diagnostic acceptability (P = 0.923), lesion conspicuity (P = 0.592), and edge sharpness (P = 0.589), while HD-FBP was rated inferior. Streak artifacts and beam hardening was significantly more prominent in HD-FBP while HD-IRIS images exhibited a slightly different noise pattern. Direct intrapatient comparison of standard FD body protocols and HD-IRIS reconstruction suggest that the latest iterative reconstruction algorithms allow for approximately 50% dose reduction without deterioration of the high image quality necessary for confident diagnosis.
Bayesian image reconstruction for emission tomography based on median root prior
International Nuclear Information System (INIS)
Alenius, S.
1997-01-01
The aim of the present study was to investigate a new type of Bayesian one-step late reconstruction method which utilizes a median root prior (MRP). The method favours images which have locally monotonous radioactivity concentrations. The new reconstruction algorithm was applied to ideal simulated data, phantom data and some patient examinations with PET. The same projection data were reconstructed with filtered back-projection (FBP) and maximum likelihood-expectation maximization (ML-EM) methods for comparison. The MRP method provided good-quality images with a similar resolution to the FBP method with a ramp filter, and at the same time the noise properties were as good as with Hann-filtered FBP images. The typical artefacts seen in FBP reconstructed images outside of the object were completely removed, as was the grainy noise inside the object. Quantitativley, the resulting average regional radioactivity concentrations in a large region of interest in images produced by the MRP method corresponded to the FBP and ML-EM results but at the pixel by pixel level the MRP method proved to be the most accurate of the tested methods. In contrast to other iterative reconstruction methods, e.g. ML-EM, the MRP method was not sensitive to the number of iterations nor to the adjustment of reconstruction parameters. Only the Bayesian parameter β had to be set. The proposed MRP method is much more simple to calculate than the methods described previously, both with regard to the parameter settings and in terms of general use. The new MRP reconstruction method was shown to produce high-quality quantitative emission images with only one parameter setting in addition to the number of iterations. (orig.)
Priori mask guided image reconstruction (p-MGIR) for ultra-low dose cone-beam computed tomography
Park, Justin C.; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Kahler, Darren L.; Liu, Chihray; Lu, Bo
2015-11-01
Recently, the compressed sensing (CS) based iterative reconstruction method has received attention because of its ability to reconstruct cone beam computed tomography (CBCT) images with good quality using sparsely sampled or noisy projections, thus enabling dose reduction. However, some challenges remain. In particular, there is always a tradeoff between image resolution and noise/streak artifact reduction based on the amount of regularization weighting that is applied uniformly across the CBCT volume. The purpose of this study is to develop a novel low-dose CBCT reconstruction algorithm framework called priori mask guided image reconstruction (p-MGIR) that allows reconstruction of high-quality low-dose CBCT images while preserving the image resolution. In p-MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions: (1) where anatomical structures are complex, and (2) where intensities are relatively uniform. The priori mask, which is the key concept of the p-MGIR algorithm, was defined as the matrix that distinguishes between the two separate CBCT regions where the resolution needs to be preserved and where streak or noise needs to be suppressed. We then alternately updated each part of image by solving two sub-minimization problems iteratively, where one minimization was focused on preserving the edge information of the first part while the other concentrated on the removal of noise/artifacts from the latter part. To evaluate the performance of the p-MGIR algorithm, a numerical head-and-neck phantom, a Catphan 600 physical phantom, and a clinical head-and-neck cancer case were used for analysis. The results were compared with the standard Feldkamp-Davis-Kress as well as conventional CS-based algorithms. Examination of the p-MGIR algorithm showed that high-quality low-dose CBCT images can be reconstructed without compromising the image resolution. For both phantom and the patient cases, the p-MGIR is able to achieve a clinically
Lim, Kyungjae; Kwon, Heejin; Cho, Jinhan; Oh, Jongyoung; Yoon, Seongkuk; Kang, Myungjin; Ha, Dongho; Lee, Jinhwa; Kang, Eunju
2015-01-01
The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image. We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V. At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.
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Chiras, J.; Palmieri, P.; Saudinos, J.; Salamon, G.
1980-01-01
The authors describe the physical basis, apparatus, normal images, and artefacts of computed tomography by reconstruction. Radio-anatomical sections enable clear comprehension of the computed tomography images. Other methods using computer reconstruction are outlined: tomography by Compton effect, tomography by positrons, tomography by gamma emission, tomography by protons, tomography by nuclear magnetic resonance [fr
International Nuclear Information System (INIS)
Bataille, F.
2007-04-01
Positron emission tomography is a medical imaging modality providing in-vivo volumetric images of functional processes of the human body, which is used for the diagnosis and the following of neuro degenerative diseases. PET efficiency is however limited by its poor spatial resolution, which generates a decrease of the image local contrast and leads to an under-estimation of small cerebral structures involved in the degenerative mechanism of those diseases. This so-called partial volume effect degradation is usually corrected in a post-reconstruction processing framework through the use of anatomical information, whose spatial resolution allows a better discrimination between functional tissues. However, this kind of method has the major drawback of being very sensitive to the residual mismatches on the anatomical information processing. We developed in this thesis an alternative methodology to compensate for the degradation, by incorporating in the reconstruction process both a model of the system impulse response and an anatomically-based image prior constraint. This methodology was validated by comparison with a post-reconstruction correction strategy, using data from an anthropomorphic phantom acquisition and then we evaluated its robustness to the residual mismatches through a realistic Monte Carlo simulation corresponding to a cerebral exam. The proposed algorithm was finally applied to clinical data reconstruction. (author)
Watanabe, Shota; Sakaguchi, Kenta; Hosono, Makoto; Ishii, Kazunari; Murakami, Takamichi; Ichikawa, Katsuhiro
The purpose of this study was to evaluate the effect of a hybrid-type iterative reconstruction method on Z-score mapping of hyperacute stroke in unenhanced computed tomography (CT) images. We used a hybrid-type iterative reconstruction [adaptive statistical iterative reconstruction (ASiR)] implemented in a CT system (Optima CT660 Pro advance, GE Healthcare). With 15 normal brain cases, we reconstructed CT images with a filtered back projection (FBP) and ASiR with a blending factor of 100% (ASiR100%). Two standardized normal brain data were created from normal databases of FBP images (FBP-NDB) and ASiR100% images (ASiR-NDB), and standard deviation (SD) values in basal ganglia were measured. The Z-score mapping was performed for 12 hyperacute stroke cases by using FBP-NDB and ASiR-NDB, and compared Z-score value on hyperacute stroke area and normal area between FBP-NDB and ASiR-NDB. By using ASiR-NDB, the SD value of standardized brain was decreased by 16%. The Z-score value of ASiR-NDB on hyperacute stroke area was significantly higher than FBP-NDB (pASiR100% for Z-score mapping had potential to improve the accuracy of Z-score mapping.
Image Reconstruction. Chapter 13
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Nuyts, J. [Department of Nuclear Medicine and Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven (Belgium); Matej, S. [Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA (United States)
2014-12-15
This chapter discusses how 2‑D or 3‑D images of tracer distribution can be reconstructed from a series of so-called projection images acquired with a gamma camera or a positron emission tomography (PET) system [13.1]. This is often called an ‘inverse problem’. The reconstruction is the inverse of the acquisition. The reconstruction is called an inverse problem because making software to compute the true tracer distribution from the acquired data turns out to be more difficult than the ‘forward’ direction, i.e. making software to simulate the acquisition. There are basically two approaches to image reconstruction: analytical reconstruction and iterative reconstruction. The analytical approach is based on mathematical inversion, yielding efficient, non-iterative reconstruction algorithms. In the iterative approach, the reconstruction problem is reduced to computing a finite number of image values from a finite number of measurements. That simplification enables the use of iterative instead of mathematical inversion. Iterative inversion tends to require more computer power, but it can cope with more complex (and hopefully more accurate) models of the acquisition process.
Incomplete-data image reconstructions in industrial x-ray computerized tomography
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Tam, K.C.; Eberhard, J.W.; Mitchell, K.W.
1989-01-01
In earlier works it was concluded that image reconstruction from incomplete data can be achieved through an iterative transform algorithm which utilizes the a priori information on the object to compensate for the missing data. The image is transformed back and forth between the object space and the projection space, being corrected by the a priori information on the object in the object space, and by the known projections in the projection space. The a priori information in the object space includes a boundary enclosing the object, and an upper bound and a lower bound of the object density. In this paper we report the results of testing the iterative transform algorithm on experimental data. X-ray sinogram data of the cross section of a F404 high-pressure turbine blade made of Ni-based superalloy were supplied to us by the Aircraft Engine Business Group of General Electric Company at Cincinnati, Ohio. From the data set we simulated two kinds of incomplete data situations, incomplete projection and limited-angle scanning, and applied the iterative transform algorithm to reconstruct the images. The results validated the practical value of the iterative transform algorithm in reconstructing images from incomplete x-ray data, both incomplete projections and limited-angle data. In all the cases tested there were significant improvements in the appearance of the images after iterations. The visual improvements are substantiated in a quantitative manner by the plots of errors in wall thickness measurements which in general decrease in magnitude with iterations
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Tseng, Hsin-Wu; Kupinski, Matthew A.; Fan, Jiahua; Sainath, Paavana; Hsieh, Jiang
2014-01-01
Purpose: A number of different techniques have been developed to reduce radiation dose in x-ray computed tomography (CT) imaging. In this paper, the authors will compare task-based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR). Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG).A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves. Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors’ task-based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%–67% (head phantom) and 68%–82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%–75% for head phantom and 67%–77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images. Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the
Liu, Yan; Ma, Jianhua; Fan, Yi; Liang, Zhengrong
2012-12-07
Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and other constraints, piecewise-smooth x-ray computed tomography (CT) can be reconstructed from sparse-view projection data without introducing notable artifacts. However, due to the piecewise constant assumption for the image, a conventional TV minimization algorithm often suffers from over-smoothness on the edges of the resulting image. To mitigate this drawback, we present an adaptive-weighted TV (AwTV) minimization algorithm in this paper. The presented AwTV model is derived by considering the anisotropic edge property among neighboring image voxels, where the associated weights are expressed as an exponential function and can be adaptively adjusted by the local image-intensity gradient for the purpose of preserving the edge details. Inspired by the previously reported TV-POCS (projection onto convex sets) implementation, a similar AwTV-POCS implementation was developed to minimize the AwTV subject to data and other constraints for the purpose of sparse-view low-dose CT image reconstruction. To evaluate the presented AwTV-POCS algorithm, both qualitative and quantitative studies were performed by computer simulations and phantom experiments. The results show that the presented AwTV-POCS algorithm can yield images with several notable gains, in terms of noise-resolution tradeoff plots and full-width at half-maximum values, as compared to the corresponding conventional TV-POCS algorithm.
Pontone, Gianluca; Muscogiuri, Giuseppe; Andreini, Daniele; Guaricci, Andrea I; Guglielmo, Marco; Baggiano, Andrea; Fazzari, Fabio; Mushtaq, Saima; Conte, Edoardo; Annoni, Andrea; Formenti, Alberto; Mancini, Elisabetta; Verdecchia, Massimo; Campari, Alessandro; Martini, Chiara; Gatti, Marco; Fusini, Laura; Bonfanti, Lorenzo; Consiglio, Elisa; Rabbat, Mark G; Bartorelli, Antonio L; Pepi, Mauro
2018-03-27
A new postprocessing algorithm named adaptive statistical iterative reconstruction (ASIR)-V has been recently introduced. The aim of this article was to analyze the impact of ASIR-V algorithm on signal, noise, and image quality of coronary computed tomography angiography. Fifty consecutive patients underwent clinically indicated coronary computed tomography angiography (Revolution CT; GE Healthcare, Milwaukee, WI). Images were reconstructed using filtered back projection and ASIR-V 0%, and a combination of filtered back projection and ASIR-V 20%-80% and ASIR-V 100%. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for left main coronary artery (LM), left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) and were compared between the different postprocessing algorithms used. Similarly a four-point Likert image quality score of coronary segments was graded for each dataset and compared. A cutoff value of P ASIR-V 0%, ASIR-V 100% demonstrated a significant reduction of image noise in all coronaries (P ASIR-V 0%, SNR was significantly higher with ASIR-V 60% in LM (P ASIR-V 0%, CNR for ASIR-V ≥60% was significantly improved in LM (P ASIR-V ≥80%. ASIR-V 60% had significantly better Likert image quality scores compared to ASIR-V 0% in segment-, vessel-, and patient-based analyses (P ASIR-V 60% provides the optimal balance between image noise, SNR, CNR, and image quality. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
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Liu, Zhenyu; Wu, Huiying
2016-01-01
Highlights: • The complex porous domain has been reconstructed with the micro CT scan images. • Pore-scale numerical model based on LB method has been established. • The correlations for flow and heat transfer were derived from the predictions. • The numerical approach developed in this work is suitable for complex porous media. - Abstract: This paper presents the numerical study on fluid flow and heat transfer in reconstructed porous media at the pore-scale with the double-population thermal lattice Boltzmann (LB) method. The porous geometry was reconstructed using micro-tomography images from micro-CT scanner. The thermal LB model was numerically tested before simulation and a good agreement was achieved by compared with the existing results. The detailed distributions of velocity and temperature in complex pore spaces were obtained from the pore-scale simulation. The correlations for flow and heat transfer in the specific porous media sample were derived based on the numerical results. The numerical method established in this work provides a promising approach to predict pore-scale flow and heat transfer characteristics in reconstructed porous domain with real geometrical effect, which can be extended for the continuum modeling of the transport process in porous media at macro-scale.
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Sun, Hongwei; Pistorius, Stephen [Department of Physics and Astronomy, University of Manitoba, CancerCare, Manitoba (Canada)
2016-08-15
PET images are affected by the presence of scattered photons. Incorrect scatter-correction may cause artifacts, particularly in 3D PET systems. Current scatter reconstruction methods do not distinguish between single and higher order scattered photons. A dual-scattered reconstruction method (GDS-MLEM) that is independent of the number of Compton scattering interactions and less sensitive to the need for high energy resolution detectors, is proposed. To avoid overcorrecting for scattered coincidences, the attenuation coefficient was calculated by integrating the differential Klein-Nishina cross-section over a restricted energy range, accounting only for scattered photons that were not detected. The optimum image can be selected by choosing an energy threshold which is the upper energy limit for the calculation of the cross-section and the lower limit for scattered photons in the reconstruction. Data was simulated using the GATE platform. 500,000 multiple scattered photon coincidences with perfect energy resolution were reconstructed using various methods. The GDS-MLEM algorithm had the highest confidence (98%) in locating the annihilation position and was capable of reconstructing the two largest hot regions. 100,000 photon coincidences, with a scatter fraction of 40%, were used to test the energy resolution dependence of different algorithms. With a 350–650 keV energy window and the restricted attenuation correction model, the GDS-MLEM algorithm was able to improve contrast recovery and reduce the noise by 7.56%–13.24% and 12.4%–24.03%, respectively. This approach is less sensitive to the energy resolution and shows promise if detector energy resolutions of 12% can be achieved.
An implementation of the NiftyRec medical imaging library for PIXE-tomography reconstruction
Michelet, C.; Barberet, P.; Desbarats, P.; Giovannelli, J.-F.; Schou, C.; Chebil, I.; Delville, M.-H.; Gordillo, N.; Beasley, D. G.; Devès, G.; Moretto, P.; Seznec, H.
2017-08-01
A new development of the TomoRebuild software package is presented, including ;thick sample; correction for non linear X-ray production (NLXP) and X-ray absorption (XA). As in the previous versions, C++ programming with standard libraries was used for easier portability. Data reduction requires different steps which may be run either from a command line instruction or via a user friendly interface, developed as a portable Java plugin in ImageJ. All experimental and reconstruction parameters can be easily modified, either directly in the ASCII parameter files or via the ImageJ interface. A detailed user guide in English is provided. Sinograms and final reconstructed images are generated in usual binary formats that can be read by most public domain graphic softwares. New MLEM and OSEM methods are proposed, using optimized methods from the NiftyRec medical imaging library. An overview of the different medical imaging methods that have been used for ion beam microtomography applications is presented. In TomoRebuild, PIXET data reduction is performed for each chemical element independently and separately from STIMT, except for two steps where the fusion of STIMT and PIXET data is required: the calculation of the correction matrix and the normalization of PIXET data to obtain mass fraction distributions. Correction matrices for NLXP and XA are calculated using procedures extracted from the DISRA code, taking into account a large X-ray detection solid angle. For this, the 3D STIMT mass density distribution is used, considering a homogeneous global composition. A first example of PIXET experiment using two detectors is presented. Reconstruction results are compared and found in good agreement between different codes: FBP, NiftyRec MLEM and OSEM of the TomoRebuild software package, the original DISRA, its accelerated version provided in JPIXET and the accelerated MLEM version of JPIXET, with or without correction.
International Nuclear Information System (INIS)
Wang, Li; Gac, Nicolas; Mohammad-Djafari, Ali
2015-01-01
In order to improve quality of 3D X-ray tomography reconstruction for Non Destructive Testing (NDT), we investigate in this paper hierarchical Bayesian methods. In NDT, useful prior information on the volume like the limited number of materials or the presence of homogeneous area can be included in the iterative reconstruction algorithms. In hierarchical Bayesian methods, not only the volume is estimated thanks to the prior model of the volume but also the hyper parameters of this prior. This additional complexity in the reconstruction methods when applied to large volumes (from 512 3 to 8192 3 voxels) results in an increasing computational cost. To reduce it, the hierarchical Bayesian methods investigated in this paper lead to an algorithm acceleration by Variational Bayesian Approximation (VBA) [1] and hardware acceleration thanks to projection and back-projection operators paralleled on many core processors like GPU [2]. In this paper, we will consider a Student-t prior on the gradient of the image implemented in a hierarchical way [3, 4, 1]. Operators H (forward or projection) and H t (adjoint or back-projection) implanted in multi-GPU [2] have been used in this study. Different methods will be evalued on synthetic volume 'Shepp and Logan' in terms of quality and time of reconstruction. We used several simple regularizations of order 1 and order 2. Other prior models also exists [5]. Sometimes for a discrete image, we can do the segmentation and reconstruction at the same time, then the reconstruction can be done with less projections
International Nuclear Information System (INIS)
Sidky, Emil Y; Pan Xiaochuan
2008-01-01
An iterative algorithm, based on recent work in compressive sensing, is developed for volume image reconstruction from a circular cone-beam scan. The algorithm minimizes the total variation (TV) of the image subject to the constraint that the estimated projection data is within a specified tolerance of the available data and that the values of the volume image are non-negative. The constraints are enforced by the use of projection onto convex sets (POCS) and the TV objective is minimized by steepest descent with an adaptive step-size. The algorithm is referred to as adaptive-steepest-descent-POCS (ASD-POCS). It appears to be robust against cone-beam artifacts, and may be particularly useful when the angular range is limited or when the angular sampling rate is low. The ASD-POCS algorithm is tested with the Defrise disk and jaw computerized phantoms. Some comparisons are performed with the POCS and expectation-maximization (EM) algorithms. Although the algorithm is presented in the context of circular cone-beam image reconstruction, it can also be applied to scanning geometries involving other x-ray source trajectories
Beattie, Bradley J; Klose, Alexander D; Le, Carl H; Longo, Valerie A; Dobrenkov, Konstantine; Vider, Jelena; Koutcher, Jason A; Blasberg, Ronald G
2009-01-01
The procedures we propose make possible the mapping of two-dimensional (2-D) bioluminescence image (BLI) data onto a skin surface derived from a three-dimensional (3-D) anatomical modality [magnetic resonance (MR) or computed tomography (CT)] dataset. This mapping allows anatomical information to be incorporated into bioluminescence tomography (BLT) reconstruction procedures and, when applied using sources visible to both optical and anatomical modalities, can be used to evaluate the accuracy of those reconstructions. Our procedures, based on immobilization of the animal and a priori determined fixed projective transforms, should be more robust and accurate than previously described efforts, which rely on a poorly constrained retrospectively determined warping of the 3-D anatomical information. Experiments conducted to measure the accuracy of the proposed registration procedure found it to have a mean error of 0.36+/-0.23 mm. Additional experiments highlight some of the confounds that are often overlooked in the BLT reconstruction process, and for two of these confounds, simple corrections are proposed.
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.
Direct image reconstruction with limited angle projection data for computerized tomography
International Nuclear Information System (INIS)
Inouye, T.
1980-01-01
Discussions are made on the minimum angle range for projection data necessary to reconstruct the complete CT image. As is easily shown from the image reconstruction theorem, the lack of projection angle provides no data for the Fourier transformed function of the object on the corresponding angular directions, where the projections are missing. In a normal situation, the Fourier transformed function of an object image holds an analytic characteristic with respect to two-dimensional orthogonal parameters. This characteristic enables uniquely prolonging the function outside the obtained region employing a sort of analytic continuation with respect to both parameters. In the method reported here, an object pattern, which is confined within a finite range, is shifted to a specified region to have complete orthogonal function expansions without changing the projection angle directions. These orthogonal functions are analytically extended to the missing projection angle range and the whole function is determined. This method does not include any estimation process, whose effectiveness is often seriously jeopardized by the presence of a slight fluctuation component. Computer simulations were carried out to demonstrate the effectiveness of the method
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Elbakri, Idris A; Fessler, Jeffrey A
2003-01-01
This paper describes a statistical image reconstruction method for x-ray CT that is based on a physical model that accounts for the polyenergetic x-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. Unlike our earlier work, the proposed algorithm does not require pre-segmentation of the object into the various tissue classes (e.g., bone and soft tissue) and allows mixed pixels. The attenuation coefficient of each voxel is modelled as the product of its unknown density and a weighted sum of energy-dependent mass attenuation coefficients. We formulate a penalized-likelihood function for this polyenergetic model and develop an iterative algorithm for estimating the unknown density of each voxel. Applying this method to simulated x-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artefacts relative to conventional beam hardening correction methods. We also apply the method to real data acquired from a phantom containing various concentrations of potassium phosphate solution. The algorithm reconstructs an image with accurate density values for the different concentrations, demonstrating its potential for quantitative CT applications
Idris A, Elbakri; Fessler, Jeffrey A
2003-08-07
This paper describes a statistical image reconstruction method for x-ray CT that is based on a physical model that accounts for the polyenergetic x-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. Unlike our earlier work, the proposed algorithm does not require pre-segmentation of the object into the various tissue classes (e.g., bone and soft tissue) and allows mixed pixels. The attenuation coefficient of each voxel is modelled as the product of its unknown density and a weighted sum of energy-dependent mass attenuation coefficients. We formulate a penalized-likelihood function for this polyenergetic model and develop an iterative algorithm for estimating the unknown density of each voxel. Applying this method to simulated x-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artefacts relative to conventional beam hardening correction methods. We also apply the method to real data acquired from a phantom containing various concentrations of potassium phosphate solution. The algorithm reconstructs an image with accurate density values for the different concentrations, demonstrating its potential for quantitative CT applications.
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Kachelriess, Marc; Sennst, Dirk-Alexander; Maxlmoser, Wolfgang; Kalender, Willi A.
2002-01-01
Subsecond single-slice, multi-slice or cone-beam spiral computed tomography (SSCT, MSCT, CBCT) offer great potential for improving heart imaging. Together with the newly developed phase-correlated cardiac reconstruction algorithms 180 deg. MCD and 180 deg. MCI [Med. Phys. 27, 1881-1902 (2000)] or related algorithms provided by the CT manufacturers, high image quality can be achieved. These algorithms require information about the cardiac motion, i.e., typically the simultaneously recorded electrocardiogram (ECG), to synchronize the reconstruction with the cardiac motion. Neither data acquired without ECG information (standard patients) nor acquisitions with corrupted ECG information can be handled adequately. We developed a method to extract the appropriate information about cardiac motion directly from the measured raw data (projection data). The so-called kymogram function is a measure of the cardiac motion as a function of time t or as a function of the projection angle α. In contrast to the ECG which is a global measure of the heart's electric excitation, the kymogram is a local measure of the heart motion at the z-position z(α) at projection angle α. The patient's local heart rate as well as the necessary synchronization information to be used with phase-correlated algorithms can be extracted from the kymogram by using a series of signal processing steps. The kymogram information is shown to be adequate to substitute the ECG information. Computer simulations with simulated ECG and patient measurements with simultaneously acquired ECG were carried out for a multislice scanner providing M=4 slices to evaluate these new approaches. Both the ECG function and the kymogram function were used for reconstruction. Both were highly correlated regarding the periodicity information used for reconstruction. In 21 out of 25 consecutive cases the kymogram approach was equivalent to the ECG-correlated reconstruction; only minor differences in image quality between both
Common-mask guided image reconstruction (c-MGIR) for enhanced 4D cone-beam computed tomography.
Park, Justin C; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Li, Jonathan G; Liu, Chihray; Lu, Bo
2015-12-07
Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm 'the common mask guided image reconstruction' (c-MGIR).In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and 'well' solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the algorithm
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Sato, Yuichi; Kanmatsuse, Katsuo; Inoue Fumio
2003-01-01
Although the excellent spatial resolution of multislice spiral computed tomography (MSCT) enables the coronary arteries to be visualized, its limited temporal resolution results in poor image reproducibility because of cardiac motion artifact (CMA) and hence limits its widespread clinical use. A novel retrospectively electrocardiogram (ECG)-gated reconstruction method has been developed to minimize CMA. In 88 consecutive patients, the scan data were reconstructed using 2 retrospectively ECG-gated reconstruction methods. Method 1: the end of the reconstruction window (250 ms) was positioned at the peak of the P wave on ECG, which corresponded to the end of the slow filling phase during diastole immediately before atrial contraction. Method 2 (conventional method): relative retrospective gating with 50% referred to the R-R interval was performed so that the beginning of the reconstruction window (250 ms) was positioned at the halfway point between the R-R intervals of the heart cycle. The quality of the coronary artery images was evaluated according to the presence or absence of CMA. The assessment was applied to the left main coronary artery (LMCA), the left anterior descending artery (LAD, segments no.6, no.7, and no.8), the left circumflex artery (LCx, segments no.11 and no.13) and the right coronary artery (RCA, segments no.1, no.2 and no.3). The first diagonal artery (no.9-1), the obtuse marginal artery (no.12-1), the posterior descending artery (no.4-PD), the atrioventricular node branch (no.4-AV) and the first right ventricular branch (RV) were also evaluated. Of the 88 patients, 85 were eligible for image evaluation. Method 1 allowed visualization of the major coronary arteries without CMA in the majority of patients. The left coronary artery (LCA) system (segments no.5-7, no.11 and no.13) and the proximal portion of the RCA were visualized in more than 94% of patients. Artifact-free visualization of the distal portion of the LAD (segment no.8) and RCA (no.4
Directory of Open Access Journals (Sweden)
Lucia Jañez-Garcia
Full Text Available To apply a fully automated method to quantify the 3D structure of the bony nasolacrimal canal (NLC from CT scans whereby the size and main morphometric characteristics of the canal can be determined.Cross-sectional study.36 eyes of 18 healthy individuals.Using software designed to detect the boundaries of the NLC on CT images, 36 NLC reconstructions were prepared. These reconstructions were then used to calculate NLC volume. The NLC axis in each case was determined according to a polygonal model and to 2nd, 3rd and 4th degree polynomials. From these models, NLC sectional areas and length were determined. For each variable, descriptive statistics and normality tests (Kolmogorov-Smirnov and Shapiro-Wilk were established.Time for segmentation, NLC volume, axis, sectional areas and length.Mean processing time was around 30 seconds for segmenting each canal. All the variables generated were normally distributed. Measurements obtained using the four models polygonal, 2nd, 3rd and 4th degree polynomial, respectively, were: mean canal length 14.74, 14.3, 14.80, and 15.03 mm; mean sectional area 15.15, 11.77, 11.43, and 11.56 mm2; minimum sectional area 8.69, 7.62, 7.40, and 7.19 mm2; and mean depth of minimum sectional area (craniocaudal 7.85, 7.71, 8.19, and 8.08 mm.The method proposed automatically reconstructs the NLC on CT scans. Using these reconstructions, morphometric measurements can be calculated from NLC axis estimates based on polygonal and 2nd, 3rd and 4th polynomial models.
International Nuclear Information System (INIS)
Tohme, Michel S; Qi Jinyi
2009-01-01
The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed positron emission tomography (PET) images. For efficient computation in reconstruction, the system model in PET can be factored into a product of a geometric projection matrix and sinogram blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. Direct measurement of a sinogram blurring matrix is difficult in practice because of the requirement of a collimated source. In this work, we propose a method to estimate the 2D blurring kernels from uncollimated point source measurements. Since the resulting sinogram blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo (MC) simulation, and hence provide a more accurate system model. Another advantage of the proposed method over MC simulation is that it can easily be applied to data that have undergone a transformation to reduce the data size (e.g., Fourier rebinning). Point source measurements were acquired with high count statistics in a relatively fine grid inside the microPET II scanner using a high-precision 2D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner and explicitly models the detector block structure. The resulting sinogram blurring matrix is incorporated into a maximum a posteriori (MAP) image reconstruction algorithm. The proposed method has been validated using a 3 x 3 line phantom, an ultra-micro resolution phantom and a 22 Na point source superimposed on a warm background. The results of the proposed method show improvements in both resolution and contrast ratio when compared with the MAP
Reconstruction of an InAs nanowire using geometric tomography
DEFF Research Database (Denmark)
Pennington, Robert S.; König, Stefan; Alpers, Andreas
Geometric tomography and conventional algebraic tomography algorithms are used to reconstruct cross-sections of an InAs nanowire from a tilt series of experimental annular dark-field images. Both algorithms are also applied to a test object to assess what factors affect the reconstruction quality....... When using the present algorithms, geometric tomography is faster, but artifacts in the reconstruction may be difficult to recognize....
Common-mask guided image reconstruction (c-MGIR) for enhanced 4D cone-beam computed tomography
International Nuclear Information System (INIS)
Park, Justin C; Li, Jonathan G; Liu, Chihray; Lu, Bo; Zhang, Hao; Chen, Yunmei; Fan, Qiyong
2015-01-01
Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm ‘the common mask guided image reconstruction’ (c-MGIR).In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and ‘well’ solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the
International Nuclear Information System (INIS)
Hosch, Waldemar; Stiller, Wolfram; Mueller, Dirk; Gitsioudis, Gitsios; Welzel, Johanna; Dadrich, Monika; Buss, Sebastian J.; Giannitsis, Evangelos; Kauczor, Hans U.; Katus, Hugo A.; Korosoglou, Grigorios
2012-01-01
Purpose: To assess the impact of body mass index (BMI)-adapted protocols and iterative reconstruction algorithms (iDose) on patient radiation exposure and image quality in patients undergoing prospective ECG-triggered 256-slice coronary computed tomography angiography (CCTA). Methods: Image quality and radiation exposure were systematically analyzed in 100 patients. 60 Patients underwent prospective ECG-triggered CCTA using a non-tailored protocol and served as a ‘control’ group (Group 1: 120 kV, 200 mA s). 40 Consecutive patients with suspected coronary artery disease (CAD) underwent prospective CCTA, using BMI-adapted tube voltage and standard (Group 2: 100/120 kV, 100–200 mA s) versus reduced tube current (Group 3: 100/120 kV, 75–150 mA s). Iterative reconstructions were provided with different iDose levels and were compared to filtered back projection (FBP) reconstructions. Image quality was assessed in consensus of 2 experienced observers and using a 5-grade scale (1 = best to 5 = worse), and signal- and contrast-to-noise ratios (SNR and CNR) were quantified. Results: CCTA was performed without adverse events in all patients (n = 100, heart rate of 47–87 bpm and BMI of 19–38 kg/m 2 ). Patients examined using the non-tailored protocol in Group 1 had the highest radiation exposure (3.2 ± 0.4 mSv), followed by Group 2 (1.7 ± 0.7 mSv) and Group 3 (1.2 ± 0.6 mSv) (radiation savings of 47% and 63%, respectively, p < 0.001). Iterative reconstructions provided increased SNR and CNR, particularly when higher iDose level 5 was applied with Multi-Frequency reconstruction (iDose5 MFR) (14.1 ± 4.6 versus 21.2 ± 7.3 for SNR and 12.0 ± 4.2 versus 18.1 ± 6.6 for CNR, for FBP versus iDose5 MFR, respectively, p < 0.001). The combination of BMI adaptation with iterative reconstruction reduced radiation exposure and simultaneously improved image quality (subjective image quality of 1.4 ± 0.4 versus 1.9 ± 0.5 for Group 2 reconstructed using iDose5 MFR versus
Zhang, Hanming; Wang, Linyuan; Yan, Bin; Li, Lei; Cai, Ailong; Hu, Guoen
2016-01-01
Total generalized variation (TGV)-based computed tomography (CT) image reconstruction, which utilizes high-order image derivatives, is superior to total variation-based methods in terms of the preservation of edge information and the suppression of unfavorable staircase effects. However, conventional TGV regularization employs l1-based form, which is not the most direct method for maximizing sparsity prior. In this study, we propose a total generalized p-variation (TGpV) regularization model to improve the sparsity exploitation of TGV and offer efficient solutions to few-view CT image reconstruction problems. To solve the nonconvex optimization problem of the TGpV minimization model, we then present an efficient iterative algorithm based on the alternating minimization of augmented Lagrangian function. All of the resulting subproblems decoupled by variable splitting admit explicit solutions by applying alternating minimization method and generalized p-shrinkage mapping. In addition, approximate solutions that can be easily performed and quickly calculated through fast Fourier transform are derived using the proximal point method to reduce the cost of inner subproblems. The accuracy and efficiency of the simulated and real data are qualitatively and quantitatively evaluated to validate the efficiency and feasibility of the proposed method. Overall, the proposed method exhibits reasonable performance and outperforms the original TGV-based method when applied to few-view problems.
Yu, Yao; Zhang, Wen-Bo; Liu, Xiao-Jing; Guo, Chuan-Bin; Yu, Guang-Yan; Peng, Xin
2017-06-01
The purpose of this study was to describe new technology assisted by 3-dimensional (3D) image fusion of 18 F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) and contrast-enhanced CT (CECT) for computer planning of a maxillectomy of recurrent maxillary squamous cell carcinoma and defect reconstruction. Treatment of recurrent maxillary squamous cell carcinoma usually includes tumor resection and free flap reconstruction. FDG-PET/CT provided images of regions of abnormal glucose uptake and thus showed metabolic tumor volume to guide tumor resection. CECT data were used to create 3D reconstructed images of vessels to show the vascular diameters and locations, so that the most suitable vein and artery could be selected during anastomosis of the free flap. The data from preoperative maxillofacial CECT scans and FDG-PET/CT imaging were imported into the navigation system (iPlan 3.0; Brainlab, Feldkirchen, Germany). Three-dimensional image fusion between FDG-PET/CT and CECT was accomplished using Brainlab software according to the position of the 2 skulls simulated in the CECT image and PET/CT image, respectively. After verification of the image fusion accuracy, the 3D reconstruction images of the metabolic tumor, vessels, and other critical structures could be visualized within the same coordinate system. These sagittal, coronal, axial, and 3D reconstruction images were used to determine the virtual osteotomy sites and reconstruction plan, which was provided to the surgeon and used for surgical navigation. The average shift of the 3D image fusion between FDG-PET/CT and CECT was less than 1 mm. This technique, by clearly showing the metabolic tumor volume and the most suitable vessels for anastomosis, facilitated resection and reconstruction of recurrent maxillary squamous cell carcinoma. We used 3D image fusion of FDG-PET/CT and CECT to successfully accomplish resection and reconstruction of recurrent maxillary squamous cell carcinoma
International Nuclear Information System (INIS)
Mendes, L.M.M.; Pereira, W.B.R.; Vieira, J.G.; Lamounier, C.S.; Gonçalves, D.A.; Carvalho, G.N.P.; Santana, P.C.; Oliveira, P.M.C.; Reis, L.P.
2017-01-01
Computed tomography had great advances in the equipment used in the diagnostic practice, directly influencing the levels of radiation for the patient. It is essential to optimize techniques that must be employed to comply with the ALARA (As Low As Reasonably Achievable) principle of radioprotection. The relationship of ASIR (Adaptive Statistical Iterative Reconstruction) with image noise was studied. Central images of a homogeneous water simulator were obtained in a 20 mm scan using a 64-channel Lightspeed VCT tomograph of General Electric in helical acquisitions with a rotation time of 0.5 seconds, Pitch 0.984: 1, and thickness of cut 0.625 mm. All these constant parameters varying the voltage in two distinct values: 120 and 140 kV with use of the automatic current by the CAE (Automatic Exposure Control), ranging from 50 to 675 mA (120 kV) and from 50 to 610 mA (140kV), minimum and maximum values, respectively allowed for each voltage. Image noise was determined through ImageJ free software. The analysis of the obtained data compared the percentage variation of the noise in the image based on the ASIR value of 10%, concluding that there is a variation of approximately 50% when compared to the values of ASIR (100%) in both tensions. Dose evaluation is required in future studies to better utilize the relationship between dose and image quality
Iterative Reconstruction Methods for Hybrid Inverse Problems in Impedance Tomography
DEFF Research Database (Denmark)
Hoffmann, Kristoffer; Knudsen, Kim
2014-01-01
For a general formulation of hybrid inverse problems in impedance tomography the Picard and Newton iterative schemes are adapted and four iterative reconstruction algorithms are developed. The general problem formulation includes several existing hybrid imaging modalities such as current density...... impedance imaging, magnetic resonance electrical impedance tomography, and ultrasound modulated electrical impedance tomography, and the unified approach to the reconstruction problem encompasses several algorithms suggested in the literature. The four proposed algorithms are implemented numerically in two...
Energy Technology Data Exchange (ETDEWEB)
Osti, Michael; Benedetto, Karl Peter [Academic Hospital Feldkirch, Department for Trauma Surgery and Sports Traumatology, Feldkirch (Austria); Krawinkel, Alessa [Academic Hospital Feldkirch, Department for Radiology, Feldkirch (Austria)
2014-12-15
Intra- and postoperative validation of anatomic footprint replication in posterior cruciate ligament (PCL) reconstruction can be conducted using fluoroscopy, radiography, or computed tomography (CT) scans. However, effectiveness and exposure to radiation of these imaging modalities are unknown. The objective of this study was to evaluate the comparative effectiveness of fluoroscopy, radiography, and CT in detecting femoral and tibial tunnel positions following an all-inside reconstruction of the PCL ligament in vivo. The study design was a retrospective case series. Intraoperative fluoroscopic images, postoperative radiographs, and CT scans were obtained in 50 consecutive patients following single-bundle PCL reconstruction. The centers of the tibial and femoral tunnel apertures were identified and correlated to measurement grid systems. The results of fluoroscopic, radiographic, and CT measurements were compared to each other and accumulated radiation dosages were calculated. Comparing the imaging groups, no statistically significant difference could be detected for the reference of the femoral tunnel to the intercondylar depth and height, for the reference of the tibial tunnel to the mediolateral diameter of the tibial plateau and for the superoinferior distance of the tibial tunnel entry to the tibial plateau and to the former physis line. Effective doses resulting from fluoroscopic, radiographic, and CT exposure averaged 2.9 mSv, standard deviation (±SD) 4.1 mSv, to 1.3 ± 0.8 mSv and to 3.6 ± 1.0 mSv, respectively. Fluoroscopy, radiography, and CT yield approximately equal effectiveness in detecting parameters used for quality validation intra- and postoperatively. An accumulating exposure to radiation must be considered. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Vernekohl, Don
2014-04-15
plain surfaces, predicted by simulations, was observed. Third, as the production of photon converters is time consuming and expensive, it was investigated whether or not thin gas detectors with single-lead-layer-converters would be an alternative to the HIDAC converter design. Following simulations, those concepts potentially offer impressive coincidence sensitivities up to 24% for plain lead foils and up to 40% for perforated lead foils. Fourth, compared to other PET scanner systems, the HIDAC concept suffers from missing energy information. Consequently, a substantial amount of scatter events can be found within the measured data. On the basis of image reconstruction and correction techniques the influence of random and scatter events and their characteristics on several simulated phantoms were presented. It was validated with the HIDAC simulator that the applied correction technique results in perfectly corrected images. Moreover, it was shown that the simulator is a credible tool to provide quantitatively improved images. Fifth, a new model for the non-collinearity of the positronium annihilation was developed, since it was observed that the model implemented in the GATE simulator does not correspond to the measured observation. The input parameter of the new model was trimmed to match to a point source measurement. The influence of both models on the spatial resolution was studied with three different reconstruction methods. Furthermore, it was demonstrated that the reduction of converter depth, proposed for increased sensitivity, also has an advantage on the spatial resolution and that a reduction of the FOV from 17 cm to 4 cm (with only 2 detector heads) results in a remarkable sensitivity increase of 150% and a substantial increase in spatial resolution. The presented simulations for the spatial resolution analysis used an intrinsic detector resolution of 0.125 x 0.125 x 3.2 mm{sup 3} and were able to reach fair resolutions down to 0.9-0.5 mm, which is an
International Nuclear Information System (INIS)
Rebled, J.M.; Yedra, Ll.; Estrade, S.; Portillo, J.; Peiro, F.
