WorldWideScience

Sample records for sart-type image reconstruction

  1. 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...

  2. Trajectory Auto-Corrected image reconstruction.

    Science.gov (United States)

    Ianni, Julianna D; Grissom, William A

    2016-09-01

    To estimate k-space trajectory errors in non-Cartesian acquisitions and reconstruct distortion-free images, without trajectory measurements or gradient calibrations. The Trajectory Auto-Corrected image Reconstruction method jointly estimates k-space trajectory errors and images, based on SENSE and SPIRiT parallel imaging reconstruction. The underlying idea is that parallel imaging and oversampling in the center of k-space provides data redundancy that can be exploited to simultaneously reconstruct images and correct trajectory errors. Trajectory errors are represented as weighted sums of trajectory-dependent error basis functions, the coefficients of which are estimated using gradient-based optimization. Trajectory Auto-Corrected image Reconstruction was applied to reconstruct images and errors in golden angle radial, center-out radial, and spiral in vivo 7 Tesla brain acquisitions in five subjects. Compared to reconstructions using nominal trajectories, Trajectory auto-corrected image reconstructions contained considerably less blurring and streaking and were of similar quality to images reconstructed using measured k-space trajectories in the center-out radial and spiral cases. Reconstruction cost function reductions and improvements in normalized image gradient squared were also similar to those for images reconstructed using measured trajectories. Trajectory Auto-Corrected image Reconstruction enables non-Cartesian image reconstructions free from trajectory errors without the need for separate gradient calibrations or trajectory measurements. Magn Reson Med 76:757-768, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  3. Method for position emission mammography image reconstruction

    Science.gov (United States)

    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.

  4. Phase-constrained parallel MR image reconstruction.

    Science.gov (United States)

    Willig-Onwuachi, Jacob D; Yeh, Ernest N; Grant, Aaron K; Ohliger, Michael A; McKenzie, Charles A; Sodickson, Daniel K

    2005-10-01

    A generalized method for phase-constrained parallel MR image reconstruction is presented that combines and extends the concepts of partial-Fourier reconstruction and parallel imaging. It provides a framework for reconstructing images employing either or both techniques and for comparing image quality achieved by varying k-space sampling schemes. The method can be used as a parallel image reconstruction with a partial-Fourier reconstruction built in. It can also be used with trajectories not readily handled by straightforward combinations of partial-Fourier and SENSE-like parallel reconstructions, including variable-density, and non-Cartesian trajectories. The phase constraint specifies a better-conditioned inverse problem compared to unconstrained parallel MR reconstruction alone. This phase-constrained parallel MRI reconstruction offers a one-step alternative to the standard combination of homodyne and SENSE reconstructions with the added benefit of flexibility of sampling trajectory. The theory of the phase-constrained approach is outlined, and its calibration requirements and limitations are discussed. Simulations, phantom experiments, and in vivo experiments are presented.

  5. Sparse Image Reconstruction in Computed Tomography

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Sauer

    (CS), have shown significant empirical potential for this purpose. For example, total variation regularized image reconstruction has been shown in some cases to allow reducing x-ray exposure by a factor of 10 or more, while maintaining or even improving image quality compared to conventional...... and limitations of sparse reconstruction methods in CT, in particular in a quantitative sense. For example, relations between image properties such as contrast, structure and sparsity, tolerable noise levels, suficient sampling levels, the choice of sparse reconstruction formulation and the achievable image...... 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...

  6. Thermographic image reconstruction using ultrasound reconstruction from virtual waves

    CERN Document Server

    Burgholzer, Peter; Gruber, Jürgen; Mayr, Günther

    2016-01-01

    Reconstruction of subsurface features from ultrasound signals measured on the surface is widely used in medicine and non-destructive testing. In this work, we introduce a concept how to use image reconstruction methods known from ultrasonic imaging for thermographic signals, i.e. on the measured temperature evolution on a sample surface. Before using these imaging methods a virtual signal is calculated by applying a transformation to the measured temperature evolution. The virtual signal is calculated locally for every detection point and has the same initial temperature distribution as the measured signal, but is a solution of the wave equation. The introduced transformation can be used for every shape of the detection surface and in every dimension. It describes all the irreversibility of the heat diffusion, which is responsible that the spatial resolution gets worse with increasing depth. Up to now, for thermographic imaging mostly one-dimensional methods, e.g., for depth-profiling were used, which are sui...

  7. Speeding up image reconstruction in computed tomography

    CERN Multimedia

    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...

  8. Building Reconstruction Using DSM and Orthorectified Images

    National Research Council Canada - National Science Library

    Hossein Arefi; Peter Reinartz

    2013-01-01

      High resolution Digital Surface Models (DSMs) produced from airborne laser-scanning or stereo satellite images provide a very useful source of information for automated 3D building reconstruction...

  9. Image Reconstruction for Prostate Specific Nuclear Medicine imagers

    Energy Technology Data Exchange (ETDEWEB)

    Mark Smith

    2007-01-11

    There is increasing interest in the design and construction of nuclear medicine detectors for dedicated prostate imaging. These include detectors designed for imaging the biodistribution of radiopharmaceuticals labeled with single gamma as well as positron-emitting radionuclides. New detectors and acquisition geometries present challenges and opportunities for image reconstruction. In this contribution various strategies for image reconstruction for these special purpose imagers are reviewed. Iterative statistical algorithms provide a framework for reconstructing prostate images from a wide variety of detectors and acquisition geometries for PET and SPECT. The key to their success is modeling the physics of photon transport and data acquisition and the Poisson statistics of nuclear decay. Analytic image reconstruction methods can be fast and are useful for favorable acquisition geometries. Future perspectives on algorithm development and data analysis for prostate imaging are presented.

  10. Variable Weighted Ordered Subset Image Reconstruction Algorithm

    Directory of Open Access Journals (Sweden)

    Jinxiao Pan

    2006-01-01

    Full Text Available We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART to improve the algebraic reconstruction technique (ART and simultaneous algebraic reconstruction technique (SART and establish their convergence. In the two algorithms, the weighting varies with the geometrical direction of the ray. Experimental results with both numerical simulation and real CT data demonstrate that the VW-ART has a significant improvement in the quality of reconstructed images over ART and OS-SART. Moreover, both VW-ART and VW-OS-SART are more promising in convergence speed than the ART and SART, respectively.

  11. 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.

  12. Bayesian image reconstruction: Application to emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Nunez, J.; Llacer, J.

    1989-02-01

    In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.

  13. Homotopy Based Reconstruction from Acoustic Images

    DEFF Research Database (Denmark)

    Sharma, Ojaswa

    with known geometry. The results of the methods shown here can be used to gain objective knowledge about the reconstructed features. It is envisioned that due to the generic nature of the algorithms developed in this research, domains other than fisheries research can benefit from the reconstruction...... are reconstruction from an organised set of linear cross sections and reconstruction from an arbitrary set of linear cross sections. The first problem is looked upon in the context of acoustic signals wherein the cross sections show a definite geometric arrangement. A reconstruction in this case can take advantage...... of the inherent arrangement. The problem of reconstruction from arbitrary cross sections is a generic problem and is also shown to be solved here using the mathematical tool of continuous deformations. As part of a complete processing, segmentation using level set methods is explored for acoustic images and fast...

  14. 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...... in analogue-to-digital conversion, faulty memory locations in hardware. Cauchy noise is characterized by a very impulsive behaviour and it is mainly used to simulate atmospheric and underwater acoustic noise, in radar and sonar applications, biomedical images and synthetic aperture radar images. For both...... that the CM estimate outperforms the MAP estimate, when the error depends on Bregman distances. This PhD project can have many applications in the modern society, in fact the reconstruction of high quality images with less noise and more details enhances the image processing operations, such as edge detection...

  15. Iterative Reconstruction for Differential Phase Contrast Imaging

    NARCIS (Netherlands)

    Koehler, T.; Brendel, B.; Roessl, E.

    2011-01-01

    Purpose: The purpose of this work is to combine two areas of active research in tomographic x-ray imaging. The first one is the use of iterative reconstruction techniques. The second one is differential phase contrast imaging (DPCI). Method: We derive an SPS type maximum likelihood (ML)

  16. Reconstruction Algorithms in Undersampled AFM Imaging

    DEFF Research Database (Denmark)

    Arildsen, Thomas; Oxvig, Christian Schou; Pedersen, Patrick Steffen

    2016-01-01

    This paper provides a study of spatial undersampling in atomic force microscopy (AFM) imaging followed by different image reconstruction techniques based on sparse approximation as well as interpolation. The main reasons for using undersampling is that it reduces the path length and thereby the s...

  17. Focusing criterion in DHM image reconstruction

    Science.gov (United States)

    Mihailescu, M.; Mihale, N.; Popescu, R. C.; Acasandrei, A.; Paun, I. A.; Dinescu, M.; Scarlat, E.

    2015-02-01

    This study is presenting the theoretical approach and the practical results of a precise activity involved in the hologram reconstruction in order to find the optimally focused image of MG63 osteoblast-like cells cultivated on polymeric flat substrates. The morphology and dynamic of the cell is investigated by digital holographic microscopy (DHM) technique. The reconstruction is digitally performed using an algorithm based on the scalar theory of diffraction in the Fresnel approximation. The quality of the 3D images of the cells is crucially depending on the focusing capability of the reconstruction chain to fit the parameters of the optical recorder, particularly the focusing value. Our proposal to find the focused image is based on the images decomposition on gray levels and their histogram analysis. More precisely the focusing criterion is based on the evaluation of the form of this distribution.

  18. Techniques in Iterative Proton CT Image Reconstruction

    CERN Document Server

    Penfold, Scott

    2015-01-01

    This is a review paper on some of the physics, modeling, and iterative algorithms in proton computed tomography (pCT) image reconstruction. The primary challenge in pCT image reconstruction lies in the degraded spatial resolution resulting from multiple Coulomb scattering within the imaged object. Analytical models such as the most likely path (MLP) have been proposed to predict the scattered trajectory from measurements of individual proton location and direction before and after the object. Iterative algorithms provide a flexible tool with which to incorporate these models into image reconstruction. The modeling leads to a large and sparse linear system of equations that can efficiently be solved by projection methods-based iterative algorithms. Such algorithms perform projections of the iterates onto the hyperlanes that are represented by the linear equations of the system. They perform these projections in possibly various algorithmic structures, such as block-iterative projections (BIP), string-averaging...

  19. 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.

  20. 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz

    1999-01-01

    The aim of this project has been to implement a software system, that is able to create a 3-D reconstruction from two or more 2-D photographic images made from different positions. The height is determined from the disparity difference of the images. The general purpose of the system is mapping o......, where various methods have been tested in order to optimize the performance. The match results are used in the reconstruction part to establish a 3-D digital representation and finally, different presentation forms are discussed....

  1. Image Reconstruction Image reconstruction by using local inverse for full field of view

    CERN Document Server

    Yang, Kang; Yang, Xintie; Zhao, Shuang-Ren

    2015-01-01

    The iterative refinement method (IRM) has been very successfully applied in many different fields for examples the modern quantum chemical calculation and CT image reconstruction. It is proved that the refinement method can create an exact inverse from an approximate inverse with a few iterations. The IRM has been used in CT image reconstruction to lower the radiation dose. The IRM utilize the errors between the original measured data and the recalculated data to correct the reconstructed images. However if it is not smooth inside the object, there often is an over-correction along the boundary of the organs in the reconstructed images. The over-correction increase the noises especially on the edges inside the image. One solution to reduce the above mentioned noises is using some kind of filters. Filtering the noise before/after/between the image reconstruction processing. However filtering the noises also means reduce the resolution of the reconstructed images. The filtered image is often applied to the imag...

  2. Image Superresolution Reconstruction via Granular Computing Clustering

    Directory of Open Access Journals (Sweden)

    Hongbing Liu

    2014-01-01

    Full Text Available The problem of generating a superresolution (SR image from a single low-resolution (LR input image is addressed via granular computing clustering in the paper. Firstly, and the training images are regarded as SR image and partitioned into some SR patches, which are resized into LS patches, the training set is composed of the SR patches and the corresponding LR patches. Secondly, the granular computing (GrC clustering is proposed by the hypersphere representation of granule and the fuzzy inclusion measure compounded by the operation between two granules. Thirdly, the granule set (GS including hypersphere granules with different granularities is induced by GrC and used to form the relation between the LR image and the SR image by lasso. Experimental results showed that GrC achieved the least root mean square errors between the reconstructed SR image and the original image compared with bicubic interpolation, sparse representation, and NNLasso.

  3. Quantitative thermoacoustic image reconstruction of conductivity profiles

    Science.gov (United States)

    Ogunlade, Olumide; Cox, Ben; Beard, Paul

    2012-02-01

    A numerical inversion scheme for recovering a map of the absolute conductivity from the absorbed power density map that is conventionally reconstructed in thermacoustic imaging is described. This offers the prospect of obtaining an image that is more closely related to the underlying tissue structure and physiology. The inversion scheme employs a full 3D full wave model of electromagnetic propagation in tissue which is iteratively fitted to the measured absorbed power density map using a simple recursive method. The reconstruction is demonstrated numerically using three examples of absorbers of varying geometries, tissue realistic complex permittivity values and noise. In these examples, the reconstruction is shown to rapidly converge to within good estimates of the true conductivity in less than 20 iterations.

  4. Image reconstruction for bioluminescence tomography

    Science.gov (United States)

    Jiang, Ming; Wang, Ge

    2004-10-01

    Motivated by bioluminescent imaging needs for studies on gene therapy and other applications in the mouse models, a bioluminescence tomography (BLT) system is being developed by our group. While the forward imaging model is described by the diffusion approximation, BLT is the inverse problem to recover an internal bioluminescent source distribution subject to Cauchy data for the diffusion equation. This inverse source problem is ill-posed and does not yield the unique solution in the general case. The uniqueness problem under practical constraints was recently studied by our group. It was found that all the inverse source solutions can be expressed as the unique minimal energy source solution plus a nonradiating source. We demonstrate that the minimal energy source solution is not physically favorable for bioluminescence tomography, although the minimal energy constraint is utilized in other applications. To find a physically meaningful unique solution, adequate prior knowledge must be utilized. Here we propose two iterative approaches in this work. The first one is a variant of the well-known EM algorithm. The second one is based on the Landweber scheme. Either of the methods is suitable for incorporating knowledge-based constraints. We discuss several issues related to the implementation of these methods, including the initial guess and stopping criteria. Also, we report our numerical simulation results to demonstrate the feasibility of bioluminescence tomography.

  5. Undersampled MR Image Reconstruction with Data-Driven Tight Frame

    National Research Council Canada - National Science Library

    Liu, Jianbo; Wang, Shanshan; Peng, Xi; Liang, Dong

    2015-01-01

    .... With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method...

  6. Performance-based assessment of reconstructed images

    Energy Technology Data Exchange (ETDEWEB)

    Hanson, Kenneth [Los Alamos National Laboratory

    2009-01-01

    During the early 90s, I engaged in a productive and enjoyable collaboration with Robert Wagner and his colleague, Kyle Myers. We explored the ramifications of the principle that tbe quality of an image should be assessed on the basis of how well it facilitates the performance of appropriate visual tasks. We applied this principle to algorithms used to reconstruct scenes from incomplete and/or noisy projection data. For binary visual tasks, we used both the conventional disk detection and a new challenging task, inspired by the Rayleigh resolution criterion, of deciding whether an object was a blurred version of two dots or a bar. The results of human and machine observer tests were summarized with the detectability index based on the area under the ROC curve. We investigated a variety of reconstruction algorithms, including ART, with and without a nonnegativity constraint, and the MEMSYS3 algorithm. We concluded that the performance of the Raleigh task was optimized when the strength of the prior was near MEMSYS's default 'classic' value for both human and machine observers. A notable result was that the most-often-used metric of rms error in the reconstruction was not necessarily indicative of the value of a reconstructed image for the purpose of performing visual tasks.

  7. Reconstructing building mass models from UAV images

    KAUST Repository

    Li, Minglei

    2015-07-26

    We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.

  8. Image-reconstruction methods in positron tomography

    CERN Document Server

    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...

  9. Building Reconstruction Using DSM and Orthorectified Images

    Directory of Open Access Journals (Sweden)

    Peter Reinartz

    2013-04-01

    Full Text Available High resolution Digital Surface Models (DSMs produced from airborne laser-scanning or stereo satellite images provide a very useful source of information for automated 3D building reconstruction. In this paper an investigation is reported about extraction of 3D building models from high resolution DSMs and orthorectified images produced from Worldview-2 stereo satellite imagery. The focus is on the generation of 3D models of parametric building roofs, which is the basis for creating Level Of Detail 2 (LOD2 according to the CityGML standard. In particular the building blocks containing several connected buildings with tilted roofs are investigated and the potentials and limitations of the modeling approach are discussed. The edge information extracted from orthorectified image has been employed as additional source of information in 3D reconstruction algorithm. A model driven approach based on the analysis of the 3D points of DSMs in a 2D projection plane is proposed. Accordingly, a building block is divided into smaller parts according to the direction and number of existing ridge lines for parametric building reconstruction. The 3D model is derived for each building part, and finally, a complete parametric model is formed by merging the 3D models of the individual building parts and adjusting the nodes after the merging step. For the remaining building parts that do not contain ridge lines, a prismatic model using polygon approximation of the corresponding boundary pixels is derived and merged to the parametric models to shape the final model of the building. A qualitative and quantitative assessment of the proposed method for the automatic reconstruction of buildings with parametric roofs is then provided by comparing the final model with the existing surface model as well as some field measurements.

  10. Structure Assisted Compressed Sensing Reconstruction of Undersampled AFM Images

    DEFF Research Database (Denmark)

    Oxvig, Christian Schou; Arildsen, Thomas; Larsen, Torben

    2017-01-01

    of the full image of it, and then use advanced computational techniques to reconstruct the remaining part of the image whenever this is possible. Our initial experiments have shown that it is possible to leverage inherent structure in acquired AFM images to improve image reconstruction. Thus, we have studied...... structure in the discrete cosine transform coefficients of typical AFM images. Based on this study, we propose a generic support structure model that may be used to improve the quality of the reconstructed AFM images. Furthermore, we propose a modification to the established iterative thresholding...... reconstruction algorithms that enables the use of our proposed structure model in the reconstruction process. Through a large set of reconstructions, the general reconstruction capability improvement achievable using our structured model is shown both quantitatively and qualitatively. Specifically, our...

  11. Reconstruction of a ring applicator using CT imaging: impact of the reconstruction method and applicator orientation

    DEFF Research Database (Denmark)

    Hellebust, Taran Paulsen; Tanderup, Kari; Bergstrand, Eva Stabell

    2007-01-01

    in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method...... applicator set and six lead pellets representing dose points, was used. The phantom was CT scanned with the ring applicator at four different angles related to the image plane. In each scan the applicator was reconstructed by three methods: (1) direct reconstruction in each image (DR), (2) reconstruction...

  12. Prior image constrained image reconstruction in emerging computed tomography applications

    Science.gov (United States)

    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

  13. Cardiac Image Reconstruction via Nonlinear Motion Correction Based on Partial Angle Reconstructed Images.

    Science.gov (United States)

    Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom

    2017-05-01

    Even though the X-ray Computed Tomography (CT) scan is considered suitable for fast imaging, motion-artifact-free cardiac imaging is still an important issue, because the gantry rotation speed is not fast enough compared with the heart motion. To obtain a heart image with less motion artifacts, a motion estimation (ME) and motion compensation (MC) approach is usually adopted. In this paper, we propose an ME/MC algorithm that can estimate a nonlinear heart motion model from a sinogram with a rotation angle of less than 360°. In this algorithm, we first assume the heart motion to be nonrigid but linear, and thereby estimate an initial 4-D motion vector field (MVF) during a half rotation by using conjugate partial angle reconstructed images, as in our previous ME/MC algorithm. We then refine the MVF to determine a more accurate nonlinear MVF by maximizing the information potential of a motion-compensated image. Finally, MC is performed by incorporating the determined MVF into the image reconstruction process, and a time-resolved heart image is obtained. By using a numerical phantom, a physical cardiac phantom, and an animal data set, we demonstrate that the proposed algorithm can noticeably improve the image quality by reducing motion artifacts throughout the image.

  14. Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors

    Directory of Open Access Journals (Sweden)

    Stanley H. Chan

    2016-11-01

    Full Text Available A quanta image sensor (QIS is a class of single-photon imaging devices that measure light intensity using oversampled binary observations. Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal of image reconstruction is to recover the underlying image from these bits. In this paper, we present a non-iterative image reconstruction algorithm for QIS. Unlike existing reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising algorithm. By skipping the usual optimization procedure, we achieve orders of magnitude improvement in speed and even better image reconstruction quality. We validate the new algorithm on synthetic datasets, as well as real videos collected by one-bit single-photon avalanche diode (SPAD cameras.

  15. Regularized Image Reconstruction for Ultrasound Attenuation Transmission Tomography

    Directory of Open Access Journals (Sweden)

    I. Peterlik

    2008-06-01

    Full Text Available The paper is focused on ultrasonic transmission tomography as a potential medical imaging modality, namely for breast cancer diagnosis. Ultrasound attenuation coefficient is one of the tissue parameters which are related to the pathological tissue state. A technique to reconstruct images of attenuation distribution is presented. Furthermore, an alternative to the commonly used filtered backprojection or algebraic reconstruction techniques is proposed. It is based on regularization of the image reconstruction problem which imposes smoothness in the resulting images while preserving edges. The approach is analyzed on synthetic data sets. The results show that it stabilizes the image restoration by compensating for main sources of estimation errors in this imaging modality.

  16. Imaging, Reconstruction, And Display Of Corneal Topography

    Science.gov (United States)

    Klyce, Stephen D.; Wilson, Steven E.

    1989-12-01

    The cornea is the major refractive element in the eye; even minor surface distortions can produce a significant reduction in visual acuity. Standard clinical methods used to evaluate corneal shape include keratometry, which assumes the cornea is ellipsoidal in shape, and photokeratoscopy, which images a series of concentric light rings on the corneal surface. These methods fail to document many of the corneal distortions that can degrade visual acuity. Algorithms have been developed to reconstruct the three dimensional shape of the cornea from keratoscope images, and to present these data in the clinically useful display of color-coded contour maps of corneal surface power. This approach has been implemented on a new generation video keratoscope system (Computed Anatomy, Inc.) with rapid automatic digitization of the image rings by a rule-based approach. The system has found clinical use in the early diagnosis of corneal shape anomalies such as keratoconus and contact lens-induced corneal warpage, in the evaluation of cataract and corneal transplant procedures, and in the assessment of corneal refractive surgical procedures. Currently, ray tracing techniques are being used to correlate corneal surface topography with potential visual acuity in an effort to more fully understand the tolerances of corneal shape consistent with good vision and to help determine the site of dysfunction in the visually impaired.

  17. Model-Based Reconstructive Elasticity Imaging Using Ultrasound

    Directory of Open Access Journals (Sweden)

    Salavat R. Aglyamov

    2007-01-01

    Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

  18. Precision Pointing Reconstruction and Geometric Metadata Generation for Cassini Images

    Science.gov (United States)

    French, R. S.; Showalter, M. R.; Gordon, M. K.

    2017-06-01

    We are reconstructing accurate pointing for 400,000 images taken by Cassini at Saturn. The results will be provided to the public along with per-pixel metadata describing precise image contents such as geographical location and viewing geometry.

  19. 3D Reconstruction of NMR Images by LabVIEW

    Directory of Open Access Journals (Sweden)

    Peter IZAK

    2007-01-01

    Full Text Available This paper introduces the experiment of 3D reconstruction NMR images via virtual instrumentation - LabVIEW. The main idea is based on marching cubes algorithm and image processing implemented by module of Vision assistant. The two dimensional images shot by the magnetic resonance device provide information about the surface properties of human body. There is implemented algorithm which can be used for 3D reconstruction of magnetic resonance images in biomedical application.

  20. Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image

    OpenAIRE

    Jingyu Guo; Hongliang Qi; Yuan Xu; Zijia Chen; Shulong Li; Linghong Zhou

    2016-01-01

    Limited-angle computed tomography (CT) has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction performance but has not been studied deeply yet. In this work, we proposed to generate optimized initial image followed by total variation (TV) based iterative reconstruction considering the feature o...

  1. Undersampled MR Image Reconstruction with Data-Driven Tight Frame

    Directory of Open Access Journals (Sweden)

    Jianbo Liu

    2015-01-01

    Full Text Available Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.

  2. Undersampled MR Image Reconstruction with Data-Driven Tight Frame.

    Science.gov (United States)

    Liu, Jianbo; Wang, Shanshan; Peng, Xi; Liang, Dong

    2015-01-01

    Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.

  3. Optimization of the alpha image reconstruction - an iterative CT-image reconstruction with well-defined image quality metrics.

    Science.gov (United States)

    Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc

    2017-09-01

    Optimization of the AIR-algorithm for improved convergence and performance. The AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

  4. Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

    Energy Technology Data Exchange (ETDEWEB)

    Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc [German Cancer Research Center, Heidelberg (Germany).

    2017-10-01

    Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

  5. Algebraic Reconstruction Technique (ART) for parallel imaging reconstruction of undersampled radial data: Application to cardiac cine

    Science.gov (United States)

    Li, Shu; Chan, Cheong; Stockmann, Jason P.; Tagare, Hemant; Adluru, Ganesh; Tam, Leo K.; Galiana, Gigi; Constable, R. Todd; Kozerke, Sebastian; Peters, Dana C.

    2014-01-01

    Purpose To investigate algebraic reconstruction technique (ART) for parallel imaging reconstruction of radial data, applied to accelerated cardiac cine. Methods A GPU-accelerated ART reconstruction was implemented and applied to simulations, point spread functions (PSF) and in twelve subjects imaged with radial cardiac cine acquisitions. Cine images were reconstructed with radial ART at multiple undersampling levels (192 Nr x Np = 96 to 16). Images were qualitatively and quantitatively analyzed for sharpness and artifacts, and compared to filtered back-projection (FBP), and conjugate gradient SENSE (CG SENSE). Results Radial ART provided reduced artifacts and mainly preserved spatial resolution, for both simulations and in vivo data. Artifacts were qualitatively and quantitatively less with ART than FBP using 48, 32, and 24 Np, although FBP provided quantitatively sharper images at undersampling levels of 48-24 Np (all pART was comparable to CG SENSE. GPU-acceleration increased ART reconstruction speed 15-fold, with little impact on the images. Conclusion GPU-accelerated ART is an alternative approach to image reconstruction for parallel radial MR imaging, providing reduced artifacts while mainly maintaining sharpness compared to FBP, as shown by its first application in cardiac studies. PMID:24753213

  6. The use of imaging in patients post breast reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Sim, Y.T. [Department of Radiology, Glasgow Royal Infirmary, Glasgow (United Kingdom); Litherland, J.C., E-mail: Janet.Litherland@ggc.scot.nhs.uk [Department of Radiology, Glasgow Royal Infirmary, Glasgow (United Kingdom)

    2012-02-15

    Aim: To evaluate the usefulness of mammographic surveillance for asymptomatic patients and as a problem-solving tool in symptomatic patients with reconstructed breasts. Materials and methods: The imaging records over 4 years identified 227 patients with a history of breast reconstruction post-mastectomy due to cancer. Clinical and imaging records were reviewed to evaluate the use of imaging in the follow-up management of these patients. Results: Records showed that 116 (51%) of the patients identified underwent surveillance mammography of the reconstructed breast, in which one recurrent cancer was detected in an autologous tissue flap reconstruction (0.86% detection rate of non-palpable recurrent cancer), with a recall rate of 4%. One other patient had interval recurrence diagnosed following presentation with pain. Mammography of the contralateral breast only was performed in 111 patients. Fifty-four patients (24%) presented on 78 occasions with symptoms relating to the breast reconstructions, most commonly lump or swelling. Half of these patient episodes subsequently found no significant abnormality, and a further 29% had fat necrosis revealed on imaging. Four recurrent cancers were diagnosed. Conclusion: There is insufficient evidence for recommending routine surveillance mammography for non-palpable recurrent cancer in the reconstructed breasts. Ultrasound and mammography are useful imaging techniques in the assessment of reconstructed breasts in the symptomatic setting. Fat necrosis is the most common benign finding on mammograms of reconstructed breasts, both in the surveillance and symptomatic groups.

  7. Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image

    Directory of Open Access Journals (Sweden)

    Jingyu Guo

    2016-01-01

    Full Text Available Limited-angle computed tomography (CT has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction performance but has not been studied deeply yet. In this work, we proposed to generate optimized initial image followed by total variation (TV based iterative reconstruction considering the feature of image symmetry. The simulated data and real data reconstruction results indicate that the proposed method effectively removes the artifacts nearby edges.

  8. Simultaneous maximum a posteriori longitudinal PET image reconstruction

    Science.gov (United States)

    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.

  9. Surface Reconstruction and Image Enhancement via $L^1$-Minimization

    KAUST Repository

    Dobrev, Veselin

    2010-01-01

    A surface reconstruction technique based on minimization of the total variation of the gradient is introduced. Convergence of the method is established, and an interior-point algorithm solving the associated linear programming problem is introduced. The reconstruction algorithm is illustrated on various test cases including natural and urban terrain data, and enhancement oflow-resolution or aliased images. Copyright © by SIAM.

  10. Face reconstruction from image sequences for forensic face comparison

    NARCIS (Netherlands)

    van Dam, C.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2016-01-01

    The authors explore the possibilities of a dense model-free three-dimensional (3D) face reconstruction method, based on image sequences from a single camera, to improve the current state of forensic face comparison. They propose a new model-free 3D reconstruction method for faces, based on the

  11. Image reconstruction in an electro-holographic display

    Science.gov (United States)

    Son, Jung-Young; Son, Wook-Ho; Kim, Jae-Han; Choo, Hyongon

    2017-05-01

    The optical phenomena arising in the process of forming reconstructed images in a hologram are explained and shown visually with the use of light field images. The light fields at different distances from the hologram on a DMD reveal that the reconstructed image of each object point is formed by the corresponding Fresnel zone pattern, which is reconstructed from the hologram when it is illuminated by a reconstruction laser beam. The reconstructed image is a circle of least confusion laden with noise and distortion. It has a finite size and does not appear at the object distance from the hologram due to the presence of aberrations, especially that of a strong astigmatism. The astigmatism appears along the direction of the rotating axis of each pixel and its cross at right angles. The aberrations and noise are responsible for the distortion and deterioration of the resolution in the reconstructed image, the difference of the image position from that of the object, and a reduction in the depth resolution. The light field images also reveal intensity fluctuations due to the addition of the in- and out-phase of the rays from the hologram.

  12. Algorithms for Reconstruction of Undersampled Atomic Force Microscopy Images Supplementary Material

    DEFF Research Database (Denmark)

    2017-01-01

    Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods.......Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods....

  13. Reconstruction of a ring applicator using CT imaging: impact of the reconstruction method and applicator orientation

    Energy Technology Data Exchange (ETDEWEB)

    Hellebust, Taran Paulsen [Department of Medical Physics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Tanderup, Kari [Department of Oncology, Aarhus University Hospital, Aarhus (Denmark); Bergstrand, Eva Stabell [Department of Medical Physics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Knutsen, Bjoern Helge [Department of Medical Physics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Roeislien, Jo [Section of Biostatistics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Olsen, Dag Rune [Institute for Cancer Research, Rikshospital-Radiumhospital Medical Center, Oslo (Norway)

    2007-08-21

    The purpose of this study is to investigate whether the method of applicator reconstruction and/or the applicator orientation influence the dose calculation to points around the applicator for brachytherapy of cervical cancer with CT-based treatment planning. A phantom, containing a fixed ring applicator set and six lead pellets representing dose points, was used. The phantom was CT scanned with the ring applicator at four different angles related to the image plane. In each scan the applicator was reconstructed by three methods: (1) direct reconstruction in each image (DR) (2) reconstruction in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method was significantly lower (p < 0.05) than for the DR and MPR methods for all but two points. All applicator orientations had similar dose calculation reproducibility. Using library plans for applicator reconstruction gives the most reproducible dose calculation. However, with restrictive guidelines for applicator reconstruction the uncertainties for all methods are low compared to other factors influencing the accuracy of brachytherapy.

  14. Reconstruction of Optical Thickness from Hoffman Modulation Contrast Images

    DEFF Research Database (Denmark)

    Olsen, Niels Holm; Sporring, Jon; Nielsen, Mads

    2003-01-01

    Hoffman microscopy imaging systems are part of numerous fertility clinics world-wide. We discuss the physics of the Hoffman imaging system from optical thickness to image intensity, implement a simple, yet fast, reconstruction algorithm using Fast Fourier Transformation and discuss the usability...

  15. Compressed Sensing Inspired Image Reconstruction from Overlapped Projections

    Directory of Open Access Journals (Sweden)

    Lin Yang

    2010-01-01

    Full Text Available The key idea discussed in this paper is to reconstruct an image from overlapped projections so that the data acquisition process can be shortened while the image quality remains essentially uncompromised. To perform image reconstruction from overlapped projections, the conventional reconstruction approach (e.g., filtered backprojection (FBP algorithms cannot be directly used because of two problems. First, overlapped projections represent an imaging system in terms of summed exponentials, which cannot be transformed into a linear form. Second, the overlapped measurement carries less information than the traditional line integrals. To meet these challenges, we propose a compressive sensing-(CS- based iterative algorithm for reconstruction from overlapped data. This algorithm starts with a good initial guess, relies on adaptive linearization, and minimizes the total variation (TV. Then, we demonstrated the feasibility of this algorithm in numerical tests.

  16. Sparse magnetic resonance imaging reconstruction using the bregman iteration

    Science.gov (United States)

    Lee, Dong-Hoon; Hong, Cheol-Pyo; Lee, Man-Woo

    2013-01-01

    Magnetic resonance imaging (MRI) reconstruction needs many samples that are sequentially sampled by using phase encoding gradients in a MRI system. It is directly connected to the scan time for the MRI system and takes a long time. Therefore, many researchers have studied ways to reduce the scan time, especially, compressed sensing (CS), which is used for sparse images and reconstruction for fewer sampling datasets when the k-space is not fully sampled. Recently, an iterative technique based on the bregman method was developed for denoising. The bregman iteration method improves on total variation (TV) regularization by gradually recovering the fine-scale structures that are usually lost in TV regularization. In this study, we studied sparse sampling image reconstruction using the bregman iteration for a low-field MRI system to improve its temporal resolution and to validate its usefulness. The image was obtained with a 0.32 T MRI scanner (Magfinder II, SCIMEDIX, Korea) with a phantom and an in-vivo human brain in a head coil. We applied random k-space sampling, and we determined the sampling ratios by using half the fully sampled k-space. The bregman iteration was used to generate the final images based on the reduced data. We also calculated the root-mean-square-error (RMSE) values from error images that were obtained using various numbers of bregman iterations. Our reconstructed images using the bregman iteration for sparse sampling images showed good results compared with the original images. Moreover, the RMSE values showed that the sparse reconstructed phantom and the human images converged to the original images. We confirmed the feasibility of sparse sampling image reconstruction methods using the bregman iteration with a low-field MRI system and obtained good results. Although our results used half the sampling ratio, this method will be helpful in increasing the temporal resolution at low-field MRI systems.

  17. Robust sparse image reconstruction of radio interferometric observations with PURIFY

    Science.gov (United States)

    Pratley, Luke; McEwen, Jason D.; d'Avezac, Mayeul; Carrillo, Rafael E.; Onose, Alexandru; Wiaux, Yves

    2018-01-01

    Next-generation radio interferometers, such as the Square Kilometre Array, will revolutionize our understanding of the Universe through their unprecedented sensitivity and resolution. However, to realize these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions while providing a computational saving and an analytic form. Secondly, we apply PURIFY to real interferometric observations from the Very Large Array and the Australia Telescope Compact Array and find that images recovered by PURIFY are of higher quality than those recovered by CLEAN. Thirdly, we discuss how PURIFY reconstructions exhibit additional advantages over those recovered by CLEAN. The latest version of PURIFY, with developments presented in this work, is made publicly available.

  18. A review of GPU-based medical image reconstruction.

    Science.gov (United States)

    Després, Philippe; Jia, Xun

    2017-10-01

    Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines. This review paper focuses on recent developments made in GPU-based medical image reconstruction, from a CT, PET, SPECT, MRI and US perspective. Strategies and approaches to get the most out of GPUs in image reconstruction are presented as well as innovative applications arising from an increased computing capacity. The future of GPU-based image reconstruction is also envisioned, based on current trends in high-performance computing. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  19. Convergence of iterative image reconstruction algorithms for Digital Breast Tomosynthesis

    DEFF Research Database (Denmark)

    Sidky, Emil; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    solutions can aid in iterative image reconstruction algorithm design. This issue is particularly acute for iterative image reconstruction in Digital Breast Tomosynthesis (DBT), where the corresponding data model IS particularly poorly conditioned. The impact of this poor conditioning is that iterative......Most iterative image reconstruction algorithms are based on some form of optimization, such as minimization of a data-fidelity term plus an image regularizing penalty term. While achieving the solution of these optimization problems may not directly be clinically relevant, accurate optimization...... algorithms applied to this system can be slow to converge. Recent developments in first-order algorithms are now beginning to allow for accurate solutions to optimization problems of interest to tomographic imaging in general. In particular, we investigate an algorithm developed by Chambolle and Pock (2011 J...

  20. Application of Super-Resolution Image Reconstruction to Digital Holography

    Directory of Open Access Journals (Sweden)

    Zhang Shuqun

    2006-01-01

    Full Text Available We describe a new application of super-resolution image reconstruction to digital holography which is a technique for three-dimensional information recording and reconstruction. Digital holography has suffered from the low resolution of CCD sensors, which significantly limits the size of objects that can be recorded. The existing solution to this problem is to use optics to bandlimit the object to be recorded, which can cause the loss of details. Here super-resolution image reconstruction is proposed to be applied in enhancing the spatial resolution of digital holograms. By introducing a global camera translation before sampling, a high-resolution hologram can be reconstructed from a set of undersampled hologram images. This permits the recording of larger objects and reduces the distance between the object and the hologram. Practical results from real and simulated holograms are presented to demonstrate the feasibility of the proposed technique.

  1. Information Propagation in Prior-Image-Based Reconstruction.

    Science.gov (United States)

    Stayman, J Webster; Prince, Jerry L; Siewerdsen, Jeffrey H

    Advanced reconstruction methods for computed tomography include sophisticated forward models of the imaging system that capture the pertinent physical processes affecting the signal and noise in projection measurements. However, most do little to integrate prior knowledge of the subject - often relying only on very general notions of local smoothness or edges. In many cases, as in longitudinal surveillance or interventional imaging, a patient has undergone a sequence of studies prior to the current image acquisition that hold a wealth of prior information on patient-specific anatomy. While traditional techniques tend to treat each data acquisition as an isolated event and disregard such valuable patient-specific prior information, some reconstruction methods, such as PICCS[1] and PIR-PLE[2], can incorporate prior images into a reconstruction objective function. Inclusion of such information allows for dramatic reduction in the data fidelity requirements and more robustly accommodate substantial undersampling and exposure reduction with consequent benefits to imaging speed and reduced radiation dose. While such prior-image-based methods offer tremendous promise, the introduction of prior information in the reconstruction raises significant concern regarding the accurate representation of features in the image and whether those features arise from the current data acquisition or from the prior images. In this work we propose a novel framework to analyze the propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by the current data acquisition and by the prior image. This decomposition quantifies the contributions from prior and current data as a spatial map and can trace specific features in the image to their source. Such "information source maps" can potentially be used as a check on confidence that a given image feature arises from the current data or from the prior and to more quantitatively

  2. Proposal of fault-tolerant tomographic image reconstruction

    CERN Document Server

    Kudo, Hiroyuki; Yamazaki, Fukashi; Nemoto, Takuya

    2016-01-01

    This paper deals with tomographic image reconstruction under the situation where some of projection data bins are contaminated with abnormal data. Such situations occur in various instances of tomography. We propose a new reconstruction algorithm called the Fault-Tolerant reconstruction outlined as follows. The least-squares (L2-norm) error function ||Ax-b||_2^2 used in ordinary iterative reconstructions is sensitive to the existence of abnormal data. The proposed algorithm utilizes the L1-norm error function ||Ax-b||_1^1 instead of the L2-norm, and we develop a row-action-type iterative algorithm using the proximal splitting framework in convex optimization fields. We also propose an improved version of the L1-norm reconstruction called the L1-TV reconstruction, in which a weak Total Variation (TV) penalty is added to the cost function. Simulation results demonstrate that reconstructed images with the L2-norm were severely damaged by the effect of abnormal bins, whereas images with the L1-norm and L1-TV reco...

  3. Compressed Sensing MR Image Reconstruction Exploiting TGV and Wavelet Sparsity

    Directory of Open Access Journals (Sweden)

    Di Zhao

    2014-01-01

    Full Text Available Compressed sensing (CS based methods make it possible to reconstruct magnetic resonance (MR images from undersampled measurements, which is known as CS-MRI. The reference-driven CS-MRI reconstruction schemes can further decrease the sampling ratio by exploiting the sparsity of the difference image between the target and the reference MR images in pixel domain. Unfortunately existing methods do not work well given that contrast changes are incorrectly estimated or motion compensation is inaccurate. In this paper, we propose to reconstruct MR images by utilizing the sparsity of the difference image between the target and the motion-compensated reference images in wavelet transform and gradient domains. The idea is attractive because it requires neither the estimation of the contrast changes nor multiple times motion compensations. In addition, we apply total generalized variation (TGV regularization to eliminate the staircasing artifacts caused by conventional total variation (TV. Fast composite splitting algorithm (FCSA is used to solve the proposed reconstruction problem in order to improve computational efficiency. Experimental results demonstrate that the proposed method can not only reduce the computational cost but also decrease sampling ratio or improve the reconstruction quality alternatively.

  4. Compressed sensing MR image reconstruction exploiting TGV and wavelet sparsity.

    Science.gov (United States)

    Zhao, Di; Du, Huiqian; Han, Yu; Mei, Wenbo

    2014-01-01

    Compressed sensing (CS) based methods make it possible to reconstruct magnetic resonance (MR) images from undersampled measurements, which is known as CS-MRI. The reference-driven CS-MRI reconstruction schemes can further decrease the sampling ratio by exploiting the sparsity of the difference image between the target and the reference MR images in pixel domain. Unfortunately existing methods do not work well given that contrast changes are incorrectly estimated or motion compensation is inaccurate. In this paper, we propose to reconstruct MR images by utilizing the sparsity of the difference image between the target and the motion-compensated reference images in wavelet transform and gradient domains. The idea is attractive because it requires neither the estimation of the contrast changes nor multiple times motion compensations. In addition, we apply total generalized variation (TGV) regularization to eliminate the staircasing artifacts caused by conventional total variation (TV). Fast composite splitting algorithm (FCSA) is used to solve the proposed reconstruction problem in order to improve computational efficiency. Experimental results demonstrate that the proposed method can not only reduce the computational cost but also decrease sampling ratio or improve the reconstruction quality alternatively.

  5. Fast dictionary-based reconstruction for diffusion spectrum imaging.

    Science.gov (United States)

    Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F; Yendiki, Anastasia; Wald, Lawrence L; Adalsteinsson, Elfar

    2013-11-01

    Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.

  6. Towards nonlinear wave reconstruction and prediction from synthetic radar images

    NARCIS (Netherlands)

    Wijaya, Andreas Parama

    2016-01-01

    The use of remotely wave sensing by a marine radar is increasingly needed to provide wave information for the sake of safety and operational effectiveness in many offshore activities. Reconstruction of radar images needs to be carried out since radar images are a poor representation of the sea

  7. Pose Reconstruction of Flexible Instruments from Endoscopic Images using Markers

    NARCIS (Netherlands)

    Reilink, Rob; Stramigioli, Stefano; Misra, Sarthak

    2012-01-01

    A system is developed that can reconstruct the pose of flexible endoscopic instruments that are used in ad- vanced flexible endoscopes using solely the endoscopic images. Four markers are placed on the instrument, whose positions are measured in the image. These measurements are compared to a

  8. Gadgetron: An Open Source Framework for Medical Image Reconstruction

    DEFF Research Database (Denmark)

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-01-01

    with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its...

  9. Radioastronomical image reconstruction with regularized least squares

    NARCIS (Netherlands)

    Naghibzadeh, S.; Mouri Sardarabadi, A.; van der Veen, A.J.; Dong, Min; Zheng, Thomas Fang

    Image formation using the data from an array of sensors is a familiar problem in many fields such as radio astronomy, biomedical and geodetic imaging. The problem can be formulated as a least squares (LS) estimation problem and becomes ill-posed at high resolutions, i.e. large number of image

  10. 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...

  11. An imaging algorithm for vertex reconstruction for ATLAS Run-2

    CERN Document Server

    The ATLAS collaboration

    2015-01-01

    The reconstruction of vertices corresponding to proton--proton collisions in ATLAS is an essential element of event reconstruction used in many performance studies and physics analyses. During Run-1 of the LHC, ATLAS has employed an iterative approach to vertex finding. In order to improve the flexibility of the algorithm and ensure continued performance for very high numbers of simultaneous collisions in future LHC data taking, a new approach to seeding vertex finding is being developed inspired by image reconstruction techniques. This note provides a brief outline of how reconstructed tracks are used to create an image of likely vertex collisions in an event and presents some preliminary results of the performance of the algorithm in simulation approximating early Run-2 conditions.

  12. DCT and DST Based Image Compression for 3D Reconstruction

    Science.gov (United States)

    Siddeq, Mohammed M.; Rodrigues, Marcos A.

    2017-03-01

    This paper introduces a new method for 2D image compression whose quality is demonstrated through accurate 3D reconstruction using structured light techniques and 3D reconstruction from multiple viewpoints. The method is based on two discrete transforms: (1) A one-dimensional Discrete Cosine Transform (DCT) is applied to each row of the image. (2) The output from the previous step is transformed again by a one-dimensional Discrete Sine Transform (DST), which is applied to each column of data generating new sets of high-frequency components followed by quantization of the higher frequencies. The output is then divided into two parts where the low-frequency components are compressed by arithmetic coding and the high frequency ones by an efficient minimization encoding algorithm. At decompression stage, a binary search algorithm is used to recover the original high frequency components. The technique is demonstrated by compressing 2D images up to 99% compression ratio. The decompressed images, which include images with structured light patterns for 3D reconstruction and from multiple viewpoints, are of high perceptual quality yielding accurate 3D reconstruction. Perceptual assessment and objective quality of compression are compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results show that the proposed compression method is superior to both JPEG and JPEG2000 concerning 3D reconstruction, and with equivalent perceptual quality to JPEG2000.

  13. Probability of correct reconstruction in compressive spectral imaging

    Directory of Open Access Journals (Sweden)

    Samuel Eduardo Pinilla

    2016-08-01

    Full Text Available Coded Aperture Snapshot Spectral Imaging (CASSI systems capture the 3-dimensional (3D spatio-spectral information of a scene using a set of 2-dimensional (2D random coded Focal Plane Array (FPA measurements. A compressed sensing reconstruction algorithm is then used to recover the underlying spatio-spectral 3D data cube. The quality of the reconstructed spectral images depends exclusively on the CASSI sensing matrix, which is determined by the statistical structure of the coded apertures. The Restricted Isometry Property (RIP of the CASSI sensing matrix is used to determine the probability of correct image reconstruction and provides guidelines for the minimum number of FPA measurement shots needed for image reconstruction. Further, the RIP can be used to determine the optimal structure of the coded projections in CASSI. This article describes the CASSI optical architecture and develops the RIP for the sensing matrix in this system. Simulations show the higher quality of spectral image reconstructions when the RIP property is satisfied. Simulations also illustrate the higher performance of the optimal structured projections in CASSI.

  14. Parallel hyperspectral image reconstruction using random projections

    Science.gov (United States)

    Sevilla, Jorge; Martín, Gabriel; Nascimento, José M. P.

    2016-10-01

    Spaceborne sensors systems are characterized by scarce onboard computing and storage resources and by communication links with reduced bandwidth. Random projections techniques have been demonstrated as an effective and very light way to reduce the number of measurements in hyperspectral data, thus, the data to be transmitted to the Earth station is reduced. However, the reconstruction of the original data from the random projections may be computationally expensive. SpeCA is a blind hyperspectral reconstruction technique that exploits the fact that hyperspectral vectors often belong to a low dimensional subspace. SpeCA has shown promising results in the task of recovering hyperspectral data from a reduced number of random measurements. In this manuscript we focus on the implementation of the SpeCA algorithm for graphics processing units (GPU) using the compute unified device architecture (CUDA). Experimental results conducted using synthetic and real hyperspectral datasets on the GPU architecture by NVIDIA: GeForce GTX 980, reveal that the use of GPUs can provide real-time reconstruction. The achieved speedup is up to 22 times when compared with the processing time of SpeCA running on one core of the Intel i7-4790K CPU (3.4GHz), with 32 Gbyte memory.

  15. High resolution image reconstruction with constrained, total-variation minimization

    CERN Document Server

    Sidky, Emil Y; Duchin, Yuval; Ullberg, Christer; Pan, Xiaochuan

    2011-01-01

    This work is concerned with applying iterative image reconstruction, based on constrained total-variation minimization, to low-intensity X-ray CT systems that have a high sampling rate. Such systems pose a challenge for iterative image reconstruction, because a very fine image grid is needed to realize the resolution inherent in such scanners. These image arrays lead to under-determined imaging models whose inversion is unstable and can result in undesirable artifacts and noise patterns. There are many possibilities to stabilize the imaging model, and this work proposes a method which may have an advantage in terms of algorithm efficiency. The proposed method introduces additional constraints in the optimization problem; these constraints set to zero high spatial frequency components which are beyond the sensing capability of the detector. The method is demonstrated with an actual CT data set and compared with another method based on projection up-sampling.

  16. Reconstructing flaw image using dataset of full matrix capture technique

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Tae Hun; Kim, Yong Sik; Lee, Jeong Seok [KHNP Central Research Institute, Daejeon (Korea, Republic of)

    2017-02-15

    A conventional phased array ultrasonic system offers the ability to steer an ultrasonic beam by applying independent time delays of individual elements in the array and produce an ultrasonic image. In contrast, full matrix capture (FMC) is a data acquisition process that collects a complete matrix of A-scans from every possible independent transmit-receive combination in a phased array transducer and makes it possible to reconstruct various images that cannot be produced by conventional phased array with the post processing as well as images equivalent to a conventional phased array image. In this paper, a basic algorithm based on the LLL mode total focusing method (TFM) that can image crack type flaws is described. And this technique was applied to reconstruct flaw images from the FMC dataset obtained from the experiments and ultrasonic simulation.

  17. Blind reconstruction of sparse images with unknown point spread function

    Science.gov (United States)

    Herrity, Kyle; Raich, Raviv; Hero, Alfred O., III

    2008-02-01

    We consider the image reconstruction problem when the original image is assumed to be sparse and when partial knowledge of the point spread function (PSF) is available. In particular, we are interested in recovering the magnetization density given magnetic resonance force microscopy (MRFM) data, and we present an iterative alternating minimization algorithm (AM) to solve this problem. A smoothing penalty is introduced on allowable PSFs to improve the reconstruction. Simulations demonstrate its performance in reconstructing both the image and unknown point spread function. In addition, we develop an optimization transfer approach to solving a total variation (TV) blind deconvolution algorithm presented in a paper by Chan and Wong. We compare the performance of the AM algorithm to the blind TV algorithm as well as to a TV based majorization-minimization algorithm developed by Figueiredo et al.

  18. Regularization Reconstruction Method for Imaging Problems in Electrical Capacitance Tomography

    Science.gov (United States)

    Chu, Pan; Lei, Jing

    2017-11-01

    The electrical capacitance tomography (ECT) is deemed to be a powerful visualization measurement technique for the parametric measurement in a multiphase flow system. The inversion task in the ECT technology is an ill-posed inverse problem, and seeking for an efficient numerical method to improve the precision of the reconstruction images is important for practical measurements. By the introduction of the Tikhonov regularization (TR) methodology, in this paper a loss function that emphasizes the robustness of the estimation and the low rank property of the imaging targets is put forward to convert the solution of the inverse problem in the ECT reconstruction task into a minimization problem. Inspired by the split Bregman (SB) algorithm, an iteration scheme is developed for solving the proposed loss function. Numerical experiment results validate that the proposed inversion method not only reconstructs the fine structures of the imaging targets, but also improves the robustness.