2011-01-01
The successful combination of electron beam precession and bright field electron tomography for 3D reconstruction is reported. Beam precession is demonstrated to be a powerful technique to reduce the contrast artifacts due to diffraction and curvature in thin foils. Taking advantage of these benefits, Precession assisted electron tomography has been applied to reconstruct the morphology of Sn precipitates embedded in an Al matrix, from a tilt series acquired in a range from +49 o to -61 o at intervals of 2 o and with a precession angle of 0.6 o in bright field mode. The combination of electron tomography and beam precession in conventional TEM mode is proposed as an alternative procedure to obtain 3D reconstructions of nano-objects without a scanning system or a high angle annular dark field detector. -- Highlights: → Electron beam precession reduces spurious diffraction contrast in bright field mode. → Bend contour related contrast depends on precession angle. → Electron beam precession is combined with bright field electron tomography. → Precession assisted BF tomography allowed 3D reconstruction of a Sn precipitate.
Energy Technology Data Exchange (ETDEWEB)
Rebled, J.M. [LENS-MIND-IN2UB, Departament d' Electronica, Universitat de Barcelona, Marti i Franques 1, 08028 Barcelona (Spain); Institut de Ciencia de Materials de Barcelona-CSIC, Campus UAB, 08193 Bellaterra (Spain); Yedra, Ll. [LENS-MIND-IN2UB, Departament d' Electronica, Universitat de Barcelona, Marti i Franques 1, 08028 Barcelona (Spain); Estrade, S.; Portillo, J. [LENS-MIND-IN2UB, Departament d' Electronica, Universitat de Barcelona, Marti i Franques 1, 08028 Barcelona (Spain); TEM-MAT, CCiT-UB, Sole i Sabaris 1, 08028 Barcelona (Spain); Peiro, F., E-mail: francesca.peiro@ub.edu [LENS-MIND-IN2UB, Departament d' Electronica, Universitat de Barcelona, Marti i Franques 1, 08028 Barcelona (Spain)
2011-08-15
The successful combination of electron beam precession and bright field electron tomography for 3D reconstruction is reported. Beam precession is demonstrated to be a powerful technique to reduce the contrast artifacts due to diffraction and curvature in thin foils. Taking advantage of these benefits, Precession assisted electron tomography has been applied to reconstruct the morphology of Sn precipitates embedded in an Al matrix, from a tilt series acquired in a range from +49{sup o} to -61{sup o} at intervals of 2{sup o} and with a precession angle of 0.6{sup o} in bright field mode. The combination of electron tomography and beam precession in conventional TEM mode is proposed as an alternative procedure to obtain 3D reconstructions of nano-objects without a scanning system or a high angle annular dark field detector. -- Highlights: {yields} Electron beam precession reduces spurious diffraction contrast in bright field mode. {yields} Bend contour related contrast depends on precession angle. {yields} Electron beam precession is combined with bright field electron tomography. {yields} Precession assisted BF tomography allowed 3D reconstruction of a Sn precipitate.
Energy Technology Data Exchange (ETDEWEB)
Fischer, Michael A.; Kartalis, Nikolaos; Aspelin, Peter; Albiin, Nils; Brismar, Torkel B. [Karolinska University Hospital, Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm (Sweden); Leidner, Bertil; Svensson, Anders [Karolinska University Hospital, Division of Medical Imaging and Technology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm (Sweden); Karolinska University Hospital Huddinge, Department of Radiology, Stockholm (Sweden)
2014-01-15
To assess feasibility and image quality (IQ) of a new post-processing algorithm for retrospective extraction of an optimised multi-phase CT (time-resolved CT) of the liver from volumetric perfusion imaging. Sixteen patients underwent clinically indicated perfusion CT using 4D spiral mode of dual-source 128-slice CT. Three image sets were reconstructed: motion-corrected and noise-reduced (MCNR) images derived from 4D raw data; maximum and average intensity projections (time MIP/AVG) of the arterial/portal/portal-venous phases and all phases (total MIP/ AVG) derived from retrospective fusion of dedicated MCNR split series. Two readers assessed the IQ, detection rate and evaluation time; one reader assessed image noise and lesion-to-liver contrast. Time-resolved CT was feasible in all patients. Each post-processing step yielded a significant reduction of image noise and evaluation time, maintaining lesion-to-liver contrast. Time MIPs/AVGs showed the highest overall IQ without relevant motion artefacts and best depiction of arterial and portal/portal-venous phases respectively. Time MIPs demonstrated a significantly higher detection rate for arterialised liver lesions than total MIPs/AVGs and the raw data series. Time-resolved CT allows data from volumetric perfusion imaging to be condensed into an optimised multi-phase liver CT, yielding a superior IQ and higher detection rate for arterialised liver lesions than the raw data series. (orig.)
Statistical reconstruction for cosmic ray muon tomography.
Schultz, Larry J; Blanpied, Gary S; Borozdin, Konstantin N; Fraser, Andrew M; Hengartner, Nicolas W; Klimenko, Alexei V; Morris, Christopher L; Orum, Chris; Sossong, Michael J
2007-08-01
Highly penetrating cosmic ray muons constantly shower the earth at a rate of about 1 muon per cm2 per minute. We have developed a technique which exploits the multiple Coulomb scattering of these particles to perform nondestructive inspection without the use of artificial radiation. In prior work [1]-[3], we have described heuristic methods for processing muon data to create reconstructed images. In this paper, we present a maximum likelihood/expectation maximization tomographic reconstruction algorithm designed for the technique. This algorithm borrows much from techniques used in medical imaging, particularly emission tomography, but the statistics of muon scattering dictates differences. We describe the statistical model for multiple scattering, derive the reconstruction algorithm, and present simulated examples. We also propose methods to improve the robustness of the algorithm to experimental errors and events departing from the statistical model.
Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia
2013-02-01
The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Qin, M; Chen, D Y; Wang, L L; Yu, X Y
2006-01-01
The subject investigated in this paper is the ECT system of 8-electrode oil-water two-phase flow, and the measuring principle is analysed. In ART image-reconstruction algorithm, an adaptive threshold image reconstruction is presented to improve quality of image reconstruction and calculating accuracy of concentration, and generally the measurement error is about 1%. Such method can well solve many defects that other measurement methods may have, such as slow speed, high cost, and poor security and so on. Therefore, it offers a new method for the concentration measurement of oil-water two-phase flow
Energy Technology Data Exchange (ETDEWEB)
Fernandez Marron, J. L.; Alberdi Primicia, J.; Barcala Riveira, J. M.
2007-12-28
The Electrical Capacitance Tomography (ECT) has not obtained a good development in order to be used at industrial level. That is due first to difficulties in the measurement of very little capacitances (in the range of femto farads) and second to the problem of reconstruction on- line of the images. This problem is due also to the small numbers of electrodes (maximum 16), that made the usual algorithms of reconstruction has many errors. In this work it is described a new purely geometrical method that could be used for this purpose. (Author) 4 refs.
Geometric reconstruction methods for electron tomography
Energy Technology Data Exchange (ETDEWEB)
Alpers, Andreas, E-mail: alpers@ma.tum.de [Zentrum Mathematik, Technische Universität München, D-85747 Garching bei München (Germany); Gardner, Richard J., E-mail: Richard.Gardner@wwu.edu [Department of Mathematics, Western Washington University, Bellingham, WA 98225-9063 (United States); König, Stefan, E-mail: koenig@ma.tum.de [Zentrum Mathematik, Technische Universität München, D-85747 Garching bei München (Germany); Pennington, Robert S., E-mail: robert.pennington@uni-ulm.de [Center for Electron Nanoscopy, Technical University of Denmark, DK-2800 Kongens Lyngby (Denmark); Boothroyd, Chris B., E-mail: ChrisBoothroyd@cantab.net [Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons and Peter Grünberg Institute, Forschungszentrum Jülich, D-52425 Jülich (Germany); Houben, Lothar, E-mail: l.houben@fz-juelich.de [Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons and Peter Grünberg Institute, Forschungszentrum Jülich, D-52425 Jülich (Germany); Dunin-Borkowski, Rafal E., E-mail: rdb@fz-juelich.de [Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons and Peter Grünberg Institute, Forschungszentrum Jülich, D-52425 Jülich (Germany); Joost Batenburg, Kees, E-mail: Joost.Batenburg@cwi.nl [Centrum Wiskunde and Informatica, NL-1098XG, Amsterdam, The Netherlands and Vision Lab, Department of Physics, University of Antwerp, B-2610 Wilrijk (Belgium)
2013-05-15
Electron tomography is becoming an increasingly important tool in materials science for studying the three-dimensional morphologies and chemical compositions of nanostructures. The image quality obtained by many current algorithms is seriously affected by the problems of missing wedge artefacts and non-linear projection intensities due to diffraction effects. The former refers to the fact that data cannot be acquired over the full 180° tilt range; the latter implies that for some orientations, crystalline structures can show strong contrast changes. To overcome these problems we introduce and discuss several algorithms from the mathematical fields of geometric and discrete tomography. The algorithms incorporate geometric prior knowledge (mainly convexity and homogeneity), which also in principle considerably reduces the number of tilt angles required. Results are discussed for the reconstruction of an InAs nanowire. - Highlights: ► Four algorithms for electron tomography are introduced that utilize prior knowledge. ► Objects are assumed to be homogeneous; convexity and regularity is also discussed. ► We are able to reconstruct slices of a nanowire from as few as four projections. ► Algorithms should be selected based on the specific reconstruction task at hand.
Geometric reconstruction methods for electron tomography
International Nuclear Information System (INIS)
Alpers, Andreas; Gardner, Richard J.; König, Stefan; Pennington, Robert S.; Boothroyd, Chris B.; Houben, Lothar; Dunin-Borkowski, Rafal E.; Joost Batenburg, Kees
2013-01-01
Electron tomography is becoming an increasingly important tool in materials science for studying the three-dimensional morphologies and chemical compositions of nanostructures. The image quality obtained by many current algorithms is seriously affected by the problems of missing wedge artefacts and non-linear projection intensities due to diffraction effects. The former refers to the fact that data cannot be acquired over the full 180° tilt range; the latter implies that for some orientations, crystalline structures can show strong contrast changes. To overcome these problems we introduce and discuss several algorithms from the mathematical fields of geometric and discrete tomography. The algorithms incorporate geometric prior knowledge (mainly convexity and homogeneity), which also in principle considerably reduces the number of tilt angles required. Results are discussed for the reconstruction of an InAs nanowire. - Highlights: ► Four algorithms for electron tomography are introduced that utilize prior knowledge. ► Objects are assumed to be homogeneous; convexity and regularity is also discussed. ► We are able to reconstruct slices of a nanowire from as few as four projections. ► Algorithms should be selected based on the specific reconstruction task at hand
International Nuclear Information System (INIS)
Chen, Xia; Hu, Hong-li; Liu, Fei; Gao, Xiang Xiang
2011-01-01
The task of image reconstruction for an electrical capacitance tomography (ECT) system is to determine the permittivity distribution and hence the phase distribution in a pipeline by measuring the electrical capacitances between sets of electrodes placed around its periphery. In view of the nonlinear relationship between the permittivity distribution and capacitances and the limited number of independent capacitance measurements, image reconstruction for ECT is a nonlinear and ill-posed inverse problem. To solve this problem, a new image reconstruction method for ECT based on a least-squares support vector machine (LS-SVM) combined with a self-adaptive particle swarm optimization (PSO) algorithm is presented. Regarded as a special small sample theory, the SVM avoids the issues appearing in artificial neural network methods such as difficult determination of a network structure, over-learning and under-learning. However, the SVM performs differently with different parameters. As a relatively new population-based evolutionary optimization technique, PSO is adopted to realize parameters' effective selection with the advantages of global optimization and rapid convergence. This paper builds up a 12-electrode ECT system and a pneumatic conveying platform to verify this image reconstruction algorithm. Experimental results indicate that the algorithm has good generalization ability and high-image reconstruction quality
Quantitative tomography simulations and reconstruction algorithms
International Nuclear Information System (INIS)
Martz, H.E.; Aufderheide, M.B.; Goodman, D.; Schach von Wittenau, A.; Logan, C.; Hall, J.; Jackson, J.; Slone, D.
2000-01-01
X-ray, neutron and proton transmission radiography and computed tomography (CT) are important diagnostic tools that are at the heart of LLNL's effort to meet the goals of the DOE's Advanced Radiography Campaign. This campaign seeks to improve radiographic simulation and analysis so that radiography can be a useful quantitative diagnostic tool for stockpile stewardship. Current radiographic accuracy does not allow satisfactory separation of experimental effects from the true features of an object's tomographically reconstructed image. This can lead to difficult and sometimes incorrect interpretation of the results. By improving our ability to simulate the whole radiographic and CT system, it will be possible to examine the contribution of system components to various experimental effects, with the goal of removing or reducing them. In this project, we are merging this simulation capability with a maximum-likelihood (constrained-conjugate-gradient-CCG) reconstruction technique yielding a physics-based, forward-model image-reconstruction code. In addition, we seek to improve the accuracy of computed tomography from transmission radiographs by studying what physics is needed in the forward model. During FY 2000, an improved version of the LLNL ray-tracing code called HADES has been coupled with a recently developed LLNL CT algorithm known as CCG. The problem of image reconstruction is expressed as a large matrix equation relating a model for the object being reconstructed to its projections (radiographs). Using a constrained-conjugate-gradient search algorithm, a maximum likelihood solution is sought. This search continues until the difference between the input measured radiographs or projections and the simulated or calculated projections is satisfactorily small
Huang, Hsuan-Ming; Hsiao, Ing-Tsung
2016-01-01
In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate.
Cui, Xiaoming; Li, Tao; Li, Xin; Zhou, Weihua
2015-05-01
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. 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. 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. 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. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Interactive reconstruction in single-photon tomography
International Nuclear Information System (INIS)
Miller, T.R.; Wallis, J.W.; Wilson, A.D.
1989-01-01
A new method is described to allow interactive selection of the reconstruction filter at the time of interpretation of images from single-photon tomography. In the filtered back projection algorithm, the only part of the reconstruction process requiring user interaction is the selection of the window function. Since the ramp and window filters have different purposes, they can be separated, placing the window at the end of the reconstruction process as a three-dimensional filter. All stages of reconstruction except the window filtering are performed before the physician begins to interpret the study. The three-dimensional filtering is performed very rapidly with use of the Chebyshev convolution algorithm. A 64 x 64 x 64 pixel cube of data is filtered in 13-33 s using filters of 3-11 lengths. Smaller volumes of image data can be filtered in less than 1 s; thus, the user can interactively choose any desired filter for a given tomographic study at the time of interpretation of the images. (orig.)
Strategies of reconstruction algorithms for computerized tomography
International Nuclear Information System (INIS)
Garderet, P.
1984-10-01
Image reconstruction from projections has progressively spread out over all fields of medical imaging. As the mathematical aspects of the problem become more and more comprehensively explored a great variety of numerical solutions have been developed best suited to such-and-such imaging medical application and taking into account the physical phenomena related to data collection (a priori properties for signal and noise). The purpose of that survey is to present the general mathematical frame and the fundamental assumptions of various strategies; Fourier methods approximate explicit deterministic inversion formula for the Radon transform. Algebraic reconstruction techniques set up an a priori discrete model through a series expansion approach of the solution. The numerical system to be solved is huge when a fine grid of pixels is to be reconstructed; iterative solutions may then be found. Recently some least square procedures have been shown to be tractable which avoid the use of iterative methods. Finally maximum like hood approach incorporates accurately the Poisson nature of photon noise and are well adapted to emission computed tomography. The various strategies will be analysed from both aspects of theoretical assumptions needed for suitable use and of computing facilities, actual performance and cost. In the end we take a glimpse of the extension of the algorithms from two dimensional imaging to fully three dimensional volume analysis in preparation of the future medical imaging technologies
Energy Technology Data Exchange (ETDEWEB)
Brix, G. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Doll, J. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Bellemann, M.E. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Trojan, H. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Haberkorn, U. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Schmidlin, P. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Ostertag, H. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany)
1997-07-01
The purpose of this work was to improve of the spatial resolution of a whole-body PET system for experimental studies of small animals by incorporation of scanner characteristics into the process of iterative image reconstruction. The image-forming characteristics of the PET camera were characterized by a spatially variant line-spread function (LSF), which was determined from 49 activated copper-64 line sources positioned over a field of view (FOV) of 21.0 cm. During the course of iterative image reconstruction, the forward projection of the estimated image was blurred with the LSF at each iteration step before the estimated projections were compared with the measured projections. Moreover, imaging studies of a rat and two nude mice were performed to evaluate the imaging properties of our approach in vivo. The spatial resolution of the scanner perpendicular to the direction of projection could be approximated by a one-dimensional Gaussian-shaped LSF with a full-width at half-maximum increasing from 6.5 mm at the centre to 6.7 mm at a radial distance of 10.5 cm. The incorporation of this blurring kernel into the iteration formula resulted in a significantly improved spatial resolution of about 3.9 mm over the examined FOV. As demonstrated by the phantom and the animal experiments, the high-resolution algorithm not only led to a better contrast resolution in the reconstructed emission scans but also improved the accuracy for quantitating activity concentrations in small tissue structures without leading to an amplification of image noise or image mottle. The presented data-handling strategy incorporates the image restoration step directly into the process of algebraic image reconstruction and obviates the need for ill-conditioned ``deconvolution`` procedures to be performed on the projections or on the reconstructed image. In our experience, the proposed algorithm is of special interest in experimental studies of small animals. (orig./AJ). With 9 figs.
International Nuclear Information System (INIS)
Brix, G.; Doll, J.; Bellemann, M.E.; Trojan, H.; Haberkorn, U.; Schmidlin, P.; Ostertag, H.
1997-01-01
The purpose of this work was to improve of the spatial resolution of a whole-body PET system for experimental studies of small animals by incorporation of scanner characteristics into the process of iterative image reconstruction. The image-forming characteristics of the PET camera were characterized by a spatially variant line-spread function (LSF), which was determined from 49 activated copper-64 line sources positioned over a field of view (FOV) of 21.0 cm. During the course of iterative image reconstruction, the forward projection of the estimated image was blurred with the LSF at each iteration step before the estimated projections were compared with the measured projections. Moreover, imaging studies of a rat and two nude mice were performed to evaluate the imaging properties of our approach in vivo. The spatial resolution of the scanner perpendicular to the direction of projection could be approximated by a one-dimensional Gaussian-shaped LSF with a full-width at half-maximum increasing from 6.5 mm at the centre to 6.7 mm at a radial distance of 10.5 cm. The incorporation of this blurring kernel into the iteration formula resulted in a significantly improved spatial resolution of about 3.9 mm over the examined FOV. As demonstrated by the phantom and the animal experiments, the high-resolution algorithm not only led to a better contrast resolution in the reconstructed emission scans but also improved the accuracy for quantitating activity concentrations in small tissue structures without leading to an amplification of image noise or image mottle. The presented data-handling strategy incorporates the image restoration step directly into the process of algebraic image reconstruction and obviates the need for ill-conditioned ''deconvolution'' procedures to be performed on the projections or on the reconstructed image. In our experience, the proposed algorithm is of special interest in experimental studies of small animals. (orig./AJ). With 9 figs
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.
International Nuclear Information System (INIS)
Park, Sook Hee
2001-02-01
This thesis implements and analyzes the parallel and networked computing libraries based on the multiprocessor computer architecture as well as networked computers, aiming at improving the computation speed of ET(Electrical Tomography) system which requires enormous CPU time in reconstructing the unknown internal state of the target object. As an instance of the typical tomography technology, ET partitions the cross-section of the target object into the tiny elements and calculates the resistivity of them with signal values measured at the boundary electrodes surrounding the surface of the object after injecting the predetermined current pattern through the object. The number of elements is determined considering the trade-off between the accuracy of the reconstructed image and the computation time. As the elements become more finer, the number of element increases, and the system can get the better image. However, the reconstruction time increases polynomially with the number of partitioned elements since the procedure consists of a number of time consuming matrix operations such as multiplication, inverse, pseudo inverse, Jacobian and so on. Consequently, the demand for improving computation speed via multiple processor grows indispensably. Moreover, currently released PCs can be stuffed with up to 4 CPUs interconnected to the shared memory while some operating systems enable the application process to benefit from such computer by allocating the threaded job to each CPU, resulting in concurrent processing. In addition, a networked computing or cluster computing environment is commonly available to almost every computer which contains communication protocol and is connected to local or global network. After partitioning the given job(numerical operation), each CPU or computer calculates the partial result independently, and the results are merged via common memory to produce the final result. It is desirable to adopt the commonly used library such as Matlab to
International Nuclear Information System (INIS)
Ryu, Young Jin; Choi, Young Hun; Cheon, Jung-Eun; Kim, Woo Sun; Kim, In-One; Ha, Seongmin
2016-01-01
CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT. To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection. We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose 4 , levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire. With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose 4 levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose 4 level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm. Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose 4 obtained at 1.81 mSv. (orig.)
Ryu, Young Jin; Choi, Young Hun; Cheon, Jung-Eun; Ha, Seongmin; Kim, Woo Sun; Kim, In-One
2016-03-01
CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT. To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection. We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose(4), levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire. With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose(4) levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose(4) level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm. Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose(4) obtained at 1.81 mSv.
International Nuclear Information System (INIS)
Pan Xiaochuan; Yu Lifeng
2003-01-01
In computed tomography (CT), the fan-beam filtered backprojection (FFBP) algorithm is used widely for image reconstruction. It is known that the FFBP algorithm can significantly amplify data noise and aliasing artifacts in situations where the focal lengths are comparable to or smaller than the size of the field of measurement (FOM). In this work, we propose an algorithm that is less susceptible to data noise, aliasing, and other data inconsistencies than is the FFBP algorithm while retaining the favorable resolution properties of the FFBP algorithm. In an attempt to evaluate the noise properties in reconstructed images, we derive analytic expressions for image variances obtained by use of the FFBP algorithm and the proposed algorithm. Computer simulation studies are conducted for quantitative evaluation of the spatial resolution and noise properties of images reconstructed by use of the algorithms. Numerical results of these studies confirm the favorable spatial resolution and noise properties of the proposed algorithm and verify the validity of the theoretically predicted image variances. The proposed algorithm and the derived analytic expressions for image variances can have practical implications for both estimation and detection/classification tasks making use of CT images, and they can readily be generalized to other fan-beam geometries
Image quality in coronary computed tomography angiography
DEFF Research Database (Denmark)
Precht, Helle; Gerke, Oke; Thygesen, Jesper
2018-01-01
Background Computed tomography (CT) technology is rapidly evolving and software solution developed to optimize image quality and/or lower radiation dose. Purpose To investigate the influence of adaptive statistical iterative reconstruction (ASIR) at different radiation doses in coronary CT...
Medical image reconstruction. A conceptual tutorial
International Nuclear Information System (INIS)
Zeng, Gengsheng Lawrence
2010-01-01
''Medical Image Reconstruction: A Conceptual Tutorial'' introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l 0 -minimization are also included. (orig.)
Wellenberg, Ruud H H; Boomsma, Martijn F; van Osch, Jochen A C; Vlassenbroek, Alain; Milles, Julien; Edens, Mireille A; Streekstra, Geert J; Slump, Cornelis H; Maas, Mario
To quantify the combined use of iterative model-based reconstruction (IMR) and orthopaedic metal artefact reduction (O-MAR) in reducing metal artefacts and improving image quality in a total hip arthroplasty phantom. Scans acquired at several dose levels and kVps were reconstructed with filtered back-projection (FBP), iterative reconstruction (iDose) and IMR, with and without O-MAR. Computed tomography (CT) numbers, noise levels, signal-to-noise-ratios and contrast-to-noise-ratios were analysed. Iterative model-based reconstruction results in overall improved image quality compared to iDose and FBP (P < 0.001). Orthopaedic metal artefact reduction is most effective in reducing severe metal artefacts improving CT number accuracy by 50%, 60%, and 63% (P < 0.05) and reducing noise by 1%, 62%, and 85% (P < 0.001) whereas improving signal-to-noise-ratios by 27%, 47%, and 46% (P < 0.001) and contrast-to-noise-ratios by 16%, 25%, and 19% (P < 0.001) with FBP, iDose, and IMR, respectively. The combined use of IMR and O-MAR strongly improves overall image quality and strongly reduces metal artefacts in the CT imaging of a total hip arthroplasty phantom.
DEFF Research Database (Denmark)
Kazantsev, Daniil; Jørgensen, Jakob Sauer; Andersen, Martin S
2018-01-01
peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually...... to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction...
International Nuclear Information System (INIS)
Arinilhaq; Widita, R
2016-01-01
Diagnosis of macular degeneration using a Stratus OCT with a fast macular thickness map (FMTM) method produced six B-scan images of macula from different angles. The images were converted into a retinal thickness chart to be evaluated by normal distribution percentile of data so that it can be classified as normal thickness of macula or as experiencing abnormality (e.g. thickening and thinning). Unfortunately, the diagnostic images only represent the retinal thickness in several areas of the macular region. Thus, this study is aims to obtain the entire retinal thickness in the macula area from Status OCT's output images. Basically, the volumetric image is obtained by combining each of the six images. Reconstruction consists of a series of processes such as pre-processing, segmentation, and interpolation. Linear interpolation techniques are used to fill the empty pixels in reconstruction matrix. Based on the results, this method is able to provide retinal thickness maps on the macula surface and the macula 3D image. Retinal thickness map can display the macula area which experienced abnormalities. The macula 3D image can show the layers of tissue in the macula that is abnormal. The system built cannot replace ophthalmologist in decision making in term of diagnosis. (paper)
Arinilhaq; Widita, R.
2016-03-01
Diagnosis of macular degeneration using a Stratus OCT with a fast macular thickness map (FMTM) method produced six B-scan images of macula from different angles. The images were converted into a retinal thickness chart to be evaluated by normal distribution percentile of data so that it can be classified as normal thickness of macula or as experiencing abnormality (e.g. thickening and thinning). Unfortunately, the diagnostic images only represent the retinal thickness in several areas of the macular region. Thus, this study is aims to obtain the entire retinal thickness in the macula area from Status OCT's output images. Basically, the volumetric image is obtained by combining each of the six images. Reconstruction consists of a series of processes such as pre-processing, segmentation, and interpolation. Linear interpolation techniques are used to fill the empty pixels in reconstruction matrix. Based on the results, this method is able to provide retinal thickness maps on the macula surface and the macula 3D image. Retinal thickness map can display the macula area which experienced abnormalities. The macula 3D image can show the layers of tissue in the macula that is abnormal. The system built cannot replace ophthalmologist in decision making in term of diagnosis.
Mow, M.; Zbijewski, W.; Sisniega, A.; Xu, J.; Dang, H.; Stayman, J. W.; Wang, X.; Foos, D. H.; Koliatsos, V.; Aygun, N.; Siewerdsen, J. H.
2017-03-01
Purpose: To improve the timely detection and treatment of intracranial hemorrhage or ischemic stroke, recent efforts include the development of cone-beam CT (CBCT) systems for perfusion imaging and new approaches to estimate perfusion parameters despite slow rotation speeds compared to multi-detector CT (MDCT) systems. This work describes development of a brain perfusion CBCT method using a reconstruction of difference (RoD) approach to enable perfusion imaging on a newly developed CBCT head scanner prototype. Methods: A new reconstruction approach using RoD with a penalized-likelihood framework was developed to image the temporal dynamics of vascular enhancement. A digital perfusion simulation was developed to give a realistic representation of brain anatomy, artifacts, noise, scanner characteristics, and hemo-dynamic properties. This simulation includes a digital brain phantom, time-attenuation curves and noise parameters, a novel forward projection method for improved computational efficiency, and perfusion parameter calculation. Results: Our results show the feasibility of estimating perfusion parameters from a set of images reconstructed from slow scans, sparse data sets, and arc length scans as short as 60 degrees. The RoD framework significantly reduces noise and time-varying artifacts from inconsistent projections. Proper regularization and the use of overlapping reconstructed arcs can potentially further decrease bias and increase temporal resolution, respectively. Conclusions: A digital brain perfusion simulation with RoD imaging approach has been developed and supports the feasibility of using a CBCT head scanner for perfusion imaging. Future work will include testing with data acquired using a 3D-printed perfusion phantom currently and translation to preclinical and clinical studies.
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Sato, Yuichi; Matsumoto, Naoya; Kato, Masahiko [Nihon Univ., Tokyo (Japan). Surugadai Hospital] [and others
2003-04-01
The present study was designed to investigate the accuracy of multislice spiral computed tomography (MSCT) in detecting coronary artery disease, compared with coronary angiography (CAG), using a new retrospectively ECG-gated reconstruction method that reduced cardiac motion artifact. The study group comprised 54 consecutive patients undergoing MSCT and CAG. MSCT was performed using a SOMATOM Volume Zoom (4-detector-row, Siemens, Germany) with slice thickness 1.0 mm, pitch 1.5 (table feed: 1.5 mm per rotation) and gantry rotation time 500 ms. Metoprolol (20-60 mg) was administered orally prior to MSCT imaging. ECG-gated image reconstruction was performed with the reconstruction window (250 ms) positioned immediately before atrial contraction in order to reduce the cardiac motion artifact caused by the abrupt diastolic ventricular movement occurring during the rapid filling and atrial contraction periods. Following inspection of the volume rendering images, multiplanar reconstruction images and axial images of the left main coronary artery (LMCA), left anterior descending artery (LAD), left circumflex artery (LCx) and right coronary artery (RCA) were obtained and evaluated for luminal narrowing. The results were compared with those obtained by CAG. Of 216 coronary arteries, 206 (95.4%) were assessable; 10 arteries were excluded from the analysis because of severe calcification (n=4), stents (n=3) or insufficient contrast enhancement (n=3). The sensitivity to detect coronary stenoses {>=}50% was 93.5% and the specificity to define luminal narrowing <50% was 97.2%. The positive predictive value and the negative predictive value were 93.5% and 97.2%, respectively. The sensitivity was still satisfactory (80.6%) even when non-assessable arteries were included in the analysis. The new retrospectively ECG-gated reconstruction method for MSCT has excellent diagnostic accuracy in detecting significant coronary artery stenoses. (author)
Kazantsev, Daniil; Jørgensen, Jakob S.; Andersen, Martin S.; Lionheart, William R. B.; Lee, Peter D.; Withers, Philip J.
2018-06-01
Rapid developments in photon-counting and energy-discriminating detectors have the potential to provide an additional spectral dimension to conventional x-ray grayscale imaging. Reconstructed spectroscopic tomographic data can be used to distinguish individual materials by characteristic absorption peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually correlated it can be advantageous to exploit this additional knowledge. In this paper, we propose a novel method which jointly reconstructs all energy channels while imposing a strong structural correlation. The core of the proposed algorithm is to employ a variational framework of parallel level sets to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction techniques including channel-wise total variation and correlative total nuclear variation regularization. Realistic simulation experiments demonstrate the performance improvements achievable by using correlative regularization methods.
Gao, Yang; Bian, Zhaoying; Huang, Jing; Zhang, Yunwan; Niu, Shanzhou; Feng, Qianjin; Chen, Wufan; Liang, Zhengrong; Ma, Jianhua
2014-06-16
To realize low-dose imaging in X-ray computed tomography (CT) examination, lowering milliampere-seconds (low-mAs) or reducing the required number of projection views (sparse-view) per rotation around the body has been widely studied as an easy and effective approach. In this study, we are focusing on low-dose CT image reconstruction from the sinograms acquired with a combined low-mAs and sparse-view protocol and propose a two-step image reconstruction strategy. Specifically, to suppress significant statistical noise in the noisy and insufficient sinograms, an adaptive sinogram restoration (ASR) method is first proposed with consideration of the statistical property of sinogram data, and then to further acquire a high-quality image, a total variation based projection onto convex sets (TV-POCS) method is adopted with a slight modification. For simplicity, the present reconstruction strategy was termed as "ASR-TV-POCS." To evaluate the present ASR-TV-POCS method, both qualitative and quantitative studies were performed on a physical phantom. Experimental results have demonstrated that the present ASR-TV-POCS method can achieve promising gains over other existing methods in terms of the noise reduction, contrast-to-noise ratio, and edge detail preservation.
Computed tomography and three-dimensional imaging
International Nuclear Information System (INIS)
Harris, L.D.; Ritman, E.L.; Robb, R.A.
1987-01-01
Presented here is a brief introduction to two-, three-, and four-dimensional computed tomography. More detailed descriptions of the mathematics of reconstruction and of CT scanner operation are presented elsewhere. The complementary tomographic imaging methods of single-photon-emission tomography (SPECT) positron-emission tomography (PET), nuclear magnetic resonance (NMR) imaging, ulltrasound sector scanning, and ulltrasound computer-assisted tomography [UCAT] are only named here. Each imaging modality ''probes'' the body with a different energy form, yielding unique and useful information about tomographic sections through the body
Greedy algorithms for diffuse optical tomography reconstruction
Dileep, B. P. V.; Das, Tapan; Dutta, Pranab K.
2018-03-01
Diffuse optical tomography (DOT) is a noninvasive imaging modality that reconstructs the optical parameters of a highly scattering medium. However, the inverse problem of DOT is ill-posed and highly nonlinear due to the zig-zag propagation of photons that diffuses through the cross section of tissue. The conventional DOT imaging methods iteratively compute the solution of forward diffusion equation solver which makes the problem computationally expensive. Also, these methods fail when the geometry is complex. Recently, the theory of compressive sensing (CS) has received considerable attention because of its efficient use in biomedical imaging applications. The objective of this paper is to solve a given DOT inverse problem by using compressive sensing framework and various Greedy algorithms such as orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP), and stagewise orthogonal matching pursuit (StOMP), regularized orthogonal matching pursuit (ROMP) and simultaneous orthogonal matching pursuit (S-OMP) have been studied to reconstruct the change in the absorption parameter i.e, Δα from the boundary data. Also, the Greedy algorithms have been validated experimentally on a paraffin wax rectangular phantom through a well designed experimental set up. We also have studied the conventional DOT methods like least square method and truncated singular value decomposition (TSVD) for comparison. One of the main features of this work is the usage of less number of source-detector pairs, which can facilitate the use of DOT in routine applications of screening. The performance metrics such as mean square error (MSE), normalized mean square error (NMSE), structural similarity index (SSIM), and peak signal to noise ratio (PSNR) have been used to evaluate the performance of the algorithms mentioned in this paper. Extensive simulation results confirm that CS based DOT reconstruction outperforms the conventional DOT imaging methods in terms of
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Cha, Sang Young [Dept. of Radiology, Inha University Hospital, Incheon (Korea, Republic of); Park, Jae Yoon [Dept. of Radiology, Incheon Christian Hospital, Incheon (Korea, Republic of); Lee, Yong Ki [Dept. of Radiological Technology, DongNam Health University, Suwon (Korea, Republic of); Kim, Jeon Hun [Dept. of Radiatioin Oncology, Konyang University Hospital, Daejeon (Korea, Republic of); Choi, Jae Ho [Dept. of Radiological Technology, Ansan University, Ansan (Korea, Republic of)
2017-09-15
The purpose of this study is to investigate the image quality and exposure dose according to kVp and mAs in CT and to confirm improvement in image quality according to None IR and IR(Iterative Reconstruction) levels. Measurement results of image quality using Image J, HU(Hounsfield units) and BN(Background Noise) are decreased, while SNR(Signal to Noise Ratio) and CTDIvol(CT dose index volume) are increased as the kVp increases and there was no change of BHU(Background Hounsfield units). BN was reduced due to increased kVp, while SNR and CTDIvol were increased. Also, the higher IR stage, the lower BN, SI(Signal Intensity) and HU while SNR was improved by about 10∼60%. Based on this, when applying IR for clinical applications, it is necessary to finely adjust kVp and mA with a phased approach.
International Nuclear Information System (INIS)
Llacer, J.; Veklerov, E.; Nolan, D.; Grafton, S.T.; Mazziotta, J.C.; Hawkins, R.A.; Hoh, C.K.; Hoffman, E.J.
1990-10-01
This paper will report on the progress to date in carrying out Receiver Operating Characteristics (ROC) studies comparing Maximum Likelihood Estimator (MLE) and Filtered Backprojection (FBP) reconstructions of normal and abnormal human brain PET data in a clinical setting. A previous statistical study of reconstructions of the Hoffman brain phantom with real data indicated that the pixel-to-pixel standard deviation in feasible MLE images is approximately proportional to the square root of the number of counts in a region, as opposed to a standard deviation which is high and largely independent of the number of counts in FBP. A preliminary ROC study carried out with 10 non-medical observers performing a relatively simple detectability task indicates that, for the majority of observers, lower standard deviation translates itself into a statistically significant detectability advantage in MLE reconstructions. The initial results of ongoing tests with four experienced neurologists/nuclear medicine physicians are presented. Normal cases of 18 F -- fluorodeoxyglucose (FDG) cerebral metabolism studies and abnormal cases in which a variety of lesions have been introduced into normal data sets have been evaluated. We report on the results of reading the reconstructions of 90 data sets, each corresponding to a single brain slice. It has become apparent that the design of the study based on reading single brain slices is too insensitive and we propose a variation based on reading three consecutive slices at a time, rating only the center slice. 9 refs., 2 figs., 1 tab
Czabaj, M. W.; Riccio, M. L.; Whitacre, W. W.
2014-01-01
A combined experimental and computational study aimed at high-resolution 3D imaging, visualization, and numerical reconstruction of fiber-reinforced polymer microstructures at the fiber length scale is presented. To this end, a sample of graphite/epoxy composite was imaged at sub-micron resolution using a 3D X-ray computed tomography microscope. Next, a novel segmentation algorithm was developed, based on concepts adopted from computer vision and multi-target tracking, to detect and estimate, with high accuracy, the position of individual fibers in a volume of the imaged composite. In the current implementation, the segmentation algorithm was based on Global Nearest Neighbor data-association architecture, a Kalman filter estimator, and several novel algorithms for virtualfiber stitching, smoothing, and overlap removal. The segmentation algorithm was used on a sub-volume of the imaged composite, detecting 508 individual fibers. The segmentation data were qualitatively compared to the tomographic data, demonstrating high accuracy of the numerical reconstruction. Moreover, the data were used to quantify a) the relative distribution of individual-fiber cross sections within the imaged sub-volume, and b) the local fiber misorientation relative to the global fiber axis. Finally, the segmentation data were converted using commercially available finite element (FE) software to generate a detailed FE mesh of the composite volume. The methodology described herein demonstrates the feasibility of realizing an FE-based, virtual-testing framework for graphite/fiber composites at the constituent level.