  19. Reconstruction of CT images by the Bayes- back projection method

    CERN Document Server

    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 ...

  20. Image reconstruction from incomplete convolution data via total variation regularization

    Directory of Open Access Journals (Sweden)

    Zhida Shen

    2015-02-01

    Full Text Available Variational models with Total Variation (TV regularization have long been known to preserve image edges and produce high quality reconstruction. On the other hand, recent theory on compressive sensing has shown that it is feasible to accurately reconstruct  images from a few linear measurements via TV regularization. However, in general TV models are difficult to solve due to the nondifferentiability and the universal coupling of variables. In this paper, we propose the use of alternating direction method for image reconstruction from highly incomplete convolution data, where an image is reconstructed as a minimizer of an energy function that sums   a TV term for image regularity and a least squares term for data fitting. Our algorithm, called RecPK, takes advantage of problem structures and has an extremely low per-iteration cost. To demonstrate the efficiency of RecPK, we  compare it with TwIST, a state-of-the-art algorithm for minimizing TV models. Moreover, we also demonstrate the usefulness of RecPK in image zooming.

  1. Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU

    Directory of Open Access Journals (Sweden)

    Arefan D

    2015-06-01

    Full Text Available Digital Breast Tomosynthesis (DBT is a technology that creates three dimensional (3D images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU. At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU card and the Graphics Processing Unit (GPU. It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU.

  2. 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.

  3. Block Compressed Sensing of Images Using Adaptive Granular Reconstruction

    Directory of Open Access Journals (Sweden)

    Ran Li

    2016-01-01

    Full Text Available In the framework of block Compressed Sensing (CS, the reconstruction algorithm based on the Smoothed Projected Landweber (SPL iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.

  4. A simulation study on image reconstruction in magnetic particle imaging with field-free-line encoding

    CERN Document Server

    Murase, Kenya

    2016-01-01

    The purpose of this study was to present image reconstruction methods for magnetic particle imaging (MPI) with a field-free-line (FFL) encoding scheme and to propose the use of the maximum likelihood-expectation maximization (ML-EM) algorithm for improving the image quality of MPI. The feasibility of these methods was investigated by computer simulations, in which the projection data were generated by summing up the Fourier harmonics obtained from the MPI signals based on the Langevin function. Images were reconstructed from the generated projection data using the filtered backprojection (FBP) method and the ML-EM algorithm. The effects of the gradient of selection magnetic field (SMF), the strength of drive magnetic field (DMF), the diameter of magnetic nanoparticles (MNPs), and the number of projection data on the image quality of the reconstructed images were investigated. The spatial resolution of the reconstructed images became better with increasing gradient of SMF and with increasing diameter of MNPs u...

  5. Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

    Science.gov (United States)

    Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

    2017-06-01

    This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

  6. Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

    Science.gov (United States)

    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.

  7. Image reconstructions from super-sampled data sets with resolution modeling in PET imaging.

    Science.gov (United States)

    Li, Yusheng; Matej, Samuel; Metzler, Scott D

    2014-12-01

    Spatial resolution in positron emission tomography (PET) is still a limiting factor in many imaging applications. To improve the spatial resolution for an existing scanner with fixed crystal sizes, mechanical movements such as scanner wobbling and object shifting have been considered for PET systems. Multiple acquisitions from different positions can provide complementary information and increased spatial sampling. The objective of this paper is to explore an efficient and useful reconstruction framework to reconstruct super-resolution images from super-sampled low-resolution data sets. The authors introduce a super-sampling data acquisition model based on the physical processes with tomographic, downsampling, and shifting matrices as its building blocks. Based on the model, we extend the MLEM and Landweber algorithms to reconstruct images from super-sampled data sets. The authors also derive a backprojection-filtration-like (BPF-like) method for the super-sampling reconstruction. Furthermore, they explore variant methods for super-sampling reconstructions: the separate super-sampling resolution-modeling reconstruction and the reconstruction without downsampling to further improve image quality at the cost of more computation. The authors use simulated reconstruction of a resolution phantom to evaluate the three types of algorithms with different super-samplings at different count levels. Contrast recovery coefficient (CRC) versus background variability, as an image-quality metric, is calculated at each iteration for all reconstructions. The authors observe that all three algorithms can significantly and consistently achieve increased CRCs at fixed background variability and reduce background artifacts with super-sampled data sets at the same count levels. For the same super-sampled data sets, the MLEM method achieves better image quality than the Landweber method, which in turn achieves better image quality than the BPF-like method. The authors also demonstrate

  8. Gadgetron: an open source framework for medical image reconstruction.

    Science.gov (United States)

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-06-01

    This work presents a new open source framework for medical image reconstruction called the "Gadgetron." The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or "Gadgets" from raw data to reconstructed images. The data processing pipeline is configured dynamically at run-time based on an extensible markup language configuration description. The framework promotes reuse and sharing of reconstruction modules and new Gadgets can be added to the Gadgetron framework through a plugin-like architecture without recompiling the basic framework infrastructure. Gadgets are typically implemented in C/C++, but the framework includes wrapper Gadgets that allow the user to implement new modules in the Python scripting language for rapid prototyping. In addition to the streaming framework infrastructure, the Gadgetron comes with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its application to Cartesian and non-Cartesian parallel magnetic resonance imaging. Copyright © 2012 Wiley Periodicals, Inc.

  9. Magnetic resonance imaging with nonlinear gradient fields signal encoding and image reconstruction

    CERN Document Server

    Schultz, Gerrit

    2013-01-01

    Within the past few decades magnetic resonance imaging has become one of the most important imaging modalities in medicine. For a reliable diagnosis of pathologies further technological improvements are of primary importance. This text deals with a radically new approach of image encoding: The fundamental principle of gradient linearity is challenged by investigating the possibilities of acquiring anatomical images with the help of nonlinear gradient fields. Besides a thorough theoretical analysis with a focus on signal encoding and image reconstruction, initial hardware implementations are tested using phantom as well as in-vivo measurements. Several applications are presented that give an impression about the implications that this technological advancement may have for future medical diagnostics.   Contents n  Image Reconstruction in MRI n  Nonlinear Gradient Encoding: PatLoc Imaging n  Presentation of Initial Hardware Designs n  Basics of Signal Encoding and Image Reconstruction in PatLoc Imaging n ...

  10. Generalized Fourier slice theorem for cone-beam image reconstruction.

    Science.gov (United States)

    Zhao, Shuang-Ren; Jiang, Dazong; Yang, Kevin; Yang, Kang

    2015-01-01

    The cone-beam reconstruction theory has been proposed by Kirillov in 1961, Tuy in 1983, Feldkamp in 1984, Smith in 1985, Pierre Grangeat in 1990. The Fourier slice theorem is proposed by Bracewell 1956, which leads to the Fourier image reconstruction method for parallel-beam geometry. The Fourier slice theorem is extended to fan-beam geometry by Zhao in 1993 and 1995. By combining the above mentioned cone-beam image reconstruction theory and the above mentioned Fourier slice theory of fan-beam geometry, the Fourier slice theorem in cone-beam geometry is proposed by Zhao 1995 in short conference publication. This article offers the details of the derivation and implementation of this Fourier slice theorem for cone-beam geometry. Especially the problem of the reconstruction from Fourier domain has been overcome, which is that the value of in the origin of Fourier space is 0/0. The 0/0 type of limit is proper handled. As examples, the implementation results for the single circle and two perpendicular circle source orbits are shown. In the cone-beam reconstruction if a interpolation process is considered, the number of the calculations for the generalized Fourier slice theorem algorithm is O(N^4), which is close to the filtered back-projection method, here N is the image size of 1-dimension. However the interpolation process can be avoid, in that case the number of the calculations is O(N5).

  11. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    Science.gov (United States)

    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.

  12. Efficient iterative image reconstruction algorithm for dedicated breast CT

    Science.gov (United States)

    Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan

    2016-03-01

    Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.

  13. Autofocus imaging : Image reconstruction based on inverse scattering theory

    NARCIS (Netherlands)

    Behura, J.; Wapenaar, C.P.A.; Snieder, R.

    2014-01-01

    Conventional imaging algorithms assume single scattering and therefore cannot image multiply scattered waves correctly. The multiply scattered events in the data are imaged at incorrect locations resulting in spurious subsurface structures and erroneous interpretation. This drawback of current

  14. Interface-sensitive imaging by an image reconstruction aided X-ray reflectivity technique1

    OpenAIRE

    Jiang, Jinxing; Hirano, Keiichi; Sakurai, Kenji

    2017-01-01

    Recently, the authors have succeeded in realizing X-ray reflectivity imaging of heterogeneous ultrathin films at specific wavevector transfers by applying a wide parallel beam and an area detector. By combining in-plane angle and grazing-incidence angle scans, it is possible to reconstruct a series of interface-sensitive X-ray reflectivity images at different grazing-incidence angles (proportional to wavevector transfers). The physical meaning of a reconstructed X-ray reflectivity image at a ...

  15. Memory and Perception-based Facial Image Reconstruction.

    Science.gov (United States)

    Chang, Chi-Hsun; Nemrodov, Dan; Lee, Andy C H; Nestor, Adrian

    2017-07-26

    Visual memory for faces has been extensively researched, especially regarding the main factors that influence face memorability. However, what we remember exactly about a face, namely, the pictorial content of visual memory, remains largely unclear. The current work aims to elucidate this issue by reconstructing face images from both perceptual and memory-based behavioural data. Specifically, our work builds upon and further validates the hypothesis that visual memory and perception share a common representational basis underlying facial identity recognition. To this end, we derived facial features directly from perceptual data and then used such features for image reconstruction separately from perception and memory data. Successful levels of reconstruction were achieved in both cases for newly-learned faces as well as for familiar faces retrieved from long-term memory. Theoretically, this work provides insights into the content of memory-based representations while, practically, it may open the path to novel applications, such as computer-based 'sketch artists'.

  16. Point spread function based image reconstruction in optical projection tomography

    Science.gov (United States)

    Trull, Anna K.; van der Horst, Jelle; Palenstijn, Willem Jan; van Vliet, Lucas J.; van Leeuwen, Tristan; Kalkman, Jeroen

    2017-10-01

    As a result of the shallow depth of focus of the optical imaging system, the use of standard filtered back projection in optical projection tomography causes space-variant tangential blurring that increases with the distance to the rotation axis. We present a novel optical tomographic image reconstruction technique that incorporates the point spread function of the imaging lens in an iterative reconstruction. The technique is demonstrated using numerical simulations, tested on experimental optical projection tomography data of single fluorescent beads, and applied to high-resolution emission optical projection tomography imaging of an entire zebrafish larva. Compared to filtered back projection our results show greatly reduced radial and tangential blurring over the entire 5.2×5.2 mm2 field of view, and a significantly improved signal to noise ratio.

  17. Progress Update on Iterative Reconstruction of Neutron Tomographic Images

    Energy Technology Data Exchange (ETDEWEB)

    Hausladen, Paul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gregor, Jens [Univ. of Tennessee, Knoxville, TN (United States)

    2016-09-15

    This report satisfies the fiscal year 2016 technical deliverable to report on progress in development of fast iterative reconstruction algorithms for project OR16-3DTomography-PD2Jb, "3D Tomography and Image Processing Using Fast Neutrons." This project has two overall goals. The first of these goals is to extend associated-particle fast neutron transmission and, particularly, induced-reaction tomographic imaging algorithms to three dimensions. The second of these goals is to automatically segment the resultant tomographic images into constituent parts, and then extract information about the parts, such as the class of shape and potentially shape parameters. This report addresses of the component of the project concerned with three-dimensional (3D) image reconstruction.

  18. Skin image reconstruction using Monte Carlo based color generation

    Science.gov (United States)

    Aizu, Yoshihisa; Maeda, Takaaki; Kuwahara, Tomohiro; Hirao, Tetsuji

    2010-11-01

    We propose a novel method of skin image reconstruction based on color generation using Monte Carlo simulation of spectral reflectance in the nine-layered skin tissue model. The RGB image and spectral reflectance of human skin are obtained by RGB camera and spectrophotometer, respectively. The skin image is separated into the color component and texture component. The measured spectral reflectance is used to evaluate scattering and absorption coefficients in each of the nine layers which are necessary for Monte Carlo simulation. Various skin colors are generated by Monte Carlo simulation of spectral reflectance in given conditions for the nine-layered skin tissue model. The new color component is synthesized to the original texture component to reconstruct the skin image. The method is promising for applications in the fields of dermatology and cosmetics.

  19. Single Image Super Resolution via Sparse Reconstruction

    NARCIS (Netherlands)

    Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.

    2012-01-01

    High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms.

  20. Realise : reconstruction of reality from image sequences

    NARCIS (Netherlands)

    Leymarie, F.; de la Fortelle, A.; Koenderink, Jan J.; Kappers, A. M L; Stavridi, M.; van Ginneken, B.; Muller, S.; Krake, S.; Faugeras, O.; Robert, L.; Gauclin, C.; Laveau, S.; Zeller, C.; Anon,

    1996-01-01

    REALISE has for principal goals to extract from sequences of images, acquired with a moving camera, information necessary for determining the 3D (CAD-like) structure of a real-life scene together with information about the radiometric signatures of surfaces bounding the extracted 3D objects (e.g.

  1. Lobe based image reconstruction in Electrical Impedance Tomography.

    Science.gov (United States)

    Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Tawhai, Merryn; Adler, Andy; Mueller-Lisse, Ullrich; Moeller, Knut

    2017-02-01

    Electrical Impedance Tomography (EIT) is an imaging modality used to generate two-dimensional cross-sectional images representing impedance change in the thorax. The impedance of lung tissue changes with change in air content of the lungs; hence, EIT can be used to examine regional lung ventilation in patients with abnormal lungs. In lung EIT, electrodes are attached around the circumference of the thorax to inject small alternating currents and measure resulting voltages. In contrast to X-ray computed tomography (CT), EIT images do not depict a thorax slice of well defined thickness, but instead visualize a lens-shaped region around the electrode plane, which results from diffuse current propagation in the thorax. Usually, this is considered a drawback, since image interpretation is impeded if 'off-plane' conductivity changes are projected onto the reconstructed two-dimensional image. In this paper we describe an approach that takes advantage of current propagation below and above the electrode plane. The approach enables estimation of the individual conductivity change in each lung lobe from boundary voltage measurements. This could be used to monitor disease progression in patients with obstructive lung diseases, such as chronic obstructive pulmonary disease (COPD) or cystic fibrosis (CF) and to obtain a more comprehensive insight into the pathophysiology of the lung. Electrode voltages resulting from different conductivities in each lung lobe were simulated utilizing a realistic 3D finite element model (FEM) of the human thorax and the lungs. Overall 200 different patterns of conductivity change were simulated. A 'lobe reconstruction' algorithm was developed, applying patient-specific anatomical information in the reconstruction process. A standard EIT image reconstruction algorithm and the proposed 'lobe reconstruction' algorithm were used to estimate conductivity change in the lobes. The agreement between simulated and reconstructed conductivity change in

  2. Image reconstruction for optical tomography using photon density waves

    Energy Technology Data Exchange (ETDEWEB)

    Khalaf, R

    1999-08-01

    Diagnostic imaging makes use of different kinds of radiation. A recent type of imaging using near-infrared light is thought to be a safer and less-expensive method of in-vivo imaging. Near infra-red light can penetrate biological tissue to certain depths. The problem of using near infrared light for imaging, is that the scattering of the photons dominates absorption, causing difficulties in the reconstruction model on which biomedical optical imaging depends crucially. The aim of this thesis is to develop and investigate the performance of a reconstruction algorithm in the frequency domain which allows fast and efficient reconstruction of the image of a limb, or an optical phantom. The forward problem of the propagation of photons inside biological tissue is modelled using the Diffusion Approximation theory solved by the finite element method. Values of DC intensity, phase shift and modulation depth at the boundary as functions of the diffusion and absorption coefficients are given. The inverse model is formulated as a nonlinear least-squares optimisation problem. The Truncated Newton method with Trust region is used to determine the optical properties. Reverse differentiation is used to calculate the error function because of its speed advantage over forward differentiation. A sensitivity analysis is performed to investigate the simultaneous reconstruction of the diffusion and absorption coefficients. The use of a combined error function of DC intensity, phase and modulation prove to be the most successful at recovering the optical parameters. The ability to distinguish between object size and size of optical parameter is also investigated. Contrast, mean and standard deviation are used as measures of the performance of the reconstruction algorithm. A Tikhonov regularisation method was used to improve ill-conditioning and behaviour in the presence of noise. An investigation of the optimal regularisation parameter is undertaken with the addition of noise to the

  3. An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging.

    Science.gov (United States)

    Valente, Solivan A; Zibetti, Marcelo V W; Pipa, Daniel R; Maia, Joaquim M; Schneider, Fabio K

    2017-03-08

    Ultrasonic image reconstruction using inverse problems has recently appeared as an alternative to enhance ultrasound imaging over beamforming methods. This approach depends on the accuracy of the acquisition model used to represent transducers, reflectivity, and medium physics. Iterative methods, well known in general sparse signal reconstruction, are also suited for imaging. In this paper, a discrete acquisition model is assessed by solving a linear system of equations by an ℓ 1 -regularized least-squares minimization, where the solution sparsity may be adjusted as desired. The paper surveys 11 variants of four well-known algorithms for sparse reconstruction, and assesses their optimization parameters with the goal of finding the best approach for iterative ultrasound imaging. The strategy for the model evaluation consists of using two distinct datasets. We first generate data from a synthetic phantom that mimics real targets inside a professional ultrasound phantom device. This dataset is contaminated with Gaussian noise with an estimated SNR, and all methods are assessed by their resulting images and performances. The model and methods are then assessed with real data collected by a research ultrasound platform when scanning the same phantom device, and results are compared with beamforming. A distinct real dataset is finally used to further validate the proposed modeling. Although high computational effort is required by iterative methods, results show that the discrete model may lead to images closer to ground-truth than traditional beamforming. However, computing capabilities of current platforms need to evolve before frame rates currently delivered by ultrasound equipments are achievable.

  4. Undersampled Hyperspectral Image Reconstruction Based on Surfacelet Transform

    Directory of Open Access Journals (Sweden)

    Lei Liu

    2015-01-01

    Full Text Available Hyperspectral imaging is a crucial technique for military and environmental monitoring. However, limited equipment hardware resources severely affect the transmission and storage of a huge amount of data for hyperspectral images. This limitation has the potentials to be solved by compressive sensing (CS, which allows reconstructing images from undersampled measurements with low error. Sparsity and incoherence are two essential requirements for CS. In this paper, we introduce surfacelet, a directional multiresolution transform for 3D data, to sparsify the hyperspectral images. Besides, a Gram-Schmidt orthogonalization is used in CS random encoding matrix, two-dimensional and three-dimensional orthogonal CS random encoding matrixes and a patch-based CS encoding scheme are designed. The proposed surfacelet-based hyperspectral images reconstruction problem is solved by a fast iterative shrinkage-thresholding algorithm. Experiments demonstrate that reconstruction of spectral lines and spatial images is significantly improved using the proposed method than using conventional three-dimensional wavelets, and growing randomness of encoding matrix can further improve the quality of hyperspectral data. Patch-based CS encoding strategy can be used to deal with large data because data in different patches can be independently sampled.

  5. A novel data processing technique for image reconstruction of penumbral imaging

    Science.gov (United States)

    Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin

    2011-06-01

    CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.

  6. Image quality of multiplanar reconstruction of pulmonary CT scans using adaptive statistical iterative reconstruction

    Science.gov (United States)

    Honda, O; Yanagawa, M; Inoue, A; Kikuyama, A; Yoshida, S; Sumikawa, H; Tobino, K; Koyama, M; Tomiyama, N

    2011-01-01

    Objective We investigated the image quality of multiplanar reconstruction (MPR) using adaptive statistical iterative reconstruction (ASIR). Methods Inflated and fixed lungs were scanned with a garnet detector CT in high-resolution mode (HR mode) or non-high-resolution (HR) mode, and MPR images were then reconstructed. Observers compared 15 MPR images of ASIR (40%) and ASIR (80%) with those of ASIR (0%), and assessed image quality using a visual five-point scale (1, definitely inferior; 5, definitely superior), with particular emphasis on normal pulmonary structures, artefacts, noise and overall image quality. Results The mean overall image quality scores in HR mode were 3.67 with ASIR (40%) and 4.97 with ASIR (80%). Those in non-HR mode were 3.27 with ASIR (40%) and 3.90 with ASIR (80%). The mean artefact scores in HR mode were 3.13 with ASIR (40%) and 3.63 with ASIR (80%), but those in non-HR mode were 2.87 with ASIR (40%) and 2.53 with ASIR (80%). The mean scores of the other parameters were greater than 3, whereas those in HR mode were higher than those in non-HR mode. There were significant differences between ASIR (40%) and ASIR (80%) in overall image quality (pASIR did not suppress the severe artefacts of contrast medium. Conclusion In general, MPR image quality with ASIR (80%) was superior to that with ASIR (40%). However, there was an increased incidence of artefacts by ASIR when CT images were obtained in non-HR mode. PMID:21081572

  7. Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction

    CERN Document Server

    Yin, Xiaoxia; Abbott, Derek

    2012-01-01

    Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...

  8. Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2016-03-01

    Electromagnetic imaging is the problem of determining material properties from scattered fields measured away from the domain under investigation. Solving this inverse problem is a challenging task because (i) it is ill-posed due to the presence of (smoothing) integral operators used in the representation of scattered fields in terms of material properties, and scattered fields are obtained at a finite set of points through noisy measurements; and (ii) it is nonlinear simply due the fact that scattered fields are nonlinear functions of the material properties. The work described in this thesis tackles the ill-posedness of the electromagnetic imaging problem using sparsity-based regularization techniques, which assume that the scatterer(s) occupy only a small fraction of the investigation domain. More specifically, four novel imaging methods are formulated and implemented. (i) Sparsity-regularized Born iterative method iteratively linearizes the nonlinear inverse scattering problem and each linear problem is regularized using an improved iterative shrinkage algorithm enforcing the sparsity constraint. (ii) Sparsity-regularized nonlinear inexact Newton method calls for the solution of a linear system involving the Frechet derivative matrix of the forward scattering operator at every iteration step. For faster convergence, the solution of this matrix system is regularized under the sparsity constraint and preconditioned by leveling the matrix singular values. (iii) Sparsity-regularized nonlinear Tikhonov method directly solves the nonlinear minimization problem using Landweber iterations, where a thresholding function is applied at every iteration step to enforce the sparsity constraint. (iv) This last scheme is accelerated using a projected steepest descent method when it is applied to three-dimensional investigation domains. Projection replaces the thresholding operation and enforces the sparsity constraint. Numerical experiments, which are carried out using

  9. Statistical reconstruction algorithms for continuous wave electron spin resonance imaging

    Science.gov (United States)

    Kissos, Imry; Levit, Michael; Feuer, Arie; Blank, Aharon

    2013-06-01

    Electron spin resonance imaging (ESRI) is an important branch of ESR that deals with heterogeneous samples ranging from semiconductor materials to small live animals and even humans. ESRI can produce either spatial images (providing information about the spatially dependent radical concentration) or spectral-spatial images, where an extra dimension is added to describe the absorption spectrum of the sample (which can also be spatially dependent). The mapping of oxygen in biological samples, often referred to as oximetry, is a prime example of an ESRI application. ESRI suffers frequently from a low signal-to-noise ratio (SNR), which results in long acquisition times and poor image quality. A broader use of ESRI is hampered by this slow acquisition, which can also be an obstacle for many biological applications where conditions may change relatively quickly over time. The objective of this work is to develop an image reconstruction scheme for continuous wave (CW) ESRI that would make it possible to reduce the data acquisition time without degrading the reconstruction quality. This is achieved by adapting the so-called "statistical reconstruction" method, recently developed for other medical imaging modalities, to the specific case of CW ESRI. Our new algorithm accounts for unique ESRI aspects such as field modulation, spectral-spatial imaging, and possible limitation on the gradient magnitude (the so-called "limited angle" problem). The reconstruction method shows improved SNR and contrast recovery vs. commonly used back-projection-based methods, for a variety of simulated synthetic samples as well as in actual CW ESRI experiments.

  10. Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR).

    Science.gov (United States)

    Notohamiprodjo, S; Deak, Z; Meurer, F; Maertz, F; Mueck, F G; Geyer, L L; Wirth, S

    2015-01-01

    The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p iterative reconstruction (MBIR) effectively decreased artefacts in cranial CT. • MBIR reconstructed images were rated with significantly higher scores for image quality. • Model-Based iterative reconstruction may allow reduced-dose diagnostic examination protocols.

  11. Tomographic Image Reconstruction Using Training Images with Matrix and Tensor Formulations

    DEFF Research Database (Denmark)

    Soltani, Sara

    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...... 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...... 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...

  12. Polarimetric ISAR: Simulation and image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, David H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-03-21

    In polarimetric ISAR the illumination platform, typically airborne, carries a pair of antennas that are directed toward a fixed point on the surface as the platform moves. During platform motion, the antennas maintain their gaze on the point, creating an effective aperture for imaging any targets near that point. The interaction between the transmitted fields and targets (e.g. ships) is complicated since the targets are typically many wavelengths in size. Calculation of the field scattered from the target typically requires solving Maxwell’s equations on a large three-dimensional numerical grid. This is prohibitive to use in any real-world imaging algorithm, so the scattering process is typically simplified by assuming the target consists of a cloud of independent, non-interacting, scattering points (centers). Imaging algorithms based on this scattering model perform well in many applications. Since polarimetric radar is not very common, the scattering model is often derived for a scalar field (single polarization) where the individual scatterers are assumed to be small spheres. However, when polarization is important, we must generalize the model to explicitly account for the vector nature of the electromagnetic fields and its interaction with objects. In this note, we present a scattering model that explicitly includes the vector nature of the fields but retains the assumption that the individual scatterers are small. The response of the scatterers is described by electric and magnetic dipole moments induced by the incident fields. We show that the received voltages in the antennas are linearly related to the transmitting currents through a scattering impedance matrix that depends on the overall geometry of the problem and the nature of the scatterers.