Gebhard, Cathérine; Fuchs, Tobias A; Fiechter, Michael; Stehli, Julia; Stähli, Barbara E; Gaemperli, Oliver; Kaufmann, Philipp A
2013-10-01
The accuracy of coronary computed tomography angiography (CCTA) in obese persons is compromised by increased image noise. We investigated CCTA image quality acquired on a high-definition 64-slice CT scanner using modern adaptive statistical iterative reconstruction (ASIR). Seventy overweight and obese patients (24 males; mean age 57 years, mean body mass index 33 kg/m(2)) were studied with clinically-indicated contrast enhanced CCTA. Thirty-five patients underwent a standard definition protocol with filtered backprojection reconstruction (SD-FBP) while 35 patients matched for gender, age, body mass index and coronary artery calcifications underwent a novel high definition protocol with ASIR (HD-ASIR). Segment by segment image quality was assessed using a four-point scale (1 = excellent, 2 = good, 3 = moderate, 4 = non-diagnostic) and revealed better scores for HD-ASIR compared to SD-FBP (1.5 ± 0.43 vs. 1.8 ± 0.48; p ASIR as compared to 1.4 ± 0.4 mm for SD-FBP (p ASIR (388.3 ± 109.6 versus 350.6 ± 90.3 Hounsfield Units, HU; p ASIR vs. SD-ASIR respectively). Compared to a standard definition backprojection protocol (SD-FBP), a newer high definition scan protocol in combination with ASIR (HD-ASIR) incrementally improved image quality and visualization of distal coronary artery segments in overweight and obese individuals, without increasing image noise and radiation dose.
Algebraic reconstruction techniques for spectral reconstruction in diffuse optical tomography
International Nuclear Information System (INIS)
Brendel, Bernhard; Ziegler, Ronny; Nielsen, Tim
2008-01-01
Reconstruction in diffuse optical tomography (DOT) necessitates solving the diffusion equation, which is nonlinear with respect to the parameters that have to be reconstructed. Currently applied solving methods are based on the linearization of the equation. For spectral three-dimensional reconstruction, the emerging equation system is too large for direct inversion, but the application of iterative methods is feasible. Computational effort and speed of convergence of these iterative methods are crucial since they determine the computation time of the reconstruction. In this paper, the iterative methods algebraic reconstruction technique (ART) and conjugated gradients (CGs) as well as a new modified ART method are investigated for spectral DOT reconstruction. The aim of the modified ART scheme is to speed up the convergence by considering the specific conditions of spectral reconstruction. As a result, it converges much faster to favorable results than conventional ART and CG methods
International Nuclear Information System (INIS)
Yang, Lin; Liang, Changhong; Zhuang, Jian; Huang, Meiping; Liu, Hui
2017-01-01
Hybrid iterative reconstruction can reduce image noise and produce better image quality compared with filtered back-projection (FBP), but few reports describe optimization of the iteration level. We optimized the iteration level of iDose"4 and evaluated image quality for pediatric cardiac CT angiography. Children (n = 160) with congenital heart disease were enrolled and divided into full-dose (n = 84) and half-dose (n = 76) groups. Four series were reconstructed using FBP, and iDose"4 levels 2, 4 and 6; we evaluated subjective quality of the series using a 5-grade scale and compared the series using a Kruskal-Wallis H test. For FBP and iDose"4-optimal images, we compared contrast-to-noise ratios (CNR) and size-specific dose estimates (SSDE) using a Student's t-test. We also compared diagnostic-accuracy of each group using a Kruskal-Wallis H test. Mean scores for iDose"4 level 4 were the best in both dose groups (all P < 0.05). CNR was improved in both groups with iDose"4 level 4 as compared with FBP. Mean decrease in SSDE was 53% in the half-dose group. Diagnostic accuracy for the four datasets were in the range 92.6-96.2% (no statistical difference). iDose"4 level 4 was optimal for both the full- and half-dose groups. Protocols with iDose"4 level 4 allowed 53% reduction in SSDE without significantly affecting image quality and diagnostic accuracy. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Yang, Lin; Liang, Changhong [Southern Medical University, Guangzhou (China); Guangdong Academy of Medical Sciences, Dept. of Radiology, Guangdong General Hospital, Guangzhou (China); Zhuang, Jian [Guangdong Academy of Medical Sciences, Dept. of Cardiac Surgery, Guangdong Cardiovascular Inst., Guangdong Provincial Key Lab. of South China Structural Heart Disease, Guangdong General Hospital, Guangzhou (China); Huang, Meiping [Guangdong Academy of Medical Sciences, Dept. of Radiology, Guangdong General Hospital, Guangzhou (China); Guangdong Academy of Medical Sciences, Dept. of Catheterization Lab, Guangdong Cardiovascular Inst., Guangdong Provincial Key Lab. of South China Structural Heart Disease, Guangdong General Hospital, Guangzhou (China); Liu, Hui [Guangdong Academy of Medical Sciences, Dept. of Radiology, Guangdong General Hospital, Guangzhou (China)
2017-01-15
Hybrid iterative reconstruction can reduce image noise and produce better image quality compared with filtered back-projection (FBP), but few reports describe optimization of the iteration level. We optimized the iteration level of iDose{sup 4} and evaluated image quality for pediatric cardiac CT angiography. Children (n = 160) with congenital heart disease were enrolled and divided into full-dose (n = 84) and half-dose (n = 76) groups. Four series were reconstructed using FBP, and iDose{sup 4} levels 2, 4 and 6; we evaluated subjective quality of the series using a 5-grade scale and compared the series using a Kruskal-Wallis H test. For FBP and iDose{sup 4}-optimal images, we compared contrast-to-noise ratios (CNR) and size-specific dose estimates (SSDE) using a Student's t-test. We also compared diagnostic-accuracy of each group using a Kruskal-Wallis H test. Mean scores for iDose{sup 4} level 4 were the best in both dose groups (all P < 0.05). CNR was improved in both groups with iDose{sup 4} level 4 as compared with FBP. Mean decrease in SSDE was 53% in the half-dose group. Diagnostic accuracy for the four datasets were in the range 92.6-96.2% (no statistical difference). iDose{sup 4} level 4 was optimal for both the full- and half-dose groups. Protocols with iDose{sup 4} level 4 allowed 53% reduction in SSDE without significantly affecting image quality and diagnostic accuracy. (orig.)
Chen, Bo; Bian, Zhaoying; Zhou, Xiaohui; Chen, Wensheng; Ma, Jianhua; Liang, Zhengrong
2018-04-12
Total variation (TV) minimization for the sparse-view x-ray computer tomography (CT) reconstruction has been widely explored to reduce radiation dose. However, due to the piecewise constant assumption for the TV model, the reconstructed images often suffer from over-smoothness on the image edges. To mitigate this drawback of TV minimization, we present a Mumford-Shah total variation (MSTV) minimization algorithm in this paper. The presented MSTV model is derived by integrating TV minimization and Mumford-Shah segmentation. Subsequently, a penalized weighted least-squares (PWLS) scheme with MSTV is developed for the sparse-view CT reconstruction. For simplicity, the proposed algorithm is named as 'PWLS-MSTV.' To evaluate the performance of the present PWLS-MSTV algorithm, both qualitative and quantitative studies were conducted by using a digital XCAT phantom and a physical phantom. Experimental results show that the present PWLS-MSTV algorithm has noticeable gains over the existing algorithms in terms of noise reduction, contrast-to-ratio measure and edge-preservation.
Energy Technology Data Exchange (ETDEWEB)
Stawinski, G
1998-10-26
Bayesian algorithms are developed to solve inverse problems in gamma imaging and photofission tomography. The first part of this work is devoted to the modeling of our measurement systems. Two models have been found for both applications: the first one is a simple conventional model and the second one is a cascaded point process model. EM and MCMC Bayesian algorithms for image restoration and image reconstruction have been developed for these models and compared. The cascaded point process model does not improve significantly the results previously obtained by the classical model. To original approaches have been proposed, which increase the results previously obtained. The first approach uses an inhomogeneous Markov Random Field as a prior law, and makes the regularization parameter spatially vary. However, the problem of the estimation of hyper-parameters has not been solved. In the case of the deconvolution of point sources, a second approach has been proposed, which introduces a high level prior model. The picture is modeled as a list of objects, whose parameters and number are unknown. The results obtained with this method are more accurate than those obtained with the conventional Markov Random Field prior model and require less computational costs. (author)
Energy Technology Data Exchange (ETDEWEB)
Drews, Bjoern Holger; Gulkin, Daniel; Guelke, Joachim; Gebhard, Florian [University of Ulm, Center of Surgery, Department for Orthopedic Trauma, Hand and Reconstructive Surgery, Ulm (Germany); Merz, Cornelia; Huth, Jochen; Mauch, Frieder [Sportklinik Stuttgart GmbH, Stuttgart (Germany)
2017-10-15
Revision ACL reconstruction is becoming more frequent because of a 10% rate of re-ruptures and insufficiencies. Currently, computed tomography (CT) represents the gold standard in detecting and measuring the tunnels of the initial ACL reconstruction. The purpose of this study was to compare measurement results of CT and thin-sliced MRI sequences, which were modified to a high soft tissue-bone contrast. Prior to an ACL revision surgery, 16 consecutive patients had an MRI in addition to the standard CT scan. A dedicated 0.25-T Esaote G-Scan (Esaote Biomedica, Cologne, Germany) with a Turbo 3D T1 sequence was used for MRI. Tunnel diameters were measured at 11 defined points of interest. For the statistical evaluation, the Mann-Whitney U test for connected samples was used. Inter- and intraobserver reliability was additionally calculated. All measured diameters showed significant to highly significant correlations between both diagnostic tools (r = 0.7-0.98). In addition, there was no significant difference (p > 0.5) between the two techniques. Almost all diameters showed nearly perfect intraobserver reliability (ICC 0.8-0.97). Interobserver reliability showed an ICC of 0.91/0.92 for only one diameter in MRI and CT. Prior to ACL revision surgery, bone tunnel measurements can be done using a 3D T1-MRI sequence in low-field MRI. MRI measurements show the same accuracy as CT scans. Preoperative radiation exposure in mainly young patients could be reduced. Also the costs of an additional CT scan could be saved. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Wang, H.
2011-10-24
systeme de la tomographie par rayons X (CT), on cherche a reconstruire une image de haute qualite avec un faible nombre de projections. Les algorithmes classiques ne sont pas adaptes a cette situation: la reconstruction est perturbee par artefacts donc instable. Une nouvelle approche basee sur la theorie recente du 'Compressed Sensing' (CS) fait l'hypothese que l'image inconnue est 'parcimonieuse' ou 'compressible', et formule la reconstruction en un probleme d'optimisation (minimisation de la norme TV/l1) afin de promouvoir la parcimonie. Pour appliquer CS en CT avec le pixel (ou le voxel en 3D) comme la base de representation, il necessite une transformation de parcimonie, de plus il faut la combiner avec le 'projecteur du rayon X' qui applique sur une image pixelisee. Dans cette these, on a adapte une base radiale de famille Gaussienne nommee 'blob' a la reconstruction en CT par CS. Le blob a une meilleure localisation spatiofrequentielle que le pixel, et des operations comme la transformee en rayons X, peuvent etre evaluee analytiquement et elles sont facilement parallelisables (sur le plate-forme GPU). Compare au blob classique du Kaisser-Bessel, la nouvelle base a une structure multi-echelle: une image est la somme des translations et des dilatations d'un chapeau Mexicain radial. Les images medicales typiques sont compressibles sous cette base, ce qui entraine que le systeme de la representation parcimonieuse intervenu dans les algorithmes ordinaires de CS n'y est plus necessaire. Des simulations numeriques en 2D ont montre que, compare a l'approche equivalente basee sur la base de pixel ou d'ondelette, les algorithmes du TV et du l1 existantes sont plus efficaces et les reconstructions ont de meilleures qualites visuelles. Cette nouvelle approche a ete egalement validee sur des donnees experimentales bi-dimensionelles, ou on a observe que le nombre de projection peut etre reduit
Resolving ambiguities in reconstructed grain maps using discrete tomography
DEFF Research Database (Denmark)
Alpers, A.; Knudsen, E.; Poulsen, H.F.
2005-01-01
reconstruct the image from diffraction data, but they are often unable to assign unambiguous values to all pixels. We present an approach that resolves these ambiguous pixels by using a Monte Carlo technique that exploits the discrete nature of the problem and utilizes proven methods of discrete tomography...
EIT image reconstruction with four dimensional regularization.
Dai, Tao; Soleimani, Manuchehr; Adler, Andy
2008-09-01
Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.
Adaptive multiresolution method for MAP reconstruction in electron tomography
Energy Technology Data Exchange (ETDEWEB)
Acar, Erman, E-mail: erman.acar@tut.fi [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland); Peltonen, Sari; Ruotsalainen, Ulla [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland)
2016-11-15
3D image reconstruction with electron tomography holds problems due to the severely limited range of projection angles and low signal to noise ratio of the acquired projection images. The maximum a posteriori (MAP) reconstruction methods have been successful in compensating for the missing information and suppressing noise with their intrinsic regularization techniques. There are two major problems in MAP reconstruction methods: (1) selection of the regularization parameter that controls the balance between the data fidelity and the prior information, and (2) long computation time. One aim of this study is to provide an adaptive solution to the regularization parameter selection problem without having additional knowledge about the imaging environment and the sample. The other aim is to realize the reconstruction using sequences of resolution levels to shorten the computation time. The reconstructions were analyzed in terms of accuracy and computational efficiency using a simulated biological phantom and publically available experimental datasets of electron tomography. The numerical and visual evaluations of the experiments show that the adaptive multiresolution method can provide more accurate results than the weighted back projection (WBP), simultaneous iterative reconstruction technique (SIRT), and sequential MAP expectation maximization (sMAPEM) method. The method is superior to sMAPEM also in terms of computation time and usability since it can reconstruct 3D images significantly faster without requiring any parameter to be set by the user. - Highlights: • An adaptive multiresolution reconstruction method is introduced for electron tomography. • The method provides more accurate results than the conventional reconstruction methods. • The missing wedge and noise problems can be compensated by the method efficiently.
Energy Technology Data Exchange (ETDEWEB)
Bataille, F
2007-04-15
Positron emission tomography is a medical imaging modality providing in-vivo volumetric images of functional processes of the human body, which is used for the diagnosis and the following of neuro degenerative diseases. PET efficiency is however limited by its poor spatial resolution, which generates a decrease of the image local contrast and leads to an under-estimation of small cerebral structures involved in the degenerative mechanism of those diseases. This so-called partial volume effect degradation is usually corrected in a post-reconstruction processing framework through the use of anatomical information, whose spatial resolution allows a better discrimination between functional tissues. However, this kind of method has the major drawback of being very sensitive to the residual mismatches on the anatomical information processing. We developed in this thesis an alternative methodology to compensate for the degradation, by incorporating in the reconstruction process both a model of the system impulse response and an anatomically-based image prior constraint. This methodology was validated by comparison with a post-reconstruction correction strategy, using data from an anthropomorphic phantom acquisition and then we evaluated its robustness to the residual mismatches through a realistic Monte Carlo simulation corresponding to a cerebral exam. The proposed algorithm was finally applied to clinical data reconstruction. (author)
Energy Technology Data Exchange (ETDEWEB)
Bataille, F
2007-04-15
Positron emission tomography is a medical imaging modality providing in-vivo volumetric images of functional processes of the human body, which is used for the diagnosis and the following of neuro degenerative diseases. PET efficiency is however limited by its poor spatial resolution, which generates a decrease of the image local contrast and leads to an under-estimation of small cerebral structures involved in the degenerative mechanism of those diseases. This so-called partial volume effect degradation is usually corrected in a post-reconstruction processing framework through the use of anatomical information, whose spatial resolution allows a better discrimination between functional tissues. However, this kind of method has the major drawback of being very sensitive to the residual mismatches on the anatomical information processing. We developed in this thesis an alternative methodology to compensate for the degradation, by incorporating in the reconstruction process both a model of the system impulse response and an anatomically-based image prior constraint. This methodology was validated by comparison with a post-reconstruction correction strategy, using data from an anthropomorphic phantom acquisition and then we evaluated its robustness to the residual mismatches through a realistic Monte Carlo simulation corresponding to a cerebral exam. The proposed algorithm was finally applied to clinical data reconstruction. (author)
A fast sparse reconstruction algorithm for electrical tomography
International Nuclear Information System (INIS)
Zhao, Jia; Xu, Yanbin; Tan, Chao; Dong, Feng
2014-01-01
Electrical tomography (ET) has been widely investigated due to its advantages of being non-radiative, low-cost and high-speed. However, the image reconstruction of ET is a nonlinear and ill-posed inverse problem and the imaging results are easily affected by measurement noise. A sparse reconstruction algorithm based on L 1 regularization is robust to noise and consequently provides a high quality of reconstructed images. In this paper, a sparse reconstruction by separable approximation algorithm (SpaRSA) is extended to solve the ET inverse problem. The algorithm is competitive with the fastest state-of-the-art algorithms in solving the standard L 2 −L 1 problem. However, it is computationally expensive when the dimension of the matrix is large. To further improve the calculation speed of solving inverse problems, a projection method based on the Krylov subspace is employed and combined with the SpaRSA algorithm. The proposed algorithm is tested with image reconstruction of electrical resistance tomography (ERT). Both simulation and experimental results demonstrate that the proposed method can reduce the computational time and improve the noise robustness for the image reconstruction. (paper)
Reconstruction of an InAs nanowire using geometric and algebraic tomography
International Nuclear Information System (INIS)
Pennington, R S; Boothroyd, C B; König, S; Alpers, A; Dunin-Borkowski, R E
2011-01-01
Geometric tomography and conventional algebraic tomography algorithms are used to reconstruct cross-sections of an InAs nanowire from a tilt series of experimental annular dark-field images. Both algorithms are also applied to a test object to assess what factors affect the reconstruction quality. When using the present algorithms, geometric tomography is faster, but artifacts in the reconstruction may be difficult to recognize.
Reconstruction of an InAs nanowire using geometric and algebraic tomography
DEFF Research Database (Denmark)
Pennington, Robert S.; König, S.; Alpers, A.
2011-01-01
Geometric tomography and conventional algebraic tomography algorithms are used to reconstruct cross-sections of an InAs nanowire from a tilt series of experimental annular dark-field images. Both algorithms are also applied to a test object to assess what factors affect the reconstruction quality....... When using the present algorithms, geometric tomography is faster, but artifacts in the reconstruction may be difficult to recognize....
DART: a practical reconstruction algorithm for discrete tomography.
Batenburg, Kees Joost; Sijbers, Jan
2011-09-01
In this paper, we present an iterative reconstruction algorithm for discrete tomography, called discrete algebraic reconstruction technique (DART). DART can be applied if the scanned object is known to consist of only a few different compositions, each corresponding to a constant gray value in the reconstruction. Prior knowledge of the gray values for each of the compositions is exploited to steer the current reconstruction towards a reconstruction that contains only these gray values. Based on experiments with both simulated CT data and experimental μCT data, it is shown that DART is capable of computing more accurate reconstructions from a small number of projection images, or from a small angular range, than alternative methods. It is also shown that DART can deal effectively with noisy projection data and that the algorithm is robust with respect to errors in the estimation of the gray values.
Fully 3-D list-mode positron emission tomography image reconstruction on a multi-GPU cluster
Energy Technology Data Exchange (ETDEWEB)
Cui, Jingyu [Stanford Univ., CA (United States). Dept. of Electrical Engineering; Prevrhal, Sven; Shao, Lingxiong [Philips Healthcare, San Jose, CA (United States); Pratx, Guillem [Stanford Univ., CA (United States). Dept. of Radiation Oncology; Levin, Craig S. [Stanford Univ., CA (United States). Dept. of Radiology, Electrical Engineering, and Physics; Stanford Univ., CA (United States). Molecular Imaging Program at Stanford (MIPS); Stanford Univ., CA (United States). School of Medicine
2011-07-01
List-mode processing is an efficient way of dealing with the sparse nature of PET data sets, and is the processing method of choice for time-of-flight (ToF) PET. We present a novel method of computing line projection operations required for list-mode ordered subsets expectation maximization (OSEM) for fully 3-D PET image reconstruction on a graphics processing unit (GPU) using the compute unified device architecture (CUDA) framework. Our method overcomes challenges such as compute thread divergence, and exploits GPU capabilities such as shared memory and atomic operations. When applied to line projection operations for list-mode time-of-flight PET, this new GPU-CUDA reformulation is 188X faster than a single-threaded reference CPU implementation. When embedded in a multi-process environment on a GPU-equipped small cluster, a speedup of 4X was observed over the same configuration but without GPU support. Image quality is preserved with root mean squared (RMS) deviation of 0.05% between CPU and GPU-generated images, which has negligible effect in typical clinical applications. (orig.)
Reconstructions in ultrasound modulated optical tomography
Allmaras, Moritz; Bangerth, Wolfgang
2011-01-01
We introduce a mathematical model for ultrasound modulated optical tomography and present a simple reconstruction scheme for recovering the spatially varying optical absorption coefficient from scanning measurements with narrowly focused ultrasound signals. Computational results for this model show that the reconstruction of sharp features of the absorption coefficient is possible. A formal linearization of the model leads to an equation with a Fredholm operator, which explains the stability observed in our numerical experiments. © de Gruyter 2011.
International Nuclear Information System (INIS)
Krimmel, S.; Stephan, J.; Baumann, J.
2005-01-01
The scope of this contribution is to identify and to quantify the influence of different parameters on the formation of image artifacts in X-ray computed tomography (CT) resulting for example, from beam hardening or from partial lack of information using 3D cone beam CT. In general, the reconstructed image quality depends on a number of acquisition parameters concerning the X-ray source (e.g. X-ray spectrum), the geometrical setup (e.g. cone beam angle), the sample properties (e.g. absorption characteristics) and the detector properties. While it is difficult to distinguish the influence of different effects clearly in experimental projection data, they can be selected individually with the help of simulated projection data by varying the parameter set. The reconstruction of the 3D data set is performed with the filtered back projection algorithm according to Feldkamp, Davis and Kress for experimental as well as for simulated projection data. The experimental data are recorded with an industrial microfocus CT system which features a focal spot size of a few micrometers and uses a digital flat panel detector for data acquisition
Yang, Fuqiang; Zhang, Dinghua; Huang, Kuidong; Gao, Zongzhao; Yang, YaFei
2018-02-01
Based on the discrete algebraic reconstruction technique (DART), this study aims to address and test a new improved algorithm applied to incomplete projection data to generate a high quality reconstruction image by reducing the artifacts and noise in computed tomography. For the incomplete projections, an augmented Lagrangian based on compressed sensing is first used in the initial reconstruction for segmentation of the DART to get higher contrast graphics for boundary and non-boundary pixels. Then, the block matching 3D filtering operator was used to suppress the noise and to improve the gray distribution of the reconstructed image. Finally, simulation studies on the polychromatic spectrum were performed to test the performance of the new algorithm. Study results show a significant improvement in the signal-to-noise ratios (SNRs) and average gradients (AGs) of the images reconstructed from incomplete data. The SNRs and AGs of the new images reconstructed by DART-ALBM were on average 30%-40% and 10% higher than the images reconstructed by DART algorithms. Since the improved DART-ALBM algorithm has a better robustness to limited-view reconstruction, which not only makes the edge of the image clear but also makes the gray distribution of non-boundary pixels better, it has the potential to improve image quality from incomplete projections or sparse projections.
Yeo, Caitlin T; MacDonald, Andrew; Ungi, Tamas; Lasso, Andras; Jalink, Diederick; Zevin, Boris; Fichtinger, Gabor; Nanji, Sulaiman
A fundamental aspect of surgical planning in liver resections is the identification of key vessel tributaries to preserve healthy liver tissue while fully resecting the tumor(s). Current surgical planning relies primarily on the surgeon's ability to mentally reconstruct 2D computed tomography/magnetic resonance (CT/MR) images into 3D and plan resection margins. This creates significant cognitive load, especially for trainees, as it relies on image interpretation, anatomical and surgical knowledge, experience, and spatial sense. The purpose of this study is to determine if 3D reconstruction of preoperative CT/MR images will assist resident-level trainees in making appropriate operative plans for liver resection surgery. Ten preoperative patient CT/MR images were selected. Images were case-matched, 5 to 2D planning and 5 to 3D planning. Images from the 3D group were segmented to create interactive digital models that the resident can manipulate to view the tumor(s) in relation to landmark hepatic structures. Residents were asked to evaluate the images and devise a surgical resection plan for each image. The resident alternated between 2D and 3D planning, in a randomly generated order. The primary outcome was the accuracy of resident's plan compared to expert opinion. Time to devise each surgical plan was the secondary outcome. Residents completed a prestudy and poststudy questionnaire regarding their experience with liver surgery and the 3D planning software. Senior level surgical residents from the Queen's University General Surgery residency program were recruited to participate. A total of 14 residents participated in the study. The median correct response rate was 2 of 5 (40%; range: 0-4) for the 2D group, and 3 of 5 (60%; range: 1-5) for the 3D group (p surgery planning increases accuracy of resident surgical planning and decreases amount of time required. 3D reconstruction would be a useful model for improving trainee understanding of liver anatomy and surgical
Fast parallel algorithm for CT image reconstruction.
Flores, Liubov A; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo
2012-01-01
In X-ray computed tomography (CT) the X rays are used to obtain the projection data needed to generate an image of the inside of an object. The image can be generated with different techniques. Iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions and from a small number of projections. Their use may be important in portable scanners for their functionality in emergency situations. However, in practice, these methods are not widely used due to the high computational cost of their implementation. In this work we analyze iterative parallel image reconstruction with the Portable Extensive Toolkit for Scientific computation (PETSc).
International Nuclear Information System (INIS)
Itokawa, Hiroshi; Moriya, Masao; Fujimoto, Michio; Nagashima, Goro; Suzuki, Ryuta; Fujimoto, Tsukasa; Yasuda, Mitsuyoshi; Kato, Kyoichi; Hirade, Tsuneo
2008-01-01
Various materials have been used for cranioplasty; however these materials frequently produce artifacts that appear when examined with conventional radiography. Computed tomography (CT) in particular, detects high density artifacts near artificial bones, which is manipulated by increased noise, and limits diagnostic performance. The purpose of this study was to evaluate the extent and shape of the artifacts due to artificial cranial bones and to consider CT imaging parameters necessary for accurate recognition of structures under the materials. Four different artificial bone materials were evaluated in this study: hydroxyapatite with 40% or 50% porosity, titanium plate, and hydroxyapatite-polymethylmethacrylate composite (HA-PMMA). CT scanning was performed with standard clinical settings. Sample specimens were placed on the right side, under the artificial bones, and CT was performed to evaluate specimen visibility. We compared the artifacts created by the four bone types listed above, and measured the CT, values of those materials. With ordinary scan settings, all the artificial bones revealed high-density artifact surrounding the materials, including the inability to accurately measure specimen thickness. The upper part of the specimen in contact with the artificial bones could not be distinguished from the artifact. The CT value in the medial aspect of the artificial bones increased more than the actual CT values. Of the four artificial bone materials studied, HA-PMMA produced the fewest artifacts. Description of the structures under the artificial bones can be improved by extending the window width to aproximately twice that of normal settings. (author)
Prospects of linear reconstruction in atomic resolution electron holographic tomography
International Nuclear Information System (INIS)
Krehl, Jonas; Lubk, Axel
2015-01-01
Tomography commonly requires a linear relation between the measured signal and the underlying specimen property; for Electron Holographic Tomography this is given by the Phase Grating Approximation (PGA). While largely valid at medium resolution, discrepancies arise at high resolution imaging conditions. We set out to investigate the artefacts that are produced if the reconstruction still assumes the PGA even with an atomic resolution tilt series. To forego experimental difficulties the holographic tilt series was simulated. The reconstructed electric potential clearly shows peaks at the positions of the atoms. These peaks have characterisitic deformations, which can be traced back to the defocus a particular atom has in the holograms of the tilt series. Exchanging an atom for one of a different atomic number results in a significant change in the reconstructed potential that is well contained within the atom's peak. - Highlights: • We simulate a holographic tilt series of a nanocrystal with atomic resolution. • Using PGA-based Holographic Tomography we reconstruct the atomic structure. • The reconstruction shows characteristic artefacts, chiefly caused by defocus. • Changing one atom's Z produces a well localised in the reconstruction
Prospects of linear reconstruction in atomic resolution electron holographic tomography
Energy Technology Data Exchange (ETDEWEB)
Krehl, Jonas, E-mail: Jonas.Krehl@triebenberg.de; Lubk, Axel
2015-03-15
Tomography commonly requires a linear relation between the measured signal and the underlying specimen property; for Electron Holographic Tomography this is given by the Phase Grating Approximation (PGA). While largely valid at medium resolution, discrepancies arise at high resolution imaging conditions. We set out to investigate the artefacts that are produced if the reconstruction still assumes the PGA even with an atomic resolution tilt series. To forego experimental difficulties the holographic tilt series was simulated. The reconstructed electric potential clearly shows peaks at the positions of the atoms. These peaks have characterisitic deformations, which can be traced back to the defocus a particular atom has in the holograms of the tilt series. Exchanging an atom for one of a different atomic number results in a significant change in the reconstructed potential that is well contained within the atom's peak. - Highlights: • We simulate a holographic tilt series of a nanocrystal with atomic resolution. • Using PGA-based Holographic Tomography we reconstruct the atomic structure. • The reconstruction shows characteristic artefacts, chiefly caused by defocus. • Changing one atom's Z produces a well localised in the reconstruction.
International Nuclear Information System (INIS)
Qureshi, S.A.; Mirza, S.M.; Arif, M.
2007-01-01
This paper present the effect of number of projections on inverse Radon transform (IRT) estimation using filtered back-projection (FBP) technique for parallel beam transmission tomography. The head phantom and the lung phantom have been used in this work. Various filters used in this study include Ram-Lak, Shepp-Logan, Cosin, Hamming and Hanning filters. The slices have been reconstructed by increasing the number of projections through parallel beam transmission tomography keeping the projections uniformly distributed. The Euclidean and Mean Squared errors and peak signal-to-noise ratio (PSNR) have been analyzed for their sensitiveness as functions of number of projections. It has found that image quality improves with the number of projections but at the cost of the computer time. The error has been minimized to get the best approximation of inverse Radon transform (IRT) as the number of projections is enhanced. The value of PSNR has been found to increase from 8.20 to 24.53 dB as the number of projections is raised from 5 to 180 for head phantom. (author)
Filter-based reconstruction methods for tomography
Pelt, D.M.
2016-01-01
In X-ray tomography, a three-dimensional image of the interior of an object is computed from multiple X-ray images, acquired over a range of angles. Two types of methods are commonly used to compute such an image: analytical methods and iterative methods. Analytical methods are computationally
Improved specimen reconstruction by Hilbert phase contrast tomography.
Barton, Bastian; Joos, Friederike; Schröder, Rasmus R
2008-11-01
The low signal-to-noise ratio (SNR) in images of unstained specimens recorded with conventional defocus phase contrast makes it difficult to interpret 3D volumes obtained by electron tomography (ET). The high defocus applied for conventional tilt series generates some phase contrast but leads to an incomplete transfer of object information. For tomography of biological weak-phase objects, optimal image contrast and subsequently an optimized SNR are essential for the reconstruction of details such as macromolecular assemblies at molecular resolution. The problem of low contrast can be partially solved by applying a Hilbert phase plate positioned in the back focal plane (BFP) of the objective lens while recording images in Gaussian focus. Images recorded with the Hilbert phase plate provide optimized positive phase contrast at low spatial frequencies, and the contrast transfer in principle extends to the information limit of the microscope. The antisymmetric Hilbert phase contrast (HPC) can be numerically converted into isotropic contrast, which is equivalent to the contrast obtained by a Zernike phase plate. Thus, in-focus HPC provides optimal structure factor information without limiting effects of the transfer function. In this article, we present the first electron tomograms of biological specimens reconstructed from Hilbert phase plate image series. We outline the technical implementation of the phase plate and demonstrate that the technique is routinely applicable for tomography. A comparison between conventional defocus tomograms and in-focus HPC volumes shows an enhanced SNR and an improved specimen visibility for in-focus Hilbert tomography.
Parallel CT image reconstruction based on GPUs
International Nuclear Information System (INIS)
Flores, Liubov A.; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo
2014-01-01
In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their implementation. Nowadays technology provides the possibility to reduce effectively this drawback. It is the goal of this work to develop a fast GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data. - Highlights: • We developed GPU-based iterative algorithm to reconstruct images. • Iterative algorithms are capable to reconstruct images from under sampled set of projections. • The computer cost of the implementation of the developed algorithm is low. • The efficiency of the algorithm increases for the large scale problems
Directory of Open Access Journals (Sweden)
Stević Miloš
2016-01-01
Full Text Available Background/Aim. Filtered back projection (FBP is a common way of processing myocardial perfusion imaging (MPI studies. There are artifacts in FBP which can cause falsepositive results. Iterative reconstruction (IR is developed to reduce false positive findings in MPI studies. The aim of this study was to evaluate the difference in the number of false positive findings in MPI studies, between FBP and IR processing. Methods. We examined 107 patients with angina pectoris with MPI and coronary angiography (CAG, 77 man and 30 woman, aged 32−82. MPI studies were processed with FBP and with IR. Positive finding at MPI was visualization of the perfusion defect. Positive finding at CAG was stenosis of coronary artery. Perfusion defect at MPI without coronary artery stenosis at CAG was considered like false positive. The results were statistically analyzed with bivariate correlation, and with one sample t-test. Results. There were 20.6% normal, and 79.4% pathologic findings at FBP, 30.8% normal and 69.2% pathologic with IR and 37.4% normal and 62.6% pathologic at CAG. FBP produced 19 false-positive findings, at IR 11 false positive findings. The correlation between FBP and CAG was 0.658 (p < 0.01 and between IR and CAG 0.784 (p < 0.01. The number of false positive findings at MPI with IR was significantly lower than at FBP (p < 0.01. Conclusion. Our study shows that IR processing MPI scintigraphy has less number of false positive findings, therefore it is our choice for processing MPI studies.
Duality reconstruction algorithm for use in electrical impedance tomography
International Nuclear Information System (INIS)
Abdullah, M.Z.; Dickin, F.J.
1996-01-01
A duality reconstruction algorithm for solving the inverse problem in electrical impedance tomography (EIT) is described. In this method, an algorithm based on the Geselowitz compensation (GC) theorem is used first to reconstruct an approximate version of the image. It is then fed as a first guessed data to the modified Newton-Raphson (MNR) algorithm which iteratively correct the image until a final acceptable solution is reached. The implementation of the GC and MNR based algorithms using the finite element method will be discussed. Reconstructed images produced by the algorithm will also be presented. Consideration is also given to the most computationally intensive aspects of the algorithm, namely the inversion of the large and sparse matrices. The methods taken to approximately compute the inverse ot those matrices will be outlined. (author)
Iterative concurrent reconstruction algorithms for emission computed tomography
International Nuclear Information System (INIS)
Brown, J.K.; Hasegawa, B.H.; Lang, T.F.
1994-01-01
Direct reconstruction techniques, such as those based on filtered backprojection, are typically used for emission computed tomography (ECT), even though it has been argued that iterative reconstruction methods may produce better clinical images. The major disadvantage of iterative reconstruction algorithms, and a significant reason for their lack of clinical acceptance, is their computational burden. We outline a new class of ''concurrent'' iterative reconstruction techniques for ECT in which the reconstruction process is reorganized such that a significant fraction of the computational processing occurs concurrently with the acquisition of ECT projection data. These new algorithms use the 10-30 min required for acquisition of a typical SPECT scan to iteratively process the available projection data, significantly reducing the requirements for post-acquisition processing. These algorithms are tested on SPECT projection data from a Hoffman brain phantom acquired with a 2 x 10 5 counts in 64 views each having 64 projections. The SPECT images are reconstructed as 64 x 64 tomograms, starting with six angular views. Other angular views are added to the reconstruction process sequentially, in a manner that reflects their availability for a typical acquisition protocol. The results suggest that if T s of concurrent processing are used, the reconstruction processing time required after completion of the data acquisition can be reduced by at least 1/3 T s. (Author)
International Nuclear Information System (INIS)
Bamba, Yohei; Nonaka, Masahiro; Nakajima, Shin; Yamasaki, Mami
2011-01-01
Surgical procedures for spinal lipoma or tethered spinal cord after myelomeningocele (MMC) repair are often difficult and complicated, because the anatomical structures can be deformed in complex and unpredictable ways. Imaging helps the surgeon understand the patient's spinal anatomy. Whereas two-dimensional images provide only limited information for surgical planning, three-dimensional (3D) reconstructed computed tomography (CT)-magnetic resonance (MR) fusion images produce clearer representations of the spinal regions. Here we describe simple and quick methods for obtaining 3D reconstructed CT-MR fusion images for preoperative planning of surgical procedures using the iPlan cranial (BrainLAB AG, Feldkirchen, Germany) neuronavigation software. 3D CT images of the vertebral bone were combined with heavily T 2 -weighted MR images of the spinal cord, lipoma, cerebrospinal fluid (CSF) space, and nerve root through a process of fusion, segmentation, and reconstruction of the 3D images. We also used our procedure called 'Image Overlay' to directly project the 3D reconstructed image onto the body surface using an light emitting diode (LED) projector. The final reconstructed 3D images took 10-30 minutes to obtain, and provided the surgeon with a representation of the individual pathological structures, so enabled the design of effective surgical plans, even in patients with bony deformity such as scoliosis. None of the 19 patients treated based on our 3D reconstruction method has had neurological complications, except for CSF leakage. This 3D reconstructed imaging method, combined with Image Overlay, improves the visual understanding of complicated surgical situations, and should improve surgical efficiency and outcome. (author)
Geometric reconstruction methods for electron tomography
DEFF Research Database (Denmark)
Alpers, Andreas; Gardner, Richard J.; König, Stefan
2013-01-01
Electron tomography is becoming an increasingly important tool in materials science for studying the three-dimensional morphologies and chemical compositions of nanostructures. The image quality obtained by many current algorithms is seriously affected by the problems of missing wedge artefacts...... and discuss several algorithms from the mathematical fields of geometric and discrete tomography. The algorithms incorporate geometric prior knowledge (mainly convexity and homogeneity), which also in principle considerably reduces the number of tilt angles required. Results are discussed...
Energy Technology Data Exchange (ETDEWEB)
Park, Juil [Seoul National University Children' s Hospital, Department of Radiology, Seoul (Korea, Republic of); Choi, Young Hun [Seoul National University Children' s Hospital, Department of Radiology, Seoul (Korea, Republic of); Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Cheon, Jung-Eun; Kim, Woo Sun; Kim, In-One [Seoul National University Children' s Hospital, Department of Radiology, Seoul (Korea, Republic of); Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul (Korea, Republic of); Pak, Seong Yong [Siemens Healthineers, Seoul (Korea, Republic of); Krauss, Bernhard [Siemens Healthineers, Forchheim (Germany)
2017-11-15
Advanced virtual monochromatic reconstruction from dual-energy brain CT has not been evaluated in children. To determine the most effective advanced virtual monochromatic imaging energy level for maximizing pediatric brain parenchymal image quality in dual-energy unenhanced brain CT and to compare this technique with conventional monochromatic reconstruction and polychromatic scanning. Using both conventional (Mono) and advanced monochromatic reconstruction (Mono+) techniques, we retrospectively reconstructed 13 virtual monochromatic imaging energy levels from 40 keV to 100 keV in 5-keV increments from dual-source, dual-energy unenhanced brain CT scans obtained in 23 children. We analyzed gray and white matter noise ratios, signal-to-noise ratios and contrast-to-noise ratio, and posterior fossa artifact. We chose the optimal mono-energetic levels and compared them with conventional CT. For Mono+maximum optima were observed at 60 keV, and minimum posterior fossa artifact at 70 keV. For Mono, optima were at 65-70 keV, with minimum posterior fossa artifact at 75 keV. Mono+ was superior to Mono and to polychromatic CT for image-quality measures. Subjective analysis rated Mono+superior to other image sets. Optimal virtual monochromatic imaging using Mono+ algorithm demonstrated better image quality for gray-white matter differentiation and reduction of the artifact in the posterior fossa. (orig.)
Reconstructed frontal and coronal cuts in computed tomography of the trunk
International Nuclear Information System (INIS)
Fochem, K.; Klumair, J.
1982-01-01
A comparison between the original coronally cuts and the reconstructed coronal cuts yielded basic information on the loss of quality by computed reconstruction of images. As for the trunk, only comparisons between the conventional linear tomography and computed frontal of trunk cuts are possible. A few examples will demonstrate that despite a considerable loss of quality, computed frontal cuts will supply additional information in certain cases. It is also shown that the reconstructed frontal cuts cannot replace conventional tomography. (orig.) [de
Energy Technology Data Exchange (ETDEWEB)
Moon, Tae Joon [Dept. of Radiology, Konkuk University Medical Center, Seoul (Korea, Republic of); Kim, Ki Jeong [Dept. of Radiology, Wonkwang University Hospital, Iksan (Korea, Republic of); Lee, Hye Nam [Dept. of Radiology, Gimsangyeong Internal Medicine Clinic, Nonsan (Korea, Republic of)
2017-06-15
The study has attempted to evaluate and compare the image evaluation and exposure dose by respectively applying filter back projection (FBP), the existing test method, and adaptive statistical iterative reconstruction (ASIR) with different values of tube voltage during the low dose computed tomography (LDCT). With the image reconstruction method as basis, chest phantom was utilized with the FBP and ASIR set at 10%, 20% respectively, and the change of tube voltage (100 kVp, 120 kVp). For image evaluation, back ground noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were measured, and, for dose assessment, CTDIvol and DLP were measured respectively. In terms of image evaluation, there was significant difference in ascending aorta (AA) SNR and inpraspinatus muscle (IM) SNR with the different amount of tube voltage (p < 0.05). In terms of CTDIvol, the measured values with the same tube voltage of 120 kVp were 2.6 mGy with no-ASIR and 2.17 mGy with 20%-ASIR respectively, decreased by 0.43 mGy, and the values with 100 kVp were 1.61 mGy with no-ASIR and 1.34 mGy with 20%-ASIR, decreased by 0.27 mGy. In terms of DLP, the measured values with 120 kVp were 103.21 mGy‧cm with no-ASIR and 85.94 mGy‧cm with 20%-ASIR, decreased by 17.27mGy‧cm (about 16.7%), and the values with 100 kVp were 63.84 mGy‧cm with no-ASIR and 53.25 mGy‧cm with 20%-ASIR, a decrease by 10.62 mGy‧cm ( about 16.7%). At lower tube voltage, the rate of dose significantly decreased, but the negative effects on image evaluation was shown due to the increase of noise.
International Nuclear Information System (INIS)
Moon, Tae Joon; Kim, Ki Jeong; Lee, Hye Nam
2017-01-01
The study has attempted to evaluate and compare the image evaluation and exposure dose by respectively applying filter back projection (FBP), the existing test method, and adaptive statistical iterative reconstruction (ASIR) with different values of tube voltage during the low dose computed tomography (LDCT). With the image reconstruction method as basis, chest phantom was utilized with the FBP and ASIR set at 10%, 20% respectively, and the change of tube voltage (100 kVp, 120 kVp). For image evaluation, back ground noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were measured, and, for dose assessment, CTDIvol and DLP were measured respectively. In terms of image evaluation, there was significant difference in ascending aorta (AA) SNR and inpraspinatus muscle (IM) SNR with the different amount of tube voltage (p < 0.05). In terms of CTDIvol, the measured values with the same tube voltage of 120 kVp were 2.6 mGy with no-ASIR and 2.17 mGy with 20%-ASIR respectively, decreased by 0.43 mGy, and the values with 100 kVp were 1.61 mGy with no-ASIR and 1.34 mGy with 20%-ASIR, decreased by 0.27 mGy. In terms of DLP, the measured values with 120 kVp were 103.21 mGy‧cm with no-ASIR and 85.94 mGy‧cm with 20%-ASIR, decreased by 17.27mGy‧cm (about 16.7%), and the values with 100 kVp were 63.84 mGy‧cm with no-ASIR and 53.25 mGy‧cm with 20%-ASIR, a decrease by 10.62 mGy‧cm ( about 16.7%). At lower tube voltage, the rate of dose significantly decreased, but the negative effects on image evaluation was shown due to the increase of noise
Reconstruction and visualization of nanoparticle composites by transmission electron tomography
Energy Technology Data Exchange (ETDEWEB)
Wang, X.Y. [National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, Canada T6H 2M9 (Canada); Department of Physics, University of Alberta, Edmonton, Canada T6G 2G7 (Canada); Lockwood, R. [National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, Canada T6H 2M9 (Canada); Malac, M., E-mail: marek.malac@nrc-cnrc.gc.ca [National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, Canada T6H 2M9 (Canada); Department of Physics, University of Alberta, Edmonton, Canada T6G 2G7 (Canada); Furukawa, H. [SYSTEM IN FRONTIER INC., 2-8-3, Shinsuzuharu bldg. 4F, Akebono-cho, Tachikawa-shi, Tokyo 190-0012 (Japan); Li, P.; Meldrum, A. [National Institute for Nanotechnology, 11421 Saskatchewan Drive, Edmonton, Canada T6H 2M9 (Canada)
2012-02-15
This paper examines the limits of transmission electron tomography reconstruction methods for a nanocomposite object composed of many closely packed nanoparticles. Two commonly used reconstruction methods in TEM tomography were examined and compared, and the sources of various artefacts were explored. Common visualization methods were investigated, and the resulting 'interpretation artefacts' ( i.e., deviations from 'actual' particle sizes and shapes arising from the visualization) were determined. Setting a known or estimated nanoparticle volume fraction as a criterion for thresholding does not in fact give a good visualization. Unexpected effects associated with common built-in image filtering methods were also found. Ultimately, this work set out to establish the common problems and pitfalls associated with electron beam tomographic reconstruction and visualization of samples consisting of closely spaced nanoparticles. -- Highlights: Black-Right-Pointing-Pointer Electron tomography limits were explored by both experiment and simulation. Black-Right-Pointing-Pointer Reliable quantitative volumetry using electron tomography is not presently feasible. Black-Right-Pointing-Pointer Volume rendering appears to be better choice for visualization of composite samples.
Practical implementation of tetrahedral mesh reconstruction in emission tomography
Boutchko, R.; Sitek, A.; Gullberg, G. T.
2013-05-01
This paper presents a practical implementation of image reconstruction on tetrahedral meshes optimized for emission computed tomography with parallel beam geometry. Tetrahedral mesh built on a point cloud is a convenient image representation method, intrinsically three-dimensional and with a multi-level resolution property. Image intensities are defined at the mesh nodes and linearly interpolated inside each tetrahedron. For the given mesh geometry, the intensities can be computed directly from tomographic projections using iterative reconstruction algorithms with a system matrix calculated using an exact analytical formula. The mesh geometry is optimized for a specific patient using a two stage process. First, a noisy image is reconstructed on a finely-spaced uniform cloud. Then, the geometry of the representation is adaptively transformed through boundary-preserving node motion and elimination. Nodes are removed in constant intensity regions, merged along the boundaries, and moved in the direction of the mean local intensity gradient in order to provide higher node density in the boundary regions. Attenuation correction and detector geometric response are included in the system matrix. Once the mesh geometry is optimized, it is used to generate the final system matrix for ML-EM reconstruction of node intensities and for visualization of the reconstructed images. In dynamic PET or SPECT imaging, the system matrix generation procedure is performed using a quasi-static sinogram, generated by summing projection data from multiple time frames. This system matrix is then used to reconstruct the individual time frame projections. Performance of the new method is evaluated by reconstructing simulated projections of the NCAT phantom and the method is then applied to dynamic SPECT phantom and patient studies and to a dynamic microPET rat study. Tetrahedral mesh-based images are compared to the standard voxel-based reconstruction for both high and low signal-to-noise ratio
Practical implementation of tetrahedral mesh reconstruction in emission tomography
International Nuclear Information System (INIS)
Boutchko, R; Gullberg, G T; Sitek, A
2013-01-01
This paper presents a practical implementation of image reconstruction on tetrahedral meshes optimized for emission computed tomography with parallel beam geometry. Tetrahedral mesh built on a point cloud is a convenient image representation method, intrinsically three-dimensional and with a multi-level resolution property. Image intensities are defined at the mesh nodes and linearly interpolated inside each tetrahedron. For the given mesh geometry, the intensities can be computed directly from tomographic projections using iterative reconstruction algorithms with a system matrix calculated using an exact analytical formula. The mesh geometry is optimized for a specific patient using a two stage process. First, a noisy image is reconstructed on a finely-spaced uniform cloud. Then, the geometry of the representation is adaptively transformed through boundary-preserving node motion and elimination. Nodes are removed in constant intensity regions, merged along the boundaries, and moved in the direction of the mean local intensity gradient in order to provide higher node density in the boundary regions. Attenuation correction and detector geometric response are included in the system matrix. Once the mesh geometry is optimized, it is used to generate the final system matrix for ML-EM reconstruction of node intensities and for visualization of the reconstructed images. In dynamic PET or SPECT imaging, the system matrix generation procedure is performed using a quasi-static sinogram, generated by summing projection data from multiple time frames. This system matrix is then used to reconstruct the individual time frame projections. Performance of the new method is evaluated by reconstructing simulated projections of the NCAT phantom and the method is then applied to dynamic SPECT phantom and patient studies and to a dynamic microPET rat study. Tetrahedral mesh-based images are compared to the standard voxel-based reconstruction for both high and low signal-to-noise ratio
Photoacoustic image reconstruction via deep learning
Antholzer, Stephan; Haltmeier, Markus; Nuster, Robert; Schwab, Johannes
2018-02-01
Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.
Image processing tensor transform and discrete tomography with Matlab
Grigoryan, Artyom M
2012-01-01
Focusing on mathematical methods in computer tomography, Image Processing: Tensor Transform and Discrete Tomography with MATLAB(R) introduces novel approaches to help in solving the problem of image reconstruction on the Cartesian lattice. Specifically, it discusses methods of image processing along parallel rays to more quickly and accurately reconstruct images from a finite number of projections, thereby avoiding overradiation of the body during a computed tomography (CT) scan. The book presents several new ideas, concepts, and methods, many of which have not been published elsewhere. New co
Dose fractionation theorem in 3-D reconstruction (tomography)
International Nuclear Information System (INIS)
Glaeser, R.M.
1997-01-01
It is commonly assumed that the large number of projections for single-axis tomography precludes its application to most beam-labile specimens. However, Hegerl and Hoppe have pointed out that the total dose required to achieve statistical significance for each voxel of a computed 3-D reconstruction is the same as that required to obtain a single 2-D image of that isolated voxel, at the same level of statistical significance. Thus a statistically significant 3-D image can be computed from statistically insignificant projections, as along as the total dosage that is distributed among these projections is high enough that it would have resulted in a statistically significant projection, if applied to only one image. We have tested this critical theorem by simulating the tomographic reconstruction of a realistic 3-D model created from an electron micrograph. The simulations verify the basic conclusions of high absorption, signal-dependent noise, varying specimen contrast and missing angular range. Furthermore, the simulations demonstrate that individual projections in the series of fractionated-dose images can be aligned by cross-correlation because they contain significant information derived from the summation of features from different depths in the structure. This latter information is generally not useful for structural interpretation prior to 3-D reconstruction, owing to the complexity of most specimens investigated by single-axis tomography. These results, in combination with dose estimates for imaging single voxels and measurements of radiation damage in the electron microscope, demonstrate that it is feasible to use single-axis tomography with soft X-ray microscopy of frozen-hydrated specimens
Dose fractionation theorem in 3-D reconstruction (tomography)
Energy Technology Data Exchange (ETDEWEB)
Glaeser, R.M. [Lawrence Berkeley National Lab., CA (United States)
1997-02-01
It is commonly assumed that the large number of projections for single-axis tomography precludes its application to most beam-labile specimens. However, Hegerl and Hoppe have pointed out that the total dose required to achieve statistical significance for each voxel of a computed 3-D reconstruction is the same as that required to obtain a single 2-D image of that isolated voxel, at the same level of statistical significance. Thus a statistically significant 3-D image can be computed from statistically insignificant projections, as along as the total dosage that is distributed among these projections is high enough that it would have resulted in a statistically significant projection, if applied to only one image. We have tested this critical theorem by simulating the tomographic reconstruction of a realistic 3-D model created from an electron micrograph. The simulations verify the basic conclusions of high absorption, signal-dependent noise, varying specimen contrast and missing angular range. Furthermore, the simulations demonstrate that individual projections in the series of fractionated-dose images can be aligned by cross-correlation because they contain significant information derived from the summation of features from different depths in the structure. This latter information is generally not useful for structural interpretation prior to 3-D reconstruction, owing to the complexity of most specimens investigated by single-axis tomography. These results, in combination with dose estimates for imaging single voxels and measurements of radiation damage in the electron microscope, demonstrate that it is feasible to use single-axis tomography with soft X-ray microscopy of frozen-hydrated specimens.
A combined reconstruction-classification method for diffuse optical tomography
Energy Technology Data Exchange (ETDEWEB)
Hiltunen, P [Department of Biomedical Engineering and Computational Science, Helsinki University of Technology, PO Box 3310, FI-02015 TKK (Finland); Prince, S J D; Arridge, S [Department of Computer Science, University College London, Gower Street London, WC1E 6B (United Kingdom)], E-mail: petri.hiltunen@tkk.fi, E-mail: s.prince@cs.ucl.ac.uk, E-mail: s.arridge@cs.ucl.ac.uk
2009-11-07
We present a combined classification and reconstruction algorithm for diffuse optical tomography (DOT). DOT is a nonlinear ill-posed inverse problem. Therefore, some regularization is needed. We present a mixture of Gaussians prior, which regularizes the DOT reconstruction step. During each iteration, the parameters of a mixture model are estimated. These associate each reconstructed pixel with one of several classes based on the current estimate of the optical parameters. This classification is exploited to form a new prior distribution to regularize the reconstruction step and update the optical parameters. The algorithm can be described as an iteration between an optimization scheme with zeroth-order variable mean and variance Tikhonov regularization and an expectation-maximization scheme for estimation of the model parameters. We describe the algorithm in a general Bayesian framework. Results from simulated test cases and phantom measurements show that the algorithm enhances the contrast of the reconstructed images with good spatial accuracy. The probabilistic classifications of each image contain only a few misclassified pixels.
Positron Emission Tomography with Three-Dimensional Reconstruction
Energy Technology Data Exchange (ETDEWEB)
Erlandsson, K.
1996-10-01
The development of two different low-cost scanners for positron emission tomography (PET) based on 3D acquisition are presented. The first scanner consists of two rotating scintillation cameras, and produces quantitative images, which have shown to be clinically useful. The second one is a system with two opposed sets of detectors, based on the limited angle tomography principle, dedicated for mammographic studies. The development of low-cost PET scanners can increase the clinical impact of PET, which is an expensive modality, only available at a few centres world-wide and mainly used as a research tool. A 3D reconstruction method was developed that utilizes all the available data. The size of the data-sets is considerably reduced, using the single-slice rebinning approximation. The 3D reconstruction is divided into 1D axial deconvolution and 2D transaxial reconstruction, which makes it relatively fast. This method was developed for the rotating scanner, but was also implemented for multi-ring scanners with and without inter plane septa. An iterative 3D reconstruction method was developed for the limited angle scanner, based on the new concept of `mobile pixels`, which reduces the finite pixel errors and leads to an improved signal to noise ratio. 100 refs.
Positron Emission Tomography with Three-Dimensional Reconstruction
International Nuclear Information System (INIS)
Erlandsson, K.
1996-10-01
The development of two different low-cost scanners for positron emission tomography (PET) based on 3D acquisition are presented. The first scanner consists of two rotating scintillation cameras, and produces quantitative images, which have shown to be clinically useful. The second one is a system with two opposed sets of detectors, based on the limited angle tomography principle, dedicated for mammographic studies. The development of low-cost PET scanners can increase the clinical impact of PET, which is an expensive modality, only available at a few centres world-wide and mainly used as a research tool. A 3D reconstruction method was developed that utilizes all the available data. The size of the data-sets is considerably reduced, using the single-slice rebinning approximation. The 3D reconstruction is divided into 1D axial deconvolution and 2D transaxial reconstruction, which makes it relatively fast. This method was developed for the rotating scanner, but was also implemented for multi-ring scanners with and without inter plane septa. An iterative 3D reconstruction method was developed for the limited angle scanner, based on the new concept of 'mobile pixels', which reduces the finite pixel errors and leads to an improved signal to noise ratio. 100 refs
System Matrix Analysis for Computed Tomography Imaging
Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo
2015-01-01
In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482
3-D image reconstruction in radiology
International Nuclear Information System (INIS)
Grangeat, P.
1999-01-01
In this course, we present highlights on fully 3-D image reconstruction algorithms used in 3-D X-ray Computed Tomography (3-D-CT) and 3-D Rotational Radiography (3-D-RR). We first consider the case of spiral CT with a one-row detector. Starting from the 2-D fan-beam inversion formula for a circular trajectory, we introduce spiral CT 3-D image reconstruction algorithm using axial interpolation for each transverse slice. In order to improve the X-ray detection efficiency and to speed the acquisition process, the future is to use multi-row detectors associated with small angle cone-beam geometry. The generalization of the 2-D fan-beam image reconstruction algorithm to cone beam defined direct inversion formula referred as Feldkamp's algorithm for a circular trajectory and Wang's algorithm for a spiral trajectory. However, large area detectors does exist such as Radiological Image Intensifiers or in a near future solid state detectors. To get a larger zoom effect, it defines a cone-beam geometry associated with a large aperture angle. For this case, we introduce indirect image reconstruction algorithm by plane re-binning in the Radon domain. We will present some results from a prototype MORPHOMETER device using the RADON reconstruction software. Lastly, we consider the special case of 3-D Rotational Digital Subtraction Angiography with a restricted number of views. We introduce constraint optimization algorithm using quadratic, entropic or half-quadratic constraints. Generalized ART (Algebraic Reconstruction Technique) iterative reconstruction algorithm can be derived from the Bregman algorithm. We present reconstructed vascular trees from a prototype MORPHOMETER device. (author)
Continuous analog of multiplicative algebraic reconstruction technique for computed tomography
Tateishi, Kiyoko; Yamaguchi, Yusaku; Abou Al-Ola, Omar M.; Kojima, Takeshi; Yoshinaga, Tetsuya
2016-03-01
We propose a hybrid dynamical system as a continuous analog to the block-iterative multiplicative algebraic reconstruction technique (BI-MART), which is a well-known iterative image reconstruction algorithm for computed tomography. The hybrid system is described by a switched nonlinear system with a piecewise smooth vector field or differential equation and, for consistent inverse problems, the convergence of non-negatively constrained solutions to a globally stable equilibrium is guaranteed by the Lyapunov theorem. Namely, we can prove theoretically that a weighted Kullback-Leibler divergence measure can be a common Lyapunov function for the switched system. We show that discretizing the differential equation by using the first-order approximation (Euler's method) based on the geometric multiplicative calculus leads to the same iterative formula of the BI-MART with the scaling parameter as a time-step of numerical discretization. The present paper is the first to reveal that a kind of iterative image reconstruction algorithm is constructed by the discretization of a continuous-time dynamical system for solving tomographic inverse problems. Iterative algorithms with not only the Euler method but also the Runge-Kutta methods of lower-orders applied for discretizing the continuous-time system can be used for image reconstruction. A numerical example showing the characteristics of the discretized iterative methods is presented.
Five and eight image tomography
International Nuclear Information System (INIS)
Bell, P.R.; Dillon, R.S.
1977-01-01
This method can be implemented with standard equipment and only requires images with the usual total count and time. The time for image reconstruction is negligible since 6 slices are reconstructed in 40 seconds. While the resolution in the slices is relatively poor, it is sufficient for the location of emitting structures shown in the standard views
Reconstruction methods for phase-contrast tomography
Energy Technology Data Exchange (ETDEWEB)
Raven, C.
1997-02-01
Phase contrast imaging with coherent x-rays can be distinguished in outline imaging and holography, depending on the wavelength {lambda}, the object size d and the object-to-detector distance r. When r << d{sup 2}{lambda}, phase contrast occurs only in regions where the refractive index fastly changes, i.e. at interfaces and edges in the sample. With increasing object-to-detector distance we come in the area of holographic imaging. The image contrast outside the shadow region of the object is due to interference of the direct, undiffracted beam and a beam diffracted by the object, or, in terms of holography, the interference of a reference wave with the object wave. Both, outline imaging and holography, offer the possibility to obtain three dimensional information of the sample in conjunction with a tomographic technique. But the data treatment and the kind of information one can obtain from the reconstruction is different.
Cellular imaging electron tomography and related techniques
2018-01-01
This book highlights important techniques for cellular imaging and covers the basics and applications of electron tomography and related techniques. In addition, it considers practical aspects and broadens the technological focus by incorporating techniques that are only now becoming accessible (e.g. block face imaging). The first part of the book describes the electron microscopy 3D technique available to scientists around the world, allowing them to characterize organelles, cells and tissues. The major emphasis is on new technologies like scanning transmission electron microscopy (STEM) tomography, though the book also reviews some of the more proven technologies like electron tomography. In turn, the second part is dedicated to the reconstruction of data sets, signal improvement and interpretation.
Tomography reconstruction methods for damage diagnosis of wood structure in construction field
Qiu, Qiwen; Lau, Denvid
2018-03-01
The structural integrity of wood building element plays a critical role in the public safety, which requires effective methods for diagnosis of internal damage inside the wood body. Conventionally, the non-destructive testing (NDT) methods such as X-ray computed tomography, thermography, radar imaging reconstruction method, ultrasonic tomography, nuclear magnetic imaging techniques, and sonic tomography have been used to obtain the information about the internal structure of wood. In this paper, the applications, advantages and disadvantages of these traditional tomography methods are reviewed. Additionally, the present article gives an overview of recently developed tomography approach that relies on the use of mechanical and electromagnetic waves for assessing the structural integrity of wood buildings. This developed tomography reconstruction method is believed to provide a more accurate, reliable, and comprehensive assessment of wood structural integrity
New possibilities of three-dimensional reconstruction of computed tomography scans
International Nuclear Information System (INIS)
Herman, M.; Tarjan, Z.; Pozzi-Mucelli, R.S.
1996-01-01
Three-dimensional (3D) computed tomography (CT) scan reconstructions provide impressive and illustrative images of various parts of the human body. Such images are reconstructed from a series of basic CT scans by dedicated software. The state of the art in 3D computed tomography is demonstrated with emphasis on the imaging of soft tissues. Examples are presented of imaging the craniofacial and maxillofacial complex, central nervous system, cardiovascular system, musculoskeletal system, gastrointestinal and urogenital systems, and respiratory system, and their potential in clinical practice is discussed. Although contributing no new essential diagnostic information against conventional CT scans, 3D scans can help in spatial orientation. 11 figs., 25 refs
International Nuclear Information System (INIS)
Nakagawa, Motoo; Ozawa, Yoshiyuki; Sakurai, Keita; Shimohira, Masashi; Shibamoto, Yuta; Ohashi, Kazuya; Asano, Miki; Yamaguchi, Sachiko
2015-01-01
Lower tube voltage has advantages for CT angiography, such as improved contrast To evaluate the image quality of low-voltage (70 kV) CT for congenital heart disease and the ability of sinogram-affirmed iterative reconstruction to improve image quality. Forty-six children with congenital heart disease (median age: 109 days) were examined using dual-source CT. Scans were performed at 80 kV and 70 kV in 21 and 25 children, respectively. A nonionic iodinated contrast medium (300 mg I/ml) was used for the 80-kV protocol. The contrast medium was diluted to 75% (225 mgI/mL) with saline for the 70-kV protocol. Image noise was measured in the two protocols for each group by extracting the standard deviations of a region of interest placed on the descending aorta. We then determined whether sinogram-affirmed iterative reconstruction reduced the image noise at 70 kV. There was more noise at 70 kV than at 80 kV (29 ± 12 vs 20 ± 4.8; P < 0.01). Sinogram-affirmed iterative reconstruction with grade 4 strength settings improved the noise (20 ± 5.9; P < 0.01) for the 70-kV group. Sinogram-affirmed iterative reconstruction improved the image quality of CT in congenital heart disease. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Nakagawa, Motoo; Ozawa, Yoshiyuki; Sakurai, Keita; Shimohira, Masashi; Shibamoto, Yuta [Nagoya City University Graduate School of Medical Sciences, Department of Radiology, Nagoya (Japan); Ohashi, Kazuya [Nagoya City University Hospital, Division of Central Radiology, Nagoya (Japan); Asano, Miki [Nagoya City University Graduate School of Medical Sciences, Department of Cardiovascular Surgery, Nagoya (Japan); Yamaguchi, Sachiko [Nagoya City University Graduate School of Medical Sciences, Department of Pediatrics and Neonatology, Nagoya (Japan)
2015-09-15
Lower tube voltage has advantages for CT angiography, such as improved contrast To evaluate the image quality of low-voltage (70 kV) CT for congenital heart disease and the ability of sinogram-affirmed iterative reconstruction to improve image quality. Forty-six children with congenital heart disease (median age: 109 days) were examined using dual-source CT. Scans were performed at 80 kV and 70 kV in 21 and 25 children, respectively. A nonionic iodinated contrast medium (300 mg I/ml) was used for the 80-kV protocol. The contrast medium was diluted to 75% (225 mgI/mL) with saline for the 70-kV protocol. Image noise was measured in the two protocols for each group by extracting the standard deviations of a region of interest placed on the descending aorta. We then determined whether sinogram-affirmed iterative reconstruction reduced the image noise at 70 kV. There was more noise at 70 kV than at 80 kV (29 ± 12 vs 20 ± 4.8; P < 0.01). Sinogram-affirmed iterative reconstruction with grade 4 strength settings improved the noise (20 ± 5.9; P < 0.01) for the 70-kV group. Sinogram-affirmed iterative reconstruction improved the image quality of CT in congenital heart disease. (orig.)
Accelerated Compressed Sensing Based CT Image Reconstruction.
Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C
2015-01-01
In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.
Accelerated Compressed Sensing Based CT Image Reconstruction
Directory of Open Access Journals (Sweden)
SayedMasoud Hashemi
2015-01-01
Full Text Available In X-ray computed tomography (CT an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.
A genetic approach to shape reconstruction in limited data tomography
International Nuclear Information System (INIS)
Turcanu, C.; Craciunescu, T.
2001-01-01
The paper proposes a new method for shape reconstruction in computerized tomography. Unlike nuclear medicine applications, in physical science problems we are often confronted with limited data sets: constraints in the number of projections or limited view angles . The problem of image reconstruction from projection may be considered as a problem of finding an image (solution) having projections that match the experimental ones. In our approach, we choose a statistical correlation coefficient to evaluate the fitness of any potential solution. The optimization process is carried out by a genetic algorithm. The algorithm has some features common to all genetic algorithms but also some problem-oriented characteristics. One of them is that a chromosome, representing a potential solution, is not linear but coded as a matrix of pixels corresponding to a two-dimensional image. This kind of internal representation reflects the genuine manifestation and slight differences between two points situated in the original problem space give rise to similar differences once they become coded. Another particular feature is a newly built crossover operator: the grid-based crossover, suitable for high dimension two-dimensional chromosomes. Except for the population size and the dimension of the cutting grid for the grid-based crossover, all the other parameters of the algorithm are independent of the geometry of the tomographic reconstruction. The performances of the method are evaluated on a phantom typical for an application with limited data sets: the determination of the neutron energy spectra with time resolution in case of short-pulsed neutron emission. A genetic reconstruction is presented. The qualitative judgement and also the quantitative one, based on some figures of merit, point out that the proposed method ensures an improved reconstruction of shapes, sizes and resolution in the image, even in the presence of noise. (authors)
Advanced reconstruction algorithms for electron tomography: From comparison to combination
Energy Technology Data Exchange (ETDEWEB)
Goris, B. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Roelandts, T. [Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Batenburg, K.J. [Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Centrum Wiskunde and Informatica, Science Park 123, NL-1098XG Amsterdam (Netherlands); Heidari Mezerji, H. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Bals, S., E-mail: sara.bals@ua.ac.be [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)
2013-04-15
In this work, the simultaneous iterative reconstruction technique (SIRT), the total variation minimization (TVM) reconstruction technique and the discrete algebraic reconstruction technique (DART) for electron tomography are compared and the advantages and disadvantages are discussed. Furthermore, we describe how the result of a three dimensional (3D) reconstruction based on TVM can provide objective information that is needed as the input for a DART reconstruction. This approach results in a tomographic reconstruction of which the segmentation is carried out in an objective manner. - Highlights: ► A comparative study between different reconstruction algorithms for tomography is performed. ► Reconstruction algorithms that uses prior knowledge about the specimen have a superior result. ► One reconstruction algorithm can provide the prior knowledge for a second algorithm.
Hongbo Guo; Xiaowei He; Muhan Liu; Zeyu Zhang; Zhenhua Hu; Jie Tian
2017-06-01
Cerenkov luminescence tomography (CLT) provides a novel technique for 3-D noninvasive detection of radiopharmaceuticals in living subjects. However, because of the severe scattering of Cerenkov light, the reconstruction accuracy and stability of CLT is still unsatisfied. In this paper, a modified weight multispectral CLT (wmCLT) reconstruction strategy was developed which split the Cerenkov radiation spectrum into several sub-spectral bands and weighted the sub-spectral results to obtain the final result. To better evaluate the property of the wmCLT reconstruction strategy in terms of accuracy, stability and practicability, several numerical simulation experiments and in vivo experiments were conducted and the results obtained were compared with the traditional multispectral CLT (mCLT) and hybrid-spectral CLT (hCLT) reconstruction strategies. The numerical simulation results indicated that wmCLT strategy significantly improved the accuracy of Cerenkov source localization and intensity quantitation and exhibited good stability in suppressing noise in numerical simulation experiments. And the comparison of the results achieved from different in vivo experiments further indicated significant improvement of the wmCLT strategy in terms of the shape recovery of the bladder and the spatial resolution of imaging xenograft tumors. Overall the strategy reported here will facilitate the development of nuclear and optical molecular tomography in theoretical study.
Image reconstruction by domain-transform manifold learning
Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.
2018-03-01
Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development
Hachouf, N; Kharfi, F; Boucenna, A
2012-10-01
An ideal neutron radiograph, for quantification and 3D tomographic image reconstruction, should be a transmission image which exactly obeys to the exponential attenuation law of a monochromatic neutron beam. There are many reasons for which this assumption does not hold for high neutron absorbing materials. The main deviations from the ideal are due essentially to neutron beam hardening effect. The main challenges of this work are the characterization of neutron transmission through boron enriched steel materials and the observation of beam hardening. Then, in our work, the influence of beam hardening effect on neutron tomographic image, for samples based on these materials, is studied. MCNP and FBP simulation are performed to adjust linear attenuation coefficients data and to perform 2D tomographic image reconstruction with and without beam hardening corrections. A beam hardening correction procedure is developed and applied based on qualitative and quantitative analyses of the projections data. Results from original and corrected 2D reconstructed images obtained shows the efficiency of the proposed correction procedure. Copyright © 2012 Elsevier Ltd. All rights reserved.
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...
Principles of medical imaging with emphasis on tomography
Energy Technology Data Exchange (ETDEWEB)
Kouris, K [Institute of Nuclear Medicine, University College, London Medical School, Mortimer Street, London W1N 8AA (United Kingdom)
1994-12-31
Medical imaging with ionizing and non-ionizing radiations belongs to the class of problems known as indirect sensing. This article is concerned with imaging methods known as image reconstruction from projections or computerized tomography. A brief comparative study of the theory is presented. Depending on the nature and modes of propagation of the employed radiation, methods are discussed either under transmission tomography (with gamma rays and X rays) or emission tomography (with gamma rays and positrons). Magnetic resonance Imaging (MRI) is described as resonant absorption and re-emission of radiofrequency energy. (author). 6 refs, 1 fig.
Iterative reconstruction with boundary detection for carbon ion computed tomography
Shrestha, Deepak; Qin, Nan; Zhang, You; Kalantari, Faraz; Niu, Shanzhou; Jia, Xun; Pompos, Arnold; Jiang, Steve; Wang, Jing
2018-03-01
In heavy ion radiation therapy, improving the accuracy in range prediction of the ions inside the patient’s body has become essential. Accurate localization of the Bragg peak provides greater conformity of the tumor while sparing healthy tissues. We investigated the use of carbon ions directly for computed tomography (carbon CT) to create the relative stopping power map of a patient’s body. The Geant4 toolkit was used to perform a Monte Carlo simulation of the carbon ion trajectories, to study their lateral and angular deflections and the most likely paths, using a water phantom. Geant4 was used to create carbonCT projections of a contrast and spatial resolution phantom, with a cone beam of 430 MeV/u carbon ions. The contrast phantom consisted of cranial bone, lung material, and PMMA inserts while the spatial resolution phantom contained bone and lung material inserts with line pair (lp) densities ranging from 1.67 lp cm-1 through 5 lp cm-1. First, the positions of each carbon ion on the rear and front trackers were used for an approximate reconstruction of the phantom. The phantom boundary was extracted from this approximate reconstruction, by using the position as well as angle information from the four tracking detectors, resulting in the entry and exit locations of the individual ions on the phantom surface. Subsequent reconstruction was performed by the iterative algebraic reconstruction technique coupled with total variation minimization (ART-TV) assuming straight line trajectories for the ions inside the phantom. The influence of number of projections was studied with reconstruction from five different sets of projections: 15, 30, 45, 60 and 90. Additionally, the effect of number of ions on the image quality was investigated by reducing the number of ions/projection while keeping the total number of projections at 60. An estimation of carbon ion range using the carbonCT image resulted in improved range prediction compared to the range calculated using a
Iterative reconstruction techniques for computed tomography Part 1: Technical principles
International Nuclear Information System (INIS)
Willemink, Martin J.; Jong, Pim A. de; Leiner, Tim; Nievelstein, Rutger A.J.; Schilham, Arnold M.R.; Heer, Linda M. de; Budde, Ricardo P.J.
2013-01-01
To explain the technical principles of and differences between commercially available iterative reconstruction (IR) algorithms for computed tomography (CT) in non-mathematical terms for radiologists and clinicians. Technical details of the different proprietary IR techniques were distilled from available scientific articles and manufacturers' white papers and were verified by the manufacturers. Clinical results were obtained from a literature search spanning January 2006 to January 2012, including only original research papers concerning IR for CT. IR for CT iteratively reduces noise and artefacts in either image space or raw data, or both. Reported dose reductions ranged from 23 % to 76 % compared to locally used default filtered back-projection (FBP) settings, with similar noise, artefacts, subjective, and objective image quality. IR has the potential to allow reducing the radiation dose while preserving image quality. Disadvantages of IR include blotchy image appearance and longer computational time. Future studies need to address differences between IR algorithms for clinical low-dose CT. circle Iterative reconstruction technology for CT is presented in non-mathematical terms. (orig.)
Optical diffraction tomography: accuracy of an off-axis reconstruction
Kostencka, Julianna; Kozacki, Tomasz
2014-05-01
Optical diffraction tomography is an increasingly popular method that allows for reconstruction of three-dimensional refractive index distribution of semi-transparent samples using multiple measurements of an optical field transmitted through the sample for various illumination directions. The process of assembly of the angular measurements is usually performed with one of two methods: filtered backprojection (FBPJ) or filtered backpropagation (FBPP) tomographic reconstruction algorithm. The former approach, although conceptually very simple, provides an accurate reconstruction for the object regions located close to the plane of focus. However, since FBPJ ignores diffraction, its use for spatially extended structures is arguable. According to the theory of scattering, more precise restoration of a 3D structure shall be achieved with the FBPP algorithm, which unlike the former approach incorporates diffraction. It is believed that with this method one is allowed to obtain a high accuracy reconstruction in a large measurement volume exceeding depth of focus of an imaging system. However, some studies have suggested that a considerable improvement of the FBPP results can be achieved with prior propagation of the transmitted fields back to the centre of the object. This, supposedly, enables reduction of errors due to approximated diffraction formulas used in FBPP. In our view this finding casts doubt on quality of the FBPP reconstruction in the regions far from the rotation axis. The objective of this paper is to investigate limitation of the FBPP algorithm in terms of an off-axis reconstruction and compare its performance with the FBPJ approach. Moreover, in this work we propose some modifications to the FBPP algorithm that allow for more precise restoration of a sample structure in off-axis locations. The research is based on extensive numerical simulations supported with wave-propagation method.
A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.
De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc
2010-09-01
In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.
Three-dimensional reconstruction of CT images
Energy Technology Data Exchange (ETDEWEB)
Watanabe, Toshiaki; Kattoh, Keiichi; Kawakami, Genichiroh; Igami, Isao; Mariya, Yasushi; Nakamura, Yasuhiko; Saitoh, Yohko; Tamura, Koreroku; Shinozaki, Tatsuyo
1986-09-01
Computed tomography (CT) has the ability to provide sensitive visualization of organs and lesions. Owing to the nature of CT to be transaxial images, a structure which is greater than a certain size appears as several serial CT images. Consequently each observer must reconstruct those images into a three-dimensional (3-D) form mentally. It has been supposed to be of great use if such a 3-D form can be described as a definite figure. A new computer program has been developed which can produce 3-D figures from the profiles of organs and lesions on CT images using spline curves. The figures obtained through this method are regarded to have practical applications.
International Nuclear Information System (INIS)
Nakamoto, Atsushi; Kim, Tonsok; Hori, Masatoshi; Onishi, Hiromitsu; Tsuboyama, Takahiro; Sakane, Makoto; Tatsumi, Mitsuaki; Tomiyama, Noriyuki
2015-01-01
Highlights: • MBIR significantly improves objective image quality. • MBIR reduces the radiation dose by 87.5% without increasing objective image noise. • A half dose will be needed to maintain the subjective image quality. - Abstract: Purpose: To evaluate the image quality of upper abdominal CT images reconstructed with model-based iterative reconstruction (MBIR) in comparison with filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) on scans acquired with various radiation exposure dose protocols. Materials and methods: This prospective study was approved by our institutional review board, and informed consent was obtained from all 90 patients who underwent both control-dose (CD) and reduced-dose (RD) CT of the upper abdomen (unenhanced: n = 45, contrast-enhanced: n = 45). The RD scan protocol was randomly selected from three protocols; Protocol A: 12.5% dose, Protocol B: 25% dose, Protocol C: 50% dose. Objective image noise, signal-to-noise (SNR) ratio for the liver parenchyma, visual image score and lesion conspicuity were compared among CD images of FBP and RD images of FBP, ASIR and MBIR. Results: RD images of MBIR yielded significantly lower objective image noise and higher SNR compared with RD images of FBP and ASIR for all protocols (P < .01) and CD images of FBP for Protocol C (P < .05). Although the subjective image quality of RD images of MBIR was almost acceptable for Protocol C, it was inferior to that of CD images of FBP for Protocols A and B (P < .0083). The conspicuity of the small lesions in RD images of MBIR tended to be superior to that in RD images of FBP and ASIR and inferior to that in CD images for Protocols A and B, although the differences were not significant (P > .0083). Conclusion: Although 12.5%-dose MBIR images (mean size-specific dose estimates [SSDE] of 1.13 mGy) yielded objective image noise and SNR comparable to CD-FBP images, at least a 50% dose (mean SSDE of 4.63 mGy) would be needed to
Energy Technology Data Exchange (ETDEWEB)
Nakamoto, Atsushi, E-mail: a-nakamoto@radiol.med.osaka-u.ac.jp; Kim, Tonsok, E-mail: kim@radiol.med.osaka-u.ac.jp; Hori, Masatoshi, E-mail: mhori@radiol.med.osaka-u.ac.jp; Onishi, Hiromitsu, E-mail: h-onishi@radiol.med.osaka-u.ac.jp; Tsuboyama, Takahiro, E-mail: t-tsuboyama@radiol.med.osaka-u.ac.jp; Sakane, Makoto, E-mail: m-sakane@radiol.med.osaka-u.ac.jp; Tatsumi, Mitsuaki, E-mail: m-tatsumi@radiol.med.osaka-u.ac.jp; Tomiyama, Noriyuki, E-mail: tomiyama@radiol.med.osaka-u.ac.jp
2015-09-15
Highlights: • MBIR significantly improves objective image quality. • MBIR reduces the radiation dose by 87.5% without increasing objective image noise. • A half dose will be needed to maintain the subjective image quality. - Abstract: Purpose: To evaluate the image quality of upper abdominal CT images reconstructed with model-based iterative reconstruction (MBIR) in comparison with filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) on scans acquired with various radiation exposure dose protocols. Materials and methods: This prospective study was approved by our institutional review board, and informed consent was obtained from all 90 patients who underwent both control-dose (CD) and reduced-dose (RD) CT of the upper abdomen (unenhanced: n = 45, contrast-enhanced: n = 45). The RD scan protocol was randomly selected from three protocols; Protocol A: 12.5% dose, Protocol B: 25% dose, Protocol C: 50% dose. Objective image noise, signal-to-noise (SNR) ratio for the liver parenchyma, visual image score and lesion conspicuity were compared among CD images of FBP and RD images of FBP, ASIR and MBIR. Results: RD images of MBIR yielded significantly lower objective image noise and higher SNR compared with RD images of FBP and ASIR for all protocols (P < .01) and CD images of FBP for Protocol C (P < .05). Although the subjective image quality of RD images of MBIR was almost acceptable for Protocol C, it was inferior to that of CD images of FBP for Protocols A and B (P < .0083). The conspicuity of the small lesions in RD images of MBIR tended to be superior to that in RD images of FBP and ASIR and inferior to that in CD images for Protocols A and B, although the differences were not significant (P > .0083). Conclusion: Although 12.5%-dose MBIR images (mean size-specific dose estimates [SSDE] of 1.13 mGy) yielded objective image noise and SNR comparable to CD-FBP images, at least a 50% dose (mean SSDE of 4.63 mGy) would be needed to
Energy Technology Data Exchange (ETDEWEB)
Razali, Azhani Mohd, E-mail: azhani@nuclearmalaysia.gov.my; Abdullah, Jaafar, E-mail: jaafar@nuclearmalaysia.gov.my [Plant Assessment Technology (PAT) Group, Industrial Technology Division, Malaysian Nuclear Agency, Bangi, 43000 Kajang (Malaysia)
2015-04-29
Single Photon Emission Computed Tomography (SPECT) is a well-known imaging technique used in medical application, and it is part of medical imaging modalities that made the diagnosis and treatment of disease possible. However, SPECT technique is not only limited to the medical sector. Many works are carried out to adapt the same concept by using high-energy photon emission to diagnose process malfunctions in critical industrial systems such as in chemical reaction engineering research laboratories, as well as in oil and gas, petrochemical and petrochemical refining industries. Motivated by vast applications of SPECT technique, this work attempts to study the application of SPECT on a Pebble Bed Reactor (PBR) using numerical phantom of pebbles inside the PBR core. From the cross-sectional images obtained from SPECT, the behavior of pebbles inside the core can be analyzed for further improvement of the PBR design. As the quality of the reconstructed image is largely dependent on the algorithm used, this work aims to compare two image reconstruction algorithms for SPECT, namely the Expectation Maximization Algorithm and the Exact Inversion Formula. The results obtained from the Exact Inversion Formula showed better image contrast and sharpness, and shorter computational time compared to the Expectation Maximization Algorithm.