  13. Optimized 3D Street Scene Reconstruction from Driving Recorder Images

    Directory of Open Access Journals (Sweden)

    Yongjun Zhang

    2015-07-01

    Full Text Available The paper presents an automatic region detection based method to reconstruct street scenes from driving recorder images. The driving recorder in this paper is a dashboard camera that collects images while the motor vehicle is moving. An enormous number of moving vehicles are included in the collected data because the typical recorders are often mounted in the front of moving vehicles and face the forward direction, which can make matching points on vehicles and guardrails unreliable. Believing that utilizing these image data can reduce street scene reconstruction and updating costs because of their low price, wide use, and extensive shooting coverage, we therefore proposed a new method, which is called the Mask automatic detecting method, to improve the structure results from the motion reconstruction. Note that we define vehicle and guardrail regions as “mask” in this paper since the features on them should be masked out to avoid poor matches. After removing the feature points in our new method, the camera poses and sparse 3D points that are reconstructed with the remaining matches. Our contrast experiments with the typical pipeline of structure from motion (SfM reconstruction methods, such as Photosynth and VisualSFM, demonstrated that the Mask decreased the root-mean-square error (RMSE of the pairwise matching results, which led to more accurate recovering results from the camera-relative poses. Removing features from the Mask also increased the accuracy of point clouds by nearly 30%–40% and corrected the problems of the typical methods on repeatedly reconstructing several buildings when there was only one target building.

  14. 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.

  15. Proton Computed Tomography: iterative image reconstruction and dose evaluation

    Science.gov (United States)

    Civinini, C.; Bonanno, D.; Brianzi, M.; Carpinelli, M.; Cirrone, G. A. P.; Cuttone, G.; Lo Presti, D.; Maccioni, G.; Pallotta, S.; Randazzo, N.; Scaringella, M.; Romano, F.; Sipala, V.; Talamonti, C.; Vanzi, E.; Bruzzi, M.

    2017-01-01

    Proton Computed Tomography (pCT) is a medical imaging method with a potential for increasing accuracy of treatment planning and patient positioning in hadron therapy. A pCT system based on a Silicon microstrip tracker and a YAG:Ce crystal calorimeter has been developed within the INFN Prima-RDH collaboration. The prototype has been tested with a 175 MeV proton beam at The Svedberg Laboratory (Uppsala, Sweden) with the aim to reconstruct and characterize a tomographic image. Algebraic iterative reconstruction methods (ART), together with the most likely path formalism, have been used to obtain tomographies of an inhomogeneous phantom to eventually extract density and spatial resolutions. These results will be presented and discussed together with an estimation of the average dose delivered to the phantom and the dependence of the image quality on the dose. Due to the heavy computation load required by the algebraic algorithms the reconstruction programs have been implemented to fully exploit the high calculation parallelism of Graphics Processing Units. An extended field of view pCT system is in an advanced construction stage. This apparatus will be able to reconstruct objects of the size of a human head making possible to characterize this pCT approach in a pre-clinical environment.

  16. SIRFING: Sparse Image Reconstruction For INterferometry using GPUs

    Science.gov (United States)

    Cranmer, Miles; Garsden, Hugh; Mitchell, Daniel A.; Greenhill, Lincoln

    2018-01-01

    We present a deconvolution code for radio interferometric imaging based on the compressed sensing algorithms in Garsden et al. (2015). Being computationally intensive, compressed sensing is ripe for parallelization over GPUs. Our compressed sensing implementation generates images using wavelets, and we have ported the underlying wavelet library to CUDA, targeting the spline filter reconstruction part of the algorithm. The speedup achieved is almost an order of magnitude. The code is modular but is also being integrated into the calibration and imaging pipeline in use by the LEDA project at the Long Wavelength Array (LWA) as well as by the Murchinson Widefield Array (MWA).

  17. Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms

    DEFF Research Database (Denmark)

    Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    We seek to characterize the sampling conditions for iterative image reconstruction exploiting gradient-magnitude sparsity. We seek the number of views necessary for accurate image reconstruction by constrained, total variation (TV) minimization, which is the optimization problem suggested...

  18. Comparison of power spectra for tomosynthesis projections and reconstructed images

    Energy Technology Data Exchange (ETDEWEB)

    Engstrom, Emma; Reiser, Ingrid; Nishikawa, Robert [Royal Institute of Technology, 11231 Stockholm (Sweden); Department of Radiology, University of Chicago, Chicago 60637 (United States)

    2009-05-15

    Burgess et al. [Med. Phys. 28, 419-437 (2001)] showed that the power spectrum of mammographic breast background follows a power law and that lesion detectability is affected by the power-law exponent {beta} which measures the amount of structure in the background. Following the study of Burgess et al., the authors measured and compared the power-law exponent of mammographic backgrounds in tomosynthesis projections and reconstructed slices to investigate the effect of tomosynthesis imaging on background structure. Our data set consisted of 55 patient cases. For each case, regions of interest (ROIs) were extracted from both projection images and reconstructed slices. The periodogram of each ROI was computed by taking the squared modulus of the Fourier transform of the ROI. The power-law exponent was determined for each periodogram and averaged across all ROIs extracted from all projections or reconstructed slices for each patient data set. For the projections, the mean {beta} averaged across the 55 cases was 3.06 (standard deviation of 0.21), while it was 2.87 (0.24) for the corresponding reconstructions. The difference in {beta} for a given patient between the projection ROIs and the reconstructed ROIs averaged across the 55 cases was 0.194, which was statistically significant (p<0.001). The 95% CI for the difference between the mean value of {beta} for the projections and reconstructions was [0.170, 0.218]. The results are consistent with the observation that the amount of breast structure in the tomosynthesis slice is reduced compared to projection mammography and that this may lead to improved lesion detectability.

  19. Missing data reconstruction using Gaussian mixture models for fingerprint images

    Science.gov (United States)

    Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary

    2016-05-01

    Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.

  20. Complications of anterior cruciate ligament reconstruction: MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Papakonstantinou, Olympia; Chung, Christine B.; Chanchairujira, Kullanuch; Resnick, Donald L. [Department of Radiology, Veterans Affairs Medical Center, University of California, 3350 La Jolla Village Dr., San Diego, CA 92161 (United States)

    2003-05-01

    Arthroscopic reconstruction of the anterior cruciate ligament (ACL) using autografts or allografts is being performed with increasing frequency, particularly in young athletes. Although the procedure is generally well tolerated, with good success rates, early and late complications have been documented. As clinical manifestations of graft complications are often non-specific and plain radiographs cannot directly visualize the graft and the adjacent soft tissues, MR imaging has a definite role in the diagnosis of complications after ACL reconstruction and may direct subsequent therapeutic management. Our purpose is to review the normal MR imaging of the ACL graft and present the MR imaging findings of a wide spectrum of complications after ACL reconstruction, such as graft impingement, graft rupture, cystic degeneration of the graft, postoperative infection of the knee, diffuse and localized (i.e., cyclops lesion) arthrofibrosis, and associated donor site abnormalities. Awareness of the MR imaging findings of complications as well as the normal appearances of the normal ACL graft is essential for correct interpretation. (orig.)

  1. Holographic images reconstructed from GMR-based fringe pattern

    Directory of Open Access Journals (Sweden)

    Kikuchi Hiroshi

    2013-01-01

    Full Text Available We have developed a magneto-optical spatial light modulator (MOSLM using giant magneto-resistance (GMR structures for realizing a holographic three-dimensional (3D display. For practical applications, reconstructed image of hologram consisting of GMR structures should be investigated in order to study the feasibility of the MOSLM. In this study, we fabricated a hologram with GMR based fringe-pattern and demonstrated a reconstructed image. A fringe-pattern convolving a crossshaped image was calculated by a conventional binary computer generated hologram (CGH technique. The CGH-pattern has 2,048 × 2,048 with 5 μm pixel pitch. The GMR stack consists of a Tb-Fe-Co/CoFe pinned layer, a Ag spacer, a Gd-Fe free layer for light modulation, and a Ru capping layer, was deposited by dc-magnetron sputtering. The GMR hologram was formed using photo-lithography and Krion milling processes, followed by the deposition of a Tb-Fe-Co reference layer with large coercivity and the same Kerr-rotation angle compared to the free layer, and a lift-off process. The reconstructed image of the ON-state was clearly observed and successfully distinguished from the OFF-state by switching the magnetization direction of the free-layer with an external magnetic field. These results indicate the possibility of realizing a holographic 3D display by the MOSLM using the GMR structures.

  2. Holographic images reconstructed from GMR-based fringe pattern

    Science.gov (United States)

    Kato, Daisuke; Aoshima, Kenichi; Machida, Kenji; Emoto, Akira; Kinjo, Hidekazu; Kuga, Kiyoshi; Ono, Hiroshi; Ishibashi, Takayuki; Kikuchi, Hiroshi; Shimidzu, Naoki

    2013-01-01

    We have developed a magneto-optical spatial light modulator (MOSLM) using giant magneto-resistance (GMR) structures for realizing a holographic three-dimensional (3D) display. For practical applications, reconstructed image of hologram consisting of GMR structures should be investigated in order to study the feasibility of the MOSLM. In this study, we fabricated a hologram with GMR based fringe-pattern and demonstrated a reconstructed image. A fringe-pattern convolving a crossshaped image was calculated by a conventional binary computer generated hologram (CGH) technique. The CGH-pattern has 2,048 × 2,048 with 5 μm pixel pitch. The GMR stack consists of a Tb-Fe-Co/CoFe pinned layer, a Ag spacer, a Gd-Fe free layer for light modulation, and a Ru capping layer, was deposited by dc-magnetron sputtering. The GMR hologram was formed using photo-lithography and Krion milling processes, followed by the deposition of a Tb-Fe-Co reference layer with large coercivity and the same Kerr-rotation angle compared to the free layer, and a lift-off process. The reconstructed image of the ON-state was clearly observed and successfully distinguished from the OFF-state by switching the magnetization direction of the free-layer with an external magnetic field. These results indicate the possibility of realizing a holographic 3D display by the MOSLM using the GMR structures.

  3. Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

    Science.gov (United States)

    Shuman, William P; Chan, Keith T; Busey, Janet M; Mitsumori, Lee M; Choi, Eunice; Koprowicz, Kent M; Kanal, Kalpana M

    2014-12-01

    To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers

  4. PHOTOGRAMMETRIC 3D BUILDING RECONSTRUCTION FROM THERMAL IMAGES

    Directory of Open Access Journals (Sweden)

    E. Maset

    2017-08-01

    Full Text Available This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.

  5. Photogrammetric 3d Building Reconstruction from Thermal Images

    Science.gov (United States)

    Maset, E.; Fusiello, A.; Crosilla, F.; Toldo, R.; Zorzetto, D.

    2017-08-01

    This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR) images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV) and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP) algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.

  6. Stokes image reconstruction for two-color microgrid polarization imaging systems.

    Science.gov (United States)

    Lemaster, Daniel A

    2011-07-18

    The Air Force Research Laboratory has developed a new microgrid polarization imaging system capable of simultaneously reconstructing linear Stokes parameter images in two colors on a single focal plane array. In this paper, an effective method for extracting Stokes images is presented for this type of camera system. It is also shown that correlations between the color bands can be exploited to significantly increase overall spatial resolution. Test data is used to show the advantages of this approach over bilinear interpolation. The bounds (in terms of available reconstruction bandwidth) on image resolution are also provided.

  7. Stable Image Registration for In-Vivo Fetoscopic Panorama Reconstruction

    Directory of Open Access Journals (Sweden)

    Floris Gaisser

    2018-01-01

    Full Text Available A Twin-to-Twin Transfusion Syndrome (TTTS is a condition that occurs in about 10% of pregnancies involving monochorionic twins. This complication can be treated with fetoscopic laser coagulation. The procedure could greatly benefit from panorama reconstruction to gain an overview of the placenta. In previous work we investigated which steps could improve the reconstruction performance for an in-vivo setting. In this work we improved this registration by proposing a stable region detection method as well as extracting matchable features based on a deep-learning approach. Finally, we extracted a measure for the image registration quality and the visibility condition. With experiments we show that the image registration performance is increased and more constant. Using these methods a system can be developed that supports the surgeon during the surgery, by giving feedback and providing a more complete overview of the placenta.

  8. A maximum entropy reconstruction technique for tomographic particle image velocimetry

    Science.gov (United States)

    Bilsky, A. V.; Lozhkin, V. A.; Markovich, D. M.; Tokarev, M. P.

    2013-04-01

    This paper studies a novel approach for reducing tomographic PIV computational complexity. The proposed approach is an algebraic reconstruction technique, termed MENT (maximum entropy). This technique computes the three-dimensional light intensity distribution several times faster than SMART, using at least ten times less memory. Additionally, the reconstruction quality remains nearly the same as with SMART. This paper presents the theoretical computation performance comparison for MENT, SMART and MART, followed by validation using synthetic particle images. Both the theoretical assessment and validation of synthetic images demonstrate significant computational time reduction. The data processing accuracy of MENT was compared to that of SMART in a slot jet experiment. A comparison of the average velocity profiles shows a high level of agreement between the results obtained with MENT and those obtained with SMART.

  9. Fan beam image reconstruction with generalized Fourier slice theorem.

    Science.gov (United States)

    Zhao, Shuangren; Yang, Kang; Yang, Kevin

    2014-01-01

    For parallel beam geometry the Fourier reconstruction works via the Fourier slice theorem (or central slice theorem, projection slice theorem). For fan beam situation, Fourier slice can be extended to a generalized Fourier slice theorem (GFST) for fan-beam image reconstruction. We have briefly introduced this method in a conference. This paper reintroduces the GFST method for fan beam geometry in details. The GFST method can be described as following: the Fourier plane is filled by adding up the contributions from all fanbeam projections individually; thereby the values in the Fourier plane are directly calculated for Cartesian coordinates such avoiding the interpolation from polar to Cartesian coordinates in the Fourier domain; inverse fast Fourier transform is applied to the image in Fourier plane and leads to a reconstructed image in spacial domain. The reconstructed image is compared between the result of the GFST method and the result from the filtered backprojection (FBP) method. The major differences of the GFST and the FBP methods are: (1) The interpolation process are at different data sets. The interpolation of the GFST method is at projection data. The interpolation of the FBP method is at filtered projection data. (2) The filtering process are done in different places. The filtering process of the GFST is at Fourier domain. The filtering process of the FBP method is the ramp filter which is done at projections. The resolution of ramp filter is variable with different location but the filter in the Fourier domain lead to resolution invariable with location. One advantage of the GFST method over the FBP method is in short scan situation, an exact solution can be obtained with the GFST method, but it can not be obtained with the FBP method. The calculation of both the GFST and the FBP methods are at O(N^3), where N is the number of pixel in one dimension.

  10. Laboratory demonstration of image reconstruction for coherent optical system of modular imaging collectors (COSMIC)

    Science.gov (United States)

    Traub, W. A.

    1984-01-01

    The first physical demonstration of the principle of image reconstruction using a set of images from a diffraction-blurred elongated aperture is reported. This is an optical validation of previous theoretical and numerical simulations of the COSMIC telescope array (coherent optical system of modular imaging collectors). The present experiment utilizes 17 diffraction blurred exposures of a laboratory light source, as imaged by a lens covered by a narrow-slit aperture; the aperture is rotated 10 degrees between each exposure. The images are recorded in digitized form by a CCD camera, Fourier transformed, numerically filtered, and added; the sum is then filtered and inverse Fourier transformed to form the final image. The image reconstruction process is found to be stable with respect to uncertainties in values of all physical parameters such as effective wavelength, rotation angle, pointing jitter, and aperture shape. Future experiments will explore the effects of low counting rates, autoguiding on the image, various aperture configurations, and separated optics.

  11. PSNR BASED OPTIMIZATION APPLIED TO ALGEBRAIC RECONSTRUCTION TECHNIQUE FOR IMAGE RECONSTRUCTION ON A MULTI-CORE SYSTEM

    Directory of Open Access Journals (Sweden)

    Bharathi Lakshmi Agnimarimuthu

    2017-06-01

    Full Text Available The present work attempts to reveal a parallel Algebraic Reconstruction Technique (pART to reduce the computational speed of reconstructing artifact-free images from projections. ART is an iterative algorithm well known to reconstruct artifact-free images with limited number of projections. In this work, a novel idea has been focused on to optimize the number of iterations mandatory based on Peak to Signal Noise Ratio (PSNR to reconstruct an image. However, it suffers of worst computation speed. Hence, an attempt is made to reduce the computation time by running iterative algorithm on a multi-core parallel environment. The execution times are computed for both serial and parallel implementations of ART using different projection data, and, tabulated for comparison. The experimental results demonstrate that the parallel computing environment provides a source of high computational power leading to obtain reconstructed image instantaneously.

  12. Task-based optimization of image reconstruction in breast CT

    Science.gov (United States)

    Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

    2014-03-01

    We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.

  13. Iterative Self-Dual Reconstruction on Radar Image Recovery

    Energy Technology Data Exchange (ETDEWEB)

    Martins, Charles; Medeiros, Fatima; Ushizima, Daniela; Bezerra, Francisco; Marques, Regis; Mascarenhas, Nelson

    2010-05-21

    Imaging systems as ultrasound, sonar, laser and synthetic aperture radar (SAR) are subjected to speckle noise during image acquisition. Before analyzing these images, it is often necessary to remove the speckle noise using filters. We combine properties of two mathematical morphology filters with speckle statistics to propose a signal-dependent noise filter to multiplicative noise. We describe a multiscale scheme that preserves sharp edges while it smooths homogeneous areas, by combining local statistics with two mathematical morphology filters: the alternating sequential and the self-dual reconstruction algorithms. The experimental results show that the proposed approach is less sensitive to varying window sizes when applied to simulated and real SAR images in comparison with standard filters.

  14. CONTEXT-BASED URBAN TERRAIN RECONSTRUCTION FROM IMAGES AND VIDEOS

    Directory of Open Access Journals (Sweden)

    D. Bulatov

    2012-07-01

    Full Text Available Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as input a high-quality Digital Surface Model (DSM, are more straight-forward and produce more robust and reliable results than those image-based methods that require matching line segments or even whole regions. This motivated us to develop a new dense matching technique for DSM generation that is capable of simultaneous integration of multiple images in the reconstruction process. The DSMs generated by this new multi-image matching technique can be used for urban object extraction. In the first contribution of this paper, two examples of external sources of information added to the reconstruction pipeline will be shown. The GIS layers are used for recognition of streets and suppressing false alarms in the depth maps that were caused by moving vehicles while the near infrared channel is applied for separating vegetation from buildings. Three examples of data sets including both UAV-borne video sequences with a relatively high number of frames and high-resolution (10 cm ground sample distance data sets consisting of (few spatial-temporarily diverse images from large-format aerial frame cameras, will be presented. By an extensive quantitative evaluation of the Vaihingen block from the ISPRS benchmark on urban object detection, it will become clear that our procedure allows a straight-forward, efficient, and reliable instantiation of 3D city models.

  15. Optimization of image reconstruction conditions with phantoms for brain FDG and amyloid PET imaging

    National Research Council Canada - National Science Library

    Akamatsu, Go; Ikari, Yasuhiko; Nishio, Tomoyuki; Nishida, Hiroyuki; Ohnishi, Akihito; Aita, Kazuki; Sasaki, Masahiro; Sasaki, Masayuki; Senda, Michio

    2016-01-01

    The purpose of this study was to optimize image reconstruction conditions for brain 18F-FDG, 11C-PiB, 18F-florbetapir and 18F-flutemetamol PET imaging with Discovery-690 PET/CT for diagnosis and research on Alzheimer’s disease (AD...

  16. Image Reconstruction and Discrimination at Low Light Levels

    Science.gov (United States)

    Zerom, Petros

    Quantum imaging is a recent and promising branch of quantum optics that exploits the quantum nature of light. Improving the limitations imposed by classical sources of light in optical imaging techniques or overcoming the classical boundaries of image formation is one of the key motivations in quantum imaging. In this thesis, I describe certain aspects of both quantum and thermal ghost imaging and I also study image discrimination with high fidelity at low light levels. First of all, I present a theoretical and experimental study of entangled-photon compressive ghost imaging. In quantum ghost imaging using entangled photon pairs, the brightness of readily available sources is rather weak. The usual technique of image acquisition in this imaging modality is to raster scan a single-pixel single-photon sensitive detector in one arm of a ghost imaging setup. In most imaging modalities, the number of measurements required to fully resolve an object is dependent on the measurement's Nyquist limit. In the first part of the thesis, I propose a ghost imaging (GI) configuration that uses bucket detectors (as opposed to a raster scanning detector) in both arms of the GI setup. High resolution image reconstruction using only 27% of the measurement's Nyquist limit using compressed sensing algorithms are presented. The second part of my thesis deals with thermal ghost imaging. Unlike in quantum GI, bright and spatially correlated classical sources of radiation are used in thermal GI. Usually high-contrast speckle patterns are used as sources of the correlated beams of radiation. I study the effect of the field statistics of the illuminating source on the quality of ghost images. I show theoretically and experimentally that a thermal GI setup can produce high quality images even when low-contrast (intensity-averaged) speckle patterns are used as an illuminating source, as long as the collected signal is mainly caused by the random fluctuation of the incident speckle field, as

  17. Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

    Science.gov (United States)

    Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

    2016-10-01

    Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

  18. Object segmentation controls image reconstruction from natural scenes.

    Science.gov (United States)

    Neri, Peter

    2017-08-01

    The structure of the physical world projects images onto our eyes. However, those images are often poorly representative of environmental structure: well-defined boundaries within the eye may correspond to irrelevant features of the physical world, while critical features of the physical world may be nearly invisible at the retinal projection. The challenge for the visual cortex is to sort these two types of features according to their utility in ultimately reconstructing percepts and interpreting the constituents of the scene. We describe a novel paradigm that enabled us to selectively evaluate the relative role played by these two feature classes in signal reconstruction from corrupted images. Our measurements demonstrate that this process is quickly dominated by the inferred structure of the environment, and only minimally controlled by variations of raw image content. The inferential mechanism is spatially global and its impact on early visual cortex is fast. Furthermore, it retunes local visual processing for more efficient feature extraction without altering the intrinsic transduction noise. The basic properties of this process can be partially captured by a combination of small-scale circuit models and large-scale network architectures. Taken together, our results challenge compartmentalized notions of bottom-up/top-down perception and suggest instead that these two modes are best viewed as an integrated perceptual mechanism.

  19. GF-4 Images Super Resolution Reconstruction Based on POCS

    Directory of Open Access Journals (Sweden)

    XU Lina

    2017-08-01

    Full Text Available The super resolution reconstruction of GF-4 is made by projection on convex sets (POCS. Papoulis-Gerchberg is used to construct reference frame which can reduce iteration and improve algorithm efficiency.Vandewalle is used to estimate motion parameter which is benefit to block process. Tested and analyzed by real GF-4 series images, it shows that sharpness of super resolution result is positive correlatie to frame amount, and signal to noise ratio (SNR is negative correlate to frame amount. After processing by 5 frames, information entropy (IE changes little; sharpness (average gradient increases from 7.803 to 14.386; SNR reduces a little, from 3.411 to 3.336. The experiment shows that after super resolution reconstruction, sharpness and detail information of results can be greatly improved.

  20. Automatic speed of sound correction with photoacoustic image reconstruction

    Science.gov (United States)

    Ye, Meng; Cao, Meng; Feng, Ting; Yuan, Jie; Cheng, Qian; Liu, XIaojun; Xu, Guan; Wang, Xueding

    2016-03-01

    Sound velocity measurement is of great importance to the application of biomedical especially in the research of acoustic detection and acoustic tomography. Using correct sound velocities in each medium other than one unified sound propagation speed, we can effectively enhance sound based imaging resolution. Photoacoustic tomography (PAT), is defined as cross-sectional or three-dimensional (3D) imaging of a material based on the photoacoustic effect and it is a developing, non-invasive imaging method in biomedical research. This contribution proposes a method to concurrently calculate multiple acoustic speeds in different mediums. Firstly, we get the size of infra-structure of the target by B-mode ultrasonic imaging method. Then we build the photoacoustic (PA) image of the same target with different acoustic speed in different medium. By repeatedly evaluate the quality of reconstruct PA image, we dynamically calibrate the acoustic speeds in different medium to build a finest PA image. Thus, we take these speeds of sound as the correct acoustic propagation velocities in according mediums. Experiments show that our non-invasive method can yield correct speed of sound with less than 0.3% error which might benefit future research in biomedical science.

  1. A quantitative reconstruction software suite for SPECT imaging

    Science.gov (United States)

    Namías, Mauro; Jeraj, Robert

    2017-11-01

    Quantitative Single Photon Emission Tomography (SPECT) imaging allows for measurement of activity concentrations of a given radiotracer in vivo. Although SPECT has usually been perceived as non-quantitative by the medical community, the introduction of accurate CT based attenuation correction and scatter correction from hybrid SPECT/CT scanners has enabled SPECT systems to be as quantitative as Positron Emission Tomography (PET) systems. We implemented a software suite to reconstruct quantitative SPECT images from hybrid or dedicated SPECT systems with a separate CT scanner. Attenuation, scatter and collimator response corrections were included in an Ordered Subset Expectation Maximization (OSEM) algorithm. A novel scatter fraction estimation technique was introduced. The SPECT/CT system was calibrated with a cylindrical phantom and quantitative accuracy was assessed with an anthropomorphic phantom and a NEMA/IEC image quality phantom. Accurate activity measurements were achieved at an organ level. This software suite helps increasing quantitative accuracy of SPECT scanners.