International Nuclear Information System (INIS)
Razali, Azhani Mohd; Abdullah, Jaafar
2015-01-01
Single Photon Emission Computed Tomography (SPECT) is a well-known imaging technique used in medical application, and it is part of medical imaging modalities that made the diagnosis and treatment of disease possible. However, SPECT technique is not only limited to the medical sector. Many works are carried out to adapt the same concept by using high-energy photon emission to diagnose process malfunctions in critical industrial systems such as in chemical reaction engineering research laboratories, as well as in oil and gas, petrochemical and petrochemical refining industries. Motivated by vast applications of SPECT technique, this work attempts to study the application of SPECT on a Pebble Bed Reactor (PBR) using numerical phantom of pebbles inside the PBR core. From the cross-sectional images obtained from SPECT, the behavior of pebbles inside the core can be analyzed for further improvement of the PBR design. As the quality of the reconstructed image is largely dependent on the algorithm used, this work aims to compare two image reconstruction algorithms for SPECT, namely the Expectation Maximization Algorithm and the Exact Inversion Formula. The results obtained from the Exact Inversion Formula showed better image contrast and sharpness, and shorter computational time compared to the Expectation Maximization Algorithm
Razali, Azhani Mohd; Abdullah, Jaafar
2015-04-01
Single Photon Emission Computed Tomography (SPECT) is a well-known imaging technique used in medical application, and it is part of medical imaging modalities that made the diagnosis and treatment of disease possible. However, SPECT technique is not only limited to the medical sector. Many works are carried out to adapt the same concept by using high-energy photon emission to diagnose process malfunctions in critical industrial systems such as in chemical reaction engineering research laboratories, as well as in oil and gas, petrochemical and petrochemical refining industries. Motivated by vast applications of SPECT technique, this work attempts to study the application of SPECT on a Pebble Bed Reactor (PBR) using numerical phantom of pebbles inside the PBR core. From the cross-sectional images obtained from SPECT, the behavior of pebbles inside the core can be analyzed for further improvement of the PBR design. As the quality of the reconstructed image is largely dependent on the algorithm used, this work aims to compare two image reconstruction algorithms for SPECT, namely the Expectation Maximization Algorithm and the Exact Inversion Formula. The results obtained from the Exact Inversion Formula showed better image contrast and sharpness, and shorter computational time compared to the Expectation Maximization Algorithm.
Energy Technology Data Exchange (ETDEWEB)
Velo, Alexandre F.; Carvalho, Diego V.; Alvarez, Alexandre G.; Hamada, Margarida M.; Mesquita, Carlos H., E-mail: afvelo@usp.br [Instituto de Pesquisas Energéticas e Nucleares (IPEN/CNEN-SP), São Paulo, SP (Brazil)
2017-07-01
The greatest impact of the tomography technology application currently occurs in medicine. The great success of medical tomography is due to the human body presents reasonably standardized dimensions with well established chemical composition. Generally, these favorable conditions are not found in large industrial objects. In the industry there is much interest in using the information of the tomograph in order to know the interior of: (1) manufactured industrial objects or (2) machines and their means of production. In these cases, the purpose of the tomograph is to: (a) control the quality of the final product and (b) optimize production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. In different industrial processes, e. g. in chemical reactors and distillation columns, the phenomena related to multiphase processes are usually fast, requiring high temporal resolution of the computed tomography (CT) data acquisition. In this context, Instant non-scanning tomograph and fifth generation tomograph meets these requirements. An instant non scanning tomography system is being developed at the IPEN/CNEN. In this work, in order to optimize the system, this tomograph comprised different collimators was simulated, with Monte Carlo method using the MCNP4C. The image quality was evaluated with MATLAB® 2013b, by analysis of the following parameters: contrast to noise (CNR), root mean square ratio (RMSE), signal to noise ratio (SNR) and the spatial resolution by the Modulation Transfer Function (MTF(f)), to analyze which collimator fits better to the instant non scanning tomography. It was simulated three situations; (1) with no collimator; (2) ?25 mm x 50 mm cylindrical collimator with a septum of ø5.0 mm x 50 mm; (3) ø25 mm x 50 mm cylindrical collimator with a slit septum of 24 mm x 5.0 mm x 50 mm. (author)
International Nuclear Information System (INIS)
Velo, Alexandre F.; Carvalho, Diego V.; Alvarez, Alexandre G.; Hamada, Margarida M.; Mesquita, Carlos H.
2017-01-01
The greatest impact of the tomography technology application currently occurs in medicine. The great success of medical tomography is due to the human body presents reasonably standardized dimensions with well established chemical composition. Generally, these favorable conditions are not found in large industrial objects. In the industry there is much interest in using the information of the tomograph in order to know the interior of: (1) manufactured industrial objects or (2) machines and their means of production. In these cases, the purpose of the tomograph is to: (a) control the quality of the final product and (b) optimize production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. In different industrial processes, e. g. in chemical reactors and distillation columns, the phenomena related to multiphase processes are usually fast, requiring high temporal resolution of the computed tomography (CT) data acquisition. In this context, Instant non-scanning tomograph and fifth generation tomograph meets these requirements. An instant non scanning tomography system is being developed at the IPEN/CNEN. In this work, in order to optimize the system, this tomograph comprised different collimators was simulated, with Monte Carlo method using the MCNP4C. The image quality was evaluated with MATLAB® 2013b, by analysis of the following parameters: contrast to noise (CNR), root mean square ratio (RMSE), signal to noise ratio (SNR) and the spatial resolution by the Modulation Transfer Function (MTF(f)), to analyze which collimator fits better to the instant non scanning tomography. It was simulated three situations; (1) with no collimator; (2) ?25 mm x 50 mm cylindrical collimator with a septum of ø5.0 mm x 50 mm; (3) ø25 mm x 50 mm cylindrical collimator with a slit septum of 24 mm x 5.0 mm x 50 mm. (author)
Scanning transmission proton microscopy tomography of reconstruction cells from simulated data
International Nuclear Information System (INIS)
Zhang Conghua; Li Min; Hou Qing
2011-01-01
For scanning transmission proton microscopy tomography, to compare cell images of the proton stopping power and relative electron density, two cell phantoms are designed and simulated by code FLUKA. The cell images are reconstructed by the filtered back projection algorithm, and compared with their tomography imaging. The images of stopping power and relative electron density slightly vary with proton energies, but the internal images are of clear with high resolution. The organic glass image of relative electron density reveals the resolution power of proton tomography. Also, the simulation results reflect effects of the boundary enhancement, the weak artifacts, and the internal structure border extension by multiple scattering. So using proton tomography to analyze internal structure of a cell is a superior. (authors)
Low dose reconstruction algorithm for differential phase contrast imaging.
Wang, Zhentian; Huang, Zhifeng; Zhang, Li; Chen, Zhiqiang; Kang, Kejun; Yin, Hongxia; Wang, Zhenchang; Marco, Stampanoni
2011-01-01
Differential phase contrast imaging computed tomography (DPCI-CT) is a novel x-ray inspection method to reconstruct the distribution of refraction index rather than the attenuation coefficient in weakly absorbing samples. In this paper, we propose an iterative reconstruction algorithm for DPCI-CT which benefits from the new compressed sensing theory. We first realize a differential algebraic reconstruction technique (DART) by discretizing the projection process of the differential phase contrast imaging into a linear partial derivative matrix. In this way the compressed sensing reconstruction problem of DPCI reconstruction can be transformed to a resolved problem in the transmission imaging CT. Our algorithm has the potential to reconstruct the refraction index distribution of the sample from highly undersampled projection data. Thus it can significantly reduce the dose and inspection time. The proposed algorithm has been validated by numerical simulations and actual experiments.
Longitudinal and transverse digital image reconstruction with a tomographic scanner
International Nuclear Information System (INIS)
Pickens, D.R.; Price, R.R.; Erickson, J.J.; Patton, J.A.; Partain, C.L.; Rollo, F.D.
1981-01-01
A Siemens Gammasonics PHO/CON-192 Multiplane Imager is interfaced to a digital computer for the purpose of performing tomographic reconstructions from the data collected during a single scan. Data from the two moving gamma cameras as well as camera position information are sent to the computer by an interface designed in the authors' laboratory. Backprojection reconstruction is implemented by the computer. Longitudinal images in whole-body format as well as smaller formats are reconstructed for up to six planes simultaneously from the list mode data. Transverse reconstructions are demonstrated for 201 T1 myocardial scans. Post-reconstruction deconvolution processing to remove the blur artifact (characteristic of focal plane tomography) is applied to a multiplane phantom. Digital data acquisition of data and reconstruction of images are practical, and can extend the usefulness of the machine when compared with the film output (author)
International Nuclear Information System (INIS)
Chinn, G.; Huang, S.C.
1997-01-01
A major drawback of statistical iterative image reconstruction for emission computed tomography is its high computational cost. The ill-posed nature of tomography leads to slow convergence for standard gradient-based iterative approaches such as the steepest descent or the conjugate gradient algorithm. In this paper new theory and methods for a class of preconditioners are developed for accelerating the convergence rate of iterative reconstruction. To demonstrate the potential of this class of preconditioners, a preconditioned conjugate gradient (PCG) iterative algorithm for weighted least squares reconstruction (WLS) was formulated for emission tomography. Using simulated positron emission tomography (PET) data of the Hoffman brain phantom, it was shown that the convergence rate of the PCG can reduce the number of iterations of the standard conjugate gradient algorithm by a factor of 2--8 times depending on the convergence criterion
Energy Technology Data Exchange (ETDEWEB)
Buhk, J.H. [Univ. Medical Center, Hamburg-Eppendorf (Germany). Dept. of Neuroradiology; Laqmani, A.; Schultzendorff, H.C. von; Hammerle, D.; Adam, G.; Regier, M. [Univ. Medical Center, Hamburg-Eppendorf (Germany). Dept. of Diagnostic and Interventional Radiology; Sehner, S. [Univ. Medical Center, Hamburg-Eppendorf (Germany). Inst. of Medical Biometry and Epidemiology; Fiehler, J. [Univ. Medical Center, Hamburg-Eppendorf (Germany). Neuroradiology; Nagel, H.D. [Dr. HD Nagel, Science and Technology for Radiology, Buchholz (Germany)
2013-08-15
Objectives: To intraindividually evaluate the potential of 4th generation iterative reconstruction (IR) on brain CT with regard to subjective and objective image quality. Methods: 31 consecutive raw data sets of clinical routine native sequential brain CT scans were reconstructed with IR level 0 (= filtered back projection), 1, 3 and 4; 3 different brain filter kernels (smooth/standard/sharp) were applied respectively. Five independent radiologists with different levels of experience performed subjective image rating. Detailed ROI analysis of image contrast and noise was performed. Statistical analysis was carried out by applying a random intercept model. Results: Subjective scores for the smooth and the standard kernels were best at low IR levels, but both, in particular the smooth kernel, scored inferior with an increasing IR level. The sharp kernel scored lowest at IR 0, while the scores substantially increased at high IR levels, reaching significantly best scores at IR 4. Objective measurements revealed an overall increase in contrast-to-noise ratio at higher IR levels, which was highest when applying the soft filter kernel. The absolute grey-white contrast decreased with an increasing IR level and was highest when applying the sharp filter kernel. All subjective effects were independent of the raters' experience and the patients' age and sex. Conclusion: Different combinations of IR level and filter kernel substantially influence subjective and objective image quality of brain CT. (orig.)
International Nuclear Information System (INIS)
Buhk, J.H.
2013-01-01
Objectives: To intraindividually evaluate the potential of 4th generation iterative reconstruction (IR) on brain CT with regard to subjective and objective image quality. Methods: 31 consecutive raw data sets of clinical routine native sequential brain CT scans were reconstructed with IR level 0 (= filtered back projection), 1, 3 and 4; 3 different brain filter kernels (smooth/standard/sharp) were applied respectively. Five independent radiologists with different levels of experience performed subjective image rating. Detailed ROI analysis of image contrast and noise was performed. Statistical analysis was carried out by applying a random intercept model. Results: Subjective scores for the smooth and the standard kernels were best at low IR levels, but both, in particular the smooth kernel, scored inferior with an increasing IR level. The sharp kernel scored lowest at IR 0, while the scores substantially increased at high IR levels, reaching significantly best scores at IR 4. Objective measurements revealed an overall increase in contrast-to-noise ratio at higher IR levels, which was highest when applying the soft filter kernel. The absolute grey-white contrast decreased with an increasing IR level and was highest when applying the sharp filter kernel. All subjective effects were independent of the raters' experience and the patients' age and sex. Conclusion: Different combinations of IR level and filter kernel substantially influence subjective and objective image quality of brain CT. (orig.)
3D fast reconstruction in positron emission tomography
International Nuclear Information System (INIS)
Egger, M.L.; Scheurer, A. Hermann; Joseph, C.; Morel, C.
1996-01-01
The issue of long reconstruction times in positron emission tomography (PET) has been addressed from several points of view, resulting in an affordable dedicated system capable of handling routine 3D reconstructions in a few minutes per frame : on the hardware side using fast processors and a parallel architecture, and on the software side, using efficient implementation of computationally less intensive algorithms
Colour reconstruction of underwater images
Hoth, Julian; Kowalczyk, Wojciech
2017-01-01
Objects look very different in the underwater environment compared to their appearance in sunlight. Images with correct colouring simplify the detection of underwater objects and may allow the use of visual SLAM algorithms developed for land-based robots underwater. Hence, image processing is required. Current algorithms focus on the colour reconstruction of scenery at diving depth where different colours can still be distinguished. At greater depth this is not the case. In this study it is i...
Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography
Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.
2014-11-01
Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as "Muon Central Slice Theorem". Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction.
Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography
International Nuclear Information System (INIS)
Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.
2014-01-01
Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as M uon Central Slice Theorem . Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction
Small scale imaging using ultrasonic tomography
International Nuclear Information System (INIS)
Zakaria, Z.; Abdul Rahim, R.; Megat Ali, M.S.A.; Baharuddin, M.Y.; Jahidin, A.H.
2009-01-01
Ultrasound technology progressed through the 1960 from simple A-mode and B-mode scans to today M-mode and Doppler two dimensional (2-D) and even three dimensional (3-D) systems. Modern ultrasound imaging has its roots in sonar technology after it was first described by Lord John Rayleigh over 100 years ago on the interaction of acoustic waves with media. Tomography technique was developed as a diagnostic tool in the medical area since the early of 1970s. This research initially focused on how to retrieve a cross sectional images from living and non-living things. After a decade, the application of tomography systems span into the industrial area. However, the long exposure time of medical radiation-based method cannot tolerate the dynamic changes in industrial process two phase liquid/ gas flow system. An alternative system such as a process tomography systems, can give information on the nature of the flow regime characteristic. The overall aim of this paper is to investigate the use of a small scale ultrasonic tomography method based on ultrasonic transmission mode tomography for online monitoring of liquid/ gas flow in pipe/ vessel system through ultrasonic transceivers application. This non-invasive technique applied sixteen transceivers as the sensing elements to cover the pipe/ vessel cross section. The paper also details the transceivers selection criteria, hardware setup, the electronic measurement circuit and also the image reconstruction algorithm applied. The system was found capable of visualizing the internal characteristics and provides the concentration profile for the corresponding liquid and gas phases. (author)
Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction
Energy Technology Data Exchange (ETDEWEB)
Koc, Gonca; Courtier, Jesse L.; Phelps, Andrew; Marcovici, Peter A.; MacKenzie, John D. [UCSF Benioff Children' s Hospital, Department of Radiology and Biomedical Imaging, San Francisco, CA (United States)
2014-07-15
Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo trademark), a technique developed to improve image quality and reduce noise. To evaluate Veo trademark as an improved method when compared to adaptive statistical iterative reconstruction (ASIR trademark) for the depiction of small vessels on pediatric CT. Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo trademark and ASIR trademark algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests. Readers stated a preference for Veo trademark over ASIR trademark images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo trademark vs. ASIR trademark reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo trademark and ASIR trademark images. Veo trademark consistently showed more of the vessel anatomy: longer vessel length and more branching vessels. When compared to the more established adaptive statistical iterative reconstruction algorithm, model
Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction
International Nuclear Information System (INIS)
Koc, Gonca; Courtier, Jesse L.; Phelps, Andrew; Marcovici, Peter A.; MacKenzie, John D.
2014-01-01
Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo trademark), a technique developed to improve image quality and reduce noise. To evaluate Veo trademark as an improved method when compared to adaptive statistical iterative reconstruction (ASIR trademark) for the depiction of small vessels on pediatric CT. Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo trademark and ASIR trademark algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests. Readers stated a preference for Veo trademark over ASIR trademark images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo trademark vs. ASIR trademark reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo trademark and ASIR trademark images. Veo trademark consistently showed more of the vessel anatomy: longer vessel length and more branching vessels. When compared to the more established adaptive statistical iterative reconstruction algorithm, model
Dual-Source Swept-Source Optical Coherence Tomography Reconstructed on Integrated Spectrum
Directory of Open Access Journals (Sweden)
Shoude Chang
2012-01-01
Full Text Available Dual-source swept-source optical coherence tomography (DS-SSOCT has two individual sources with different central wavelengths, linewidth, and bandwidths. Because of the difference between the two sources, the individually reconstructed tomograms from each source have different aspect ratio, which makes the comparison and integration difficult. We report a method to merge two sets of DS-SSOCT raw data in a common spectrum, on which both data have the same spectrum density and a correct separation. The reconstructed tomographic image can seamlessly integrate the two bands of OCT data together. The final image has higher axial resolution and richer spectroscopic information than any of the individually reconstructed tomography image.
Edge-promoting reconstruction of absorption and diffusivity in optical tomography
DEFF Research Database (Denmark)
Hannukainen, A.; Harhanen, Lauri Oskari; Hyvönen, N.
2015-01-01
In optical tomography a physical body is illuminated with near-infrared light and the resulting outward photon flux is measured at the object boundary. The goal is to reconstruct internal optical properties of the body, such as absorption and diffusivity. In this work, it is assumed that the imaged...... measurement noise model. The method is based on iteratively combining a lagged diffusivity step and a linearization of the measurement model of diffuse optical tomography with priorconditioned LSQR. The performance of the reconstruction technique is tested via three-dimensional numerical experiments...
Use of a model for 3D image reconstruction
International Nuclear Information System (INIS)
Delageniere, S.; Grangeat, P.
1991-01-01
We propose a software for 3D image reconstruction in transmission tomography. This software is based on the use of a model and of the RADON algorithm developed at LETI. The introduction of a markovian model helps us to enhance contrast and straitened the natural transitions existing in the objects studied, whereas standard transform methods smoothe them
3D imaging of nanomaterials by discrete tomography.
Batenburg, K J; Bals, S; Sijbers, J; Kübel, C; Midgley, P A; Hernandez, J C; Kaiser, U; Encina, E R; Coronado, E A; Van Tendeloo, G
2009-05-01
The field of discrete tomography focuses on the reconstruction of samples that consist of only a few different materials. Ideally, a three-dimensional (3D) reconstruction of such a sample should contain only one grey level for each of the compositions in the sample. By exploiting this property in the reconstruction algorithm, either the quality of the reconstruction can be improved significantly, or the number of required projection images can be reduced. The discrete reconstruction typically contains fewer artifacts and does not have to be segmented, as it already contains one grey level for each composition. Recently, a new algorithm, called discrete algebraic reconstruction technique (DART), has been proposed that can be used effectively on experimental electron tomography datasets. In this paper, we propose discrete tomography as a general reconstruction method for electron tomography in materials science. We describe the basic principles of DART and show that it can be applied successfully to three different types of samples, consisting of embedded ErSi(2) nanocrystals, a carbon nanotube grown from a catalyst particle and a single gold nanoparticle, respectively.
3D imaging of nanomaterials by discrete tomography
International Nuclear Information System (INIS)
Batenburg, K.J.; Bals, S.; Sijbers, J.; Kuebel, C.; Midgley, P.A.; Hernandez, J.C.; Kaiser, U.; Encina, E.R.; Coronado, E.A.; Van Tendeloo, G.
2009-01-01
The field of discrete tomography focuses on the reconstruction of samples that consist of only a few different materials. Ideally, a three-dimensional (3D) reconstruction of such a sample should contain only one grey level for each of the compositions in the sample. By exploiting this property in the reconstruction algorithm, either the quality of the reconstruction can be improved significantly, or the number of required projection images can be reduced. The discrete reconstruction typically contains fewer artifacts and does not have to be segmented, as it already contains one grey level for each composition. Recently, a new algorithm, called discrete algebraic reconstruction technique (DART), has been proposed that can be used effectively on experimental electron tomography datasets. In this paper, we propose discrete tomography as a general reconstruction method for electron tomography in materials science. We describe the basic principles of DART and show that it can be applied successfully to three different types of samples, consisting of embedded ErSi 2 nanocrystals, a carbon nanotube grown from a catalyst particle and a single gold nanoparticle, respectively.
BPF-type region-of-interest reconstruction for parallel translational computed tomography.
Wu, Weiwen; Yu, Hengyong; Wang, Shaoyu; Liu, Fenglin
2017-01-01
The objective of this study is to present and test a new ultra-low-cost linear scan based tomography architecture. Similar to linear tomosynthesis, the source and detector are translated in opposite directions and the data acquisition system targets on a region-of-interest (ROI) to acquire data for image reconstruction. This kind of tomographic architecture was named parallel translational computed tomography (PTCT). In previous studies, filtered backprojection (FBP)-type algorithms were developed to reconstruct images from PTCT. However, the reconstructed ROI images from truncated projections have severe truncation artefact. In order to overcome this limitation, we in this study proposed two backprojection filtering (BPF)-type algorithms named MP-BPF and MZ-BPF to reconstruct ROI images from truncated PTCT data. A weight function is constructed to deal with data redundancy for multi-linear translations modes. Extensive numerical simulations are performed to evaluate the proposed MP-BPF and MZ-BPF algorithms for PTCT in fan-beam geometry. Qualitative and quantitative results demonstrate that the proposed BPF-type algorithms cannot only more accurately reconstruct ROI images from truncated projections but also generate high-quality images for the entire image support in some circumstances.
Electrical Resistance Tomography imaging of concrete
International Nuclear Information System (INIS)
Karhunen, Kimmo; Seppaenen, Aku; Lehikoinen, Anssi; Monteiro, Paulo J.M.; Kaipio, Jari P.
2010-01-01
We apply Electrical Resistance Tomography (ERT) for three dimensional imaging of concrete. In ERT, alternating currents are injected into the target using an array of electrodes attached to the target surface, and the resulting voltages are measured using the same electrodes. These boundary measurements are used for reconstructing the internal (3D) conductivity distribution of the target. In reinforced concrete, the metallic phases (reinforcing bars and fibers), cracks and air voids, moisture gradients, and the chloride distribution in the matrix carry contrast with respect to conductivity. While electrical measurements have been widely used to characterize the properties of concrete, only preliminary results of applying ERT to concrete imaging have been published so far. The aim of this paper is to carry out a feasibility evaluation with specifically cast samples. The results indicate that ERT may be a feasible modality for non-destructive evaluation of concrete.
Electrical Resistance Tomography imaging of concrete
Karhunen, Kimmo
2010-01-01
We apply Electrical Resistance Tomography (ERT) for three dimensional imaging of concrete. In ERT, alternating currents are injected into the target using an array of electrodes attached to the target surface, and the resulting voltages are measured using the same electrodes. These boundary measurements are used for reconstructing the internal (3D) conductivity distribution of the target. In reinforced concrete, the metallic phases (reinforcing bars and fibers), cracks and air voids, moisture gradients, and the chloride distribution in the matrix carry contrast with respect to conductivity. While electrical measurements have been widely used to characterize the properties of concrete, only preliminary results of applying ERT to concrete imaging have been published so far. The aim of this paper is to carry out a feasibility evaluation with specifically cast samples. The results indicate that ERT may be a feasible modality for non-destructive evaluation of concrete. © 2009 Elsevier Ltd. All rights reserved.
Regularization iteration imaging algorithm for electrical capacitance tomography
Tong, Guowei; Liu, Shi; Chen, Hongyan; Wang, Xueyao
2018-03-01
The image reconstruction method plays a crucial role in real-world applications of the electrical capacitance tomography technique. In this study, a new cost function that simultaneously considers the sparsity and low-rank properties of the imaging targets is proposed to improve the quality of the reconstruction images, in which the image reconstruction task is converted into an optimization problem. Within the framework of the split Bregman algorithm, an iterative scheme that splits a complicated optimization problem into several simpler sub-tasks is developed to solve the proposed cost function efficiently, in which the fast-iterative shrinkage thresholding algorithm is introduced to accelerate the convergence. Numerical experiment results verify the effectiveness of the proposed algorithm in improving the reconstruction precision and robustness.
Emission tomography for adrenal imaging
International Nuclear Information System (INIS)
Britton, K.E.; Shapiro, B.; Hawkins, L.A.
1980-01-01
Single photon emission tomography (SPET) of the adrenals was compared to convential gamma camera images. Depths of 19 adrenals were assessed by both the lateral skin-upper kidney pole method and by SPET. Eleven patients with adrenal disorders were also studied. An advantage of using SPET was that the analogue transverse section image showed improvement over the conventional posterior view because the liver activity was well separated from the adrenal. Furthermore, non-adrenal tissue background was virtually eliminated and adrenal depth determination facilitated. (U.K.)
Zhu, Dianwen; Zhang, Wei; Zhao, Yue; Li, Changqing
2016-03-01
Dynamic fluorescence molecular tomography (FMT) has the potential to quantify physiological or biochemical information, known as pharmacokinetic parameters, which are important for cancer detection, drug development and delivery etc. To image those parameters, there are indirect methods, which are easier to implement but tend to provide images with low signal-to-noise ratio, and direct methods, which model all the measurement noises together and are statistically more efficient. The direct reconstruction methods in dynamic FMT have attracted a lot of attention recently. However, the coupling of tomographic image reconstruction and nonlinearity of kinetic parameter estimation due to the compartment modeling has imposed a huge computational burden to the direct reconstruction of the kinetic parameters. In this paper, we propose to take advantage of both the direct and indirect reconstruction ideas through a variable splitting strategy under the augmented Lagrangian framework. Each iteration of the direct reconstruction is split into two steps: the dynamic FMT image reconstruction and the node-wise nonlinear least squares fitting of the pharmacokinetic parameter images. Through numerical simulation studies, we have found that the proposed algorithm can achieve good reconstruction results within a small amount of time. This will be the first step for a combined dynamic PET and FMT imaging in the future.
Energy Technology Data Exchange (ETDEWEB)
Zhuge, Xiaodong [Computational Imaging, Centrum Wiskunde & Informatica, Science park 123, 1098XG Amsterdam (Netherlands); Jinnai, Hiroshi [Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai 980-8577 (Japan); Dunin-Borkowski, Rafal E.; Migunov, Vadim [Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons and Peter Grünberg Institute, Forschungszentrum Jülich, D-52425 Jülich (Germany); Bals, Sara [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Cool, Pegie [Laboratory of Adsorption and Catalysis, Department of Chemistry, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk (Belgium); Bons, Anton-Jan [European Technology Center, ExxonMobil Chemical Europe Inc., Hermeslaan 2, B-1831 Machelen (Belgium); Batenburg, Kees Joost [Computational Imaging, Centrum Wiskunde & Informatica, Science park 123, 1098XG Amsterdam (Netherlands)
2017-04-15
Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials. - Highlights: • Automated discrete electron tomography capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts and requires significantly
International Nuclear Information System (INIS)
Zhuge, Xiaodong; Jinnai, Hiroshi; Dunin-Borkowski, Rafal E.; Migunov, Vadim; Bals, Sara; Cool, Pegie; Bons, Anton-Jan; Batenburg, Kees Joost
2017-01-01
Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials. - Highlights: • Automated discrete electron tomography capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts and requires significantly
DEFF Research Database (Denmark)
Zhu, Yansong; Jha, Abhinav K.; Dreyer, Jakob K.
2017-01-01
Fluorescence molecular tomography (FMT) is a promising tool for real time in vivo quantification of neurotransmission (NT) as we pursue in our BRAIN initiative effort. However, the acquired image data are noisy and the reconstruction problem is ill-posed. Further, while spatial sparsity of the NT...... matrix coherence. The resultant image data are input to a homotopy-based reconstruction strategy that exploits sparsity via ℓ1 regularization. The reconstructed image is then input to a maximum-likelihood expectation maximization (MLEM) algorithm that retains the sparseness of the input estimate...... and improves upon the quantitation by accurate Poisson noise modeling. The proposed reconstruction method was evaluated in a three-dimensional simulated setup with fluorescent sources in a cuboidal scattering medium with optical properties simulating human brain cortex (reduced scattering coefficient: 9.2 cm-1...
The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation
International Nuclear Information System (INIS)
Zhao, Zhanqi; Möller, Knut; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich
2014-01-01
Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton–Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR C ) and (4) GREIT with individual thorax geometry (GR T ). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal–Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms. (paper)
The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.
Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut
2014-06-01
Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.
Robust statistical reconstruction for charged particle tomography
Schultz, Larry Joe; Klimenko, Alexei Vasilievich; Fraser, Andrew Mcleod; Morris, Christopher; Orum, John Christopher; Borozdin, Konstantin N; Sossong, Michael James; Hengartner, Nicolas W
2013-10-08
Systems and methods for charged particle detection including statistical reconstruction of object volume scattering density profiles from charged particle tomographic data to determine the probability distribution of charged particle scattering using a statistical multiple scattering model and determine a substantially maximum likelihood estimate of object volume scattering density using expectation maximization (ML/EM) algorithm to reconstruct the object volume scattering density. The presence of and/or type of object occupying the volume of interest can be identified from the reconstructed volume scattering density profile. The charged particle tomographic data can be cosmic ray muon tomographic data from a muon tracker for scanning packages, containers, vehicles or cargo. The method can be implemented using a computer program which is executable on a computer.
Multi-Detector Computed Tomography Imaging Techniques in Arterial Injuries
Directory of Open Access Journals (Sweden)
Cameron Adler
2018-04-01
Full Text Available Cross-sectional imaging has become a critical aspect in the evaluation of arterial injuries. In particular, angiography using computed tomography (CT is the imaging of choice. A variety of techniques and options are available when evaluating for arterial injuries. Techniques involve contrast bolus, various phases of contrast enhancement, multiplanar reconstruction, volume rendering, and maximum intensity projection. After the images are rendered, a variety of features may be seen that diagnose the injury. This article provides a general overview of the techniques, important findings, and pitfalls in cross sectional imaging of arterial imaging, particularly in relation to computed tomography. In addition, the future directions of computed tomography, including a few techniques in the process of development, is also discussed.
Directory of Open Access Journals (Sweden)
Peigang Ning
Full Text Available OBJECTIVE: This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR and model-based iterative reconstruction (MBIR algorithms in reducing computed tomography (CT radiation dosages in abdominal imaging. METHODS: CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP, 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol were recorded. RESULTS: At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. CONCLUSIONS: Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.
Diffuse Optical Tomography for Brain Imaging: Theory
Yuan, Zhen; Jiang, Huabei
Diffuse optical tomography (DOT) is a noninvasive, nonionizing, and inexpensive imaging technique that uses near-infrared light to probe tissue optical properties. Regional variations in oxy- and deoxy-hemoglobin concentrations as well as blood flow and oxygen consumption can be imaged by monitoring spatiotemporal variations in the absorption spectra. For brain imaging, this provides DOT unique abilities to directly measure the hemodynamic, metabolic, and neuronal responses to cells (neurons), and tissue and organ activations with high temporal resolution and good tissue penetration. DOT can be used as a stand-alone modality or can be integrated with other imaging modalities such as fMRI/MRI, PET/CT, and EEG/MEG in studying neurophysiology and pathology. This book chapter serves as an introduction to the basic theory and principles of DOT for neuroimaging. It covers the major aspects of advances in neural optical imaging including mathematics, physics, chemistry, reconstruction algorithm, instrumentation, image-guided spectroscopy, neurovascular and neurometabolic coupling, and clinical applications.
ADART: an adaptive algebraic reconstruction algorithm for discrete tomography.
Maestre-Deusto, F Javier; Scavello, Giovanni; Pizarro, Joaquín; Galindo, Pedro L
2011-08-01
In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.
Energy Technology Data Exchange (ETDEWEB)
Beasley, D.G., E-mail: dgbeasley@ctn.ist.utl.pt [IST/C2TN, Universidade de Lisboa, Campus Tecnológico e Nuclear, E.N.10, 2686-953 Sacavém (Portugal); Alves, L.C. [IST/C2TN, Universidade de Lisboa, Campus Tecnológico e Nuclear, E.N.10, 2686-953 Sacavém (Portugal); Barberet, Ph.; Bourret, S.; Devès, G.; Gordillo, N.; Michelet, C. [Univ. Bordeaux, CENBG, UMR 5797, F-33170 Gradignan (France); CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan (France); Le Trequesser, Q. [Univ. Bordeaux, CENBG, UMR 5797, F-33170 Gradignan (France); CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan (France); Institut de Chimie de la Matière Condensée de Bordeaux (ICMCB, UPR9048) CNRS, Université de Bordeaux, 87 avenue du Dr. A. Schweitzer, Pessac F-33608 (France); Marques, A.C. [IST/IPFN, Universidade de Lisboa, Campus Tecnológico e Nuclear, E.N.10, 2686-953 Sacavém (Portugal); Seznec, H. [Univ. Bordeaux, CENBG, UMR 5797, F-33170 Gradignan (France); CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan (France); Silva, R.C. da [IST/IPFN, Universidade de Lisboa, Campus Tecnológico e Nuclear, E.N.10, 2686-953 Sacavém (Portugal)
2014-07-15
The tomographic reconstruction of biological specimens requires robust algorithms, able to deal with low density contrast and low element concentrations. At the IST/ITN microprobe facility new GPU-accelerated reconstruction software, JPIXET, has been developed, which can significantly increase the speed of quantitative reconstruction of Proton Induced X-ray Emission Tomography (PIXE-T) data. It has a user-friendly graphical user interface for pre-processing, data analysis and reconstruction of PIXE-T and Scanning Transmission Ion Microscopy Tomography (STIM-T). The reconstruction of PIXE-T data is performed using either an algorithm based on a GPU-accelerated version of the Maximum Likelihood Expectation Maximisation (MLEM) method or a GPU-accelerated version of the Discrete Image Space Reconstruction Algorithm (DISRA) (Sakellariou (2001) [2]). The original DISRA, its accelerated version, and the MLEM algorithm, were compared for the reconstruction of a biological sample of Caenorhabditis elegans – a small worm. This sample was analysed at the microbeam line of the AIFIRA facility of CENBG, Bordeaux. A qualitative PIXE-T reconstruction was obtained using the CENBG software package TomoRebuild (Habchi et al. (2013) [6]). The effects of pre-processing and experimental conditions on the elemental concentrations are discussed.
Michalski, Andrew S; Edwards, W Brent; Boyd, Steven K
2017-10-17
Quantitative computed tomography has been posed as an alternative imaging modality to investigate osteoporosis. We examined the influence of computed tomography convolution back-projection reconstruction kernels on the analysis of bone quantity and estimated mechanical properties in the proximal femur. Eighteen computed tomography scans of the proximal femur were reconstructed using both a standard smoothing reconstruction kernel and a bone-sharpening reconstruction kernel. Following phantom-based density calibration, we calculated typical bone quantity outcomes of integral volumetric bone mineral density, bone volume, and bone mineral content. Additionally, we performed finite element analysis in a standard sideways fall on the hip loading configuration. Significant differences for all outcome measures, except integral bone volume, were observed between the 2 reconstruction kernels. Volumetric bone mineral density measured using images reconstructed by the standard kernel was significantly lower (6.7%, p kernel. Furthermore, the whole-bone stiffness and the failure load measured in images reconstructed by the standard kernel were significantly lower (16.5%, p kernel. These data suggest that for future quantitative computed tomography studies, a standardized reconstruction kernel will maximize reproducibility, independent of the use of a quantitative calibration phantom. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.
Angle Statistics Reconstruction: a robust reconstruction algorithm for Muon Scattering Tomography
Stapleton, M.; Burns, J.; Quillin, S.; Steer, C.
2014-11-01
Muon Scattering Tomography (MST) is a technique for using the scattering of cosmic ray muons to probe the contents of enclosed volumes. As a muon passes through material it undergoes multiple Coulomb scattering, where the amount of scattering is dependent on the density and atomic number of the material as well as the path length. Hence, MST has been proposed as a means of imaging dense materials, for instance to detect special nuclear material in cargo containers. Algorithms are required to generate an accurate reconstruction of the material density inside the volume from the muon scattering information and some have already been proposed, most notably the Point of Closest Approach (PoCA) and Maximum Likelihood/Expectation Maximisation (MLEM) algorithms. However, whilst PoCA-based algorithms are easy to implement, they perform rather poorly in practice. Conversely, MLEM is a complicated algorithm to implement and computationally intensive and there is currently no published, fast and easily-implementable algorithm that performs well in practice. In this paper, we first provide a detailed analysis of the source of inaccuracy in PoCA-based algorithms. We then motivate an alternative method, based on ideas first laid out by Morris et al, presenting and fully specifying an algorithm that performs well against simulations of realistic scenarios. We argue this new algorithm should be adopted by developers of Muon Scattering Tomography as an alternative to PoCA.
Zhuge, Xiaodong; Jinnai, Hiroshi; Dunin-Borkowski, Rafal E; Migunov, Vadim; Bals, Sara; Cool, Pegie; Bons, Anton-Jan; Batenburg, Kees Joost
2017-04-01
Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials. Copyright © 2017 Elsevier B.V. All rights reserved.
Simultaneous maximum a posteriori longitudinal PET image reconstruction
Ellis, Sam; Reader, Andrew J.