  2. Dynamic relaxation in algebraic reconstruction technique (ART) for breast tomosynthesis imaging.

    Science.gov (United States)

    Oliveira, N; Mota, A M; Matela, N; Janeiro, L; Almeida, P

    2016-08-01

    A major challenge in Digital Breast Tomosynthesis (DBT) is handling image noise since the 3D reconstructed images are obtained from low dose projections and limited angular range. The use of the iterative reconstruction algorithm Algebraic Reconstruction Technique (ART) in clinical context depends on two key factors: the number of iterations needed (time consuming) and the image noise after iterations. Both factors depend highly on a relaxation coefficient (λ), which may give rise to slow or noisy reconstructions, when a single λ value is considered for the entire iterative process. The aim of this work is to present a new implementation for the ART that takes into account a dynamic mode to calculate λ in DBT image reconstruction. A set of initial reconstructions of real phantom data was done using constant λ values. The results were used to choose, for each iteration, the suitable λ value, taking into account the image noise level and the convergence speed. A methodology to optimize λ automatically during the image reconstruction was proposed. Results showed we can dynamically choose λ values in such a way that the time needed to reconstruct the images can be significantly reduced (up to 70%) while achieving similar image quality. These results were confirmed with one clinical dataset. With simple methodology we were able to dynamically choose λ in DBT image reconstruction with ART, allowing a shorter image reconstruction time without increasing image noise. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. Local Surface Reconstruction from MER images using Stereo Workstation

    Science.gov (United States)

    Shin, Dongjoe; Muller, Jan-Peter

    2010-05-01

    The authors present a semi-automatic workflow that reconstructs the 3D shape of the martian surface from local stereo images delivered by PnCam or NavCam on systems such as the NASA Mars Exploration Rover (MER) Mission and in the future the ESA-NASA ExoMars rover PanCam. The process is initiated with manually selected tiepoints on a stereo workstation which is then followed by a tiepoint refinement, stereo-matching using region growing and Levenberg-Marquardt Algorithm (LMA)-based bundle adjustment processing. The stereo workstation, which is being developed by UCL in collaboration with colleagues at the Jet Propulsion Laboratory (JPL) within the EU FP7 ProVisG project, includes a set of practical GUI-based tools that enable an operator to define a visually correct tiepoint via a stereo display. To achieve platform and graphic hardware independence, the stereo application has been implemented using JPL's JADIS graphic library which is written in JAVA and the remaining processing blocks used in the reconstruction workflow have also been developed as a JAVA package to increase the code re-usability, portability and compatibility. Although initial tiepoints from the stereo workstation are reasonably acceptable as true correspondences, it is often required to employ an optional validity check and/or quality enhancing process. To meet this requirement, the workflow has been designed to include a tiepoint refinement process based on the Adaptive Least Square Correlation (ALSC) matching algorithm so that the initial tiepoints can be further enhanced to sub-pixel precision or rejected if they fail to pass the ALSC matching threshold. Apart from the accuracy of reconstruction, it is obvious that the other criterion to assess the quality of reconstruction is the density (or completeness) of reconstruction, which is not attained in the refinement process. Thus, we re-implemented a stereo region growing process, which is a core matching algorithm within the UCL

  4. Analysis of discrete-to-discrete imaging models for iterative tomographic image reconstruction and compressive sensing

    CERN Document Server

    Jørgensen, Jakob H; Pan, Xiaochuan

    2011-01-01

    Discrete-to-discrete imaging models for computed tomography (CT) are becoming increasingly ubiquitous as the interest in iterative image reconstruction algorithms has heightened. Despite this trend, all the intuition for algorithm and system design derives from analysis of continuous-to-continuous models such as the X-ray and Radon transform. While the similarity between these models justifies some crossover, questions such as what are sufficient sampling conditions can be quite different for the two models. This sampling issue is addressed extensively in the first half of the article using singular value decomposition analysis for determining sufficient number of views and detector bins. The question of full sampling for CT is particularly relevant to current attempts to adapt compressive sensing (CS) motivated methods to application in CT image reconstruction. The second half goes in depth on this subject and discusses the link between object sparsity and sufficient sampling for accurate reconstruction. Par...

  5. [Image reconstruction of conductivity on magnetoacoustic tomography with magnetic induction].

    Science.gov (United States)

    Li, Jingyu; Yin, Tao; Liu, Zhipeng; Xu, Guohui

    2010-04-01

    The electric characteristics such as impedance and conductivity of the organization will change in the case where pathological changes occurred in the biological tissue. The change in electric characteristics usually took place before the change in the density of tissues, and also, the difference in electric characteristics such as conductivity between normal tissue and pathological tissue is obvious. The method of magneto-acoustic tomography with magnetic induction is based on the theory of magnetic eddy current induction, the principle of vibration generation and acoustic transmission to get the boundary of the pathological tissue. The pathological change could be inspected by electricity characteristic imaging which is invasive to the tissue. In this study, a two-layer concentric spherical model is established to simulate the malignant tumor tissue surrounded by normal tissue mutual relations of the magneto-sound coupling effect and the coupling equations in the magnetic field are used to get the algorithms for reconstructing the conductivity. Simulation study is conducted to test the proposed model and validate the performance of the reconstructed algorithms. The result indicates that the use of signal processing method in this paper can image the conductivity boundaries of the sample in the scanning cross section. The computer simulating results validate the feasibility of applying the method of magneto-acoustic tomography with magnetic induction for malignant tumor imaging.

  6. Filtered gradient reconstruction algorithm for compressive spectral imaging

    Science.gov (United States)

    Mejia, Yuri; Arguello, Henry

    2017-04-01

    Compressive sensing matrices are traditionally based on random Gaussian and Bernoulli entries. Nevertheless, they are subject to physical constraints, and their structure unusually follows a dense matrix distribution, such as the case of the matrix related to compressive spectral imaging (CSI). The CSI matrix represents the integration of coded and shifted versions of the spectral bands. A spectral image can be recovered from CSI measurements by using iterative algorithms for linear inverse problems that minimize an objective function including a quadratic error term combined with a sparsity regularization term. However, current algorithms are slow because they do not exploit the structure and sparse characteristics of the CSI matrices. A gradient-based CSI reconstruction algorithm, which introduces a filtering step in each iteration of a conventional CSI reconstruction algorithm that yields improved image quality, is proposed. Motivated by the structure of the CSI matrix, Φ, this algorithm modifies the iterative solution such that it is forced to converge to a filtered version of the residual ΦTy, where y is the compressive measurement vector. We show that the filtered-based algorithm converges to better quality performance results than the unfiltered version. Simulation results highlight the relative performance gain over the existing iterative algorithms.

  7. Analysis of Interpolation Methods in the Image Reconstruction Tasks

    Directory of Open Access Journals (Sweden)

    V. T. Nguyen

    2017-01-01

    Full Text Available The article studies the interpolation methods used for image reconstruction. These methods were also implemented and tested with several images to estimate their effectiveness.The considered interpolation methods are a nearest-neighbor method, linear method, a cubic B-spline method, a cubic convolution method, and a Lanczos method. For each method were presented an interpolation kernel (interpolation function and a frequency response (Fourier transform.As a result of the experiment, the following conclusions were drawn:-         the nearest neighbor algorithm is very simple and often used. With using this method, the reconstructed images contain artifacts (blurring and haloing;-         the linear method is quickly and easily performed. It also reduces some visual distortion caused by changing image size. Despite the advantages using this method causes a large amount of interpolation artifacts, such as blurring and haloing;-         cubic B-spline method provides smoothness of reconstructed images and eliminates apparent ramp phenomenon. But in the interpolation process a low-pass filter is used, and a high frequency component is suppressed. This will lead to fuzzy edge and false artificial traces;-         cubic convolution method offers less distortion interpolation. But its algorithm is more complicated and more execution time is required as compared to the nearest-neighbor method and the linear method;-         using the Lanczos method allows us to achieve a high-definition image. In spite of the great advantage the method requires more execution time as compared to the other methods of interpolation.The result obtained not only shows a comparison of the considered interpolation methods for various aspects, but also enables users to select an appropriate interpolation method for their applications.It is advisable to study further the existing methods and develop new ones using a number of methods

  8. Quantitative image reconstruction for total-body PET imaging using the 2-meter long EXPLORER scanner.

    Science.gov (United States)

    Zhang, Xuezhu; Zhou, Jian; Cherry, Simon R; Badawi, Ramsey D; Qi, Jinyi

    2017-03-21

    The EXPLORER project aims to build a 2 meter long total-body PET scanner, which will provide extremely high sensitivity for imaging the entire human body. It will possess a range of capabilities currently unavailable to state-of-the-art clinical PET scanners with a limited axial field-of-view. The huge number of lines-of-response (LORs) of the EXPLORER poses a challenge to the data handling and image reconstruction. The objective of this study is to develop a quantitative image reconstruction method for the EXPLORER and compare its performance with current whole-body scanners. Fully 3D image reconstruction was performed using time-of-flight list-mode data with parallel computation. To recover the resolution loss caused by the parallax error between crystal pairs at a large axial ring difference or transaxial radial offset, we applied an image domain resolution model estimated from point source data. To evaluate the image quality, we conducted computer simulations using the SimSET Monte-Carlo toolkit and XCAT 2.0 anthropomorphic phantom to mimic a 20 min whole-body PET scan with an injection of 25 MBq 18 F-FDG. We compare the performance of the EXPLORER with a current clinical scanner that has an axial FOV of 22 cm. The comparison results demonstrated superior image quality from the EXPLORER with a 6.9-fold reduction in noise standard deviation comparing with multi-bed imaging using the clinical scanner.

  9. Quantitative image reconstruction for total-body PET imaging using the 2-meter long EXPLORER scanner

    Science.gov (United States)

    Zhang, Xuezhu; Zhou, Jian; Cherry, Simon R.; Badawi, Ramsey D.; Qi, Jinyi

    2017-03-01

    The EXPLORER project aims to build a 2 meter long total-body PET scanner, which will provide extremely high sensitivity for imaging the entire human body. It will possess a range of capabilities currently unavailable to state-of-the-art clinical PET scanners with a limited axial field-of-view. The huge number of lines-of-response (LORs) of the EXPLORER poses a challenge to the data handling and image reconstruction. The objective of this study is to develop a quantitative image reconstruction method for the EXPLORER and compare its performance with current whole-body scanners. Fully 3D image reconstruction was performed using time-of-flight list-mode data with parallel computation. To recover the resolution loss caused by the parallax error between crystal pairs at a large axial ring difference or transaxial radial offset, we applied an image domain resolution model estimated from point source data. To evaluate the image quality, we conducted computer simulations using the SimSET Monte-Carlo toolkit and XCAT 2.0 anthropomorphic phantom to mimic a 20 min whole-body PET scan with an injection of 25 MBq 18F-FDG. We compare the performance of the EXPLORER with a current clinical scanner that has an axial FOV of 22 cm. The comparison results demonstrated superior image quality from the EXPLORER with a 6.9-fold reduction in noise standard deviation comparing with multi-bed imaging using the clinical scanner.

  10. Detail displaying difference of the digital holographic reconstructed image between the convolution algorithm and Fresnel algorithm.

    Science.gov (United States)

    Zhong, Liyun; Li, Hongyan; Tao, Tao; Zhang, Zhun; Lu, Xiaoxu

    2011-11-07

    To reach the limiting resolution of a digital holographic system and improve the displaying quality of the reconstructed image, the subdivision convolution algorithm and the subdivision Fresnel algorithm are presented, respectively. The obtained results show that the lateral size of the reconstructed image obtained by two kinds of subdivision algorithms is the same in the central region of the reconstructed image-plane; moreover, the size of the central region is in proportional to the recording distance. Importantly, in the central region of the reconstructed image-plane, the reconstruction can be performed by the subdivision Fresnel algorithm instead of the subdivision convolution algorithm effectively, and, based on these subdivision approaches, both the displaying quality and the resolution of the reconstructed image can be improved significantly. Furthermore, in the reconstruction of the digital hologram with the large numerical aperture, the computer's memory consumed and the calculating time resulting from the subdivision Fresnel algorithm is significantly less than those from the subdivision convolution algorithm.

  11. Reconstruction algorithm medical imaging DRR; Algoritmo de construccion de imagenes medicas DRR

    Energy Technology Data Exchange (ETDEWEB)

    Estrada Espinosa, J. C.

    2013-07-01

    The method of reconstruction for digital radiographic Imaging (DRR), is based on two orthogonal images, on the dorsal and lateral decubitus position of the simulation. DRR images are reconstructed with an algorithm that simulates running a conventional X-ray, a single rendition team, beam emitted is not divergent, in this case, the rays are considered to be parallel in the image reconstruction DRR, for this purpose, it is necessary to use all the values of the units (HU) hounsfield of each voxel in all axial cuts that form the study TC, finally obtaining the reconstructed image DRR performing a transformation from 3D to 2D. (Author)

  12. Combined use of iterative reconstruction and monochromatic imaging in spinal fusion CT images.

    Science.gov (United States)

    Wang, Fengdan; Zhang, Yan; Xue, Huadan; Han, Wei; Yang, Xianda; Jin, Zhengyu; Zwar, Richard

    2017-01-01

    Spinal fusion surgery is an important procedure for treating spinal diseases and computed tomography (CT) is a critical tool for postoperative evaluation. However, CT image quality is considerably impaired by metal artifacts and image noise. To explore whether metal artifacts and image noise can be reduced by combining two technologies, adaptive statistical iterative reconstruction (ASIR) and monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. A total of 51 patients with 318 spinal pedicle screws were prospectively scanned by dual-energy CT using fast kV-switching GSI between 80 and 140 kVp. Monochromatic GSI images at 110 keV were reconstructed either without or with various levels of ASIR (30%, 50%, 70%, and 100%). The quality of five sets of images was objectively and subjectively assessed. With objective image quality assessment, metal artifacts decreased when increasing levels of ASIR were applied (P ASIR to GSI also decreased image noise (P ASIR levels (P ASIR and GSI decreased image noise and improved image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels ≥70%. © The Foundation Acta Radiologica 2016.

  13. Iterative PET Image Reconstruction Using Translation Invariant Wavelet Transform.

    Science.gov (United States)

    Zhou, Jian; Senhadji, Lotfi; Coatrieux, Jean-Louis; Luo, Limin

    2009-02-01

    The present work describes a Bayesian maximum a posteriori (MAP) method using a statistical multiscale wavelet prior model. Rather than using the orthogonal discrete wavelet transform (DWT), this prior is built on the translation invariant wavelet transform (TIWT). The statistical modeling of wavelet coefficients relies on the generalized Gaussian distribution. Image reconstruction is performed in spatial domain with a fast block sequential iteration algorithm. We study theoretically the TIWT MAP method by analyzing the Hessian of the prior function to provide some insights on noise and resolution properties of image reconstruction. We adapt the key concept of local shift invariance and explore how the TIWT MAP algorithm behaves with different scales. It is also shown that larger support wavelet filters do not offer better performance in contrast recovery studies. These theoretical developments are confirmed through simulation studies. The results show that the proposed method is more attractive than other MAP methods using either the conventional Gibbs prior or the DWT-based wavelet prior.

  14. 3D Image Reconstruction from X-Ray Measurements with Overlap

    CERN Document Server

    Klodt, Maria

    2016-01-01

    3D image reconstruction from a set of X-ray projections is an important image reconstruction problem, with applications in medical imaging, industrial inspection and airport security. The innovation of X-ray emitter arrays allows for a novel type of X-ray scanners with multiple simultaneously emitting sources. However, two or more sources emitting at the same time can yield measurements from overlapping rays, imposing a new type of image reconstruction problem based on nonlinear constraints. Using traditional linear reconstruction methods, respective scanner geometries have to be implemented such that no rays overlap, which severely restricts the scanner design. We derive a new type of 3D image reconstruction model with nonlinear constraints, based on measurements with overlapping X-rays. Further, we show that the arising optimization problem is partially convex, and present an algorithm to solve it. Experiments show highly improved image reconstruction results from both simulated and real-world measurements.

  15. Improvement of image quality and dose management in CT fluoroscopy by iterative 3D image reconstruction.

    Science.gov (United States)

    Grosser, Oliver S; Wybranski, Christian; Kupitz, Dennis; Powerski, Maciej; Mohnike, Konrad; Pech, Maciej; Amthauer, Holger; Ricke, Jens

    2017-09-01

    The objective of this study was to assess the influence of an iterative CT reconstruction algorithm (IA), newly available for CT-fluoroscopy (CTF), on image noise, readers' confidence and effective dose compared to filtered back projection (FBP). Data from 165 patients (FBP/IA = 82/74) with CTF in the thorax, abdomen and pelvis were included. Noise was analysed in a large-diameter vessel. The impact of reconstruction and variables (e.g. X-ray tube current I) influencing noise and effective dose were analysed by ANOVA and a pairwise t-test with Bonferroni-Holm correction. Noise and readers' confidence were evaluated by three readers. Noise was significantly influenced by reconstruction, I, body region and circumference (all p ≤ 0.0002). IA reduced the noise significantly compared to FBP (p = 0.02). The effect varied for body regions and circumferences (p ≤ 0.001). The effective dose was influenced by the reconstruction, body region, interventional procedure and I (all p ≤ 0.02). The inter-rater reliability for noise and readers' confidence was good (W ≥ 0.75, p confidence were significantly better in AIDR-3D compared to FBP (p ≤ 0.03). Generally, IA yielded a significant reduction of the median effective dose. The CTF reconstruction by IA showed a significant reduction in noise and effective dose while readers' confidence increased. • CTF is performed for image guidance in interventional radiology. • Patient exposure was estimated from DLP documented by the CT. • Iterative CT reconstruction is appropriate to reduce image noise in CTF. • Using iterative CT reconstruction, the effective dose was significantly reduced in abdominal interventions.

  16. A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.

    Science.gov (United States)

    Konkle, Justin J; Goodwill, Patrick W; Hensley, Daniel W; Orendorff, Ryan D; Lustig, Michael; Conolly, Steven M

    2015-01-01

    Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.

  17. TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT.

    Science.gov (United States)

    Liu, Jiulong; Ding, Huanjun; Molloi, Sabee; Zhang, Xiaoqun; Gao, Hao

    2016-12-01

    This work develops a material reconstruction method for spectral CT, namely Total Image Constrained Material Reconstruction (TICMR), to maximize the utility of projection data in terms of both spectral information and high signal-to-noise ratio (SNR). This is motivated by the following fact: when viewed as a spectrally-integrated measurement, the projection data can be used to reconstruct a total image without spectral information, which however has a relatively high SNR; when viewed as a spectrally-resolved measurement, the projection data can be utilized to reconstruct the material composition, which however has a relatively low SNR. The material reconstruction synergizes material decomposition and image reconstruction, i.e., the direct reconstruction of material compositions instead of a two-step procedure that first reconstructs images and then decomposes images. For material reconstruction with high SNR, we propose TICMR with nonlocal total variation (NLTV) regularization. That is, first we reconstruct a total image using spectrally-integrated measurement without spectral binning, and build the NLTV weights from this image that characterize nonlocal image features; then the NLTV weights are incorporated into a NLTV-based iterative material reconstruction scheme using spectrally-binned projection data, so that these weights serve as a high-SNR reference to regularize material reconstruction. Note that the nonlocal property of NLTV is essential for material reconstruction, since material compositions may have significant local intensity variations although their structural information is often similar. In terms of solution algorithm, TICMR is formulated as an iterative reconstruction method with the NLTV regularization, in which the nonlocal divergence is utilized based on the adjoint relationship. The alternating direction method of multipliers is developed to solve this sparsity optimization problem. The proposed TICMR method was validated using both simulated

  18. Computed tomography image source identification by discriminating CT-scanner image reconstruction process.

    Science.gov (United States)

    Duan, Y; Coatrieux, G; Shu, H Z

    2015-08-01

    In this paper, we focus on the identification of the Computed Tomography (CT) scanner that has produced a CT image. To do so, we propose to discriminate CT-Scanner systems based on their reconstruction process, the footprint or the signature of which can be established based on the way they modify the intrinsic sensor noise of X-ray detectors. After having analyzed how the sensor noise is modified in the reconstruction process, we define a set of image features so as to serve as CT acquisition system footprint. These features are used to train a SVM based classifier. Experiments conducted on images issued from 15 different CT-Scanner models of 4 distinct manufacturers show it is possible to identify the origin of one CT image with high accuracy.

  19. Images from the Mind: BCI image reconstruction based on Rapid Serial Visual Presentations of polygon primitives

    Directory of Open Access Journals (Sweden)

    Luís F Seoane

    2015-04-01

    Full Text Available We provide a proof of concept for an EEG-based reconstruction of a visual image which is on a user's mind. Our approach is based on the Rapid Serial Visual Presentation (RSVP of polygon primitives and Brain-Computer Interface (BCI technology. In an experimental setup, subjects were presented bursts of polygons: some of them contributed to building a target image (because they matched the shape and/or color of the target while some of them did not. The presentation of the contributing polygons triggered attention-related EEG patterns. These Event Related Potentials (ERPs could be determined using BCI classification and could be matched to the stimuli that elicited them. These stimuli (i.e. the ERP-correlated polygons were accumulated in the display until a satisfactory reconstruction of the target image was reached. As more polygons were accumulated, finer visual details were attained resulting in more challenging classification tasks. In our experiments, we observe an average classification accuracy of around 75%. An in-depth investigation suggests that many of the misclassifications were not misinterpretations of the BCI concerning the users' intent, but rather caused by ambiguous polygons that could contribute to reconstruct several different images. When we put our BCI-image reconstruction in perspective with other RSVP BCI paradigms, there is large room for improvement both in speed and accuracy. These results invite us to be optimistic. They open a plethora of possibilities to explore non-invasive BCIs for image reconstruction both in healthy and impaired subjects and, accordingly, suggest interesting recreational and clinical applications.

  20. SPIRiT: Iterative Self-consistent Parallel Imaging Reconstruction from Arbitrary k-Space

    Science.gov (United States)

    Lustig, Michael; Pauly, John M.

    2010-01-01

    A new approach to autocalibrating, coil-by-coil parallel imaging reconstruction is presented. It is a generalized reconstruction framework based on self consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k-space sampling patterns. The formulation can flexibly incorporate additional image priors such as off-resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k-space domain are presented. These are based on a projection over convex sets (POCS) and a conjugate gradient (CG) algorithms. Phantom and in-vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off-resonance correction and nonlinear ℓ1-wavelet regularization are also demonstrated. PMID:20665790

  1. AN IMAGE-BASED TECHNIQUE FOR 3D BUILDING RECONSTRUCTION USING MULTI-VIEW UAV IMAGES

    OpenAIRE

    F. Alidoost; H. Arefi

    2015-01-01

    Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs) images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud gen...

  2. Comparison of clinical and physics scoring of PET images when image reconstruction parameters are varied.

    Science.gov (United States)

    Walsh, C; Johnston, C; Sheehy, N; O' Reilly, G

    2013-02-01

    In this study the quantitative and qualitative image quality (IQ) measurements with clinical judgement of IQ in positron emission tomography (PET) were compared. The limitations of IQ metrics and the proposed criteria of acceptability for PET scanners are discussed. Phantom and patient images were reconstructed using seven different iterative reconstruction protocols. For each reconstructed set of images, IQ was scored based both on the visual analysis and on the quantitative metrics. The quantitative physics metrics did not rank the reconstruction protocols in the same order as the clinicians' scoring of perceived IQ (R(s)=-0.54). Better agreement was achieved when comparing the clinical perception of IQ to the physicist's visual assessment of IQ in the phantom images (R(s)=+0.59). The closest agreement was seen between the quantitative physics metrics and the measurement of the standard uptake values (SUVs) in small tumours (R(s)=+0.92). Given the disparity between the clinical perception of IQ and the physics metrics a cautious approach to use of IQ measurements for determining suspension levels is warranted.

  3. Resolution enhanced 3D image reconstruction by use of ray tracing and auto-focus in computational integral imaging

    Science.gov (United States)

    Yuan, Ying; Yu, Shuo; Wang, Xiaorui; Zhang, Jianlei

    2017-12-01

    We propose a three-dimensional (3D) image reconstruction algorithm that can computationally reconstruct the light field image with enhanced resolution. This method is based on ray tracing and can reconstruct the elemental images from arbitrary viewpoints. In the conventional integral imaging reconstruction process, a plane needs to be selected to make the reconstructed image in focus, so prior knowledge is required. Auto-focus (AF) of the digital camera is applied in the integral imaging reconstruction process and the optimal reconstruction plane can be selected automatically without any prior knowledge. Thus, the integral imaging system can record the light field of 3D scene without focusing on them and image focusing will be completed in the computational post-processing process. To our knowledge, this is the first time to apply auto-focus method to 3D integral imaging reconstruction. Furthermore, the depth-of-field can be controlled by adjusting the transmission angle of light ray from the elemental images. Experimental results are presented to demonstrate the feasibility and effectiveness of the proposed method.

  4. Muscle Activity Map Reconstruction from High Density Surface EMG Signals With Missing Channels Using Image Inpainting and Surface Reconstruction Methods.

    Science.gov (United States)

    Ghaderi, Parviz; Marateb, Hamid R

    2017-07-01

    The aim of this study was to reconstruct low-quality High-density surface EMG (HDsEMG) signals, recorded with 2-D electrode arrays, using image inpainting and surface reconstruction methods. It is common that some fraction of the electrodes may provide low-quality signals. We used variety of image inpainting methods, based on partial differential equations (PDEs), and surface reconstruction methods to reconstruct the time-averaged or instantaneous muscle activity maps of those outlier channels. Two novel reconstruction algorithms were also proposed. HDsEMG signals were recorded from the biceps femoris and brachial biceps muscles during low-to-moderate-level isometric contractions, and some of the channels (5-25%) were randomly marked as outliers. The root-mean-square error (RMSE) between the original and reconstructed maps was then calculated. Overall, the proposed Poisson and wave PDE outperformed the other methods (average RMSE 8.7 μVrms ± 6.1 μVrms and 7.5 μVrms ± 5.9 μVrms) for the time-averaged single-differential and monopolar map reconstruction, respectively. Biharmonic Spline, the discrete cosine transform, and the Poisson PDE outperformed the other methods for the instantaneous map reconstruction. The running time of the proposed Poisson and wave PDE methods, implemented using a Vectorization package, was 4.6 ± 5.7 ms and 0.6 ± 0.5 ms, respectively, for each signal epoch or time sample in each channel. The proposed reconstruction algorithms could be promising new tools for reconstructing muscle activity maps in real-time applications. Proper reconstruction methods could recover the information of low-quality recorded channels in HDsEMG signals.

  5. Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer.