2017-09-01
Positron emission tomography (PET) is frequently used to monitor functional changes that occur over extended time scales, for example in longitudinal oncology PET protocols that include routine clinical follow-up scans to assess the efficacy of a course of treatment. In these contexts PET datasets are currently reconstructed into images using single-dataset reconstruction methods. Inspired by recently proposed joint PET-MR reconstruction methods, we propose to reconstruct longitudinal datasets simultaneously by using a joint penalty term in order to exploit the high degree of similarity between longitudinal images. We achieved this by penalising voxel-wise differences between pairs of longitudinal PET images in a one-step-late maximum a posteriori (MAP) fashion, resulting in the MAP simultaneous longitudinal reconstruction (SLR) method. The proposed method reduced reconstruction errors and visually improved images relative to standard maximum likelihood expectation-maximisation (ML-EM) in simulated 2D longitudinal brain tumour scans. In reconstructions of split real 3D data with inserted simulated tumours, noise across images reconstructed with MAP-SLR was reduced to levels equivalent to doubling the number of detected counts when using ML-EM. Furthermore, quantification of tumour activities was largely preserved over a variety of longitudinal tumour changes, including changes in size and activity, with larger changes inducing larger biases relative to standard ML-EM reconstructions. Similar improvements were observed for a range of counts levels, demonstrating the robustness of the method when used with a single penalty strength. The results suggest that longitudinal regularisation is a simple but effective method of improving reconstructed PET images without using resolution degrading priors.
International Nuclear Information System (INIS)
Zhang Jin; Shi Daxin; Anastasio, Mark A; Sillanpaa, Jussi; Chang Jenghwa
2005-01-01
We propose and investigate weighted expectation maximization (EM) algorithms for image reconstruction in x-ray tomography. The development of the algorithms is motivated by the respiratory-gated megavoltage tomography problem, in which the acquired asymmetric cone-beam projections are limited in number and unevenly sampled over view angle. In these cases, images reconstructed by use of the conventional EM algorithm can contain ring- and streak-like artefacts that are attributable to a combination of data inconsistencies and truncation of the projection data. By use of computer-simulated and clinical gated fan-beam megavoltage projection data, we demonstrate that the proposed weighted EM algorithms effectively mitigate such image artefacts. (note)
General surface reconstruction for cone-beam multislice spiral computed tomography
International Nuclear Information System (INIS)
Chen Laigao; Liang Yun; Heuscher, Dominic J.
2003-01-01
A new family of cone-beam reconstruction algorithm, the General Surface Reconstruction (GSR), is proposed and formulated in this paper for multislice spiral computed tomography (CT) reconstructions. It provides a general framework to allow the reconstruction of planar or nonplanar surfaces on a set of rebinned short-scan parallel beam projection data. An iterative surface formation method is proposed as an example to show the possibility to form nonplanar reconstruction surfaces to minimize the adverse effect between the collected cone-beam projection data and the reconstruction surfaces. The improvement in accuracy of the nonplanar surfaces over planar surfaces in the two-dimensional approximate cone-beam reconstructions is mathematically proved and demonstrated using numerical simulations. The proposed GSR algorithm is evaluated by the computer simulation of cone-beam spiral scanning geometry and various mathematical phantoms. The results demonstrate that the GSR algorithm generates much better image quality compared to conventional multislice reconstruction algorithms. For a table speed up to 100 mm per rotation, GSR demonstrates good image quality for both the low-contrast ball phantom and thorax phantom. All other performance parameters are comparable to the single-slice 180 deg. LI (linear interpolation) algorithm, which is considered the 'gold standard'. GSR also achieves high computing efficiency and good temporal resolution, making it an attractive alternative for the reconstruction of next generation multislice spiral CT data
Few-view image reconstruction with dual dictionaries
International Nuclear Information System (INIS)
Lu Yang; Zhao Jun; Wang Ge
2012-01-01
In this paper, we formulate the problem of computed tomography (CT) under sparsity and few-view constraints, and propose a novel algorithm for image reconstruction from few-view data utilizing the simultaneous algebraic reconstruction technique (SART) coupled with dictionary learning, sparse representation and total variation (TV) minimization on two interconnected levels. The main feature of our algorithm is the use of two dictionaries: a transitional dictionary for atom matching and a global dictionary for image updating. The atoms in the global and transitional dictionaries represent the image patches from high-quality and low-quality CT images, respectively. Experiments with simulated and real projections were performed to evaluate and validate the proposed algorithm. The results reconstructed using the proposed approach are significantly better than those using either SART or SART–TV. (paper)
Liu, Xin; Wang, Hongkai; Yan, Zhuangzhi
2016-11-01
Dynamic fluorescence molecular tomography (FMT) plays an important role in drug delivery research. However, the majority of current reconstruction methods focus on solving the stationary FMT problems. If the stationary reconstruction methods are applied to the time-varying fluorescence measurements, the reconstructed results may suffer from a high level of artifacts. In addition, based on the stationary methods, only one tomographic image can be obtained after scanning one circle projection data. As a result, the movement of fluorophore in imaged object may not be detected due to the relative long data acquisition time (typically >1 min). In this paper, we apply extended kalman filter (EKF) technique to solve the non-stationary fluorescence tomography problem. Especially, to improve the EKF reconstruction performance, the generalized inverse of kalman gain is calculated by a second-order iterative method. The numerical simulation, phantom, and in vivo experiments are performed to evaluate the performance of the method. The experimental results indicate that by using the proposed EKF-based second-order iterative (EKF-SOI) method, we cannot only clearly resolve the time-varying distributions of fluorophore within imaged object, but also greatly improve the reconstruction time resolution (~2.5 sec/frame) which makes it possible to detect the movement of fluorophore during the imaging processes.
International Nuclear Information System (INIS)
Stevendaal, U. van; Schlomka, J.-P.; Harding, A.; Grass, M.
2003-01-01
Coherent scatter computed tomography (CSCT) is a reconstructive x-ray imaging technique that yields the spatially resolved coherent-scatter form factor of the investigated object. Reconstruction from coherently scattered x-rays is commonly done using algebraic reconstruction techniques (ART). In this paper, we propose an alternative approach based on filtered back-projection. For the first time, a three-dimensional (3D) filtered back-projection technique using curved 3D back-projection lines is applied to two-dimensional coherent scatter projection data. The proposed algorithm is tested with simulated projection data as well as with projection data acquired with a demonstrator setup similar to a multi-line CT scanner geometry. While yielding comparable image quality as ART reconstruction, the modified 3D filtered back-projection algorithm is about two orders of magnitude faster. In contrast to iterative reconstruction schemes, it has the advantage that subfield-of-view reconstruction becomes feasible. This allows a selective reconstruction of the coherent-scatter form factor for a region of interest. The proposed modified 3D filtered back-projection algorithm is a powerful reconstruction technique to be implemented in a CSCT scanning system. This method gives coherent scatter CT the potential of becoming a competitive modality for medical imaging or nondestructive testing
International Nuclear Information System (INIS)
Brady, Samuel L.; Shulkin, Barry L.
2015-01-01
Purpose: To develop ultralow dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultralow doses (10–35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUV bw ) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. Results: CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUV bw , background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3–0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. Conclusions: Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake
Energy Technology Data Exchange (ETDEWEB)
Brady, Samuel L., E-mail: samuel.brady@stjude.org [Division of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105 (United States); Shulkin, Barry L. [Nuclear Medicine and Department of Radiological Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105 (United States)
2015-02-15
Purpose: To develop ultralow dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultralow doses (10–35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUV{sub bw}) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. Results: CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUV{sub bw}, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3–0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. Conclusions: Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake.
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.
International Nuclear Information System (INIS)
Knesaurek, K.; Machac, J.; Vallabhajosula, S.; Buchsbaum, M.S.
1996-01-01
A new interative reconstruction technique (NIRT) for positron emission computed tomography (PET), which uses transmission data for nonuniform attenuation correction, is described. Utilizing the general inverse problem theory, a cost functional which includes a noise term was derived. The cost functional was minimized using a weighted-least-square maximum a posteriori conjugate gradient (CG) method. The procedure involves a change in the Hessian of the cost function by adding an additional term. Two phantoms were used in a real data acquisition. The first was a cylinder phantom filled with uniformly distributed activity of 74 MBq of fluorine-18. Two different inserts were placed in the phantom. The second was a Hoffman brain phantom filled with uniformly distributed activity of 7.4 MBq of 18 F. Resulting reconstructed images were used to test and compare a new interative reconstruction technique with a standard filtered backprojection (FBP) method. The results confirmed that NIRT, based on the conjugate gradient method, converges rapidly and provides good reconstructed images. In comaprison with standard results obtained by the FBP method, the images reconstructed by NIRT showed better noise properties. The noise was measured as rms% noise and was less, by a factor of 1.75, in images reconstructed by NIRT than in the same images reconstructed by FBP. The distance between the Hoffman brain slice created from the MRI image was 0.526, while the same distance for the Hoffman brain slice reconstructed by NIRT was 0.328. The NIRT method suppressed the propagation of the noise without visible loss of resolution in the reconstructed PET images. (orig.)
Reconstruction of conductivity change in lung lobes utilizing electrical impedance tomography
Directory of Open Access Journals (Sweden)
Schullcke Benjamin
2017-09-01
Full Text Available Electrical Impedance Tomography (EIT is a novel medical imaging technology which is expected to give valuable information for the treatment of mechanically ventilated patients as well as for patients with obstructive lung diseases. In lung-EIT electrodes are attached around the thorax to inject small alternating currents and to measure resulting voltages. These voltages depend on the internal conductivity distribution and thus on the amount of air in the lungs. Based on the measured voltages, image reconstruction algorithms are employed to generate tomographic images reflecting the regional ventilation of the lungs. However, the ill-posedness of the reconstruction problem leads to reconstructed images that are severely blurred compared to morphological imaging technologies, such as X-ray computed tomography or Magnetic Resonance Imaging. Thus, a correct identification of the particular ventilation in anatomically assignable units, e.g. lung-lobes, is often hindered. In this study a 3D-FEM model of a human thorax has been used to simulate electrode voltages at different lung conditions. Two electrode planes with 16 electrodes at each layer have been used and different amount of emphysema and mucus plugging was simulated with different severity in the lung lobes. Patient specific morphological information about the lung lobes is used in the image reconstruction process. It is shown that this kind of prior information leads to better reconstructions of the conductivity change in particular lung lobes than in classical image reconstruction approaches, where the anatomy of the patients’ lungs is not considered. Thus, the described approach has the potential to open new and promising applications for EIT. It might be used for diagnosis and disease monitoring for patients with obstructive lung diseases but also in other applications, e.g. during the placement of endobronchial valves in patients with severe emphysema.
Denoising multicriterion iterative reconstruction in emission spectral tomography
Wan, Xiong; Yin, Aihan
2007-03-01
In the study of optical testing, the computed tomogaphy technique has been widely adopted to reconstruct three-dimensional distributions of physical parameters of various kinds of fluid fields, such as flame, plasma, etc. In most cases, projection data are often stained by noise due to environmental disturbance, instrumental inaccuracy, and other random interruptions. To improve the reconstruction performance in noisy cases, an algorithm that combines a self-adaptive prefiltering denoising approach (SPDA) with a multicriterion iterative reconstruction (MCIR) is proposed and studied. First, the level of noise is approximately estimated with a frequency domain statistical method. Then the cutoff frequency of a Butterworth low-pass filter was established based on the evaluated noise energy. After the SPDA processing, the MCIR algorithm was adopted for limited-view optical computed tomography reconstruction. Simulated reconstruction of two test phantoms and a flame emission spectral tomography experiment were employed to evaluate the performance of SPDA-MCIR in noisy cases. Comparison with some traditional methods and experiment results showed that the SPDA-MCIR combination had obvious improvement in the case of noisy data reconstructions.
Sparse image representation for jet neutron and gamma tomography
Energy Technology Data Exchange (ETDEWEB)
Craciunescu, T. [EURATOM-MEdC Association, Institute for Laser, Plasma and Radiation Physics, Bucharest (Romania); Kiptily, V. [EURATOM/CCFE Association, Culham Science Centre, Abingdon (United Kingdom); Murari, A. [Consorzio RFX, Associazione EURATOM-ENEA per la Fusione, Padova (Italy); Tiseanu, I.; Zoita, V. [EURATOM-MEdC Association, Institute for Laser, Plasma and Radiation Physics, Bucharest (Romania)
2013-10-15
Highlights: •A new tomographic method for the reconstruction of the 2-D neutron and gamma emissivity on JET. •The method is based on the sparse representation of the reconstructed image in an over-complete dictionary. •Several techniques, based on a priori information are used to regularize this highly limited data set tomographic problem. •The proposed method provides good reconstructions in terms of shapes and resolution. -- Abstract: The JET gamma/neutron profile monitor plasma coverage of the emissive region enables tomographic reconstruction. However, due to the availability of only two projection angles and to the coarse sampling, tomography is a highly limited data set problem. A new reconstruction method, based on the sparse representation of the reconstructed image in an over-complete dictionary, has been developed and applied to JET neutron/gamma tomography. The method has been tested on JET experimental data and significant results are presented. The proposed method provides good reconstructions in terms of shapes and resolution.
High Speed impedance tomography for cardiac imaging
International Nuclear Information System (INIS)
Tehrani, J.N.; Jin, C.; Schaik, Andre
2010-01-01
Full text: Electrical Impedance Tomography (EIT) calculates the internal conductivity distribution within a body using electrical contact measurements. Previous investigation has shown that optimizing electrode placement can give better information about the stroke volume and better separation between the ventricles and atria than with the electrodes attached in the transverse plane. In our investigation we are developing fast three dimensional imaging of the heart (two planes of 16 electrodes) including internal electrodes in esophagus. The reconstruction speed in EIT is one of the main limitations for real time imaging when using a detailed three dimensional finite element mesh. For that reason we investigated new iterative algorithms for solving large scale LJ regularization. In this research we compare these algorithms on noise reliability and speed for 2D cardiac models. The four methods were as follows: (I) an interior point method for solving Ll-regularized least squares problems (Ll-LS); (2) total variation using a Lagrangian multiplier (TV AL3); (3) a two step iterative shrinkage/thresholding method (TWIST) for solving the Lo-regularized least squares problem; (4) The Least Absolute Shrinkage and Selection Operator (LASSO). In our investigation, using 1600 elements, we found all four algorithms provided an improvement over the best conventional EIT reconstruction method, Total Variation, in three important areas: robustness to noise, increased computational speed of at least 40 x and a visually apparent improvement in spatial resolution. Out of the four algorithms we found TWIST was the fastest with at least a 1 00 x speed increase. (author)
3D reconstruction of radioactive sample utilizing gamma tomography
Zoul, David; Zháňal, Pavel
2018-07-01
Unique three-dimensional (3D) tomography apparatus was developed and successfully tested at Research Centre Rez, which concentrates at investigation of the degradation of microstructural and mechanical properties of structural materials of nuclear reactors components after a long-term operating exposure. The apparatus allows a 3D view into the interior of low-dimension radioactive samples with a diameter up to several centimeters and a resolution in order of cubic millimeters. It is designed to detect domains with different levels of radioactivity such as cavities, cracks or regions with different chemical composition. The unique collimator design, the use of stepper motors for fine and accurate sample scanning, along with advanced 3D image reconstruction software developed at Research Centre Rez, enables a resolution approaching 1 mm3. Devices working on a similar principle have been used for decades, e.g., in nuclear medicine for the diagnosis of malignant tumors, and are increasingly being applied in the nuclear industry. However, for the first time similar equipment is used for non-destructive testing of low-dimension radioactive samples.
Tomographic image reconstruction using Artificial Neural Networks
International Nuclear Information System (INIS)
Paschalis, P.; Giokaris, N.D.; Karabarbounis, A.; Loudos, G.K.; Maintas, D.; Papanicolas, C.N.; Spanoudaki, V.; Tsoumpas, Ch.; Stiliaris, E.
2004-01-01
A new image reconstruction technique based on the usage of an Artificial Neural Network (ANN) is presented. The most crucial factor in designing such a reconstruction system is the network architecture and the number of the input projections needed to reconstruct the image. Although the training phase requires a large amount of input samples and a considerable CPU time, the trained network is characterized by simplicity and quick response. The performance of this ANN is tested using several image patterns. It is intended to be used together with a phantom rotating table and the γ-camera of IASA for SPECT image reconstruction
Optoelectronic Computer Architecture Development for Image Reconstruction
National Research Council Canada - National Science Library
Forber, Richard
1996-01-01
.... Specifically, we collaborated with UCSD and ERIM on the development of an optically augmented electronic computer for high speed inverse transform calculations to enable real time image reconstruction...
Time-of-flight PET image reconstruction using origin ensembles
Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven
2015-03-01
The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.
A heuristic statistical stopping rule for iterative reconstruction in emission tomography
International Nuclear Information System (INIS)
Ben Bouallegue, F.; Mariano-Goulart, D.; Crouzet, J.F.
2013-01-01
We propose a statistical stopping criterion for iterative reconstruction in emission tomography based on a heuristic statistical description of the reconstruction process. The method was assessed for maximum likelihood expectation maximization (MLEM) reconstruction. Based on Monte-Carlo numerical simulations and using a perfectly modeled system matrix, our method was compared with classical iterative reconstruction followed by low-pass filtering in terms of Euclidian distance to the exact object, noise, and resolution. The stopping criterion was then evaluated with realistic PET data of a Hoffman brain phantom produced using the Geant4 application in emission tomography (GATE) platform for different count levels. The numerical experiments showed that compared with the classical method, our technique yielded significant improvement of the noise-resolution tradeoff for a wide range of counting statistics compatible with routine clinical settings. When working with realistic data, the stopping rule allowed a qualitatively and quantitatively efficient determination of the optimal image. Our method appears to give a reliable estimation of the optimal stopping point for iterative reconstruction. It should thus be of practical interest as it produces images with similar or better quality than classical post-filtered iterative reconstruction with a mastered computation time. (author)
Tsao, Kim; Cheng, Andrew; Goss, Alastair; Donovan, David
2014-07-01
Computed tomography (CT) is currently the standard in postoperative evaluation of orbital wall fracture reconstruction, but cone beam computed tomography (CBCT) offers potential advantages including reduced radiation dose and cost. The purpose of this study is to examine objectively the image quality of CBCT in the postoperative evaluation of orbital fracture reconstruction, its radiation dose, and cost compared with CT. Four consecutive patients with orbital wall fractures in whom surgery was indicated underwent orbital reconstruction with radio-opaque grafts (bone, titanium-reinforced polyethylene, and titanium plate) and were assessed postoperatively with orbital CBCT. CBCT was evaluated for its ability to provide objective information regarding the adequacy of orbital reconstruction, radiation dose, and cost. In all patients, CBCT was feasible and provided hard tissue image quality comparable to CT with significantly reduced radiation dose and cost. However, it has poorer soft tissue resolution, which limits its ability to identify the extraocular muscles, their relationship to the reconstructive graft, and potential muscle entrapment. CBCT is a viable alternative to CT in the routine postoperative evaluation of orbital fracture reconstruction. However, in the patient who develops gaze restriction postoperatively, conventional CT is preferred over CBCT for its superior soft tissue resolution to exclude extraocular muscle entrapment.
Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm
International Nuclear Information System (INIS)
Zhou Xiaolin; Yun Mingkai; Cao Xuexiang; Liu Shuangquan; Wang Lu; Huang Xianchao; Wei Long
2014-01-01
Single-photon emission computerized tomography and positron emission tomography are essential medical imaging tools, for which the sampling angle number and scan time should be carefully chosen to give a good compromise between image quality and radiopharmaceutical dose. In this study, the image quality of different acquisition protocols was evaluated via varied angle number and count number per angle with Monte Carlo simulation data. It was shown that, when similar imaging counts were used, the factor of acquisition counts was more important than that of the sampling number in emission computerized tomography. To further reduce the activity requirement and the scan duration, an iterative image reconstruction algorithm for limited-view and low-dose tomography based on compressed sensing theory has been developed. The total variation regulation was added to the reconstruction process to improve the signal to noise Ratio and reduce artifacts caused by the limited angle sampling. Maximization of the maximum likelihood of the estimated image and the measured data and minimization of the total variation of the image are alternatively implemented. By using this advanced algorithm, the reconstruction process is able to achieve image quality matching or exceed that of normal scans with only half of the injection radiopharmaceutical dose. (authors)
Optical computed tomography for imaging the breast: first look
Grable, Richard J.; Ponder, Steven L.; Gkanatsios, Nikolaos A.; Dieckmann, William; Olivier, Patrick F.; Wake, Robert H.; Zeng, Yueping
2000-07-01
The purpose of the study is to compare computed tomography optical imaging with traditional breast imaging techniques. Images produced by computed tomography laser mammography (CTLMTM) scanner are compared with images obtained from mammography, and in some cases ultrasound and/or magnetic resonance imaging (MRI). During the CTLM procedure, a near infrared laser irradiates the breast and an array of photodiodes detectors records light scattered through the breast tissue. The laser and detectors rotate synchronously around the breast to acquire a series of slice data along the coronal place. The procedure is performed without any breast compression or optical matching fluid. Cross-sectional slices of the breast are produced using a reconstruction algorithm. Reconstruction based on the diffusion theory is used to produce cross-sectional slices of the breast. Multiple slice images are combined to produce a three dimensional volumetric array of the imaged breast. This array is used to derive axial and sagittal images of the breast corresponding to cranio-caudal and medio-lateral images used in mammography. Over 200 women and 3 men have been scanned in clinical trials. The most obvious features seen in images produced by the optical tomography scanner are vascularization and significant lesions. Breast features caused by fibrocystic changes and cysts are less obvious. Breast density does not appear to be a significant factor in the quality of the image. We see correlation of the optical image structure with that seen with traditional breast imaging techniques. Further testing is being conducted to explore the sensitivity and specificity of optical tomography of the breast.
Direct iterative reconstruction of computed tomography trajectories (DIRECTT)
International Nuclear Information System (INIS)
Lange, A.; Hentschel, M.P.; Schors, J.
2004-01-01
The direct reconstruction approach employs an iterative procedure by selection of and angular averaging over projected trajectory data of volume elements. This avoids the blur effects of the classical Fourier method due to the sampling theorem. But longer computing time is required. The reconstructed tomographic images reveal at least the spatial resolution of the radiation detector. Any set of projection angles may be selected for the measurements. Limited rotation of the object yields still good reconstruction of details. Projections of a partial region of the object can be reconstructed without additional artifacts thus reducing the overall radiation dose. Noisy signal data from low dose irradiation have low impact on spatial resolution. The image quality is monitored during all iteration steps and is pre-selected according to the specific requirements. DIRECTT can be applied independently from the measurement equipment in addition to conventional reconstruction or as a refinement filter. (author)
High-speed reconstruction of compressed images
Cox, Jerome R., Jr.; Moore, Stephen M.
1990-07-01
A compression scheme is described that allows high-definition radiological images with greater than 8-bit intensity resolution to be represented by 8-bit pixels. Reconstruction of the images with their original intensity resolution can be carried out by means of a pipeline architecture suitable for compact, high-speed implementation. A reconstruction system is described that can be fabricated according to this approach and placed between an 8-bit display buffer and the display's video system thereby allowing contrast control of images at video rates. Results for 50 CR chest images are described showing that error-free reconstruction of the original 10-bit CR images can be achieved.
One step linear reconstruction method for continuous wave diffuse optical tomography
Ukhrowiyah, N.; Yasin, M.
2017-09-01
The method one step linear reconstruction method for continuous wave diffuse optical tomography is proposed and demonstrated for polyvinyl chloride based material and breast phantom. Approximation which used in this method is selecting regulation coefficient and evaluating the difference between two states that corresponding to the data acquired without and with a change in optical properties. This method is used to recovery of optical parameters from measured boundary data of light propagation in the object. The research is demonstrated by simulation and experimental data. Numerical object is used to produce simulation data. Chloride based material and breast phantom sample is used to produce experimental data. Comparisons of results between experiment and simulation data are conducted to validate the proposed method. The results of the reconstruction image which is produced by the one step linear reconstruction method show that the image reconstruction almost same as the original object. This approach provides a means of imaging that is sensitive to changes in optical properties, which may be particularly useful for functional imaging used continuous wave diffuse optical tomography of early diagnosis of breast cancer.
Tomographic Image Reconstruction Using Training Images with Matrix and Tensor Formulations
DEFF Research Database (Denmark)
Soltani, Sara
the image resolution compared to a classical reconstruction method such as Filtered Back Projection (FBP). Some priors for the tomographic reconstruction take the form of cross-section images of similar objects, providing a set of the so-called training images, that hold the key to the structural......Reducing X-ray exposure while maintaining the image quality is a major challenge in computed tomography (CT); since the imperfect data produced from the few view and/or low intensity projections results in low-quality images that are suffering from severe artifacts when using conventional...... information about the solution. The training images must be reliable and application-specific. This PhD project aims at providing a mathematical and computational framework for the use of training sets as non-parametric priors for the solution in tomographic image reconstruction. Through an unsupervised...
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. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Imaging granulomatous lesions with optical coherence tomography
DEFF Research Database (Denmark)
Banzhaf, Christina; Jemec, Gregor B E
2012-01-01
To investigate and compare the presentation of granulomatous lesions in optical coherence tomography (OCT) images and compare this to previous studies of nonmelanoma skin tumors.......To investigate and compare the presentation of granulomatous lesions in optical coherence tomography (OCT) images and compare this to previous studies of nonmelanoma skin tumors....
GPU based Monte Carlo for PET image reconstruction: detector modeling
International Nuclear Information System (INIS)
Légrády; Cserkaszky, Á; Lantos, J.; Patay, G.; Bükki, T.
2011-01-01
Monte Carlo (MC) calculations and Graphical Processing Units (GPUs) are almost like the dedicated hardware designed for the specific task given the similarities between visible light transport and neutral particle trajectories. A GPU based MC gamma transport code has been developed for Positron Emission Tomography iterative image reconstruction calculating the projection from unknowns to data at each iteration step taking into account the full physics of the system. This paper describes the simplified scintillation detector modeling and its effect on convergence. (author)
Iterative image reconstruction in ECT
International Nuclear Information System (INIS)
Chintu Chen; Ordonez, C.E.; Wernick, M.N.; Aarsvold, J.N.; Gunter, D.L.; Wong, W.H.; Kapp, O.H.; Xiaolong Ouyang; Levenson, M.; Metz, C.E.
1992-01-01
A series of preliminary studies has been performed in the authors laboratories to explore the use of a priori information in Bayesian image restoration and reconstruction. One piece of a priori information is the fact that intensities of neighboring pixels tend to be similar if they belong to the same region within which similar tissue characteristics are exhibited. this property of local continuity can be modeled by the use of Gibbs priors, as first suggested by German and Geman. In their investigation, they also included line sites between each pair of neighboring pixels in the Gibbs prior and used discrete binary numbers to indicate the absence or presence of boundaries between regions. These two features of the a priori model permit averaging within boundaries of homogeneous regions to alleviate the degradation caused by Poisson noise. with the use of this Gibbs prior in combination with the technique of stochastic relaxation, German and Geman demonstrated that noise levels can be reduced significantly in 2-D image restoration. They have developed a Bayesian method that utilizes a Gibbs prior to describe the spatial correlation of neighboring regions and takes into account the effect of limited spatial resolution as well. The statistical framework of the proposed approach is based on the data augmentation scheme suggested by Tanner and Wong. Briefly outlined here, this Bayesian method is based on Geman and Geman's approach
Computed tomography with selectable image resolution
International Nuclear Information System (INIS)
Dibianca, F.A.; Dallapiazza, D.G.
1981-01-01
A computed tomography system x-ray detector has a central group of half-width detector elements and groups of full-width elements on each side of the central group. To obtain x-ray attenuation data for whole body layers, the half-width elements are switched effectively into paralleled pairs so all elements act like full-width elements and an image of normal resolution is obtained. For narrower head layers, the elements in the central group are used as half-width elements so resolution which is twice as great as normal is obtained. The central group is also used in the half-width mode and the outside groups are used in the full-width mode to obtain a high resolution image of a body zone within a full body layer. In one embodiment data signals from the detector are switched by electronic multiplexing and in another embodiment a processor chooses the signals for the various kinds of images that are to be reconstructed. (author)
Level-set-based reconstruction algorithm for EIT lung images: first clinical results.
Rahmati, Peyman; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz; Adler, Andy
2012-05-01
We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.
Level-set-based reconstruction algorithm for EIT lung images: first clinical results
International Nuclear Information System (INIS)
Rahmati, Peyman; Adler, Andy; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz
2012-01-01
We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure–volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM. (paper)
Vectorization with SIMD extensions speeds up reconstruction in electron tomography.
Agulleiro, J I; Garzón, E M; García, I; Fernández, J J
2010-06-01
Electron tomography allows structural studies of cellular structures at molecular detail. Large 3D reconstructions are needed to meet the resolution requirements. The processing time to compute these large volumes may be considerable and so, high performance computing techniques have been used traditionally. This work presents a vector approach to tomographic reconstruction that relies on the exploitation of the SIMD extensions available in modern processors in combination to other single processor optimization techniques. This approach succeeds in producing full resolution tomograms with an important reduction in processing time, as evaluated with the most common reconstruction algorithms, namely WBP and SIRT. The main advantage stems from the fact that this approach is to be run on standard computers without the need of specialized hardware, which facilitates the development, use and management of programs. Future trends in processor design open excellent opportunities for vector processing with processor's SIMD extensions in the field of 3D electron microscopy.
Discrete Tomography and Imaging of Polycrystalline Structures
DEFF Research Database (Denmark)
Alpers, Andreas
High resolution transmission electron microscopy is commonly considered as the standard application for discrete tomography. While this has yet to be technically realized, new applications with a similar flavor have emerged in materials science. In our group at Ris� DTU (Denmark's National...... Laboratory for Sustainable Energy), for instance, we study polycrystalline materials via synchrotron X-ray diffraction. Several reconstruction problems arise, most of them exhibit inherently discrete aspects. In this talk I want to give a concise mathematical introduction to some of these reconstruction...... problems. Special focus is on their relationship to classical discrete tomography. Several open mathematical questions will be mentioned along the way....
Energy Technology Data Exchange (ETDEWEB)
Mendes, L.M.M.; Pereira, W.B.R.; Vieira, J.G.; Lamounier, C.S.; Gonçalves, D.A.; Carvalho, G.N.P.; Santana, P.C., E-mail: lucasmoacir2010@hotmail.com [Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG (Brazil); Oliveira, P.M.C.; Reis, L.P., E-mail: paulomarcio2000@gmail.com [Centro de Desenvolvimento de Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2017-07-01
Computed tomography had great advances in the equipment used in the diagnostic practice, directly influencing the levels of radiation for the patient. It is essential to optimize techniques that must be employed to comply with the ALARA (As Low As Reasonably Achievable) principle of radioprotection. The relationship of ASIR (Adaptive Statistical Iterative Reconstruction) with image noise was studied. Central images of a homogeneous water simulator were obtained in a 20 mm scan using a 64-channel Lightspeed VCT tomograph of General Electric in helical acquisitions with a rotation time of 0.5 seconds, Pitch 0.984: 1, and thickness of cut 0.625 mm. All these constant parameters varying the voltage in two distinct values: 120 and 140 kV with use of the automatic current by the CAE (Automatic Exposure Control), ranging from 50 to 675 mA (120 kV) and from 50 to 610 mA (140kV), minimum and maximum values, respectively allowed for each voltage. Image noise was determined through ImageJ free software. The analysis of the obtained data compared the percentage variation of the noise in the image based on the ASIR value of 10%, concluding that there is a variation of approximately 50% when compared to the values of ASIR (100%) in both tensions. Dose evaluation is required in future studies to better utilize the relationship between dose and image quality.
Baikejiang, Reheman; Zhang, Wei; Li, Changqing
2017-01-01
Diffuse optical tomography (DOT) has attracted attentions in the last two decades due to its intrinsic sensitivity in imaging chromophores of tissues such as hemoglobin, water, and lipid. However, DOT has not been clinically accepted yet due to its low spatial resolution caused by strong optical scattering in tissues. Structural guidance provided by an anatomical imaging modality enhances the DOT imaging substantially. Here, we propose a computed tomography (CT) guided multispectral DOT imaging system for breast cancer imaging. To validate its feasibility, we have built a prototype DOT imaging system which consists of a laser at the wavelength of 650 nm and an electron multiplying charge coupled device (EMCCD) camera. We have validated the CT guided DOT reconstruction algorithms with numerical simulations and phantom experiments, in which different imaging setup parameters, such as projection number of measurements and width of measurement patch, have been investigated. Our results indicate that an air-cooling EMCCD camera is good enough for the transmission mode DOT imaging. We have also found that measurements at six angular projections are sufficient for DOT to reconstruct the optical targets with 2 and 4 times absorption contrast when the CT guidance is applied. Finally, we have described our future research plan on integration of a multispectral DOT imaging system into a breast CT scanner.
Cerenkov Luminescence Tomography for In Vivo Radiopharmaceutical Imaging
Directory of Open Access Journals (Sweden)
Jianghong Zhong
2011-01-01
Full Text Available Cerenkov luminescence imaging (CLI is a cost-effective molecular imaging tool for biomedical applications of radiotracers. The introduction of Cerenkov luminescence tomography (CLT relative to planar CLI can be compared to the development of X-ray CT based on radiography. With CLT, quantitative and localized analysis of a radiopharmaceutical distribution becomes feasible. In this contribution, a feasibility study of in vivo radiopharmaceutical imaging in heterogeneous medium is presented. Coupled with a multimodal in vivo imaging system, this CLT reconstruction method allows precise anatomical registration of the positron probe in heterogeneous tissues and facilitates the more widespread application of radiotracers. Source distribution inside the small animal is obtained from CLT reconstruction. The experimental results demonstrated that CLT can be employed as an available in vivo tomographic imaging of charged particle emitters in a heterogeneous medium.
Kobayashi, Yoshiomi; Shinozaki, Yoshio; Takahashi, Yohei; Takaishi, Hironari; Ogawa, Jun
2017-01-01
Intervertebral instability risks following L5-S1 transforaminal lumbar interbody fusion (TLIF) and causes of bony bridge formation on computed tomography (CT) remain largely unknown. We evaluated the temporal changes on plain radiographs and reconstructed CT images from 178 patients who had undergone single-level L5-S1 TLIF between February 2011 and February 2015. We statistically analyzed temporal changes the L5-S1 angle on radiographs and intervertebral stability (IVS) at the last observation. Bony bridge formation between the L5-S1 vertebral bodies and the titanium cage subsidence were analyzed by using reconstructed CT. Preoperative L5-S1 angle in the non-IVS group was significantly greater than that in the IVS group. The cage subsidence was classified as follows: type A, both upper and lower endplates; type B, either endplate; or type C, no subsidence. Types B and C decreased over time, whereas type A increased after surgery. The bony bridges between vertebral bodies were found in 87.2% of patients, and 94.5% of all bony bridges were found only in the cage, not on the contralateral side. Our findings suggested that high preoperative L5-S1 angle increased the risk of intervertebral instability after TLIF. The L5-S1 angle decreased over time with increasing type A subsidence, and almost all bony bridges were found only in the cage. These results suggest that the vertebral bodies were stabilized because of cage subsidence, and final bony bridges were created. Methods to improve bony bridge creation are needed to obtain reliable L5-S1 intervertebral bone union. Copyright © 2016 Elsevier Ltd. All rights reserved.
Computed tomography imaging for superior semicircular canal dehiscence syndrome
International Nuclear Information System (INIS)
Dobeli, Karen
2006-01-01
Superior semicircular canal dehiscence is a newly described syndrome of sound and/or pressure induced vertigo. Computed tomography (CT) imaging plays an important role in confirmation of a defect in the bone overlying the canal. A high resolution CT technique utilising 0.5 mm or thinner slices and multi-planar reconstructions parallel to the superior semicircular canal is required. Placement of a histogram over a suspected defect can assist CT diagnosis
Reconstruction of Undersampled Atomic Force Microscopy Images
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm; Arildsen, Thomas; Østergaard, Jan
2013-01-01
Atomic force microscopy (AFM) is one of the most advanced tools for high-resolution imaging and manipulation of nanoscale matter. Unfortunately, standard AFM imaging requires a timescale on the order of seconds to minutes to acquire an image which makes it complicated to observe dynamic processes....... Moreover, it is often required to take several images before a relevant observation region is identified. In this paper we show how to significantly reduce the image acquisition time by undersampling. The reconstruction of an undersampled AFM image can be viewed as an inpainting, interpolating problem...... should be reconstructed using interpolation....
A simulation of portable PET with a new geometric image reconstruction method
Energy Technology Data Exchange (ETDEWEB)
Kawatsu, Shoji [Department of Radiology, Kyoritu General Hospital, 4-33 Go-bancho, Atsuta-ku, Nagoya-shi, Aichi 456 8611 (Japan): Department of Brain Science and Molecular Imaging, National Institute for Longevity Sciences, National Center for Geriatrics and Gerontology, 36-3, Gengo Moriaka-cho, Obu-shi, Aichi 474 8522 (Japan)]. E-mail: b6rgw@fantasy.plala.or.jp; Ushiroya, Noboru [Department of General Education, Wakayama National College of Technology, 77 Noshima, Nada-cho, Gobo-shi, Wakayama 644 0023 (Japan)
2006-12-20
A new method is proposed for three-dimensional positron emission tomography image reconstruction. The method uses the elementary geometric property of line of response whereby two lines of response, which originate from radioactive isotopes in the same position, lie within a few millimeters distance of each other. The method differs from the filtered back projection method and the iterative reconstruction method. The method is applied to a simulation of portable positron emission tomography.
Reconstruction of CT images by the Bayes- back projection method
Haruyama, M; Takase, M; Tobita, H
2002-01-01
In the course of research on quantitative assay of non-destructive measurement of radioactive waste, the have developed a unique program based on the Bayesian theory for reconstruction of transmission computed tomography (TCT) image. The reconstruction of cross-section images in the CT technology usually employs the Filtered Back Projection method. The new imaging reconstruction program reported here is based on the Bayesian Back Projection method, and it has a function of iterative improvement images by every step of measurement. Namely, this method has the capability of prompt display of a cross-section image corresponding to each angled projection data from every measurement. Hence, it is possible to observe an improved cross-section view by reflecting each projection data in almost real time. From the basic theory of Baysian Back Projection method, it can be not only applied to CT types of 1st, 2nd, and 3rd generation. This reported deals with a reconstruction program of cross-section images in the CT of ...
Positron emission tomography imaging of gene expression
International Nuclear Information System (INIS)
Tang Ganghua
2001-01-01
The merging of molecular biology and nuclear medicine is developed into molecular nuclear medicine. Positron emission tomography (PET) of gene expression in molecular nuclear medicine has become an attractive area. Positron emission tomography imaging gene expression includes the antisense PET imaging and the reporter gene PET imaging. It is likely that the antisense PET imaging will lag behind the reporter gene PET imaging because of the numerous issues that have not yet to be resolved with this approach. The reporter gene PET imaging has wide application into animal experimental research and human applications of this approach will likely be reported soon
Edge-promoting reconstruction of absorption and diffusivity in optical tomography
International Nuclear Information System (INIS)
Hannukainen, A; Hyvönen, N; Majander, H; Harhanen, L
2016-01-01
In optical tomography a physical body is illuminated with near-infrared light and the resulting outward photon flux is measured at the object boundary. The goal is to reconstruct internal optical properties of the body, such as absorption and diffusivity. In this work, it is assumed that the imaged object is composed of an approximately homogeneous background with clearly distinguishable embedded inhomogeneities. An algorithm for finding the maximum a posteriori estimate for the absorption and diffusion coefficients is introduced assuming an edge-preferring prior and an additive Gaussian measurement noise model. The method is based on iteratively combining a lagged diffusivity step and a linearization of the measurement model of diffuse optical tomography with priorconditioned LSQR. The performance of the reconstruction technique is tested via three-dimensional numerical experiments with simulated data. (paper)
Sparsity reconstruction in electrical impedance tomography: An experimental evaluation
Gehre, Matthias
2012-02-01
We investigate the potential of sparsity constraints in the electrical impedance tomography (EIT) inverse problem of inferring the distributed conductivity based on boundary potential measurements. In sparsity reconstruction, inhomogeneities of the conductivity are a priori assumed to be sparse with respect to a certain basis. This prior information is incorporated into a Tikhonov-type functional by including a sparsity-promoting ℓ1-penalty term. The functional is minimized with an iterative soft shrinkage-type algorithm. In this paper, the feasibility of the sparsity reconstruction approach is evaluated by experimental data from water tank measurements. The reconstructions are computed both with sparsity constraints and with a more conventional smoothness regularization approach. The results verify that the adoption of ℓ1-type constraints can enhance the quality of EIT reconstructions: in most of the test cases the reconstructions with sparsity constraints are both qualitatively and quantitatively more feasible than that with the smoothness constraint. © 2011 Elsevier B.V. All rights reserved.