    Science.gov (United States)

    Knoll, Florian; Holler, Martin; Koesters, Thomas; Otazo, Ricardo; Bredies, Kristian; Sodickson, Daniel K

    2017-01-01

    While current state of the art MR-PET scanners enable simultaneous MR and PET measurements, the acquired data sets are still usually reconstructed separately. We propose a new multi-modality reconstruction framework using second order Total Generalized Variation (TGV) as a dedicated multi-channel regularization functional that jointly reconstructs images from both modalities. In this way, information about the underlying anatomy is shared during the image reconstruction process while unique differences are preserved. Results from numerical simulations and in-vivo experiments using a range of accelerated MR acquisitions and different MR image contrasts demonstrate improved PET image quality, resolution, and quantitative accuracy.

  6. Impact of model-based iterative reconstruction on image quality of contrast-enhanced neck CT.

    Science.gov (United States)

    Gaddikeri, S; Andre, J B; Benjert, J; Hippe, D S; Anzai, Y

    2015-02-01

    Improved image quality is clinically desired for contrast-enhanced CT of the neck. We compared 30% adaptive statistical iterative reconstruction and model-based iterative reconstruction algorithms for the assessment of image quality of contrast-enhanced CT of the neck. Neck contrast-enhanced CT data from 64 consecutive patients were reconstructed retrospectively by using 30% adaptive statistical iterative reconstruction and model-based iterative reconstruction. Objective image quality was assessed by comparing SNR, contrast-to-noise ratio, and background noise at levels 1 (mandible) and 2 (superior mediastinum). Two independent blinded readers subjectively graded the image quality on a scale of 1-5, (grade 5 = excellent image quality without artifacts and grade 1 = nondiagnostic image quality with significant artifacts). The percentage of agreement and disagreement between the 2 readers was assessed. Compared with 30% adaptive statistical iterative reconstruction, model-based iterative reconstruction significantly improved the SNR and contrast-to-noise ratio at levels 1 and 2. Model-based iterative reconstruction also decreased background noise at level 1 (P = .016), though there was no difference at level 2 (P = .61). Model-based iterative reconstruction was scored higher than 30% adaptive statistical iterative reconstruction by both reviewers at the nasopharynx (P iterative reconstruction. Model-based iterative reconstruction offers improved subjective and objective image quality as evidenced by a higher SNR and contrast-to-noise ratio and lower background noise within the same dataset for contrast-enhanced neck CT. Model-based iterative reconstruction has the potential to reduce the radiation dose while maintaining the image quality, with a minor downside being prominent artifacts related to thyroid shield use on model-based iterative reconstruction. © 2015 by American Journal of Neuroradiology.

  7. An adaptive total variation image reconstruction method for speckles through disordered media

    Science.gov (United States)

    Gong, Changmei; Shao, Xiaopeng; Wu, Tengfei

    2013-09-01

    Multiple scattering of light in highly disordered medium can break the diffraction limit of conventional optical system combined with image reconstruction method. Once the transmission matrix of the imaging system is obtained, the target image can be reconstructed from its speckle pattern by image reconstruction algorithm. Nevertheless, the restored image attained by common image reconstruction algorithms such as Tikhonov regularization has a relatively low signal-tonoise ratio (SNR) due to the experimental noise and reconstruction noise, greatly reducing the quality of the result image. In this paper, the speckle pattern of the test image is simulated by the combination of light propagation theories and statistical optics theories. Subsequently, an adaptive total variation (ATV) algorithm—the TV minimization by augmented Lagrangian and alternating direction algorithms (TVAL3), which is based on augmented Lagrangian and alternating direction algorithm, is utilized to reconstruct the target image. Numerical simulation experimental results show that, the TVAL3 algorithm can effectively suppress the noise of the restored image and preserve more image details, thus greatly boosts the SNR of the restored image. It also indicates that, compared with the image directly formed by `clean' system, the reconstructed results can overcoming the diffraction limit of the `clean' system, therefore being conductive to the observation of cells and protein molecules in biological tissues and other structures in micro/nano scale.

  8. 2-D Fused Image Reconstruction approach for Microwave Tomography: a theoretical assessment using FDTD Model.

    Science.gov (United States)

    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.

  9. Time Reversal Reconstruction Algorithm Based on PSO Optimized SVM Interpolation for Photoacoustic Imaging

    Directory of Open Access Journals (Sweden)

    Mingjian Sun

    2015-01-01

    Full Text Available Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO optimized support vector machine (SVM interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.

  10. Image reconstruction for a Positron Emission Tomograph optimized for breast cancer imaging

    Energy Technology Data Exchange (ETDEWEB)

    Virador, Patrick R.G. [Univ. of California, Berkeley, CA (United States)

    2000-04-01

    The author performs image reconstruction for a novel Positron Emission Tomography camera that is optimized for breast cancer imaging. This work addresses for the first time, the problem of fully-3D, tomographic reconstruction using a septa-less, stationary, (i.e. no rotation or linear motion), and rectangular camera whose Field of View (FOV) encompasses the entire volume enclosed by detector modules capable of measuring Depth of Interaction (DOI) information. The camera is rectangular in shape in order to accommodate breasts of varying sizes while allowing for soft compression of the breast during the scan. This non-standard geometry of the camera exacerbates two problems: (a) radial elongation due to crystal penetration and (b) reconstructing images from irregularly sampled data. Packing considerations also give rise to regions in projection space that are not sampled which lead to missing information. The author presents new Fourier Methods based image reconstruction algorithms that incorporate DOI information and accommodate the irregular sampling of the camera in a consistent manner by defining lines of responses (LORs) between the measured interaction points instead of rebinning the events into predefined crystal face LORs which is the only other method to handle DOI information proposed thus far. The new procedures maximize the use of the increased sampling provided by the DOI while minimizing interpolation in the data. The new algorithms use fixed-width evenly spaced radial bins in order to take advantage of the speed of the Fast Fourier Transform (FFT), which necessitates the use of irregular angular sampling in order to minimize the number of unnormalizable Zero-Efficiency Bins (ZEBs). In order to address the persisting ZEBs and the issue of missing information originating from packing considerations, the algorithms (a) perform nearest neighbor smoothing in 2D in the radial bins (b) employ a semi-iterative procedure in order to estimate the unsampled data

  11. Improved Liver Lesion Conspicuity With Iterative Reconstruction in Computed Tomography Imaging.

    Science.gov (United States)

    Jensen, Kristin; Andersen, Hilde Kjernlie; Tingberg, Anders; Reisse, Claudius; Fosse, Erik; Martinsen, Anne Catrine T

    2016-01-01

    Studies on iterative reconstruction techniques on computed tomographic (CT) scanners show reduced noise and changed image texture. The purpose of this study was to address the possibility of dose reduction and improved conspicuity of lesions in a liver phantom for different iterative reconstruction algorithms. An anthropomorphic upper abdomen phantom, specially designed for receiver operating characteristic analysis was scanned with 2 different CT models from the same vendor, GE CT750 HD and GE Lightspeed VCT. Images were obtained at 3 dose levels, 5, 10, and 15mGy, and reconstructed with filtered back projection (FBP), and 2 different iterative reconstruction algorithms; adaptive statistical iterative reconstruction and Veo. Overall, 5 interpreters evaluated the images and receiver operating characteristic analysis was performed. Standard deviation and the contrast to noise ratio were measured. Veo image reconstruction resulted in larger area under curves compared with those adaptive statistical iterative reconstruction and FBP image reconstruction for given dose levels. For the CT750 HD, iterative reconstruction at the 10mGy dose level resulted in larger or similar area under curves compared with FBP at the 15mGy dose level (0.88-0.95 vs 0.90). This was not shown for the Lightspeed VCT (0.83-0.85 vs 0.92). The results in this study indicate that the possibility for radiation dose reduction using iterative reconstruction techniques depends on both reconstruction technique and the CT scanner model used. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Interface-sensitive imaging by an image reconstruction aided X-ray reflectivity technique1

    Science.gov (United States)

    Hirano, Keiichi

    2017-01-01

    Recently, the authors have succeeded in realizing X-ray reflectivity imaging of heterogeneous ultrathin films at specific wavevector transfers by applying a wide parallel beam and an area detector. By combining in-plane angle and grazing-incidence angle scans, it is possible to reconstruct a series of interface-sensitive X-ray reflectivity images at different grazing-incidence angles (proportional to wavevector transfers). The physical meaning of a reconstructed X-ray reflectivity image at a specific wavevector transfer is the two-dimensional reflectivity distribution of the sample. In this manner, it is possible to retrieve the micro-X-ray reflectivity (where the pixel size is on the microscale) profiles at different local positions on the sample. PMID:28656036

  13. Interface-sensitive imaging by an image reconstruction aided X-ray reflectivity technique.

    Science.gov (United States)

    Jiang, Jinxing; Hirano, Keiichi; Sakurai, Kenji

    2017-06-01

    Recently, the authors have succeeded in realizing X-ray reflectivity imaging of heterogeneous ultrathin films at specific wavevector transfers by applying a wide parallel beam and an area detector. By combining in-plane angle and grazing-incidence angle scans, it is possible to reconstruct a series of interface-sensitive X-ray reflectivity images at different grazing-incidence angles (proportional to wavevector transfers). The physical meaning of a reconstructed X-ray reflectivity image at a specific wavevector transfer is the two-dimensional reflectivity distribution of the sample. In this manner, it is possible to retrieve the micro-X-ray reflectivity (where the pixel size is on the microscale) profiles at different local positions on the sample.

  14. Exploring the Nuclear Landscape by Image Reconstruction Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Morales, I.; Mendoza T, J.; Lopez V, J.C.; Barea, J.; Hirsch, J.G.; Frank, A. [Instituto de Ciencias Nucleares, UNAM, AP 70-543, 04510 Mexico D.F. (Mexico); Velazquez, V. [Departamento de Fisica, Facultad de Ciencias, UNAM, AP 70-348, 04511 Mexico D.F. (Mexico)]. e-mail: frank@nucleares.unam.mx

    2007-12-15

    In spite of the development of ever more elaborate techniques for the calculation of nuclear properties, the calculation of the most basic property of atomic nuclei, their mass, still represents a challenging task. The differences between measured masses and Liquid Drop Model (LDM) predictions have well known regularities. They contain information related to shell closures, nuclear deformation and the residual nuclear interactions, and display a well defined pattern, which can be viewed as a two-dimensional image. In the present work the more than 2000 known nuclear masses are studied as an array in the N-Z plane viewed through a mask, behind which the approximately 7000 unknown unstable nuclei that can exist between the proton and neutron drip lines are hidden. Employing a Fourier transform deconvolution method these masses can be predicted. Measured masses are reconstructed with and r.m.s. error of less than 100 keV. Potential applications of the present approach are outlined. (Author)

  15. Cardiovascular CT angiography in neonates and children : Image quality and potential for radiation dose reduction with iterative image reconstruction techniques

    NARCIS (Netherlands)

    Tricarico, Francesco; Hlavacek, Anthony M.; Schoepf, U. Joseph; Ebersberger, Ullrich; Nance, John W.; Vliegenthart, Rozemarijn; Cho, Young Jun; Spears, J. Reid; Secchi, Francesco; Savino, Giancarlo; Marano, Riccardo; Schoenberg, Stefan O.; Bonomo, Lorenzo; Apfaltrer, Paul

    To evaluate image quality (IQ) of low-radiation-dose paediatric cardiovascular CT angiography (CTA), comparing iterative reconstruction in image space (IRIS) and sinogram-affirmed iterative reconstruction (SAFIRE) with filtered back-projection (FBP) and estimate the potential for further dose

  16. Molecular Imaging : Computer Reconstruction and Practice - Proceedings of the NATO Advanced Study Institute on Molecular Imaging from Physical Principles to Computer Reconstruction and Practice

    CERN Document Server

    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...

  17. Optimization-based image reconstruction with artifact reduction in C-arm CBCT

    Science.gov (United States)

    Xia, Dan; Langan, David A.; Solomon, Stephen B.; Zhang, Zheng; Chen, Buxin; Lai, Hao; Sidky, Emil Y.; Pan, Xiaochuan

    2016-10-01

    We investigate an optimization-based reconstruction, with an emphasis on image-artifact reduction, from data collected in C-arm cone-beam computed tomography (CBCT) employed in image-guided interventional procedures. In the study, an image to be reconstructed is formulated as a solution to a convex optimization program in which a weighted data divergence is minimized subject to a constraint on the image total variation (TV); a data-derivative fidelity is introduced in the program specifically for effectively suppressing dominant, low-frequency data artifact caused by, e.g. data truncation; and the Chambolle-Pock (CP) algorithm is tailored to reconstruct an image through solving the program. Like any other reconstructions, the optimization-based reconstruction considered depends upon numerous parameters. We elucidate the parameters, illustrate their determination, and demonstrate their impact on the reconstruction. The optimization-based reconstruction, when applied to data collected from swine and patient subjects, yields images with visibly reduced artifacts in contrast to the reference reconstruction, and it also appears to exhibit a high degree of robustness against distinctively different anatomies of imaged subjects and scanning conditions of clinical significance. Knowledge and insights gained in the study may be exploited for aiding in the design of practical reconstructions of truly clinical-application utility.

  18. Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR)

    Energy Technology Data Exchange (ETDEWEB)

    Notohamiprodjo, S.; Deak, Z.; Meurer, F.; Maertz, F.; Mueck, F.G.; Geyer, L.L.; Wirth, S. [Ludwig-Maximilians University Hospital of Munich, Institute for Clinical Radiology, Munich (Germany)

    2015-01-15

    The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01). MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. (orig.)

  19. Optoacoustic Imaging and Tomography: Reconstruction Approaches and Outstanding Challenges in Image Performance and Quantification

    Directory of Open Access Journals (Sweden)

    Daniel Razansky

    2013-06-01

    Full Text Available This paper comprehensively reviews the emerging topic of optoacoustic imaging from the image reconstruction and quantification perspective. Optoacoustic imaging combines highly attractive features, including rich contrast and high versatility in sensing diverse biological targets, excellent spatial resolution not compromised by light scattering, and relatively low cost of implementation. Yet, living objects present a complex target for optoacoustic imaging due to the presence of a highly heterogeneous tissue background in the form of strong spatial variations of scattering and absorption. Extracting quantified information on the actual distribution of tissue chromophores and other biomarkers constitutes therefore a challenging problem. Image quantification is further compromised by some frequently-used approximated inversion formulae. In this review, the currently available optoacoustic image reconstruction and quantification approaches are assessed, including back-projection and model-based inversion algorithms, sparse signal representation, wavelet-based approaches, methods for reduction of acoustic artifacts as well as multi-spectral methods for visualization of tissue bio-markers. Applicability of the different methodologies is further analyzed in the context of real-life performance in small animal and clinical in-vivo imaging scenarios.

  20. Postoperative evaluation after anterior cruciate ligament reconstruction: Measurements and abnormalities on radiographic and CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Cheol; Choi, Yun Sun; KIm, Hyoung Seop; Choi, Nam Hong [Nowon Eulji Medical Center, Eulji University, Seoul (Korea, Republic of)

    2016-11-15

    Reconstruction of a ruptured anterior cruciate ligament (ACL) is a well-established procedure for repair of ACL injury. Despite improvement of surgical and rehabilitation techniques over the past decades, up to 25% of patients still fail to regain satisfactory function after an ACL reconstruction. With development of CT imaging techniques for reducing metal artifacts, multi-planar reconstruction, and three-dimensional reconstruction, early post-operative imaging is increasingly being used to provide immediate feedback to surgeons regarding tunnel positioning, fixation, and device placement. Early post-operative radiography and CT imaging are easy to perform and serve as the baseline examinations for future reference.

  1. CT Image Reconstruction from Sparse Projections Using Adaptive TpV Regularization

    Directory of Open Access Journals (Sweden)

    Hongliang Qi

    2015-01-01

    Full Text Available Radiation dose reduction without losing CT image quality has been an increasing concern. Reducing the number of X-ray projections to reconstruct CT images, which is also called sparse-projection reconstruction, can potentially avoid excessive dose delivered to patients in CT examination. To overcome the disadvantages of total variation (TV minimization method, in this work we introduce a novel adaptive TpV regularization into sparse-projection image reconstruction and use FISTA technique to accelerate iterative convergence. The numerical experiments demonstrate that the proposed method suppresses noise and artifacts more efficiently, and preserves structure information better than other existing reconstruction methods.

  2. Postoperative Evaluation after Anterior Cruciate Ligament Reconstruction: Measurements and Abnormalities on Radiographic and CT Imaging.

    Science.gov (United States)

    Kim, Minchul; Choi, Yun Sun; Kim, Hyoungseop; Choi, Nam-Hong

    2016-01-01

    Reconstruction of a ruptured anterior cruciate ligament (ACL) is a well-established procedure for repair of ACL injury. Despite improvement of surgical and rehabilitation techniques over the past decades, up to 25% of patients still fail to regain satisfactory function after an ACL reconstruction. With development of CT imaging techniques for reducing metal artifacts, multi-planar reconstruction, and three-dimensional reconstruction, early post-operative imaging is increasingly being used to provide immediate feedback to surgeons regarding tunnel positioning, fixation, and device placement. Early post-operative radiography and CT imaging are easy to perform and serve as the baseline examinations for future reference.

  3. Research on assessment and improvement method of remote sensing image reconstruction

    Science.gov (United States)

    Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

    2018-01-01

    Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

  4. Research on super-resolution image reconstruction based on an improved POCS algorithm

    Science.gov (United States)

    Xu, Haiming; Miao, Hong; Yang, Chong; Xiong, Cheng

    2015-07-01

    Super-resolution image reconstruction (SRIR) can improve the fuzzy image's resolution; solve the shortage of the spatial resolution, excessive noise, and low-quality problem of the image. Firstly, we introduce the image degradation model to reveal the essence of super-resolution reconstruction process is an ill-posed inverse problem in mathematics. Secondly, analysis the blurring reason of optical imaging process - light diffraction and small angle scattering is the main reason for the fuzzy; propose an image point spread function estimation method and an improved projection onto convex sets (POCS) algorithm which indicate effectiveness by analyzing the changes between the time domain and frequency domain algorithm in the reconstruction process, pointed out that the improved POCS algorithms based on prior knowledge have the effect to restore and approach the high frequency of original image scene. Finally, we apply the algorithm to reconstruct synchrotron radiation computer tomography (SRCT) image, and then use these images to reconstruct the three-dimensional slice images. Comparing the differences between the original method and super-resolution algorithm, it is obvious that the improved POCS algorithm can restrain the noise and enhance the image resolution, so it is indicated that the algorithm is effective. This study and exploration to super-resolution image reconstruction by improved POCS algorithm is proved to be an effective method. It has important significance and broad application prospects - for example, CT medical image processing and SRCT ceramic sintering analyze of microstructure evolution mechanism.

  5. Evaluating image reconstruction methods for tumor detection performance in whole-body PET oncology imaging

    Science.gov (United States)

    Lartizien, Carole; Kinahan, Paul E.; Comtat, Claude; Lin, Michael; Swensson, Richard G.; Trebossen, Regine; Bendriem, Bernard

    2000-04-01

    This work presents initial results from observer detection performance studies using the same volume visualization software tools that are used in clinical PET oncology imaging. Research into the FORE+OSEM and FORE+AWOSEM statistical image reconstruction methods tailored to whole- body 3D PET oncology imaging have indicated potential improvements in image SNR compared to currently used analytic reconstruction methods (FBP). To assess the resulting impact of these reconstruction methods on the performance of human observers in detecting and localizing tumors, we use a non- Monte Carlo technique to generate multiple statistically accurate realizations of 3D whole-body PET data, based on an extended MCAT phantom and with clinically realistic levels of statistical noise. For each realization, we add a fixed number of randomly located 1 cm diam. lesions whose contrast is varied among pre-calibrated values so that the range of true positive fractions is well sampled. The observer is told the number of tumors and, similar to the AFROC method, asked to localize all of them. The true positive fraction for the three algorithms (FBP, FORE+OSEM, FORE+AWOSEM) as a function of lesion contrast is calculated, although other protocols could be compared. A confidence level for each tumor is also recorded for incorporation into later AFROC analysis.

  6. A two-step filtering-based iterative image reconstruction method for interior tomography.

    Science.gov (United States)

    Zhang, Hanming; Li, Lei; Yan, Bin; Wang, Linyuan; Cai, Ailong; Hu, Guoen

    2016-10-06

    The optimization-based method that utilizes the additional sparse prior of region-of-interest (ROI) image, such as total variation, has been the subject of considerable research in problems of interior tomography reconstruction. One challenge for optimization-based iterative ROI image reconstruction is to build the relationship between ROI image and truncated projection data. When the reconstruction support region is smaller than the original object, an unsuitable representation of data fidelity may lead to bright truncation artifacts in the boundary region of field of view. In this work, we aim to develop an iterative reconstruction method to suppress the truncation artifacts and improve the image quality for direct ROI image reconstruction. A novel reconstruction approach is proposed based on an optimization problem involving a two-step filtering-based data fidelity. Data filtering is achieved in two steps: the first takes the derivative of projection data; in the second step, Hilbert filtering is applied in the differentiated data. Numerical simulations and real data reconstructions have been conducted to validate the new reconstruction method. Both qualitative and quantitative results indicate that, as theoretically expected, the proposed method brings reasonable performance in suppressing truncation artifacts and preserving detailed features. The presented local reconstruction method based on the two-step filtering strategy provides a simple and efficient approach for the iterative reconstruction from truncated projections.

  7. MR Image Reconstruction Based on Iterative Split Bregman Algorithm and Nonlocal Total Variation

    Directory of Open Access Journals (Sweden)

    Varun P. Gopi

    2013-01-01

    and least-square data-fitting term to reconstruct the MR images from undersampled k-space data. The nonlocal total variation is taken as the L1-regularization functional and solved using Split Bregman iteration. The proposed algorithm is compared with previous methods in terms of the reconstruction accuracy and computational complexity. The comparison results demonstrate the superiority of the proposed algorithm for compressed MR image reconstruction.

  8. dPIRPLE: a joint estimation framework for deformable registration and penalized-likelihood CT image reconstruction using prior images

    Science.gov (United States)

    Dang, H.; Wang, A. S.; Sussman, Marc S.; Siewerdsen, J. H.; Stayman, J. W.

    2014-09-01

    Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration, and

  9. Influence of iterative image reconstruction on CT-based calcium score measurements

    NARCIS (Netherlands)

    van Osch, Jochen A. C.; Mouden, Mohamed; van Dalen, Jorn A.; Timmer, Jorik R.; Reiffers, Stoffer; Knollema, Siert; Greuter, Marcel J. W.; Ottervanger, Jan Paul; Jager, Piet L.

    Iterative reconstruction techniques for coronary CT angiography have been introduced as an alternative for traditional filter back projection (FBP) to reduce image noise, allowing improved image quality and a potential for dose reduction. However, the impact of iterative reconstruction on the

  10. Iterative Image Reconstruction for PROPELLER-MRI using the NonUniform Fast Fourier Transform

    Science.gov (United States)

    Tamhane, Ashish A.; Anastasio, Mark A.; Gui, Minzhi; Arfanakis, Konstantinos

    2013-01-01

    Purpose To investigate an iterative image reconstruction algorithm using the non-uniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping parallEL Lines with Enhanced Reconstruction) MRI. Materials and Methods Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it to that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. Results It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased SNR, reduced artifacts, for similar spatial resolution, compared to gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. Conclusion An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter the new reconstruction technique may provide PROPELLER images with improved image quality compared to conventional gridding. PMID:20578028

  11. Improvement of image quality and dose management in CT fluoroscopy by iterative 3D image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Grosser, Oliver S.; Kupitz, Dennis; Powerski, Maciej; Mohnike, Konrad; Ricke, Jens [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Wybranski, Christian [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Cologne (Germany); Pech, Maciej [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Medical University of Gdansk, Second Department of Radiology, Gdansk (Poland); Amthauer, Holger [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Charite, Department of Nuclear Medicine, Berlin (Germany)

    2017-09-15

    The objective of this study was to assess the influence of an iterative CT reconstruction algorithm (IA), newly available for CT-fluoroscopy (CTF), on image noise, readers' confidence and effective dose compared to filtered back projection (FBP). Data from 165 patients (FBP/IA = 82/74) with CTF in the thorax, abdomen and pelvis were included. Noise was analysed in a large-diameter vessel. The impact of reconstruction and variables (e.g. X-ray tube current I) influencing noise and effective dose were analysed by ANOVA and a pairwise t-test with Bonferroni-Holm correction. Noise and readers' confidence were evaluated by three readers. Noise was significantly influenced by reconstruction, I, body region and circumference (all p ≤ 0.0002). IA reduced the noise significantly compared to FBP (p = 0.02). The effect varied for body regions and circumferences (p ≤ 0.001). The effective dose was influenced by the reconstruction, body region, interventional procedure and I (all p ≤ 0.02). The inter-rater reliability for noise and readers' confidence was good (W ≥ 0.75, p < 0.0001). Noise and readers' confidence were significantly better in AIDR-3D compared to FBP (p ≤ 0.03). Generally, IA yielded a significant reduction of the median effective dose. The CTF reconstruction by IA showed a significant reduction in noise and effective dose while readers' confidence increased. (orig.)

  12. Digital aberration correction of fluorescent images with coherent holographic image reconstruction by phase transfer (CHIRPT)

    Science.gov (United States)

    Field, Jeffrey J.; Bartels, Randy A.

    2016-03-01

    Coherent holographic image reconstruction by phase transfer (CHIRPT) is an imaging method that permits digital holographic propagation of fluorescent light. The image formation process in CHIRPT is based on illuminating the specimen with a precisely controlled spatio-temporally varying intensity pattern. This pattern is formed by focusing a spatially coherent illumination beam to a line focus on a spinning modulation mask, and image relaying the mask plane to the focal plane of an objective lens. Deviations from the designed spatio-temporal illumination pattern due to imperfect mounting of the circular modulation mask onto the rotation motor induce aberrations in the recovered image. Here we show that these aberrations can be measured and removed non-iteratively by measuring the disk aberration phase externally. We also demonstrate measurement and correction of systematic optical aberrations in the CHIRPT microscope.

  13. Stepwise method based on Wiener estimation for spectral reconstruction in spectroscopic Raman imaging.

    Science.gov (United States)

    Chen, Shuo; Wang, Gang; Cui, Xiaoyu; Liu, Quan

    2017-01-23

    Raman spectroscopy has demonstrated great potential in biomedical applications. However, spectroscopic Raman imaging is limited in the investigation of fast changing phenomena because of slow data acquisition. Our previous studies have indicated that spectroscopic Raman imaging can be significantly sped up using the approach of narrow-band imaging followed by spectral reconstruction. A multi-channel system was built to demonstrate the feasibility of fast wide-field spectroscopic Raman imaging using the approach of simultaneous narrow-band image acquisition followed by spectral reconstruction based on Wiener estimation in phantoms. To further improve the accuracy of reconstructed Raman spectra, we propose a stepwise spectral reconstruction method in this study, which can be combined with the earlier developed sequential weighted Wiener estimation to improve spectral reconstruction accuracy. The stepwise spectral reconstruction method first reconstructs the fluorescence background spectrum from narrow-band measurements and then the pure Raman narrow-band measurements can be estimated by subtracting the estimated fluorescence background from the overall narrow-band measurements. Thereafter, the pure Raman spectrum can be reconstructed from the estimated pure Raman narrow-band measurements. The result indicates that the stepwise spectral reconstruction method can improve spectral reconstruction accuracy significantly when combined with sequential weighted Wiener estimation, compared with the traditional Wiener estimation. In addition, qualitatively accurate cell Raman spectra were successfully reconstructed using the stepwise spectral reconstruction method from the narrow-band measurements acquired by a four-channel wide-field Raman spectroscopic imaging system. This method can potentially facilitate the adoption of spectroscopic Raman imaging to the investigation of fast changing phenomena.

  14. Image artefact propagation in motion estimation and reconstruction in interventional cardiac C-arm CT

    Science.gov (United States)

    Müller, K.; Maier, A. K.; Schwemmer, C.; Lauritsch, G.; De Buck, S.; Wielandts, J.-Y.; Hornegger, J.; Fahrig, R.

    2014-06-01

    The acquisition of data for cardiac imaging using a C-arm computed tomography system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable three-dimensional (3D)/3D registration performed on initial 3D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3D images. In this paper, the sensitivity of the 3D/3D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing combined with the improved total variation algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical

  15. Electrodynamics sensor for the image reconstruction process in an electrical charge tomography system.

    Science.gov (United States)

    Rahmat, Mohd Fua'ad; Isa, Mohd Daud; Rahim, Ruzairi Abdul; Hussin, Tengku Ahmad Raja

    2009-01-01

    Electrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image of materials being conveyed based on data measured by an electrodynamics sensor installed around the pipe. Image reconstruction in electrical charge tomography is vital and has not been widely studied before. Three methods have been introduced before, namely the linear back projection method, the filtered back projection method and the least square method. These methods normally face ill-posed problems and their solutions are unstable and inaccurate. In order to ensure the stability and accuracy, a special solution should be applied to obtain a meaningful image reconstruction result. In this paper, a new image reconstruction method - Least squares with regularization (LSR) will be introduced to reconstruct the image of material in a gravity mode conveyor pipeline for electrical charge tomography. Numerical analysis results based on simulation data indicated that this algorithm efficiently overcomes the numerical instability. The results show that the accuracy of the reconstruction images obtained using the proposed algorithm was enhanced and similar to the image captured by a CCD Camera. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.

  16. Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification

    KAUST Repository

    Zhu, Xiaofeng

    2015-05-28

    This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple visual features, the MMKR first maps them into a high-dimensional space, e.g., a reproducing kernel Hilbert space (RKHS), where test images are then linearly reconstructed by some representative training images, rather than all of them. Furthermore a classification rule is proposed to classify test images. Experimental results on real datasets show the effectiveness of the proposed MMKR while comparing to state-of-the-art algorithms.

  17. Effects of acquisition time and reconstruction algorithm on image quality, quantitative parameters, and clinical interpretation of myocardial perfusion imaging

    DEFF Research Database (Denmark)

    Enevoldsen, Lotte H; Menashi, Changez A K; Andersen, Ulrik B

    2013-01-01

    -RR) and for quantitative analysis (FT-FBP, HT-FBP, and HT-RR). The datasets were analyzed using commercially available QGS/QPS software and read by two observers evaluating image quality and clinical interpretation. Image quality was assessed on a 10-cm visual analog scale score. RESULTS: HT imaging was associated......BACKGROUND: Recently introduced iterative reconstruction algorithms with resolution recovery (RR) and noise-reduction technology seem promising for reducing scan time or radiation dose without loss of image quality. However, the relative effects of reduced acquisition time and reconstruction...... with loss of image quality that was compensated for by RR reconstruction. HT imaging was also associated with increasing perfusion defect extents, an effect more pronounced using RR than FBP reconstruction. Compared to standard FT-FBP, HT-RR significantly reduced left ventricular volumes whereas HT...

  18. On multigrid methods for image reconstruction from projections

    Energy Technology Data Exchange (ETDEWEB)

    Henson, V.E.; Robinson, B.T. [Naval Postgraduate School, Monterey, CA (United States); Limber, M. [Simon Fraser Univ., Burnaby, British Columbia (Canada)

    1994-12-31

    The sampled Radon transform of a 2D function can be represented as a continuous linear map R : L{sup 1} {yields} R{sup N}. The image reconstruction problem is: given a vector b {element_of} R{sup N}, find an image (or density function) u(x, y) such that Ru = b. Since in general there are infinitely many solutions, the authors pick the solution with minimal 2-norm. Numerous proposals have been made regarding how best to discretize this problem. One can, for example, select a set of functions {phi}{sub j} that span a particular subspace {Omega} {contained_in} L{sup 1}, and model R : {Omega} {yields} R{sup N}. The subspace {Omega} may be chosen as a member of a sequence of subspaces whose limit is dense in L{sup 1}. One approach to the choice of {Omega} gives rise to a natural pixel discretization of the image space. Two possible choices of the set {phi}{sub j} are the set of characteristic functions of finite-width `strips` representing energy transmission paths and the set of intersections of such strips. The authors have studied the eigenstructure of the matrices B resulting from these choices and the effect of applying a Gauss-Seidel iteration to the problem Bw = b. There exists a near null space into which the error vectors migrate with iteration, after which Gauss-Seidel iteration stalls. The authors attempt to accelerate convergence via a multilevel scheme, based on the principles of McCormick`s Multilevel Projection Method (PML). Coarsening is achieved by thickening the rays which results in a much smaller discretization of an optimal grid, and a halving of the number of variables. This approach satisfies all the requirements of the PML scheme. They have observed that a multilevel approach based on this idea accelerates convergence at least to the point where noise in the data dominates.

  19. A biomechanical modeling guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

    Science.gov (United States)

    Huang, Xiaokun; Zhang, You; Wang, Jing

    2017-03-01

    Four-dimensional (4D) cone-beam computed tomography (CBCT) enables motion tracking of anatomical structures and removes artifacts introduced by motion. However, the imaging time/dose of 4D-CBCT is substantially longer/higher than traditional 3D-CBCT. We previously developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, to reconstruct high-quality 4D-CBCT from limited number of projections to reduce the imaging time/dose. However, the accuracy of SMEIR is limited in reconstructing low-contrast regions with fine structure details. In this study, we incorporate biomechanical modeling into the SMEIR algorithm (SMEIR-Bio), to improve the reconstruction accuracy at low-contrast regions with fine details. The efficacy of SMEIR-Bio is evaluated using 11 lung patient cases and compared to that of the original SMEIR algorithm. Qualitative and quantitative comparisons showed that SMEIR-Bio greatly enhances the accuracy of reconstructed 4D-CBCT volume in low-contrast regions, which can potentially benefit multiple clinical applications including the treatment outcome analysis.

  20. Real-time SPARSE-SENSE cardiac cine MR imaging: optimization of image reconstruction and sequence validation.

    Science.gov (United States)

    Goebel, Juliane; Nensa, Felix; Bomas, Bettina; Schemuth, Haemi P; Maderwald, Stefan; Gratz, Marcel; Quick, Harald H; Schlosser, Thomas; Nassenstein, Kai

    2016-12-01

    Improved real-time cardiac magnetic resonance (CMR) sequences have currently been introduced, but so far only limited practical experience exists. This study aimed at image reconstruction optimization and clinical validation of a new highly accelerated real-time cine SPARSE-SENSE sequence. Left ventricular (LV) short-axis stacks of a real-time free-breathing SPARSE-SENSE sequence with high spatiotemporal resolution and of a standard segmented cine SSFP sequence were acquired at 1.5 T in 11 volunteers and 15 patients. To determine the optimal iterations, all volunteers' SPARSE-SENSE images were reconstructed using 10-200 iterations, and contrast ratios, image entropies, and reconstruction times were assessed. Subsequently, the patients' SPARSE-SENSE images were reconstructed with the clinically optimal iterations. LV volumetric values were evaluated and compared between both sequences. Sufficient image quality and acceptable reconstruction times were achieved when using 80 iterations. Bland-Altman plots and Passing-Bablok regression showed good agreement for all volumetric parameters. 80 iterations are recommended for iterative SPARSE-SENSE image reconstruction in clinical routine. Real-time cine SPARSE-SENSE yielded comparable volumetric results as the current standard SSFP sequence. Due to its intrinsic low image acquisition times, real-time cine SPARSE-SENSE imaging with iterative image reconstruction seems to be an attractive alternative for LV function analysis. • A highly accelerated real-time CMR sequence using SPARSE-SENSE was evaluated. • SPARSE-SENSE allows free breathing in real-time cardiac cine imaging. • For clinically optimal SPARSE-SENSE image reconstruction, 80 iterations are recommended. • Real-time SPARSE-SENSE imaging yielded comparable volumetric results as the reference SSFP sequence. • The fast SPARSE-SENSE sequence is an attractive alternative to standard SSFP sequences.

  1. Recent improvements in Hurricane Imaging Radiometer’s brightness temperature image reconstruction

    Directory of Open Access Journals (Sweden)

    Sayak K. Biswas

    Full Text Available NASA MSFCs airborne Hurricane Imaging Radiometer (HIRAD uses interferometric aperture synthesis to produce high resolution wide swath images of scene brightness temperature (Tb distribution at four discrete C-band microwave frequencies (4.0, 5.0, 6.0 and 6.6 GHz. Images of ocean surface wind speed under heavy precipitation such as in tropical cyclones, is inferred from these measurements. The baseline HIRAD Tb reconstruction algorithm had produced prominent along-track streaks in the Tb images. Particularly the 4.0 GHz channel had been so dominated by the streaks as to be unusable.The loss of a frequency channel had compromised the final wind speed retrievals. During 2016, the HIRAD team made substantial progress in developing a quality controlled signal processing technique for the HIRAD data collected in 2015’s Tropical Cyclone Intensity (TCI experiment and reduced the effect of streaks in all channels including 4.0 GHz. 2000 MSC: 41A05, 41A10, 65D05, 65D17, Keywords: Microwave radiometry, Aperture synthesis, Image reconstruction, Hurricane winds

  2. An automatic panoramic image reconstruction scheme from dental computed tomography images.

    Science.gov (United States)

    Papakosta, Thekla K; Savva, Antonis D; Economopoulos, Theodore L; Matsopoulos, George K; Gröhndal, H G

    2017-04-01

    Panoramic images of the jaws are extensively used for dental examinations and/or surgical planning because they provide a general overview of the patient's maxillary and mandibular regions. Panoramic images are two-dimensional projections of three-dimensional (3D) objects. Therefore, it should be possible to reconstruct them from 3D radiographic representations of the jaws, produced by CBCT scanning, obviating the need for additional exposure to X-rays, should there be a need of panoramic views. The aim of this article is to present an automated method for reconstructing panoramic dental images from CBCT data. The proposed methodology consists of a series of sequential processing stages for detecting a fitting dental arch which is used for projecting the 3D information of the CBCT data to the two-dimensional plane of the panoramic image. The detection is based on a template polynomial which is constructed from a training data set. A total of 42 CBCT data sets of real clinical pre-operative and post-operative representations from 21 patients were used. Eight data sets were used for training the system and the rest for testing. The proposed methodology was successfully applied to CBCT data sets, producing corresponding panoramic images, suitable for examining pre-operatively and post-operatively the patients' maxillary and mandibular regions.

  3. A BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT.

    Science.gov (United States)

    Cho, Seungryong; Xia, Dan; Pellizzari, Charles A; Pan, Xiaochuan

    2010-01-01

    Reverse helical cone-beam computed tomography (CBCT) is a scanning configuration for potential applications in image-guided radiation therapy in which an accurate anatomic image of the patient is needed for image-guidance procedures. The authors previously developed an algorithm for image reconstruction from nontruncated data of an object that is completely within the reverse helix. The purpose of this work is to develop an image reconstruction approach for reverse helical CBCT of a long object that extends out of the reverse helix and therefore constitutes data truncation. The proposed approach comprises of two reconstruction steps. In the first step, a chord-based backprojection-filtration (BPF) algorithm reconstructs a volumetric image of an object from the original cone-beam data. Because there exists a chordless region in the middle of the reverse helix, the image obtained in the first step contains an unreconstructed central-gap region. In the second step, the gap region is reconstructed by use of a Pack-Noo-formula-based filteredback-projection (FBP) algorithm from the modified cone-beam data obtained by subtracting from the original cone-beam data the reprojection of the image reconstructed in the first step. The authors have performed numerical studies to validate the proposed approach in image reconstruction from reverse helical cone-beam data. The results confirm that the proposed approach can reconstruct accurate images of a long object without suffering from data-truncation artifacts or cone-angle artifacts. They developed and validated a BPF-FBP tandem algorithm to reconstruct images of a long object from reverse helical cone-beam data. The chord-based BPF algorithm was utilized for converting the long-object problem into a short-object problem. The proposed approach is applicable to other scanning configurations such as reduced circular sinusoidal trajectories.

  4. A Superresolution Image Reconstruction Algorithm Based on Landweber in Electrical Capacitance Tomography

    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.

  5. Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT.

    Science.gov (United States)

    Gebhard, Cathérine; Fiechter, Michael; Fuchs, Tobias A; Stehli, Julia; Müller, Ennio; Stähli, Barbara E; Gebhard, Caroline E; Ghadri, Jelena R; Klaeser, Bernd; Gaemperli, Oliver; Kaufmann, Philipp A

    2013-10-01

    The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT. In 50 stents of 28 patients (mean age 64 ± 10 years) undergoing coronary CT angiography (CCTA) on an HDCT scanner the mean in-stent luminal diameter, stent length, image quality, in-stent contrast attenuation, and image noise were assessed. Studies were reconstructed using filtered back projection (FBP) and ASIR-FBP composites. ASIR resulted in reduced image noise vs. FBP (P ASIR with significantly larger luminal area visualization compared with FBP (+42.1 ± 5.4% with 100% ASIR vs. FBP alone; P Reconstruction of CCTA from HDCT using 40 and 60% ASIR incrementally improves intra-stent luminal area, diameter visualization, and image quality compared with FBP reconstruction.

  6. Alternating Direction Total Variation Image Reconstruction and Practical Decomposition for Dual-energy Computed Tomography

    CERN Document Server

    Li, Lei; Wang, Linyuan; Yan, Bin; Zhang, Hanming; Zheng, Zhizhong; Zhang, Wenkun; Lu, Wanli; Hu, Guoen

    2016-01-01

    Dual-energy computed tomography (DECT) has shown great potential and promising applications in advanced imaging fields for its capabilities of material decomposition. However, image reconstructions and decompositions under sparse views dataset suffers severely from multi factors, such as insufficiencies of data, appearances of noise, and inconsistencies of observations. Under sparse views, conventional filtered back-projection type reconstruction methods fails to provide CT images with satisfying quality. Moreover, direct image decomposition is unstable and meet with noise boost even with full views dataset. This paper proposes an iterative image reconstruction algorithm and a practical image domain decomposition method for DECT. On one hand, the reconstruction algorithm is formulated as an optimization problem, which containing total variation regularization term and data fidelity term. The alternating direction method is utilized to design the corresponding algorithm which shows faster convergence speed com...

  7. Ultra-low-dose CT of the lung: effect of iterative reconstruction techniques on image quality.

    Science.gov (United States)

    Yanagawa, Masahiro; Gyobu, Tomoko; Leung, Ann N; Kawai, Misa; Kawata, Yutaka; Sumikawa, Hiromitsu; Honda, Osamu; Tomiyama, Noriyuki

    2014-06-01

    To compare quality of ultra-low-dose thin-section computed tomography (CT) images of the lung reconstructed using model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASIR) to filtered back projection (FBP) and to determine the minimum tube current-time product on MBIR images by comparing to standard-dose FBP images. Ten cadaveric lungs were scanned using 120 kVp and four different tube current-time products (8, 16, 32, and 80 mAs). Thin-section images were reconstructed using MBIR, three ASIR blends (30%, 60%, and 90%), and FBP. Using the 8-mAs data, side-to-side comparison of the four iterative reconstruction image sets to FBP was performed by two independent observers who evaluated normal and abnormal findings, subjective image noise, streak artifact, and overall image quality. Image noise was also measured quantitatively. Subsequently, 8-, 16-, and 32-mAs MBIR images were compared to standard-dose FBP images. Comparisons of image sets were analyzed using the Wilcoxon signed rank test with Bonferroni correction. At 8 mAs, MBIR images were significantly better (P reconstruction techniques except in evaluation of interlobular septal thickening. Each set of low-dose MBIR images had significantly lower (P < .001) subjective and objective noise and streak artifacts than standard-dose FBP images. Conspicuity and visibility of normal and abnormal findings were not significantly different between 16-mAs MBIR and 80-mAs FBP images except in identification of intralobular reticular opacities. MBIR imaging shows higher overall quality with lower noise and streak artifacts than ASIR or FBP imaging, resulting in nearly 80% dose reduction without any degradations of overall image quality. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  8. Approximate Sparsity and Nonlocal Total Variation Based Compressive MR Image Reconstruction

    Directory of Open Access Journals (Sweden)

    Chengzhi Deng

    2014-01-01

    Full Text Available Recent developments in compressive sensing (CS show that it is possible to accurately reconstruct the magnetic resonance (MR image from undersampled k-space data by solving nonsmooth convex optimization problems, which therefore significantly reduce the scanning time. In this paper, we propose a new MR image reconstruction method based on a compound regularization model associated with the nonlocal total variation (NLTV and the wavelet approximate sparsity. Nonlocal total variation can restore periodic textures and local geometric information better than total variation. The wavelet approximate sparsity achieves more accurate sparse reconstruction than fixed wavelet l0 and l1 norm. Furthermore, a variable splitting and augmented Lagrangian algorithm is presented to solve the proposed minimization problem. Experimental results on MR image reconstruction demonstrate that the proposed method outperforms many existing MR image reconstruction methods both in quantitative and in visual quality assessment.

  9. 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.

  10. Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions.

    Science.gov (United States)

    Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T

    2017-08-12

    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 V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P 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.

  11. Image Quality in Children with Low-Radiation Chest CT Using Adaptive Statistical Iterative Reconstruction and Model-Based Iterative Reconstruction

    OpenAIRE

    Jihang Sun; Yun Peng; Xiaomin Duan; Tong Yu; Qifeng Zhang; Yong Liu; Di Hu

    2014-01-01

    OBJECTIVE: To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR) and a full model-based iterative reconstruction (MBIR) algorithm. METHODS: Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years) who received low-dose chest CT scans were included. Age-dependent noise index (NI) was used for acquisition. Images were retrospectively reconstructed using three me...

  12. A comparative study of three dimensional reconstructive images using computed tomograms of facial bone injuries

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Eun Suk; Koh, Kwang Joon [Dept. of Oral and Maxillofacial Radiology, College of Dentistry, Chonbuk National University, Chonju (Korea, Republic of)

    1994-08-15

    The purpose of this study was to clarify the spatial relationship in presurgical examination and to aid surgical planning and postoperative evaluation of patients with facial bone injury. For this study, three-dimensional images of facial bone fracture were reconstructed by computed image analysis system and three-dimensional reconstructive program integrated in computed tomography. The obtained results were as follows: 1. Serial conventional computed tomograms were value in accurately depicting the facial bone injuries and three-dimensional reconstructive images demonstrated an overall look. 2. The degree of deterioration of spatial resolution was proportional to the thickness of the slice. 3. Facial bone fractures were the most distinctly demonstrated on inferoanterior views of three dimensional reconstructive images. 4. Although three-dimensional reconstructive images made diagnosis of fracture lines, it was difficult to identify maxillary fractures. 5. The diagnosis of zygomatic fractures could be made equally well with computed image analysis system and three-dimensional reconstructive program integrated in computed tomography. 6. The diagnosis of mandibular fractures could be made equally well with computed image analysis system and three-dimensional reconstructive program integrated in computed tomography.

  13. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images.

    Science.gov (United States)

    Li, Lin; Wang, Wei; Luo, Heng; Ying, Shen

    2017-05-07

    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images.

  14. 3-D Reconstruction From 2-D Radiographic Images and Its Application to Clinical Veterinary Medicine

    Science.gov (United States)

    Hamamoto, Kazuhiko; Sato, Motoyoshi

    3D imaging technique is very important and indispensable in diagnosis. The main stream of the technique is one in which 3D image is reconstructed from a set of slice images, such as X-ray CT and MRI. However, these systems require large space and high costs. On the other hand, a low cost and small size 3D imaging system is needed in clinical veterinary medicine, for example, in the case of diagnosis in X-ray car or pasture area. We propose a novel 3D imaging technique using 2-D X-ray radiographic images. This system can be realized by cheaper system than X-ray CT and enables to get 3D image in X-ray car or portable X-ray equipment. In this paper, a 3D visualization technique from 2-D radiographic images is proposed and several reconstructions are shown. These reconstructions are evaluated by veterinarians.

  15. Multiple-image hiding using super resolution reconstruction in high-frequency domains

    Science.gov (United States)

    Li, Xiao-Wei; Zhao, Wu-Xiang; Wang, Jun; Wang, Qiong-Hua

    2017-12-01

    In this paper, a robust multiple-image hiding method using the computer-generated integral imaging and the modified super-resolution reconstruction algorithm is proposed. In our work, the host image is first transformed into frequency domains by cellular automata (CA), to assure the quality of the stego-image, the secret images are embedded into the CA high-frequency domains. The proposed method has the following advantages: (1) robustness to geometric attacks because of the memory-distributed property of elemental images, (2) increasing quality of the reconstructed secret images as the scheme utilizes the modified super-resolution reconstruction algorithm. The simulation results show that the proposed multiple-image hiding method outperforms other similar hiding methods and is robust to some geometric attacks, e.g., Gaussian noise and JPEG compression attacks.

  16. Improvement of the optical image reconstruction based on multiplexed quantum ghost images

    Science.gov (United States)

    Balakin, D. A.; Belinsky, A. V.; Chirkin, A. S.

    2017-08-01

    Ghost imaging allows one to obtain information on an object from the spatial correlation function between photons propagating through or reflected from the object and photons of the reference arm. In this case, detection in the object arm is performed over the entire aperture of the beam and, therefore, it does not give information on the object. The reference beam does not interact with the object, but is recorded with a scanning point detector or a CCD array permitting the measurement of the spatial correlation function of photons in two arms. The use of multimode entangled quantum light beams by illuminating the object by one beam and orienting other beams to reference arms makes it possible to obtain simultaneously several ghost images (GIs). Cross correlations of multiplexed GIs (MGIs) are determined by eighth-order field correlation functions. A special algorithm is developed for calculating higher-order correlations of Bose operators. The presence of GI cross correlations is used for improving the quality of the reconstructed object's image by their processing using the measurement reduction method. An example of the computer simulation of the image reconstruction by MGIs formed in the field of four-frequency entangled quantum states is considered. It is found that in this case the reduced GI has a signal-to-noise ratio several times higher than that of GIs.

  17. Image reconstruction method IRBis for optical/infrared long-baseline interferometry

    Science.gov (United States)

    Hofmann, Karl-Heinz; Heininger, Matthias; Schertl, Dieter; Weigelt, Gerd; Millour, Florentin; Berio, Philippe

    2016-07-01

    IRBis is an image reconstruction method for optical/infrared long-baseline interferometry. IRBis can reconstruct images from (a) measured visibilities and closure phases, or from (b) measured complex visibilities (i.e. the Fourier phases and visibilities). The applied optimization routine ASA CG is based on conjugate gradients. The method allows the user to implement different regularizers, as for example, maximum entropy, smoothness, total variation, etc., and apply residual ratios as an additional metric for goodness-of-fit. In addition, IRBis allows the user to change the following reconstruction parameters: (a) FOV of the area to be reconstructed, (b) the size of the pixel-grid used, (c) size of a binary mask in image space allowing reconstructed intensities real astronomical objects: (a) We have investigated image reconstruction experiments of MATISSE target candidates by computer simulations. We have modeled gaps in a disk of a young stellar object and have simulated interferometric data (squared visibilities and closure phases) with a signal-to-noise ratio as expected for MATISSE observations. We have performed image reconstruction experiments with this model for different flux levels of the target and different amount of observing time, that is, with different uv coverages. As expected, the quality of the reconstructions clearly depends on the flux of the source and the completeness of the uv coverage. (b) We also discuss reconstructions of the Luminous Blue Variable η Carinae obtained from AMBER observations in the high spectral resolution mode in the K band. The images were reconstruction (1) using the closure phases and (2) using the absolute phases derived from the measured wavelength-differential phases and the closure phase reconstruction in the continuum.

  18. On the Reconstruction of a Weak Phase-Amplitude Object. IV New Sampling Theorems for Object Reconstruction even for Non-Isoplanatic Imaging. I. One Dimensional Object Reconstruction

    NARCIS (Netherlands)

    Ferwerda, H.A.; Hoenders, B.J.