Functional imaging of small tissue volumes with diffuse optical tomography
Klose, Alexander D.; Hielscher, Andreas H.
2006-03-01
Imaging of dynamic changes in blood parameters, functional brain imaging, and tumor imaging are the most advanced application areas of diffuse optical tomography (DOT). When dealing with the image reconstruction problem one is faced with the fact that near-infrared photons, unlike X-rays, are highly scattered when they traverse biological tissue. Image reconstruction schemes are required that model the light propagation inside biological tissue and predict measurements on the tissue surface. By iteratively changing the tissue-parameters until the predictions agree with the real measurements, a spatial distribution of optical properties inside the tissue is found. The optical properties can be related to the tissue oxygenation, inflammation, or to the fluorophore concentration of a biochemical marker. If the model of light propagation is inaccurate, the reconstruction process will lead to an inaccurate result as well. Here, we focus on difficulties that are encountered when DOT is employed for functional imaging of small tissue volumes, for example, in cancer studies involving small animals, or human finger joints for early diagnosis of rheumatoid arthritis. Most of the currently employed image reconstruction methods rely on the diffusion theory that is an approximation to the equation of radiative transfer. But, in the cases of small tissue volumes and tissues that contain low scattering regions diffusion theory has been shown to be of limited applicability Therefore, we employ a light propagation model that is based on the equation of radiative transfer, which promises to overcome the limitations.
Brief review of image reconstruction methods for imaging in nuclear medicine
International Nuclear Information System (INIS)
Murayama, Hideo
1999-01-01
Emission computed tomography (ECT) has as its major emphasis the quantitative determination of the moment to moment changes in the chemistry and flow physiology of injected or inhaled compounds labeled with radioactive atoms in a human body. The major difference lies in the fact that ECT seeks to describe the location and intensity of sources of emitted photons in an attenuating medium whereas transmission X-ray computed tomography (TCT) seeks to determine the distribution of the attenuating medium. A second important difference between ECT and TCT is that of available statistics. ECT statistics are low because each photon without control in emitting direction must be detected and analyzed, not as in TCT. The following sections review the historical development of image reconstruction methods for imaging in nuclear medicine, relevant intrinsic concepts for image reconstruction on ECT, and current status of volume imaging as well as a unique approach on iterative techniques for ECT. (author). 130 refs
Application of cone beam computed tomography in facial imaging science
Institute of Scientific and Technical Information of China (English)
Zacharias Fourie; Janalt Damstra; Yijin Ren
2012-01-01
The use of three-dimensional (3D) methods for facial imaging has increased significantly over the past years.Traditional 2D imaging has gradually being replaced by 3D images in different disciplines,particularly in the fields of orthodontics,maxillofacial surgery,plastic and reconstructive surgery,neurosurgery and forensic sciences.In most cases,3D facial imaging overcomes the limitations of traditional 2D methods and provides the clinician with more accurate information regarding the soft-tissues and the underlying skeleton.The aim of this study was to review the types of imaging methods used for facial imaging.It is important to realize the difference between the types of 3D imaging methods as application and indications thereof may differ.Since 3D cone beam computed tomography (CBCT) imaging will play an increasingly importanl role in orthodontics and orthognathic surgery,special emphasis should be placed on discussing CBCT applications in facial evaluations.
Algorithms for reconstructing images for industrial applications
International Nuclear Information System (INIS)
Lopes, R.T.; Crispim, V.R.
1986-01-01
Several algorithms for reconstructing objects from their projections are being studied in our Laboratory, for industrial applications. Such algorithms are useful locating the position and shape of different composition of materials in the object. A Comparative study of two algorithms is made. The two investigated algorithsm are: The MART (Multiplicative - Algebraic Reconstruction Technique) and the Convolution Method. The comparison are carried out from the point view of the quality of the image reconstructed, number of views and cost. (Author) [pt
Huang, Shi-Hao; Wang, Shiang-Jiu; Tseng, Snow H.
2015-03-01
Optical coherence tomography (OCT) provides high resolution, cross-sectional image of internal microstructure of biological tissue. We use the Finite-Difference Time-Domain method (FDTD) to analyze the data acquired by OCT, which can help us reconstruct the refractive index of the biological tissue. We calculate the refractive index tomography and try to match the simulation with the data acquired by OCT. Specifically, we try to reconstruct the structure of melanin, which has complex refractive indices and is the key component of human pigment system. The results indicate that better reconstruction can be achieved for homogenous sample, whereas the reconstruction is degraded for samples with fine structure or with complex interface. Simulation reconstruction shows structures of the Melanin that may be useful for biomedical optics applications.
Quantitative damage imaging using Lamb wave diffraction tomography
International Nuclear Information System (INIS)
Zhang Hai-Yan; Ruan Min; Zhu Wen-Fa; Chai Xiao-Dong
2016-01-01
In this paper, we investigate the diffraction tomography for quantitative imaging damages of partly through-thickness holes with various shapes in isotropic plates by using converted and non-converted scattered Lamb waves generated numerically. Finite element simulations are carried out to provide the scattered wave data. The validity of the finite element model is confirmed by the comparison of scattering directivity pattern (SDP) of circle blind hole damage between the finite element simulations and the analytical results. The imaging method is based on a theoretical relation between the one-dimensional (1D) Fourier transform of the scattered projection and two-dimensional (2D) spatial Fourier transform of the scattering object. A quantitative image of the damage is obtained by carrying out the 2D inverse Fourier transform of the scattering object. The proposed approach employs a circle transducer network containing forward and backward projections, which lead to so-called transmission mode (TMDT) and reflection mode diffraction tomography (RMDT), respectively. The reconstructed results of the two projections for a non-converted S0 scattered mode are investigated to illuminate the influence of the scattering field data. The results show that Lamb wave diffraction tomography using the combination of TMDT and RMDT improves the imaging effect compared with by using only the TMDT or RMDT. The scattered data of the converted A0 mode are also used to assess the performance of the diffraction tomography method. It is found that the circle and elliptical shaped damages can still be reasonably identified from the reconstructed images while the reconstructed results of other complex shaped damages like crisscross rectangles and racecourse are relatively poor. (special topics)
Software for 3D diagnostic image reconstruction and analysis
International Nuclear Information System (INIS)
Taton, G.; Rokita, E.; Sierzega, M.; Klek, S.; Kulig, J.; Urbanik, A.
2005-01-01
Recent advances in computer technologies have opened new frontiers in medical diagnostics. Interesting possibilities are the use of three-dimensional (3D) imaging and the combination of images from different modalities. Software prepared in our laboratories devoted to 3D image reconstruction and analysis from computed tomography and ultrasonography is presented. In developing our software it was assumed that it should be applicable in standard medical practice, i.e. it should work effectively with a PC. An additional feature is the possibility of combining 3D images from different modalities. The reconstruction and data processing can be conducted using a standard PC, so low investment costs result in the introduction of advanced and useful diagnostic possibilities. The program was tested on a PC using DICOM data from computed tomography and TIFF files obtained from a 3D ultrasound system. The results of the anthropomorphic phantom and patient data were taken into consideration. A new approach was used to achieve spatial correlation of two independently obtained 3D images. The method relies on the use of four pairs of markers within the regions under consideration. The user selects the markers manually and the computer calculates the transformations necessary for coupling the images. The main software feature is the possibility of 3D image reconstruction from a series of two-dimensional (2D) images. The reconstructed 3D image can be: (1) viewed with the most popular methods of 3D image viewing, (2) filtered and processed to improve image quality, (3) analyzed quantitatively (geometrical measurements), and (4) coupled with another, independently acquired 3D image. The reconstructed and processed 3D image can be stored at every stage of image processing. The overall software performance was good considering the relatively low costs of the hardware used and the huge data sets processed. The program can be freely used and tested (source code and program available at
Iterative methods for dose reduction and image enhancement in tomography
Miao, Jianwei; Fahimian, Benjamin Pooya
2012-09-18
A system and method for creating a three dimensional cross sectional image of an object by the reconstruction of its projections that have been iteratively refined through modification in object space and Fourier space is disclosed. The invention provides systems and methods for use with any tomographic imaging system that reconstructs an object from its projections. In one embodiment, the invention presents a method to eliminate interpolations present in conventional tomography. The method has been experimentally shown to provide higher resolution and improved image quality parameters over existing approaches. A primary benefit of the method is radiation dose reduction since the invention can produce an image of a desired quality with a fewer number projections than seen with conventional methods.
Parallel Algorithm for Reconstruction of TAC Images
International Nuclear Information System (INIS)
Vidal Gimeno, V.
2012-01-01
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.
Patra, Rusha; Dutta, Pranab K.
2015-07-01
Reconstruction of the absorption coefficient of tissue with good contrast is of key importance in functional diffuse optical imaging. A hybrid approach using model-based iterative image reconstruction and a genetic algorithm is proposed to enhance the contrast of the reconstructed image. The proposed method yields an observed contrast of 98.4%, mean square error of 0.638×10-3, and object centroid error of (0.001 to 0.22) mm. Experimental validation of the proposed method has also been provided with tissue-like phantoms which shows a significant improvement in image quality and thus establishes the potential of the method for functional diffuse optical tomography reconstruction with continuous wave setup. A case study of finger joint imaging is illustrated as well to show the prospect of the proposed method in clinical diagnosis. The method can also be applied to the concentration measurement of a region of interest in a turbid medium.
International Nuclear Information System (INIS)
Zhang, Maomao; Soleimani, Manuchehr
2016-01-01
Electrical capacitance tomography (ECT) is an imaging method mainly capable of reconstructing dielectric permittivity. Generally, the reactance part of complex admittance is measured in a selected frequency. This paper presents for the first time an in depth and systematic analysis of complex admittance data for simultaneous reconstruction of both electrical conductivity and dielectric permittivity. A complex-valued forward model, Jacobian matrix and inverse solution are developed in the time harmonic excitation mode to allow for multi-frequency measurements. Realistic noise models are used to evaluate the performance of complex admittance ECT in a range of excitation frequencies. This paper demonstrates far greater potential for ECT as a versatile imaging tool through novel analysis of complex admittance imaging using a dual conductivity permittivity inversion method. The paper demonstrates that various classes of contactless capacitance based measurement devices can be analysed through complex multi-frequency ECT. (paper)
Energy Technology Data Exchange (ETDEWEB)
Saghi, Zineb, E-mail: saghizineb@gmail.com [Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS (United Kingdom); Divitini, Giorgio [Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS (United Kingdom); Winter, Benjamin [Center for Nanoanalysis and Electron Microscopy (CENEM), Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstraße 6, 91058 Erlangen (Germany); Leary, Rowan [Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS (United Kingdom); Spiecker, Erdmann [Center for Nanoanalysis and Electron Microscopy (CENEM), Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstraße 6, 91058 Erlangen (Germany); Ducati, Caterina [Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS (United Kingdom); Midgley, Paul A., E-mail: pam33@cam.ac.uk [Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS (United Kingdom)
2016-01-15
Electron tomography is an invaluable method for 3D cellular imaging. The technique is, however, limited by the specimen geometry, with a loss of resolution due to a restricted tilt range, an increase in specimen thickness with tilt, and a resultant need for subjective and time-consuming manual segmentation. Here we show that 3D reconstructions of needle-shaped biological samples exhibit isotropic resolution, facilitating improved automated segmentation and feature detection. By using scanning transmission electron tomography, with small probe convergence angles, high spatial resolution is maintained over large depths of field and across the tilt range. Moreover, the application of compressed sensing methods to the needle data demonstrates how high fidelity reconstructions may be achieved with far fewer images (and thus greatly reduced dose) than needed by conventional methods. These findings open the door to high fidelity electron tomography over critically relevant length-scales, filling an important gap between existing 3D cellular imaging techniques. - Highlights: • On-axis electron tomography of a needle-shaped biological sample is presented. • A reconstruction with isotropic resolution is achieved. • Compressed sensing methods are compared to conventional reconstruction algorithms. • High fidelity reconstructions are achieved with greatly undersampled datasets.
International Nuclear Information System (INIS)
Saghi, Zineb; Divitini, Giorgio; Winter, Benjamin; Leary, Rowan; Spiecker, Erdmann; Ducati, Caterina; Midgley, Paul A.
2016-01-01
Electron tomography is an invaluable method for 3D cellular imaging. The technique is, however, limited by the specimen geometry, with a loss of resolution due to a restricted tilt range, an increase in specimen thickness with tilt, and a resultant need for subjective and time-consuming manual segmentation. Here we show that 3D reconstructions of needle-shaped biological samples exhibit isotropic resolution, facilitating improved automated segmentation and feature detection. By using scanning transmission electron tomography, with small probe convergence angles, high spatial resolution is maintained over large depths of field and across the tilt range. Moreover, the application of compressed sensing methods to the needle data demonstrates how high fidelity reconstructions may be achieved with far fewer images (and thus greatly reduced dose) than needed by conventional methods. These findings open the door to high fidelity electron tomography over critically relevant length-scales, filling an important gap between existing 3D cellular imaging techniques. - Highlights: • On-axis electron tomography of a needle-shaped biological sample is presented. • A reconstruction with isotropic resolution is achieved. • Compressed sensing methods are compared to conventional reconstruction algorithms. • High fidelity reconstructions are achieved with greatly undersampled datasets.
A shape-based quality evaluation and reconstruction method for electrical impedance tomography.
Antink, Christoph Hoog; Pikkemaat, Robert; Malmivuo, Jaakko; Leonhardt, Steffen
2015-06-01
Linear methods of reconstruction play an important role in medical electrical impedance tomography (EIT) and there is a wide variety of algorithms based on several assumptions. With the Graz consensus reconstruction algorithm for EIT (GREIT), a novel linear reconstruction algorithm as well as a standardized framework for evaluating and comparing methods of reconstruction were introduced that found widespread acceptance in the community. In this paper, we propose a two-sided extension of this concept by first introducing a novel method of evaluation. Instead of being based on point-shaped resistivity distributions, we use 2759 pairs of real lung shapes for evaluation that were automatically segmented from human CT data. Necessarily, the figures of merit defined in GREIT were adjusted. Second, a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed. Using our novel method of evaluation, this approach is compared to the classical point-shaped approach. Results show that most figures of merit improve with the use of eigenimages as training data. Moreover, the possibility of tuning the reconstruction by modifying the desired point spread function is shown. Finally, the reconstruction of real EIT data shows that higher contrasts and fewer artifacts can be achieved in ventilation- and perfusion-related images.
A shape-based quality evaluation and reconstruction method for electrical impedance tomography
International Nuclear Information System (INIS)
Antink, Christoph Hoog; Pikkemaat, Robert; Leonhardt, Steffen; Malmivuo, Jaakko
2015-01-01
Linear methods of reconstruction play an important role in medical electrical impedance tomography (EIT) and there is a wide variety of algorithms based on several assumptions. With the Graz consensus reconstruction algorithm for EIT (GREIT), a novel linear reconstruction algorithm as well as a standardized framework for evaluating and comparing methods of reconstruction were introduced that found widespread acceptance in the community.In this paper, we propose a two-sided extension of this concept by first introducing a novel method of evaluation. Instead of being based on point-shaped resistivity distributions, we use 2759 pairs of real lung shapes for evaluation that were automatically segmented from human CT data. Necessarily, the figures of merit defined in GREIT were adjusted. Second, a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed.Using our novel method of evaluation, this approach is compared to the classical point-shaped approach. Results show that most figures of merit improve with the use of eigenimages as training data. Moreover, the possibility of tuning the reconstruction by modifying the desired point spread function is shown. Finally, the reconstruction of real EIT data shows that higher contrasts and fewer artifacts can be achieved in ventilation- and perfusion-related images. (paper)
PET image reconstruction: mean, variance, and optimal minimax criterion
International Nuclear Information System (INIS)
Liu, Huafeng; Guo, Min; Gao, Fei; Shi, Pengcheng; Xue, Liying; Nie, Jing
2015-01-01
Given the noise nature of positron emission tomography (PET) measurements, it is critical to know the image quality and reliability as well as expected radioactivity map (mean image) for both qualitative interpretation and quantitative analysis. While existing efforts have often been devoted to providing only the reconstructed mean image, we present a unified framework for joint estimation of the mean and corresponding variance of the radioactivity map based on an efficient optimal min–max criterion. The proposed framework formulates the PET image reconstruction problem to be a transformation from system uncertainties to estimation errors, where the minimax criterion is adopted to minimize the estimation errors with possibly maximized system uncertainties. The estimation errors, in the form of a covariance matrix, express the measurement uncertainties in a complete way. The framework is then optimized by ∞-norm optimization and solved with the corresponding H ∞ filter. Unlike conventional statistical reconstruction algorithms, that rely on the statistical modeling methods of the measurement data or noise, the proposed joint estimation stands from the point of view of signal energies and can handle from imperfect statistical assumptions to even no a priori statistical assumptions. The performance and accuracy of reconstructed mean and variance images are validated using Monte Carlo simulations. Experiments on phantom scans with a small animal PET scanner and real patient scans are also conducted for assessment of clinical potential. (paper)
3D ultrasound computer tomography: Hardware setup, reconstruction methods and first clinical results
Gemmeke, Hartmut; Hopp, Torsten; Zapf, Michael; Kaiser, Clemens; Ruiter, Nicole V.
2017-11-01
A promising candidate for improved imaging of breast cancer is ultrasound computer tomography (USCT). Current experimental USCT systems are still focused in elevation dimension resulting in a large slice thickness, limited depth of field, loss of out-of-plane reflections, and a large number of movement steps to acquire a stack of images. 3D USCT emitting and receiving spherical wave fronts overcomes these limitations. We built an optimized 3D USCT, realizing for the first time the full benefits of a 3D system. The point spread function could be shown to be nearly isotropic in 3D, to have very low spatial variability and fit the predicted values. The contrast of the phantom images is very satisfactory in spite of imaging with a sparse aperture. The resolution and imaged details of the reflectivity reconstruction are comparable to a 3 T MRI volume. Important for the obtained resolution are the simultaneously obtained results of the transmission tomography. The KIT 3D USCT was then tested in a pilot study on ten patients. The primary goals of the pilot study were to test the USCT device, the data acquisition protocols, the image reconstruction methods and the image fusion techniques in a clinical environment. The study was conducted successfully; the data acquisition could be carried out for all patients with an average imaging time of six minutes per breast. The reconstructions provide promising images. Overlaid volumes of the modalities show qualitative and quantitative information at a glance. This paper gives a summary of the involved techniques, methods, and first results.
The Role of Synthetic Reconstruction Tests in Seismic Tomography
Rawlinson, N.; Spakman, W.
2015-12-01
Synthetic reconstruction tests are widely used in seismic tomography as a means for assessing the robustness of solutions produced by linear or iterative non-linear inversion schemes. The most common test is the so-called checkerboard resolution test, which uses an alternating pattern of high and low wavespeeds (or some other seismic property such as attenuation). However, checkerboard tests have a number of limitations, including that they (1) only provide indirect evidence of quantitative measures of reliability such as resolution and uncertainty; (2) give a potentially misleading impression of the range of scale-lengths that can be resolved; (3) don't give a true picture of the structural distortion or smearing caused by the data coverage; and (4) result in an inverse problem that is biased towards an accurate reconstruction. The widespread use of synthetic reconstruction tests in seismic tomography is likely to continue for some time yet, so it is important to implement best practice where possible. The goal here is to provide a general set of guidelines, derived from the underlying theory and illustrated by a series of numerical experiments, on their implementation in seismic tomography. In particular, we recommend (1) using a sparse distribution of spikes, rather than the more conventional tightly-spaced checkerboard; (2) using the identical data coverage (e.g. geometric rays) for the synthetic model that was computed for the observation-based model; (3) carrying out multiple tests using anomalies of different scale length; (4) exercising caution when analysing synthetic recovery tests that use anomaly patterns that closely mimic the observation-based model; (5) investigating the trade-off between data noise levels and the minimum wavelength of recovered structure; (6) where possible, test the extent to which preconditioning (e.g. identical parameterization for input and output models) influences the recovery of anomalies.
Parametric image reconstruction using spectral analysis of PET projection data
International Nuclear Information System (INIS)
Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat
1998-01-01
Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)
Electrical Resistance Tomography imaging of concrete
Karhunen, Kimmo; Seppä nen, Aku; Lehikoinen, Anssi; Monteiro, Paulo J.M.; Kaipio, Jari P.
2010-01-01
We apply Electrical Resistance Tomography (ERT) for three dimensional imaging of concrete. In ERT, alternating currents are injected into the target using an array of electrodes attached to the target surface, and the resulting voltages are measured
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 scanning time as well as the amount of interaction between the AFM probe and the specimen. It can easily be applied on conventional AFM hardware. Due to undersampling, it is then necessary to further process the acquired image in order to reconstruct an approximation of the image. Based on real AFM cell...... images, our simulations reveal that using a simple raster scanning pattern in combination with conventional image interpolation performs very well. Moreover, this combination enables a reduction by a factor 10 of the scanning time while retaining an average reconstruction quality around 36 dB PSNR...
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.
Energy Technology Data Exchange (ETDEWEB)
Melli, Seyed Ali, E-mail: sem649@mail.usask.ca [Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK (Canada); Wahid, Khan A. [Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK (Canada); Babyn, Paul [Department of Medical Imaging, University of Saskatchewan, Saskatoon, SK (Canada); Montgomery, James [College of Medicine, University of Saskatchewan, Saskatoon, SK (Canada); Snead, Elisabeth [Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK (Canada); El-Gayed, Ali [College of Medicine, University of Saskatchewan, Saskatoon, SK (Canada); Pettitt, Murray; Wolkowski, Bailey [College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK (Canada); Wesolowski, Michal [Department of Medical Imaging, University of Saskatchewan, Saskatoon, SK (Canada)
2016-01-11
Synchrotron source propagation-based X-ray phase contrast computed tomography is increasingly used in pre-clinical imaging. However, it typically requires a large number of projections, and subsequently a large radiation dose, to produce high quality images. To improve the applicability of this imaging technique, reconstruction algorithms that can reduce the radiation dose and acquisition time without degrading image quality are needed. The proposed research focused on using a novel combination of Douglas–Rachford splitting and randomized Kaczmarz algorithms to solve large-scale total variation based optimization in a compressed sensing framework to reconstruct 2D images from a reduced number of projections. Visual assessment and quantitative performance evaluations of a synthetic abdomen phantom and real reconstructed image of an ex-vivo slice of canine prostate tissue demonstrate that the proposed algorithm is competitive in reconstruction process compared with other well-known algorithms. An additional potential benefit of reducing the number of projections would be reduction of time for motion artifact to occur if the sample moves during image acquisition. Use of this reconstruction algorithm to reduce the required number of projections in synchrotron source propagation-based X-ray phase contrast computed tomography is an effective form of dose reduction that may pave the way for imaging of in-vivo samples.
FIRST: Fast Iterative Reconstruction Software for (PET) tomography
International Nuclear Information System (INIS)
Herraiz, J L; Espana, S; Vaquero, J J; Desco, M; UdIas, J M
2006-01-01
Small animal PET scanners require high spatial resolution and good sensitivity. To reconstruct high-resolution images in 3D-PET, iterative methods, such as OSEM, are superior to analytical reconstruction algorithms, although their high computational cost is still a serious drawback. The higher performance of modern computers could make iterative image reconstruction fast enough to be viable, provided we are able to deal with the large number of probability coefficients for the system response matrix in high-resolution PET scanners, which is a difficult task that prevents the algorithms from reaching peak computing performance. Considering all possible axial and in-plane symmetries, as well as certain quasi-symmetries, we have been able to reduce the memory requirements to store the system response matrix (SRM) well below 1 GB, which allows us to keep the whole response matrix of the system inside RAM of ordinary industry-standard computers, so that the reconstruction algorithm can achieve near peak performance. The elements of the SRM are stored as cubic spline profiles and matched to voxel size during reconstruction. In this way, the advantages of 'on-the-fly' calculation and of fully stored SRM are combined. The on-the-fly part of the calculation (matching the profile functions to voxel size) of the SRM accounts for 10-30% of the reconstruction time, depending on the number of voxels chosen. We tested our approach with real data from a commercial small animal PET scanner. The results (image quality and reconstruction time) show that the proposed technique is a feasible solution
FIRST: Fast Iterative Reconstruction Software for (PET) tomography
Energy Technology Data Exchange (ETDEWEB)
Herraiz, J L [Dpto. Fisica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid (Spain); Espana, S [Dpto. Fisica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid (Spain); Vaquero, J J [Unidad de Medicina y CirugIa Experimental, Hospital GU Gregorio Maranon, Madrid (Spain); Desco, M [Unidad de Medicina y CirugIa Experimental, Hospital GU Gregorio Maranon, Madrid (Spain); UdIas, J M [Dpto. Fisica Atomica, Molecular y Nuclear, Universidad Complutense de Madrid (Spain)
2006-09-21
Small animal PET scanners require high spatial resolution and good sensitivity. To reconstruct high-resolution images in 3D-PET, iterative methods, such as OSEM, are superior to analytical reconstruction algorithms, although their high computational cost is still a serious drawback. The higher performance of modern computers could make iterative image reconstruction fast enough to be viable, provided we are able to deal with the large number of probability coefficients for the system response matrix in high-resolution PET scanners, which is a difficult task that prevents the algorithms from reaching peak computing performance. Considering all possible axial and in-plane symmetries, as well as certain quasi-symmetries, we have been able to reduce the memory requirements to store the system response matrix (SRM) well below 1 GB, which allows us to keep the whole response matrix of the system inside RAM of ordinary industry-standard computers, so that the reconstruction algorithm can achieve near peak performance. The elements of the SRM are stored as cubic spline profiles and matched to voxel size during reconstruction. In this way, the advantages of 'on-the-fly' calculation and of fully stored SRM are combined. The on-the-fly part of the calculation (matching the profile functions to voxel size) of the SRM accounts for 10-30% of the reconstruction time, depending on the number of voxels chosen. We tested our approach with real data from a commercial small animal PET scanner. The results (image quality and reconstruction time) show that the proposed technique is a feasible solution.
Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing
2013-09-15
For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.
Directory of Open Access Journals (Sweden)
Schullcke Benjamin
2016-09-01
Full Text Available Electrical impedance tomography (EIT is used to monitor the regional distribution of ventilation in a transversal plane of the thorax. In this manuscript we evaluate the impact of different quantities of electrodes used for current injection and voltage measurement on the reconstructed shape of the lungs. Results indicate that the shape of reconstructed impedance changes in the body depends on the number of electrodes. In this manuscript, we demonstrate that a higher number of electrodes do not necessarily increase the image quality. For the used stimulation pattern, utilizing neighboring electrodes for current injection and voltage measurement, we conclude that the shape of the lungs is best reconstructed if 16 electrodes are used.
Ni, Yusu; Dai, Peidong; Dai, Chunfu; Li, Huawei
2017-01-01
To explore the structural characteristics of the cochlea in three-dimensional (3D) detail using 3D micro-computed tomography (mCT) image reconstruction of the osseous labyrinth, with the aim of improving the structural design of electrodes, the selection of stimulation sites, and the effectiveness of cochlear implantation. Three temporal bones were selected from among adult donors' temporal bone specimens. A micro-CT apparatus (GE eXplore) was used to scan three specimens with a voxel resolution of 45 μm. We obtained about 460 slices/specimen, which produced abundant data. The osseous labyrinth images of three specimens were reconstructed from mCT. The cochlea and its spiral characteristics were measured precisely using Able Software 3D-DOCTOR. The 3D images of the osseous labyrinth, including the cochlea, vestibule, and semicircular canals, were reconstructed. The 3D models of the cochlea showed the spatial relationships and surface structural characteristics. Quantitative data concerning the cochlea and its spiral structural characteristics were analyzed with regard to cochlear implantation. The 3D reconstruction of mCT images clearly displayed the detailed spiral structural characteristics of the osseous labyrinth. Quantitative data regarding the cochlea and its spiral structural characteristics could help to improve electrode structural design, signal processing, and the effectiveness of cochlear implantation. Clin. Anat. 30:39-43, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Wang, Kun; Schoonover, Robert W; Su, Richard; Oraevsky, Alexander; Anastasio, Mark A
2014-05-01
Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles. Iterative image reconstruction algorithms that are based on discrete imaging models are actively being developed for OAT due to their ability to improve image quality by incorporating accurate models of the imaging physics, instrument response, and measurement noise. In this work, we investigate the use of discrete imaging models based on Kaiser-Bessel window functions for iterative image reconstruction in OAT. A closed-form expression for the pressure produced by a Kaiser-Bessel function is calculated, which facilitates accurate computation of the system matrix. Computer-simulation and experimental studies are employed to demonstrate the potential advantages of Kaiser-Bessel function-based iterative image reconstruction in OAT.
Joint model of motion and anatomy for PET image reconstruction
International Nuclear Information System (INIS)
Qiao Feng; Pan Tinsu; Clark, John W. Jr.; Mawlawi, Osama
2007-01-01
Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem
Noise and contrast detection in computed tomography images
International Nuclear Information System (INIS)
Faulkner, K.; Moores, B.M.
1984-01-01
A discrete representation of the reconstruction process is used in an analysis of noise in computed tomography (CT) images. This model is consistent with the method of data collection in actual machines. An expression is derived which predicts the variance on the measured linear attenuation coefficient of a single pixel in an image. The dependence of the variance on various CT scanner design parameters such as pixel size, slice width, scan time, number of detectors, etc., is then described. The variation of noise with sampling area is theoretically explained. These predictions are in good agreement with a set of experimental measurements made on a range of CT scanners. The equivalent sampling aperture of the CT process is determined and the effect of the reconstruction filter on the variance of the linear attenuation coefficient is also noted, in particular, the choice and its consequences for reconstructed images and noise behaviour. The theory has been extended to include contrast detail behaviour, and these predictions compare favourably with experimental measurements. The theory predicts that image smoothing will have little effect on the contrast-detail detectability behaviour of reconstructed images. (author)
LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation
International Nuclear Information System (INIS)
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
MR image reconstruction via guided filter.
Huang, Heyan; Yang, Hang; Wang, Kang
2018-04-01
Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.
Photoacoustic image reconstruction: a quantitative analysis
Sperl, Jonathan I.; Zell, Karin; Menzenbach, Peter; Haisch, Christoph; Ketzer, Stephan; Marquart, Markus; Koenig, Hartmut; Vogel, Mika W.
2007-07-01
Photoacoustic imaging is a promising new way to generate unprecedented contrast in ultrasound diagnostic imaging. It differs from other medical imaging approaches, in that it provides spatially resolved information about optical absorption of targeted tissue structures. Because the data acquisition process deviates from standard clinical ultrasound, choice of the proper image reconstruction method is crucial for successful application of the technique. In the literature, multiple approaches have been advocated, and the purpose of this paper is to compare four reconstruction techniques. Thereby, we focused on resolution limits, stability, reconstruction speed, and SNR. We generated experimental and simulated data and reconstructed images of the pressure distribution using four different methods: delay-and-sum (DnS), circular backprojection (CBP), generalized 2D Hough transform (HTA), and Fourier transform (FTA). All methods were able to depict the point sources properly. DnS and CBP produce blurred images containing typical superposition artifacts. The HTA provides excellent SNR and allows a good point source separation. The FTA is the fastest and shows the best FWHM. In our study, we found the FTA to show the best overall performance. It allows a very fast and theoretically exact reconstruction. Only a hardware-implemented DnS might be faster and enable real-time imaging. A commercial system may also perform several methods to fully utilize the new contrast mechanism and guarantee optimal resolution and fidelity.
Bayesian PET image reconstruction incorporating anato-functional joint entropy
International Nuclear Information System (INIS)
Tang Jing; Rahmim, Arman
2009-01-01
We developed a maximum a posterior (MAP) reconstruction method for positron emission tomography (PET) image reconstruction incorporating magnetic resonance (MR) image information, with the joint entropy between the PET and MR image features serving as the regularization constraint. A non-parametric method was used to estimate the joint probability density of the PET and MR images. Using realistically simulated PET and MR human brain phantoms, the quantitative performance of the proposed algorithm was investigated. Incorporation of the anatomic information via this technique, after parameter optimization, was seen to dramatically improve the noise versus bias tradeoff in every region of interest, compared to the result from using conventional MAP reconstruction. In particular, hot lesions in the FDG PET image, which had no anatomical correspondence in the MR image, also had improved contrast versus noise tradeoff. Corrections were made to figures 3, 4 and 6, and to the second paragraph of section 3.1 on 13 November 2009. The corrected electronic version is identical to the print version.
Directory of Open Access Journals (Sweden)
Lukas Ebner
2014-01-01
Full Text Available Objective:The aim of the present study was to evaluate a dose reduction in contrast-enhanced chest computed tomography (CT by comparing the three latest generations of Siemens CT scanners used in clinical practice. We analyzed the amount of radiation used with filtered back projection (FBP and an iterative reconstruction (IR algorithm to yield the same image quality. Furthermore, the influence on the radiation dose of the most recent integrated circuit detector (ICD; Stellar detector, Siemens Healthcare, Erlangen, Germany was investigated. Materials and Methods: 136 Patients were included. Scan parameters were set to a thorax routine: SOMATOM Sensation 64 (FBP, SOMATOM Definition Flash (IR, and SOMATOM Definition Edge (ICD and IR. Tube current was set constantly to the reference level of 100 mA automated tube current modulation using reference milliamperes. Care kV was used on the Flash and Edge scanner, while tube potential was individually selected between 100 and 140 kVp by the medical technologists at the SOMATOM Sensation. Quality assessment was performed on soft-tissue kernel reconstruction. Dose was represented by the dose length product. Results: Dose-length product (DLP with FBP for the average chest CT was 308 mGycm ± 99.6. In contrast, the DLP for the chest CT with IR algorithm was 196.8 mGycm ± 68.8 (P = 0.0001. Further decline in dose can be noted with IR and the ICD: DLP: 166.4 mGycm ± 54.5 (P = 0.033. The dose reduction compared to FBP was 36.1% with IR and 45.6% with IR/ICD. Signal-to-noise ratio (SNR was favorable in the aorta, bone, and soft tissue for IR/ICD in combination compared to FBP (the P values ranged from 0.003 to 0.048. Overall contrast-to-noise ratio (CNR improved with declining DLP. Conclusion: The most recent technical developments, namely IR in combination with integrated circuit detectors, can significantly lower radiation dose in chest CT examinations.
Modelling the physics in iterative reconstruction for transmission computed tomography
Nuyts, Johan; De Man, Bruno; Fessler, Jeffrey A.; Zbijewski, Wojciech; Beekman, Freek J.
2013-01-01
There is an increasing interest in iterative reconstruction (IR) as a key tool to improve quality and increase applicability of X-ray CT imaging. IR has the ability to significantly reduce patient dose, it provides the flexibility to reconstruct images from arbitrary X-ray system geometries and it allows to include detailed models of photon transport and detection physics, to accurately correct for a wide variety of image degrading effects. This paper reviews discretisation issues and modelling of finite spatial resolution, Compton scatter in the scanned object, data noise and the energy spectrum. Widespread implementation of IR with highly accurate model-based correction, however, still requires significant effort. In addition, new hardware will provide new opportunities and challenges to improve CT with new modelling. PMID:23739261
Filter assessment applied to analytical reconstruction for industrial third-generation tomography
Energy Technology Data Exchange (ETDEWEB)
Velo, Alexandre F.; Martins, Joao F.T.; Oliveira, Adriano S.; Carvalho, Diego V.S.; Faria, Fernando S.; Hamada, Margarida M.; Mesquita, Carlos H., E-mail: afvelo@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2015-07-01
Multiphase systems are structures that contain a mixture of solids, liquids and gases inside a chemical reactor or pipes in a dynamic process. These systems are found in chemical, food, pharmaceutical and petrochemical industries. The gamma ray computed tomography (CT) system has been applied to visualize the distribution of multiphase systems without interrupting production. CT systems have been used to improve design, operation and troubleshooting of industrial processes. Computer tomography for multiphase processes is being developed at several laboratories. It is well known that scanning systems demand high processing time, limited set of data projections and views to obtain an image. Because of it, the image quality is dependent on the number of projection, number of detectors, acquisition time and reconstruction time. A phantom containing air, iron and aluminum was used on the third generation industrial tomography with 662 keV ({sup 137}Cs) radioactive source. It was applied the Filtered Back Projection algorithm to reconstruct the images. An efficient tomography is dependent of the image quality, thus the objective of this research was to apply different types of filters on the analytical algorithm and compare each other using the figure of merit denominated root mean squared error (RMSE), the filter that presents lower value of RMSE has better quality. On this research, five types of filters were used: Ram-Lak, Shepp-Logan, Cosine, Hamming and Hann filters. As results, all filters presented lower values of RMSE, that means the filters used have low stand deviation compared to the mass absorption coefficient, however, the Hann filter presented better RMSE and CNR compared to the others. (author)
Filter assessment applied to analytical reconstruction for industrial third-generation tomography
International Nuclear Information System (INIS)
Velo, Alexandre F.; Martins, Joao F.T.; Oliveira, Adriano S.; Carvalho, Diego V.S.; Faria, Fernando S.; Hamada, Margarida M.; Mesquita, Carlos H.
2015-01-01
Multiphase systems are structures that contain a mixture of solids, liquids and gases inside a chemical reactor or pipes in a dynamic process. These systems are found in chemical, food, pharmaceutical and petrochemical industries. The gamma ray computed tomography (CT) system has been applied to visualize the distribution of multiphase systems without interrupting production. CT systems have been used to improve design, operation and troubleshooting of industrial processes. Computer tomography for multiphase processes is being developed at several laboratories. It is well known that scanning systems demand high processing time, limited set of data projections and views to obtain an image. Because of it, the image quality is dependent on the number of projection, number of detectors, acquisition time and reconstruction time. A phantom containing air, iron and aluminum was used on the third generation industrial tomography with 662 keV ( 137 Cs) radioactive source. It was applied the Filtered Back Projection algorithm to reconstruct the images. An efficient tomography is dependent of the image quality, thus the objective of this research was to apply different types of filters on the analytical algorithm and compare each other using the figure of merit denominated root mean squared error (RMSE), the filter that presents lower value of RMSE has better quality. On this research, five types of filters were used: Ram-Lak, Shepp-Logan, Cosine, Hamming and Hann filters. As results, all filters presented lower values of RMSE, that means the filters used have low stand deviation compared to the mass absorption coefficient, however, the Hann filter presented better RMSE and CNR compared to the others. (author)
Heuristic optimization in penumbral image for high resolution reconstructed image
International Nuclear Information System (INIS)
Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.
2010-01-01
Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.
Computational acceleration for MR image reconstruction in partially parallel imaging.
Ye, Xiaojing; Chen, Yunmei; Huang, Feng
2011-05-01
In this paper, we present a fast numerical algorithm for solving total variation and l(1) (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images.
Reconstruction of the refractive index gradient by x-ray diffraction enhanced computed tomography
Energy Technology Data Exchange (ETDEWEB)
Wang Junyue [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Zhu Peiping [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Yuan Qingxi [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Huang Wanxia [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Shu Hang [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Chen Bo [Department of Physics, University of Science and Technology of China, Hefei 230026 (China); Hu Tiandou [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Wu Ziyu [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)
2006-07-21
The computed tomography technique cannot easily be extended to diffraction enhanced imaging (DEI) because, while from DEI we may extract the refractive index gradient in one dimension, from the conventional CT reconstruction algorithm we may reconstruct only a scalar quantity. However, recently we showed that changing the direction of the scan axis, and collecting a set of data related to the three-dimensional distribution of the refractive index gradient of the sample, a CT image was obtained. The algorithm we used is based on the conventional CT algorithm but with a specific pre-processing of the projection data. The mathematical framework of the procedure and a simple CT experiment are presented and discussed.
Reconstruction of the refractive index gradient by x-ray diffraction enhanced computed tomography
International Nuclear Information System (INIS)
Wang Junyue; Zhu Peiping; Yuan Qingxi; Huang Wanxia; Shu Hang; Chen Bo; Hu Tiandou; Wu Ziyu
2006-01-01
The computed tomography technique cannot easily be extended to diffraction enhanced imaging (DEI) because, while from DEI we may extract the refractive index gradient in one dimension, from the conventional CT reconstruction algorithm we may reconstruct only a scalar quantity. However, recently we showed that changing the direction of the scan axis, and collecting a set of data related to the three-dimensional distribution of the refractive index gradient of the sample, a CT image was obtained. The algorithm we used is based on the conventional CT algorithm but with a specific pre-processing of the projection data. The mathematical framework of the procedure and a simple CT experiment are presented and discussed
Ahmad, Moiz; Balter, Peter; Pan, Tinsu
2011-10-01
Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4-6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3-8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm
Muon tomography imaging improvement using optimized limited angle data
Bai, Chuanyong; Simon, Sean; Kindem, Joel; Luo, Weidong; Sossong, Michael J.; Steiger, Matthew
2014-05-01
Image resolution of muon tomography is limited by the range of zenith angles of cosmic ray muons and the flux rate at sea level. Low flux rate limits the use of advanced data rebinning and processing techniques to improve image quality. By optimizing the limited angle data, however, image resolution can be improved. To demonstrate the idea, physical data of tungsten blocks were acquired on a muon tomography system. The angular distribution and energy spectrum of muons measured on the system was also used to generate simulation data of tungsten blocks of different arrangement (geometry). The data were grouped into subsets using the zenith angle and volume images were reconstructed from the data subsets using two algorithms. One was a distributed PoCA (point of closest approach) algorithm and the other was an accelerated iterative maximal likelihood/expectation maximization (MLEM) algorithm. Image resolution was compared for different subsets. Results showed that image resolution was better in the vertical direction for subsets with greater zenith angles and better in the horizontal plane for subsets with smaller zenith angles. The overall image resolution appeared to be the compromise of that of different subsets. This work suggests that the acquired data can be grouped into different limited angle data subsets for optimized image resolution in desired directions. Use of multiple images with resolution optimized in different directions can improve overall imaging fidelity and the intended applications.
A PC-based discrete tomography imaging software system for assaying radioactive waste containers
International Nuclear Information System (INIS)
Palacios, J.C.; Longoria, L.C.; Santos, J.; Perry, R.T.
2003-01-01
A PC-based discrete tomography imaging software system for assaying radioactive waste containers for use in facilities in Mexico has been developed. The software system consists of three modules: (i) for reconstruction transmission tomography, (ii) for reconstruction emission tomography, and (iii) for simulation tomography. The Simulation Module is an interactive computer program that is used to create simulated databases for input to the Reconstruction Modules. These databases may be used in the absence of physical measurements to insure that the tomographic theoretical models are valid and that the coding accurately describes these models. Simulation may also be used to determine the detection limits of the reconstruction methodology. A description of the system, the theory, and a demonstration of the systems capabilities is provided in the paper. The hardware for this system is currently under development
International Nuclear Information System (INIS)
Sidky, Emil Y.; Pan Xiaochuan; Reiser, Ingrid S.; Nishikawa, Robert M.; Moore, Richard H.; Kopans, Daniel B.
2009-01-01
Purpose: The authors develop a practical, iterative algorithm for image-reconstruction in undersampled tomographic systems, such as digital breast tomosynthesis (DBT). Methods: The algorithm controls image regularity by minimizing the image total p variation (TpV), a function that reduces to the total variation when p=1.0 or the image roughness when p=2.0. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets. The fact that the tomographic system is undersampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) Reduction in the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in undersampled tomography. Results: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. Conclusions: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging.
Directory of Open Access Journals (Sweden)
Lee Sangkyu
2016-01-01
Full Text Available In this paper, we present a new algorithm that improves muon-based generated tomography images with increased precision and reduced image noise applicable to the detection of nuclear materials. Cosmic muon tomography is an interrogation-based imaging technique that, over the last decade, has been frequently employed for the detection of high-Z materials. This technique exploits a magnitude of cosmic muon scattering angles in order to construct an image. The scattering angles of the muons striking the geometry of interest are non-uniform, as cosmic muons vary in energy. The randomness of the scattering angles leads to significant noise in the muon tomography image. GEANT4 is used to numerically create data on the momenta and positions of scattered muons in a predefined geometry that includes high-Z materials. The numerically generated information is then processed with the point of closest approach reconstruction method to construct a muon tomography image; statistical filters are then developed to refine the point of closest approach reconstructed images. The filtered images exhibit reduced noise and enhanced precision when attempting to identify the presence of high-Z materials. The average precision from the point of closest approach reconstruction method is 13 %; for the integrated method, 88 %. The filtered image, therefore, results in a seven-fold improvement in precision compared to the point of closest approach reconstructed image.
A combinational fast algorithm for image reconstruction
International Nuclear Information System (INIS)
Wu Zhongquan
1987-01-01
A combinational fast algorithm has been developed in order to increase the speed of reconstruction. First, an interpolation method based on B-spline functions is used in image reconstruction. Next, the influence of the boundary conditions assumed here on the interpolation of filtered projections and on the image reconstruction is discussed. It is shown that this boundary condition has almost no influence on the image in the central region of the image space, because the error of interpolation rapidly decreases by a factor of ten in shifting two pixels from the edge toward the center. In addition, a fast algorithm for computing the detecting angle has been used with the mentioned interpolation algorithm, and the cost for detecting angle computaton is reduced by a factor of two. The implementation results show that in the same subjective and objective fidelity, the computational cost for the interpolation using this algorithm is about one-twelfth of the conventional algorithm
Brunner, Stephen; Nett, Brian E; Tolakanahalli, Ranjini; Chen, Guang-Hong
2011-02-21
X-ray scatter is a significant problem in cone-beam computed tomography when thicker objects and larger cone angles are used, as scattered radiation can lead to reduced contrast and CT number inaccuracy. Advances have been made in x-ray computed tomography (CT) by incorporating a high quality prior image into the image reconstruction process. In this paper, we extend this idea to correct scatter-induced shading artifacts in cone-beam CT image-guided radiation therapy. Specifically, this paper presents a new scatter correction algorithm which uses a prior image with low scatter artifacts to reduce shading artifacts in cone-beam CT images acquired under conditions of high scatter. The proposed correction algorithm begins with an empirical hypothesis that the target image can be written as a weighted summation of a series of basis images that are generated by raising the raw cone-beam projection data to different powers, and then, reconstructing using the standard filtered backprojection algorithm. The weight for each basis image is calculated by minimizing the difference between the target image and the prior image. The performance of the scatter correction algorithm is qualitatively and quantitatively evaluated through phantom studies using a Varian 2100 EX System with an on-board imager. Results show that the proposed scatter correction algorithm using a prior image with low scatter artifacts can substantially mitigate scatter-induced shading artifacts in both full-fan and half-fan modes.
Robust linearized image reconstruction for multifrequency EIT of the breast.
Boverman, Gregory; Kao, Tzu-Jen; Kulkarni, Rujuta; Kim, Bong Seok; Isaacson, David; Saulnier, Gary J; Newell, Jonathan C
2008-10-01
Electrical impedance tomography (EIT) is a developing imaging modality that is beginning to show promise for detecting and characterizing tumors in the breast. At Rensselaer Polytechnic Institute, we have developed a combined EIT-tomosynthesis system that allows for the coregistered and simultaneous analysis of the breast using EIT and X-ray imaging. A significant challenge in EIT is the design of computationally efficient image reconstruction algorithms which are robust to various forms of model mismatch. Specifically, we have implemented a scaling procedure that is robust to the presence of a thin highly-resistive layer of skin at the boundary of the breast and we have developed an algorithm to detect and exclude from the image reconstruction electrodes that are in poor contact with the breast. In our initial clinical studies, it has been difficult to ensure that all electrodes make adequate contact with the breast, and thus procedures for the use of data sets containing poorly contacting electrodes are particularly important. We also present a novel, efficient method to compute the Jacobian matrix for our linearized image reconstruction algorithm by reducing the computation of the sensitivity for each voxel to a quadratic form. Initial clinical results are presented, showing the potential of our algorithms to detect and localize breast tumors.
International Nuclear Information System (INIS)
Bastarrika, Gorka; Arraiza, Maria; Pueyo, Jesus C.; Cecco, Carlo N. de; Ubilla, Matias; Mastrobuoni, Stefano; Rabago, Gregorio
2008-01-01
The image quality and optimal reconstruction interval for coronary arteries in heart transplant recipients undergoing non-invasive dual-source computed tomography (DSCT) coronary angiography was evaluated. Twenty consecutive heart transplant recipients who underwent DSCT coronary angiography were included (19 male, one female; mean age 63.1±10.7 years). Data sets were reconstructed in 5% steps from 30% to 80% of the R-R interval. Two blinded independent observers assessed the image quality of each coronary segments using a five-point scale (from 0 = not evaluative to 4=excellent quality). A total of 289 coronary segments in 20 heart transplant recipients were evaluated. Mean heart rate during the scan was 89.1±10.4 bpm. At the best reconstruction interval, diagnostic image quality (score ≥2) was obtained in 93.4% of the coronary segments (270/289) with a mean image quality score of 3.04± 0.63. Systolic reconstruction intervals provided better image quality scores than diastolic reconstruction intervals (overall mean quality scores obtained with the systolic and diastolic reconstructions 3.03±1.06 and 2.73±1.11, respectively; P<0.001). Different systolic reconstruction intervals (35%, 40%, 45% of RR interval) did not yield to significant differences in image quality scores for the coronary segments (P=0.74). Reconstructions obtained at the systolic phase of the cardiac cycle allowed excellent diagnostic image quality coronary angiograms in heart transplant recipients undergoing DSCT coronary angiography. (orig.)
International Nuclear Information System (INIS)
Wang, Jinguo; Zhao, Zhiqin; Song, Jian; Chen, Guoping; Nie, Zaiping; Liu, Qing-Huo
2015-01-01
Purpose: An iterative reconstruction method has been previously reported by the authors of this paper. However, the iterative reconstruction method was demonstrated by solely using the numerical simulations. It is essential to apply the iterative reconstruction method to practice conditions. The objective of this work is to validate the capability of the iterative reconstruction method for reducing the effects of acoustic heterogeneity with the experimental data in microwave induced thermoacoustic tomography. Methods: Most existing reconstruction methods need to combine the ultrasonic measurement technology to quantitatively measure the velocity distribution of heterogeneity, which increases the system complexity. Different to existing reconstruction methods, the iterative reconstruction method combines time reversal mirror technique, fast marching method, and simultaneous algebraic reconstruction technique to iteratively estimate the velocity distribution of heterogeneous tissue by solely using the measured data. Then, the estimated velocity distribution is used subsequently to reconstruct the highly accurate image of microwave absorption distribution. Experiments that a target placed in an acoustic heterogeneous environment are performed to validate the iterative reconstruction method. Results: By using the estimated velocity distribution, the target in an acoustic heterogeneous environment can be reconstructed with better shape and higher image contrast than targets that are reconstructed with a homogeneous velocity distribution. Conclusions: The distortions caused by the acoustic heterogeneity can be efficiently corrected by utilizing the velocity distribution estimated by the iterative reconstruction method. The advantage of the iterative reconstruction method over the existing correction methods is that it is successful in improving the quality of the image of microwave absorption distribution without increasing the system complexity
Yu, Baihui; Zhao, Ziran; Wang, Xuewu; Wu, Dufan; Zeng, Zhi; Zeng, Ming; Wang, Yi; Cheng, Jianping
2016-01-01
The Tsinghua University MUon Tomography facilitY (TUMUTY) has been built up and it is utilized to reconstruct the special objects with complex structure. Since fine image is required, the conventional Maximum likelihood Scattering and Displacement (MLSD) algorithm is employed. However, due to the statistical characteristics of muon tomography and the data incompleteness, the reconstruction is always instable and accompanied with severe noise. In this paper, we proposed a Maximum a Posterior (MAP) algorithm for muon tomography regularization, where an edge-preserving prior on the scattering density image is introduced to the object function. The prior takes the lp norm (p>0) of the image gradient magnitude, where p=1 and p=2 are the well-known total-variation (TV) and Gaussian prior respectively. The optimization transfer principle is utilized to minimize the object function in a unified framework. At each iteration the problem is transferred to solving a cubic equation through paraboloidal surrogating. To validate the method, the French Test Object (FTO) is imaged by both numerical simulation and TUMUTY. The proposed algorithm is used for the reconstruction where different norms are detailedly studied, including l2, l1, l0.5, and an l2-0.5 mixture norm. Compared with MLSD method, MAP achieves better image quality in both structure preservation and noise reduction. Furthermore, compared with the previous work where one dimensional image was acquired, we achieve the relatively clear three dimensional images of FTO, where the inner air hole and the tungsten shell is visible.
Correction for polychromatic aberration in computed tomography images
International Nuclear Information System (INIS)
Naparstek, A.
1979-01-01
A method and apparatus for correcting a computed tomography image for polychromatic aberration caused by the non-linear interaction (i.e. the energy dependent attenuation characteristics) of different body constituents, such as bone and soft tissue, with a polychromatic X-ray beam are described in detail. An initial image is conventionally computed from path measurements made as source and detector assembly scan a body section. In the improvement, each image element of the initial computed image representing attenuation is recorded in a store and is compared with two thresholds, one representing bone and the other soft tissue. Depending on the element value relative to the thresholds, a proportion of the respective constituent is allocated to that element location and corresponding bone and soft tissue projections are determined and stored. An error projection generator calculates projections of polychromatic aberration errors in the raw image data from recalled bone and tissue projections using a multidimensional polynomial function which approximates the non-linear interaction involved. After filtering, these are supplied to an image reconstruction computer to compute image element correction values which are subtracted from raw image element values to provide a corrected reconstructed image for display. (author)
Pragmatic fully 3D image reconstruction for the MiCES mouse imaging PET scanner
International Nuclear Information System (INIS)
Lee, Kisung; Kinahan, Paul E; Fessler, Jeffrey A; Miyaoka, Robert S; Janes, Marie; Lewellen, Tom K
2004-01-01
We present a pragmatic approach to image reconstruction for data from the micro crystal elements system (MiCES) fully 3D mouse imaging positron emission tomography (PET) scanner under construction at the University of Washington. Our approach is modelled on fully 3D image reconstruction used in clinical PET scanners, which is based on Fourier rebinning (FORE) followed by 2D iterative image reconstruction using ordered-subsets expectation-maximization (OSEM). The use of iterative methods allows modelling of physical effects (e.g., statistical noise, detector blurring, attenuation, etc), while FORE accelerates the reconstruction process by reducing the fully 3D data to a stacked set of independent 2D sinograms. Previous investigations have indicated that non-stationary detector point-spread response effects, which are typically ignored for clinical imaging, significantly impact image quality for the MiCES scanner geometry. To model the effect of non-stationary detector blurring (DB) in the FORE+OSEM(DB) algorithm, we have added a factorized system matrix to the ASPIRE reconstruction library. Initial results indicate that the proposed approach produces an improvement in resolution without an undue increase in noise and without a significant increase in the computational burden. The impact on task performance, however, remains to be evaluated
A photoacoustic tomography system for imaging of biological tissues
International Nuclear Information System (INIS)
Su Yixiong; Zhang Fan; Xu Kexin; Yao Jianquan; Wang, Ruikang K
2005-01-01
Non-invasive laser-induced photoacoustic tomography (PAT) is a promising imaging modality in the biomedical optical imaging field. This technology, based on the intrinsic optical properties of tissue and ultrasonic detection, overcomes the resolution disadvantage of pure-optical imaging caused by strong light scattering and the contrast and speckle disadvantages of pure ultrasonic imaging. Here, we report a PAT experimental system constructed in our laboratory. In our system, a Q-switched Nd : YAG pulse laser operated at 532 nm with a 8 ns pulse width is used to generate a photoacoustic signal. By using this system, the two-dimensional distribution of optical absorption in the tissue-mimicking phantom is reconstructed and has an excellent agreement with the original ones. The spatial resolution of the imaging system approaches 100 μm through about 4 cm of highly scattering medium
Three-dimensional reconstruction of functional brain images
International Nuclear Information System (INIS)
Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao
1999-01-01
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
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
International Nuclear Information System (INIS)
Stute, Simon
2010-01-01
Positron Emission Tomography (PET) is a medical imaging technique that plays a major role in oncology, especially using "1"8F-Fluoro-Deoxyglucose. However, PET images suffer from a modest spatial resolution and from high noise. As a result, there is still no consensus on how tumor metabolically active volume and tumor uptake should be characterized. In the meantime, research groups keep producing new methods for such characterizations that need to be assessed. A Monte Carlo simulation based method has been developed to produce simulated PET images of patients suffering from cancer, indistinguishable from clinical images, and for which all parameters are known. The method uses high resolution PET images from patient acquisitions, from which the physiological heterogeneous activity distribution can be modeled. It was shown that the performance of quantification methods on such highly realistic simulated images are significantly lower and more variable than using simple phantom studies. Fourteen different quantification methods were also compared in realistic conditions using a group of such simulated patients. In addition, the proposed method was extended to simulate serial PET scans in the context of patient monitoring, including a modeling of the tumor changes, as well as the variability over time of non-tumoral physiological activity distribution. Monte Carlo simulations were also used to study the detection probability inside the crystals of the tomograph. A model of the crystal response was derived and included in the system matrix involved in tomographic reconstruction. The resulting reconstruction method was compared with other sophisticated methods for modeling the detector response in the image space, proposed in the literature. We demonstrated the superiority of the proposed method over equivalent approaches on simulated data, and illustrated its robustness on clinical data. For a same noise level, it is possible to reconstruct PET images offering a
International Nuclear Information System (INIS)
Liu, J; Gao, H
2016-01-01
Purpose: Different from the conventional computed tomography (CT), spectral CT based on energy-resolved photon-counting detectors is able to provide the unprecedented material composition. However, an important missing piece for accurate spectral CT is to incorporate the detector response function (DRF), which is distorted by factors such as pulse pileup and charge-sharing. In this work, we propose material reconstruction methods for spectral CT with DRF. Methods: The polyenergetic X-ray forward model takes the DRF into account for accurate material reconstruction. Two image reconstruction methods are proposed: a direct method based on the nonlinear data fidelity from DRF-based forward model; a linear-data-fidelity based method that relies on the spectral rebinning so that the corresponding DRF matrix is invertible. Then the image reconstruction problem is regularized with the isotropic TV term and solved by alternating direction method of multipliers. Results: The simulation results suggest that the proposed methods provided more accurate material compositions than the standard method without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Conclusion: We have proposed material reconstruction methods for spectral CT with DRF, whichprovided more accurate material compositions than the standard methods without DRF. Moreover, the proposed method with linear data fidelity had improved reconstruction quality from the proposed method with nonlinear data fidelity. Jiulong Liu and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).
Projection model for flame chemiluminescence tomography based on lens imaging
Wan, Minggang; Zhuang, Jihui
2018-04-01
For flame chemiluminescence tomography (FCT) based on lens imaging, the projection model is essential because it formulates the mathematical relation between the flame projections captured by cameras and the chemiluminescence field, and, through this relation, the field is reconstructed. This work proposed the blurry-spot (BS) model, which takes more universal assumptions and has higher accuracy than the widely applied line-of-sight model. By combining the geometrical camera model and the thin-lens equation, the BS model takes into account perspective effect of the camera lens; by combining ray-tracing technique and Monte Carlo simulation, it also considers inhomogeneous distribution of captured radiance on the image plane. Performance of these two models in FCT was numerically compared, and results showed that using the BS model could lead to better reconstruction quality in wider application ranges.
Research of ART method in CT image reconstruction
International Nuclear Information System (INIS)
Li Zhipeng; Cong Peng; Wu Haifeng
2005-01-01
This paper studied Algebraic Reconstruction Technique (ART) in CT image reconstruction. Discussed the ray number influence on image quality. And the adopting of smooth method got high quality CT image. (authors)
GPU based Monte Carlo for PET image reconstruction: parameter optimization
International Nuclear Information System (INIS)
Cserkaszky, Á; Légrády, D.; Wirth, A.; Bükki, T.; Patay, G.
2011-01-01
This paper presents the optimization of a fully Monte Carlo (MC) based iterative image reconstruction of Positron Emission Tomography (PET) measurements. With our MC re- construction method all the physical effects in a PET system are taken into account thus superior image quality is achieved in exchange for increased computational effort. The method is feasible because we utilize the enormous processing power of Graphical Processing Units (GPUs) to solve the inherently parallel problem of photon transport. The MC approach regards the simulated positron decays as samples in mathematical sums required in the iterative reconstruction algorithm, so to complement the fast architecture, our work of optimization focuses on the number of simulated positron decays required to obtain sufficient image quality. We have achieved significant results in determining the optimal number of samples for arbitrary measurement data, this allows to achieve the best image quality with the least possible computational effort. Based on this research recommendations can be given for effective partitioning of computational effort into the iterations in limited time reconstructions. (author)
Tomographic image reconstruction and rendering with texture-mapping hardware
International Nuclear Information System (INIS)
Azevedo, S.G.; Cabral, B.K.; Foran, J.
1994-07-01
The image reconstruction problem, also known as the inverse Radon transform, for x-ray computed tomography (CT) is found in numerous applications in medicine and industry. The most common algorithm used in these cases is filtered backprojection (FBP), which, while a simple procedure, is time-consuming for large images on any type of computational engine. Specially-designed, dedicated parallel processors are commonly used in medical CT scanners, whose results are then passed to graphics workstation for rendering and analysis. However, a fast direct FBP algorithm can be implemented on modern texture-mapping hardware in current high-end workstation platforms. This is done by casting the FBP algorithm as an image warping operation with summing. Texture-mapping hardware, such as that on the Silicon Graphics Reality Engine (TM), shows around 600 times speedup of backprojection over a CPU-based implementation (a 100 Mhz R4400 in this case). This technique has the further advantages of flexibility and rapid programming. In addition, the same hardware can be used for both image reconstruction and for volumetric rendering. The techniques can also be used to accelerate iterative reconstruction algorithms. The hardware architecture also allows more complex operations than straight-ray backprojection if they are required, including fan-beam, cone-beam, and curved ray paths, with little or no speed penalties
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.
Energy Technology Data Exchange (ETDEWEB)
Chen, Xueli, E-mail: xlchen@xidian.edu.cn, E-mail: jimleung@mail.xidian.edu.cn; Yang, Defu; Zhang, Qitan; Liang, Jimin, E-mail: xlchen@xidian.edu.cn, E-mail: jimleung@mail.xidian.edu.cn [School of Life Science and Technology, Xidian University, Xi' an 710071 (China); Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education (China)
2014-05-14
Even though bioluminescence tomography (BLT) exhibits significant potential and wide applications in macroscopic imaging of small animals in vivo, the inverse reconstruction is still a tough problem that has plagued researchers in a related area. The ill-posedness of inverse reconstruction arises from insufficient measurements and modeling errors, so that the inverse reconstruction cannot be solved directly. In this study, an l{sub 1/2} regularization based numerical method was developed for effective reconstruction of BLT. In the method, the inverse reconstruction of BLT was constrained into an l{sub 1/2} regularization problem, and then the weighted interior-point algorithm (WIPA) was applied to solve the problem through transforming it into obtaining the solution of a series of l{sub 1} regularizers. The feasibility and effectiveness of the proposed method were demonstrated with numerical simulations on a digital mouse. Stability verification experiments further illustrated the robustness of the proposed method for different levels of Gaussian noise.
Le Moal, Julien; Peillon, Christophe; Dacher, Jean-Nicolas; Baste, Jean-Marc
2018-01-01
The objective of our pilot study was to assess if three-dimensional (3D) reconstruction performed by Visible Patient™ could be helpful for the operative planning, efficiency and safety of robot-assisted segmentectomy. Between 2014 and 2015, 3D reconstructions were provided by the Visible Patient™ online service and used for the operative planning of robotic segmentectomy. To obtain 3D reconstruction, the surgeon uploaded the anonymized computed tomography (CT) image of the patient to the secured Visible Patient™ server and then downloaded the model after completion. Nine segmentectomies were performed between 2014 and 2015 using a pre-operative 3D model. All 3D reconstructions met our expectations: anatomical accuracy (bronchi, arteries, veins, tumor, and the thoracic wall with intercostal spaces), accurate delimitation of each segment in the lobe of interest, margin resection, free space rotation, portability (smartphone, tablet) and time saving technique. We have shown that operative planning by 3D CT using Visible Patient™ reconstruction is useful in our practice of robot-assisted segmentectomy. The main disadvantage is the high cost. Its impact on reducing complications and improving surgical efficiency is the object of an ongoing study.
International Nuclear Information System (INIS)
Devaux, J.Y.; Mazelier, L.; Lefkopoulos, D.
1997-01-01
We have earlier shown that the method of singular value decomposition (SVD) allows the image reconstruction in single-photon-tomography with precision higher than the classical method of filtered back-projections. Actually, the establishing of an elementary response matrix which incorporates both the photon attenuation phenomenon, the scattering, the translation non-invariance principle and the detector response, allows to take into account the totality of physical parameters of acquisition. By an non-consecutive optimized truncation of the singular values we have obtained a significant improvement in the efficiency of the regularization of bad conditioning of this problem. The present study aims at verifying the stability of this truncation under modifications of acquisition conditions. Two series of parameters were tested, first, those modifying the geometry of acquisition: the influence of rotation center, the asymmetric disposition of the elementary-volume sources against the detector and the precision of rotation angle, and secondly, those affecting the correspondence between the matrix and the space to be reconstructed: the effect of partial volume and a noise propagation in the experimental model. For the parameters which introduce a spatial distortion, the alteration of reconstruction has been, as expected, comparable to that observed with the classical reconstruction and proportional with the amplitude of shift from the normal one. In exchange, for the effect of partial volume and of noise, the study of truncation signature revealed a variation in the optimal choice of the conserved singular values but with no effect on the global precision of reconstruction
Approaches for improving image quality in magnetic induction tomography
International Nuclear Information System (INIS)
Maimaitijiang, Y; Roula, M A; Kahlert, J
2010-01-01
Magnetic induction tomography (MIT) is a contactless and non-invasive method for imaging the passive electrical properties of objects. Measuring the weak signal produced by eddy currents within biological soft tissues can be challenging in the presence of noise and the large signals resulting from the direct excitation–detection coil coupling. To detect haemorrhagic stroke in the brain, for instance, high measurement accuracy is required to enable images with enough contrast to differentiate between normal and haemorrhaged brain tissues. The reconstructed images are often very sensitive to inevitable measurement noise from the environment, system instabilities and patient-related artefacts such as movement and sweating. We propose methods for mitigating signal noise and improving image reconstruction. We evaluated and compared the use of a range wavelet transforms for signal denoising. Adaptive regularization methods including L-curve, generalized cross validation (GCV) and noise estimation were also compared. We evaluated all these described methods with measurements of in vitro tissues resembling a peripheral haemorrhagic cerebral stroke created by placing a bio-membrane package filled with 10 ml blood in a swine brain of 100 ml. We show that wavelet packet denoising combined with adaptive regularization can improve the quality of reconstructed images
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...... to the ill-posedness of the problem, the simple inversion of the degradation model does not give any good reconstructions. Therefore, to deal with the ill-posedness it is necessary to use some prior information on the solution or the model and the Bayesian approach. Additive Gaussian noise has been......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...
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...
Pinhole single-photon emission tomography reconstruction based on median root prior
International Nuclear Information System (INIS)
Sohlberg, Antti; Kuikka, Jyrki T.; Ruotsalainen, Ulla
2003-01-01
The maximum likelihood expectation maximisation (ML-EM) algorithm can be used to reduce reconstruction artefacts produced by filtered backprojection (FBP) methods in pinhole single-photon emission tomography (SPET). However, ML-EM suffers from noise propagation along iterations, which leads to quantitatively unpleasant reconstruction results. To avoid this increase in noise, the median root prior (MRP) algorithm for pinhole SPET was implemented. Projection data of a line source and Picker's thyroid phantom were collected using a single-head gamma camera with a pinhole collimator. MRP was added to existing pinhole ML-EM reconstruction algorithm and the phantom studies were reconstructed using MRP, ML-EM and FBP for comparison. Coefficients of variation, contrasts and full-widths at half-maximum were calculated and showed a clear reduction in noise without significant loss of resolution or decrease in contrast when MRP was applied. MRP also produced visually pleasing images even with high iteration numbers, free of the checkerboard-type noise patterns which are typical of ML-EM images. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Saha, Krishnendu [Ohio Medical Physics Consulting, Dublin, Ohio 43017 (United States); Straus, Kenneth J.; Glick, Stephen J. [Department of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655 (United States); Chen, Yu. [Department of Radiation Oncology, Columbia University, New York, New York 10032 (United States)
2014-08-28
To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.
Contemporary imaging: Magnetic resonance imaging, computed tomography, and interventional radiology
International Nuclear Information System (INIS)
Goldberg, H.I.; Higgins, C.; Ring, E.J.
1985-01-01
In addition to discussing the most recent advances in magnetic resonance imaging (MRI), computerized tomography (CT), and the vast array of interventional procedures, this book explores the appropriate clinical applications of each of these important modalities
Energy Technology Data Exchange (ETDEWEB)
Bouchet, F.
1996-09-25
The tomography by positron emission has for aim to explore an organ by injection of a radiotracer and bidimensional representation with processing techniques. The most used in routine is the filtered retro projection that gives smoothed images. this work realizes a comparative study of new techniques. The methods of preservations of contours are studied here, the idea is to use NMR imaging as a priori information. Two techniques of images construction are viewed more particularly: the resolution by pseudo inverse and the Bayesian method. (N.C.).
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
The SRT reconstruction algorithm for semiquantification in PET imaging
International Nuclear Information System (INIS)
Kastis, George A.; Gaitanis, Anastasios; Samartzis, Alexandros P.; Fokas, Athanasios S.
2015-01-01
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 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
Superfast maximum-likelihood reconstruction for quantum tomography
Shang, Jiangwei; Zhang, Zhengyun; Ng, Hui Khoon
2017-06-01
Conventional methods for computing maximum-likelihood estimators (MLE) often converge slowly in practical situations, leading to a search for simplifying methods that rely on additional assumptions for their validity. In this work, we provide a fast and reliable algorithm for maximum-likelihood reconstruction that avoids this slow convergence. Our method utilizes the state-of-the-art convex optimization scheme, an accelerated projected-gradient method, that allows one to accommodate the quantum nature of the problem in a different way than in the standard methods. We demonstrate the power of our approach by comparing its performance with other algorithms for n -qubit state tomography. In particular, an eight-qubit situation that purportedly took weeks of computation time in 2005 can now be completed in under a minute for a single set of data, with far higher accuracy than previously possible. This refutes the common claim that MLE reconstruction is slow and reduces the need for alternative methods that often come with difficult-to-verify assumptions. In fact, recent methods assuming Gaussian statistics or relying on compressed sensing ideas are demonstrably inapplicable for the situation under consideration here. Our algorithm can be applied to general optimization problems over the quantum state space; the philosophy of projected gradients can further be utilized for optimization contexts with general constraints.
2D and 3D reconstructions in acousto-electric tomography
Kuchment, Peter; Kunyansky, Leonid
2011-01-01
We propose and test stable algorithms for the reconstruction of the internal conductivity of a biological object using acousto-electric measurements. Namely, the conventional impedance tomography scheme is supplemented by scanning the object with acoustic waves that slightly perturb the conductivity and cause the change in the electric potential measured on the boundary of the object. These perturbations of the potential are then used as the data for the reconstruction of the conductivity. The present method does not rely on 'perfectly focused' acoustic beams. Instead, more realistic propagating spherical fronts are utilized, and then the measurements that would correspond to perfect focusing are synthesized. In other words, we use synthetic focusing. Numerical experiments with simulated data show that our techniques produce high-quality images, both in 2D and 3D, and that they remain accurate in the presence of high-level noise in the data. Local uniqueness and stability for the problem also hold. © 2011 IOP Publishing Ltd.
2D and 3D reconstructions in acousto-electric tomography
Kuchment, Peter
2011-04-18
We propose and test stable algorithms for the reconstruction of the internal conductivity of a biological object using acousto-electric measurements. Namely, the conventional impedance tomography scheme is supplemented by scanning the object with acoustic waves that slightly perturb the conductivity and cause the change in the electric potential measured on the boundary of the object. These perturbations of the potential are then used as the data for the reconstruction of the conductivity. The present method does not rely on \\'perfectly focused\\' acoustic beams. Instead, more realistic propagating spherical fronts are utilized, and then the measurements that would correspond to perfect focusing are synthesized. In other words, we use synthetic focusing. Numerical experiments with simulated data show that our techniques produce high-quality images, both in 2D and 3D, and that they remain accurate in the presence of high-level noise in the data. Local uniqueness and stability for the problem also hold. © 2011 IOP Publishing Ltd.
Petersen, T. C.; Ringer, S. P.
2010-03-01
Upon discerning the mere shape of an imaged object, as portrayed by projected perimeters, the full three-dimensional scattering density may not be of particular interest. In this situation considerable simplifications to the reconstruction problem are possible, allowing calculations based upon geometric principles. Here we describe and provide an algorithm which reconstructs the three-dimensional morphology of specimens from tilt series of images for application to electron tomography. Our algorithm uses a differential approach to infer the intersection of projected tangent lines with surfaces which define boundaries between regions of different scattering densities within and around the perimeters of specimens. Details of the algorithm implementation are given and explained using reconstruction calculations from simulations, which are built into the code. An experimental application of the algorithm to a nano-sized Aluminium tip is also presented to demonstrate practical analysis for a real specimen. Program summaryProgram title: STOMO version 1.0 Catalogue identifier: AEFS_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2988 No. of bytes in distributed program, including test data, etc.: 191 605 Distribution format: tar.gz Programming language: C/C++ Computer: PC Operating system: Windows XP RAM: Depends upon the size of experimental data as input, ranging from 200 Mb to 1.5 Gb Supplementary material: Sample output files, for the test run provided, are available. Classification: 7.4, 14 External routines: Dev-C++ ( http://www.bloodshed.net/devcpp.html) Nature of problem: Electron tomography of specimens for which conventional back projection may fail and/or data for which there is a limited angular
Ellis, Sam; Reader, Andrew J
2018-04-26
Many clinical contexts require the acquisition of multiple positron emission tomography (PET) scans of a single subject, for example to observe and quantify changes in functional behaviour in tumours after treatment in oncology. Typically, the datasets from each of these scans are reconstructed individually, without exploiting the similarities between them. We have recently shown that sharing information between longitudinal PET datasets by penalising voxel-wise differences during image reconstruction can improve reconstructed images by reducing background noise and increasing the contrast-to-noise ratio of high activity lesions. Here we present two additional novel longitudinal difference-image priors and evaluate their performance using 2D simulation studies and a 3D real dataset case study. We have previously proposed a simultaneous difference-image-based penalised maximum likelihood (PML) longitudinal image reconstruction method that encourages sparse difference images (DS-PML), and in this work we propose two further novel prior terms. The priors are designed to encourage longitudinal images with corresponding differences which have i) low entropy (DE-PML), and ii) high sparsity in their spatial gradients (DTV-PML). These two new priors and the originally proposed longitudinal prior were applied to 2D simulated treatment response [ 18 F]fluorodeoxyglucose (FDG) brain tumour datasets and compared to standard maximum likelihood expectation-maximisation (MLEM) reconstructions. These 2D simulation studies explored the effects of penalty strengths, tumour behaviour, and inter-scan coupling on reconstructed images. Finally, a real two-scan longitudinal data series acquired from a head and neck cancer patient was reconstructed with the proposed methods and the results compared to standard reconstruction methods. Using any of the three priors with an appropriate penalty strength produced images with noise levels equivalent to those seen when using standard
Clinical applications of imaging reconstruction by virtual sonography
International Nuclear Information System (INIS)
Mori, Akihiro; Oohashi, Noritsugu; Maruyama, Takako; Tatebe, Hideharu; Fushimi, Nobutoshi; Asano, Takayuki; Inoue, Hiroshi; Okuno, Masataka
2008-01-01
One of the pitfalls in managing multiple liver tumors is the difficulty in identifying individual tumors on ultrasonography. Computed tomography (CT)-assisted virtual sonography has been shown to improve sonographic diagnosis, however it requires additional equipment and software. We have developed a simple reconstruction method of virtual sonography (SRVS). We reconstructed SRVS mimicking ultrasonographic images, utilizing a workstation software attached to a multi-detector row CT system without any additional program. We have performed SRVS in 32 patients with 41 liver tumors that could hardly be identify on ultrasonography. SRVS assisted the identification of malignant form non-pathologic ones and thereby contributed to the appropriate clinical strategy including radiofrequency ablation (RFA) (18 tumors), liver biopsy (2 tumors), other therapies (4 tumors) and follow-up (17 tumors). We have developed virtual sonography using conventional CT software. SRVS seems useful in the clinical practice in managing liver tumors. (author)
On an image reconstruction method for ECT
Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro
2007-04-01
An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.
Cone Beam X-Ray Luminescence Tomography Imaging Based on KA-FEM Method for Small Animals.
Chen, Dongmei; Meng, Fanzhen; Zhao, Fengjun; Xu, Cao
2016-01-01
Cone beam X-ray luminescence tomography can realize fast X-ray luminescence tomography imaging with relatively low scanning time compared with narrow beam X-ray luminescence tomography. However, cone beam X-ray luminescence tomography suffers from an ill-posed reconstruction problem. First, the feasibility of experiments with different penetration and multispectra in small animal has been tested using nanophosphor material. Then, the hybrid reconstruction algorithm with KA-FEM method has been applied in cone beam X-ray luminescence tomography for small animals to overcome the ill-posed reconstruction problem, whose advantage and property have been demonstrated in fluorescence tomography imaging. The in vivo mouse experiment proved the feasibility of the proposed method.
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.
Image characterization metrics for muon tomography
Luo, Weidong; Lehovich, Andre; Anashkin, Edward; Bai, Chuanyong; Kindem, Joel; Sossong, Michael; Steiger, Matt
2014-05-01
Muon tomography uses naturally occurring cosmic rays to detect nuclear threats in containers. Currently there are no systematic image characterization metrics for muon tomography. We propose a set of image characterization methods to quantify the imaging performance of muon tomography. These methods include tests of spatial resolution, uniformity, contrast, signal to noise ratio (SNR) and vertical smearing. Simulated phantom data and analysis methods were developed to evaluate metric applicability. Spatial resolution was determined as the FWHM of the point spread functions in X, Y and Z axis for 2.5cm tungsten cubes. Uniformity was measured by drawing a volume of interest (VOI) within a large water phantom and defined as the standard deviation of voxel values divided by the mean voxel value. Contrast was defined as the peak signals of a set of tungsten cubes divided by the mean voxel value of the water background. SNR was defined as the peak signals of cubes divided by the standard deviation (noise) of the water background. Vertical smearing, i.e. vertical thickness blurring along the zenith axis for a set of 2 cm thick tungsten plates, was defined as the FWHM of vertical spread function for the plate. These image metrics provided a useful tool to quantify the basic imaging properties for muon tomography.
Vector tomography for reconstructing electric fields with non-zero divergence in bounded domains
Koulouri, Alexandra; Brookes, Mike; Rimpiläinen, Ville
2017-01-01
In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along the integration lines and are called the longitudinal and transverse measurements, respectively. In most cases, however, the transverse measurements cannot be physically acquired. Therefore, the VT methods are typically used to reconstruct divergence-free (or source-free) velocity and flow fields that can be reconstructed solely from the longitudinal measurements. In this paper, we show how vector fields with non-zero divergence in a bounded domain can also be reconstructed from the longitudinal measurements without the need of explicitly evaluating the transverse measurements. To the best of our knowledge, VT has not previously been used for this purpose. In particular, we study low-frequency, time-harmonic electric fields generated by dipole sources in convex bounded domains which arise, for example, in electroencephalography (EEG) source imaging. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modeling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field.