    1974-01-01

    New inversion procedures are derived for one-dimensional object reconstruction which use sampling values of known distributions. Whittaker-Shannon sampling is derived as a special case. The theorems apply to optical imaging with aberrations which violate the isoplanacy condition. Also a

  19. Comparative assessment of three image reconstruction techniques for image quality and radiation dose in patients undergoing abdominopelvic multidetector CT examinations

    Science.gov (United States)

    Desai, G S; Thabet, A; Elias, A Y A; Sahani, D V

    2013-01-01

    Objective To compare image quality and radiation dose of abdominal CT examinations reconstructed with three image reconstruction techniques. Methods In this Institutional Review Board-approved study, contrast-enhanced (CE) abdominopelvic CT scans from 23 patients were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR) and iterative reconstruction in image space (IRIS) and were reviewed by two blinded readers. Subjective (acceptability, sharpness, noise and artefacts) and objective (noise) measures of image quality were recorded for each image data set. Radiation doses in CT dose index (CTDI) dose–length product were also calculated for each examination type and compared. Imaging parameters were compared using the Wilcoxon signed rank test and a paired t-test. Results All 69 CECT examinations were of diagnostic quality and similar for overall acceptability (mean grade for ASiR, 3.9±0.3; p=0.2 for Readers 1 and 2; IRIS, 3.9±0.4, p=0.2; FBP, 3.8±0.9). Objective noise was considerably lower with both iterative techniques (pASiR and IRIS). Recorded mean radiation dose, i.e. CTDIvol, was 24% and 10% less with ASiR (11.4±3.4 mGy; preconstructed with ASiR and IRIS provide diagnostic images with reduced image noise and 10–24% lower radiation dose than FBP. Advances in knowledge CT images reconstructed with FBP are frequently noisy on lowering the radiation dose. Newer iterative reconstruction techniques have different approaches to produce images with less noise; ASiR and IRIS provide diagnostic abdominal CT images with reduced image noise and radiation dose compared with FBP. This has been documented in this study. PMID:23255538

  20. Hybrid iterative reconstruction algorithm improves image quality in craniocervical CT angiography.

    Science.gov (United States)

    Löve, Askell; Siemund, Roger; Höglund, Peter; Ramgren, Birgitta; Undrén, Per; Björkman-Burtscher, Isabella M

    2013-12-01

    The purpose of this study was to evaluate the potential of a hybrid iterative reconstruction algorithm for improving image quality in craniocervical CT angiography (CTA) and to assess observer performance. Thirty patients (mean age, 58 years; range 16-80 years) underwent standard craniocervical CTA (volume CT dose index, 6.8 mGy, 2.8 mSv). Images were reconstructed using both filtered back projection (FBP) and a hybrid iterative reconstruction algorithm. Five neuroradiologists assessed general image quality and delineation of the vessel lumen in seven arterial segments using a 4-grade scale. Interobserver and intraobserver variability were determined. Mean attenuation and noise were measured and signal-to-noise and contrast-to-noise ratios calculated. Descriptive statistics are presented and data analyzed using linear mixed-effects models. In pooled data, image quality in iterative reconstruction was graded superior to FBP regarding all five quality criteria (p Iterative reconstruction resulted in elimination of arterial segments graded poor. Interobserver percentage agreement was significantly better (p = 0.024) for iterative reconstruction (69%) than for FBP (66%) but worse than intraobserver percentage agreement (mean, 79%). Noise levels, signal-to-noise ratio, and contrast-to-noise ratio were significantly (p iterative reconstruction at all measured levels. The iterative reconstruction algorithm significantly improves image quality in craniocervical CT, especially at the thoracic inlet. Despite careful study design, considerable interobserver and intraobserver variability was noted.

  1. GPU-accelerated Kernel Regression Reconstruction for Freehand 3D Ultrasound Imaging.

    Science.gov (United States)

    Wen, Tiexiang; Li, Ling; Zhu, Qingsong; Qin, Wenjian; Gu, Jia; Yang, Feng; Xie, Yaoqin

    2017-07-01

    Volume reconstruction method plays an important role in improving reconstructed volumetric image quality for freehand three-dimensional (3D) ultrasound imaging. By utilizing the capability of programmable graphics processing unit (GPU), we can achieve a real-time incremental volume reconstruction at a speed of 25-50 frames per second (fps). After incremental reconstruction and visualization, hole-filling is performed on GPU to fill remaining empty voxels. However, traditional pixel nearest neighbor-based hole-filling fails to reconstruct volume with high image quality. On the contrary, the kernel regression provides an accurate volume reconstruction method for 3D ultrasound imaging but with the cost of heavy computational complexity. In this paper, a GPU-based fast kernel regression method is proposed for high-quality volume after the incremental reconstruction of freehand ultrasound. The experimental results show that improved image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of [Formula: see text] and kernel bandwidth of 1.0. The computational performance of the proposed GPU-based method can be over 200 times faster than that on central processing unit (CPU), and the volume with size of 50 million voxels in our experiment can be reconstructed within 10 seconds.

  2. Accurate image reconstruction in CT from projection data taken at few-views

    Science.gov (United States)

    Sidky, Emil Y.; Kao, Chien-Min; Pan, Xiaochuan

    2006-03-01

    Image reconstruction from few-view CT is of interest because of the potential to reduce scanning time and radiation dose. The challenge of few-view CT for image reconstruction is essentially a problem of interpolation from under-sampled data. Recently, a new algorithm for inverting the Fourier transform from under-sampled data has been developed by Candes et al. IEEE Trans. Inf. Theory , 52 489 (2006). This algorithm can be directly applied to image reconstruction in 2D parallel-beam CT because of the central slice theorem. This article presents a discussion of the new algorithm, showing examples for different degrees of under-sampling.

  3. Incorporation of local dependent reliability information into the Prior Image Constrained Compressed Sensing (PICCS) reconstruction algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Vaegler, Sven; Sauer, Otto [Wuerzburg Univ. (Germany). Dept. of Radiation Oncology; Stsepankou, Dzmitry; Hesser, Juergen [University Medical Center Mannheim, Mannheim (Germany). Dept. of Experimental Radiation Oncology

    2015-07-01

    The reduction of dose in cone beam computer tomography (CBCT) arises from the decrease of the tube current for each projection as well as from the reduction of the number of projections. In order to maintain good image quality, sophisticated image reconstruction techniques are required. The Prior Image Constrained Compressed Sensing (PICCS) incorporates prior images into the reconstruction algorithm and outperforms the widespread used Feldkamp-Davis-Kress-algorithm (FDK) when the number of projections is reduced. However, prior images that contain major variations are not appropriately considered so far in PICCS. We therefore propose the partial-PICCS (pPICCS) algorithm. This framework is a problem-specific extension of PICCS and enables the incorporation of the reliability of the prior images additionally. We assumed that the prior images are composed of areas with large and small deviations. Accordingly, a weighting matrix considered the assigned areas in the objective function. We applied our algorithm to the problem of image reconstruction from few views by simulations with a computer phantom as well as on clinical CBCT projections from a head-and-neck case. All prior images contained large local variations. The reconstructed images were compared to the reconstruction results by the FDK-algorithm, by Compressed Sensing (CS) and by PICCS. To show the gain of image quality we compared image details with the reference image and used quantitative metrics (root-mean-square error (RMSE), contrast-to-noise-ratio (CNR)). The pPICCS reconstruction framework yield images with substantially improved quality even when the number of projections was very small. The images contained less streaking, blurring and inaccurately reconstructed structures compared to the images reconstructed by FDK, CS and conventional PICCS. The increased image quality is also reflected in large RMSE differences. We proposed a modification of the original PICCS algorithm. The pPICCS algorithm

  4. Parallel Algorithm for Reconstruction of TAC Images; Algoritmo Paralelo de Reconstruccion de Imagenes TAC

    Energy Technology Data Exchange (ETDEWEB)

    Vidal Gimeno, V.

    2012-07-01

    The algebraic reconstruction methods are based on solving a system of linear equations. In a previous study, was used and showed as the PETSc library, was and is a scientific computing tool, which facilitates and enables the optimal use of a computer system in the image reconstruction process.

  5. Investigation of Iterative Image Reconstruction in Low-dose Breast CT

    Science.gov (United States)

    Bian, Junguo; Yang, Kai; Boone, John M.; Han, Xiao; Sidky, Emil Y.

    2014-01-01

    Interest exists in developing computed tomography (CT) dedicated for breast-cancer imaging. Because breast tissues are radiation-sensitive, the total radiation exposure in a breast-CT scan is kept low, often comparable to a typical two-view mammography exam, thus resulting in a challenging low-dose-data-reconstruction problem. In recent years, evidence exists suggesting that iterative reconstruction may yield images of improved quality from low-dose data. In this work, based upon the constrained image-total-variation (TV) minimization program and its numerical solver, i.e., the adaptive steepest descent-projection onto the convex set (ASD-POCS), we investigate and evaluate iterative image reconstructions from low-dose breast-CT data of patients, with focuses on identifying and determining key reconstruction parameters, devising surrogate utility metrics for characterizing reconstruction quality, and tailoring the program and ASD-POCS to the specific reconstruction task under consideration. The ASD-POCS reconstructions appear to outperform the corresponding clinical FDK reconstructions, in terms of subjective visualization and surrogate utility metrics. PMID:24786683

  6. Accelerated gradient methods for total-variation-based CT image reconstruction

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Heide; Jensen, Tobias Lindstrøm; Hansen, Per Christian

    2011-01-01

    reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-demanding methods such as Newton’s method. The simple gradient method has much lower memory requirements, but exhibits slow convergence...

  7. The quality of three-dimensional images reconstructed with volume-scan CT

    Energy Technology Data Exchange (ETDEWEB)

    Shimbashi, Takeshi; Sakurai, Nobuaki; Watanabe, Norimitsu (Jikei Univ., Tokyo (Japan). School of Medicine); Takagi, Hiroshi; Takeuchi, Yutaka

    1993-05-01

    Volume-scan CT is based on slip-ring technology which leads to continuous scanning. It permits remarkable reduction in scanning time, which is especially meaningful where children and elderly patients are concerned. One scan takes one second, with a maximum continuous time of 50 seconds. Slice widths of 2, 3, 5 and 100 mm can be selected and table changed from 1.5 to 20 mm/second. The reconstruction index is 1 to 10 mm, and reconstruction time about 10 seconds. As both the patient and table are moved simultaneously, it is possible to scan a wide area in a short time. Volume-scan CT is suitable for three-dimensional (3-D) images because of the good continuity of slices. The authors reconstructed 3-D phantom images using both ordinary CT and volume-scan CT, and then compared the quality of these images. Under the condition of 3 mm slice width and 3 mm/sec table speed, the 3-D images reconstructed with volume-scan CT were clearly better than those reconstructed using ordinary CT. The quality of both has improved after interpolation. In particular, the periorbital and zygomatic areas of 3-D images reconstructed with volume-scan CT are quite natural. When a phantom was scanned under the condition of 10 mm slice width and 10 mm/sec table speed, the quality of 3-D image reconstructed with ordinary CT was not sufficient to be distinct. Even under interpolation, the quality of image was not natural. Useful images could not be obtained when the phantom was moving. It was found that volume-scan CT is suitable for reconstruction of 3-D images. (author).

  8. Suppression of zero order diffraction from the reconstructed images in digital holography

    Directory of Open Access Journals (Sweden)

    M R Rashidian Vaziri

    2016-02-01

    Full Text Available The numerically reconstructed images in digital holography contain two undesirable features. After reconstruction, the zero order diffraction as well as the complex conjugate image will be present in pictures and drastically reduce their qualities. Practical applications of digital holography in the context of characterization and measuring the physical properties of objects require the suppression of these two features, before starting the reconstruction phase. In this work, using the required mathematical functions for suppressing the zero order diffraction and by transforming them to their discrete form, numerical filters for passing over the CCD images have been constructed. After passing these filters over the experimentally recorded CCD images, the reconstruction phase has been completed applying the discrete Fresnel transform. Carefully investigating the quality of various reconstructed images, we came to the conclusion that if a filter covers a smaller neighborhood of the recorded CCD images, it will have a better performance in suppressing the zero order diffraction. Among the used filters in this work, a 3×3 average filter showed the best performance in suppressing the zero order diffraction from the reconstructed images.

  9. Monte Carlo SURE-based parameter selection for parallel magnetic resonance imaging reconstruction.

    Science.gov (United States)

    Weller, Daniel S; Ramani, Sathish; Nielsen, Jon-Fredrik; Fessler, Jeffrey A

    2014-05-01

    Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein's unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods that preserve the undersampled acquired data, which cannot be accomplished using existing techniques. We derive a weighted MSE criterion appropriate for data-preserving regularized parallel imaging reconstruction and the corresponding weighted Stein's unbiased risk estimate. We describe a Monte Carlo approximation of the weighted Stein's unbiased risk estimate that uses two evaluations of the reconstruction method per candidate parameter value. We reconstruct images using the denoising sparse images from GRAPPA using the nullspace method (DESIGN) and L1 iterative self-consistent parallel imaging (L1 -SPIRiT). We validate Monte Carlo Stein's unbiased risk estimate against the weighted MSE. We select the regularization parameter using these methods for various noise levels and undersampling factors and compare the results to those using MSE-optimal parameters. Our method selects nearly MSE-optimal regularization parameters for both DESIGN and L1 -SPIRiT over a range of noise levels and undersampling factors. The proposed method automatically provides nearly MSE-optimal choices of regularization parameters for data-preserving nonlinear parallel MRI reconstruction methods. Copyright © 2013 Wiley Periodicals, Inc.

  10. Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study.

    Directory of Open Access Journals (Sweden)

    Oliver S Grosser

    Full Text Available Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT or positron emission tomography (PET with computed tomography (CT. Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR on the image quality of the low-dose CT images.Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88 and the contrast-to-noise ratio (CNR was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04. In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001.In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.

  11. Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

    Science.gov (United States)

    Grosser, Oliver S.; Kupitz, Dennis; Ruf, Juri; Czuczwara, Damian; Steffen, Ingo G.; Furth, Christian; Thormann, Markus; Loewenthal, David; Ricke, Jens; Amthauer, Holger

    2015-01-01

    Background Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images. Methodology/Principal Findings Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001). Conclusion/Significance In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality. PMID:26390216

  12. Development and evaluation of QSPECT open-source software for the iterative reconstruction of SPECT images.

    Science.gov (United States)

    Loudos, George K; Papadimitroulas, Panagiotis; Zotos, Panteleimon; Tsougos, Ioannis; Georgoulias, Panagiotis

    2010-06-01

    In this study open-source software (QSPECT) suitable for the iterative reconstruction of single-photon emission computed tomography (SPECT) data is presented. QSPECT implements maximum likelihood expectation maximization and ordered subsets expectation maximization algorithms in a user-friendly graphical interface. The software functionality is described and validation results are presented. Maximum likelihood expectation maximization and ordered subsets expectation maximization algorithms are implemented in C++. The Qt toolkit, a standard C++ framework for developing high-performance cross-platform applications, has been used for the graphical user interface development. QSPECT is tested using original projection data from two clinical SPECT systems: (i) APEX SPX-6/6HR and (ii) Millennium MG. Phantom experiments were carried out to evaluate the quality of reconstructed images in terms of (i) spatial resolution, (ii) sensitivity to activity variations, and (iii) the presence of scatter media. A cardiac phantom was used to simulate a normal and abnormal scenario. Finally, clinical cardiac SPECT images were reconstructed. In all cases, QSPECT results were compared with the clinical systems reconstruction software that uses the standard filtered backprojection algorithm. The reconstructed images show that QSPECT, when compared with standard clinical reconstruction, provides images with higher contrast, reduced background, and better separation of small sources located in small distances. In addition, reconstruction with QSPECT provides more quantitative images, and reduces the background created by scatter media. Finally, the phantom and clinical cardiac images are reconstructed with similar quality. QSPECT is a freely distributed, open-source standalone application that provides real-time, high-quality SPECT images. The software can be further modified to improve reconstruction algorithms, and include more correction techniques, such as, scatter and attenuation

  13. Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images

    DEFF Research Database (Denmark)

    Oxvig, Christian Schou; Pedersen, Patrick Steffen; Arildsen, Thomas

    2014-01-01

    Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also...

  14. Skeletal camera network embedded structure-from-motion for 3D scene reconstruction from UAV images.

    NARCIS (Netherlands)

    Xu, Z.; Wu, L.; Gerke, M.; Wang, R.; Yang, H.

    2016-01-01

    Structure-from-Motion (SfM) techniques have been widely used for 3D scene reconstruction from multi-view images. However, due to the large computational costs of SfM methods there is a major challenge in processing highly overlapping images, e.g. images from unmanned aerial vehicles (UAV). This

  15. A comparison of reconstruction methods for undersampled atomic force microscopy images

    Science.gov (United States)

    Luo, Yufan; Andersson, Sean B.

    2015-12-01

    Non-raster scanning and undersampling of atomic force microscopy (AFM) images is a technique for improving imaging rate and reducing the amount of tip-sample interaction needed to produce an image. Generation of the final image can be done using a variety of image processing techniques based on interpolation or optimization. The choice of reconstruction method has a large impact on the quality of the recovered image and the proper choice depends on the sample under study. In this work we compare interpolation through the use of inpainting algorithms with reconstruction based on optimization through the use of the basis pursuit algorithm commonly used for signal recovery in compressive sensing. Using four different sampling patterns found in non-raster AFM, namely row subsampling, spiral scanning, Lissajous scanning, and random scanning, we subsample data from existing images and compare reconstruction performance against the original image. The results illustrate that inpainting generally produces superior results when the image contains primarily low frequency content while basis pursuit is better when the images have mixed, but sparse, frequency content. Using support vector machines, we then classify images based on their frequency content and sparsity and, from this classification, develop a fast decision strategy to select a reconstruction algorithm to be used on subsampled data. The performance of the classification and decision test are demonstrated on test AFM images.

  16. Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.

    Science.gov (United States)

    Li, Liang; Wang, Bigong; Wang, Ge

    2016-01-01

    In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.

  17. A singular K-space model for fast reconstruction of magnetic resonance images from undersampled data.

    Science.gov (United States)

    Luo, Jianhua; Mou, Zhiying; Qin, Binjie; Li, Wanqing; Ogunbona, Philip; Robini, Marc C; Zhu, Yuemin

    2017-12-09

    Reconstructing magnetic resonance images from undersampled k-space data is a challenging problem. This paper introduces a novel method of image reconstruction from undersampled k-space data based on the concept of singularizing operators and a novel singular k-space model. Exploring the sparsity of an image in the k-space, the singular k-space model (SKM) is proposed in terms of the k-space functions of a singularizing operator. The singularizing operator is constructed by combining basic difference operators. An algorithm is developed to reliably estimate the model parameters from undersampled k-space data. The estimated parameters are then used to recover the missing k-space data through the model, subsequently achieving high-quality reconstruction of the image using inverse Fourier transform. Experiments on physical phantom and real brain MR images have shown that the proposed SKM method constantly outperforms the popular total variation (TV) and the classical zero-filling (ZF) methods regardless of the undersampling rates, the noise levels, and the image structures. For the same objective quality of the reconstructed images, the proposed method requires much less k-space data than the TV method. The SKM method is an effective method for fast MRI reconstruction from the undersampled k-space data. Graphical abstract Two Real Images and their sparsified images by singularizing operator.

  18. Imaging of limb salvage surgery and pelvic reconstruction following resection of malignant bone tumours

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Tien Jin, E-mail: tien_jin_tan@cgh.com.sg [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada); Aljefri, Ahmad M. [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada); Clarkson, Paul W.; Masri, Bassam A. [Department of Orthopaedics, University of British Columbia, Vancouver, BC (Canada); Ouellette, Hugue A.; Munk, Peter L.; Mallinson, Paul I. [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada)

    2015-09-15

    Highlights: • Advances in reconstructive orthopaedic techniques now allow for limb salvage and prosthetic reconstruction procedures to be performed on patients who would otherwise be required to undergo debilitating limb amputations for malignant bone tumours. • The resulting post-operative imaging of such cases can be daunting for the radiologist to interpret, particularly in the presence of distorted anatomy and unfamiliar hardware. • This article reviews the indications for limb salvage surgery, prosthetic reconstruction devices involved, expected post-operative imaging findings, as well as the potential hardware related complications that may be encountered in the management of such cases. • By being aware of the various types of reconstructive techniques used in limb salvage surgery as well as the potential complications, the reporting radiologist should possess greater confidence in making an accurate assessment of the expected post-operative imaging findings in the management of such cases. - Abstract: Advances in reconstructive orthopaedic techniques now allow for limb salvage and prosthetic reconstruction procedures to be performed on patients who would otherwise be required to undergo debilitating limb amputations for malignant bone tumours. The resulting post-operative imaging of such cases can be daunting for the radiologist to interpret, particularly in the presence of distorted anatomy and unfamiliar hardware. This article reviews the indications for limb salvage surgery, prosthetic reconstruction devices involved, expected post-operative imaging findings, as well as the potential hardware related complications that may be encountered in the management of such cases.

  19. Genetic algorithms applied to reconstructing coded imaging of neutrons and analysis of residual watermark.

    Science.gov (United States)

    Zhang, Tiankui; Hu, Huasi; Jia, Qinggang; Zhang, Fengna; Chen, Da; Li, Zhenghong; Wu, Yuelei; Liu, Zhihua; Hu, Guang; Guo, Wei

    2012-11-01

    Monte-Carlo simulation of neutron coded imaging based on encoding aperture for Z-pinch of large field-of-view with 5 mm radius has been investigated, and then the coded image has been obtained. Reconstruction method of source image based on genetic algorithms (GA) has been established. "Residual watermark," which emerges unavoidably in reconstructed image, while the peak normalization is employed in GA fitness calculation because of its statistical fluctuation amplification, has been discovered and studied. Residual watermark is primarily related to the shape and other parameters of the encoding aperture cross section. The properties and essential causes of the residual watermark were analyzed, while the identification on equivalent radius of aperture was provided. By using the equivalent radius, the reconstruction can also be accomplished without knowing the point spread function (PSF) of actual aperture. The reconstruction result is close to that by using PSF of the actual aperture.

  20. Clinical impact of model-based type iterative reconstruction with fast reconstruction time on image quality of low-dose screening chest CT.

    Science.gov (United States)

    Yuki, Hideaki; Oda, Seitaro; Utsunomiya, Daisuke; Funama, Yoshinori; Kidoh, Masafumi; Namimoto, Tomohiro; Katahira, Kazuhiro; Honda, Keiichi; Tokuyasu, Shinichi; Yamashita, Yasuyuki

    2016-03-01

    Model-based type iterative reconstruction algorithms with fast reconstruction times are now available. The clinical feasibility of their reconstruction has not been evaluated adequately. To investigate the effects of model-based type iterative reconstruction, i.e. iterative model reconstruction (IMR), with fast reconstruction time on the qualitative and quantitative image quality at low-dose chest computed tomography (CT). Thirty-one patients undergoing low-dose screening chest CT were enrolled. Images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (HIR), and IMR algorithms. The CT attenuation and image noise for all reconstructions were calculated at the lung apex, middle, and base. Using a 4-point scale, two reviewers visually evaluated the image quality with respect to vessel sharpness, streak artifact, the mediastinum, and the overall image quality of each reconstruction method. The mean estimated effective dose was 1.0 ± 0.3 mSv. There was no significant difference in the CT attenuation among the three reconstructions. The mean image noise of FBP, HIR, and IMR images was 124.3 ± 57.3, 34.8 ± 10.2, and 22.9 ± 5.8 HU, respectively. There were significant differences for all comparison combinations among the three methods (P reconstruction time for IMR was within 3 min in all cases. At low-dose chest CT, IMR can improve the qualitative and quantitative visualization of both lung and mediastinal structures especially in the lung apex at a clinically acceptable reconstruction time. Its application may improve diagnostic performance. © The Foundation Acta Radiologica 2015.

  1. Fat-constrained 18F-FDG PET reconstruction in hybrid PET/MR imaging.

    Science.gov (United States)

    Prevrhal, Sven; Heinzer, Susanne; Wülker, Christian; Renisch, Steffen; Ratib, Osman; Börnert, Peter

    2014-10-01

    Fusion of information from PET and MR imaging can increase the diagnostic value of both modalities. This work sought to improve (18)F FDG PET image quality by using MR Dixon fat-constrained images to constrain PET image reconstruction to low-fat regions, with the working hypothesis that fatty tissue metabolism is low in glucose consumption. A novel constrained PET reconstruction algorithm was implemented via a modification of the system matrix in list-mode time-of-flight ordered-subsets expectation maximization reconstruction, similar to the way time-of-flight weighting is incorporated. To demonstrate its use in PET/MR imaging, we modeled a constraint based on fat/water-separating Dixon MR images that shift activity away from regions of fat tissue during PET image reconstruction. PET and MR imaging scans of a modified National Electrical Manufacturers Association/International Electrotechnical Commission body phantom simulating body fat/water composition and in vivo experiments on 2 oncology patients were performed on a commercial time-of-flight PET/MR imaging system. Fat-constrained PET reconstruction visibly and quantitatively increased resolution and contrast between high-uptake and fatty-tissue regions without significantly affecting the images in nonfat regions. The incorporation of MR tissue information, such as fat, in image reconstruction can improve the quality of PET images. The combination of a variety of potential other MR tissue characteristics with PET represents a further justification for merging MR data with PET data in hybrid systems. © 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

  2. CT x-ray tube voltage optimisation and image reconstruction evaluation using visual grading analysis

    Science.gov (United States)

    Zheng, Xiaoming; Kim, Ted M.; Davidson, Rob; Lee, Seongju; Shin, Cheongil; Yang, Sook

    2014-03-01

    The purposes of this work were to find an optimal x-ray voltage for CT imaging and to determine the diagnostic effectiveness of image reconstruction techniques by using the visual grading analysis (VGA). Images of the PH-5 CT abdomen phantom (Kagaku Co, Kyoto) were acquired by the Toshiba Aquillion One 320 slices CT system with various exposures (from 10 to 580 mAs) under different tube peak voltages (80, 100 and 120 kVp). The images were reconstructed by employing the FBP and the AIDR 3D iterative reconstructions with Mild, Standard and Strong FBP blending. Image quality was assessed by measuring noise, contrast to noise ratio and human observer's VGA scores. The CT dose index CTDIv was obtained from the values displayed on the images. The best fit for the curves of the image quality VGA vs dose CTDIv is a logistic function from the SPSS estimation. A threshold dose Dt is defined as the CTDIv at the just acceptable for diagnostic image quality and a figure of merit (FOM) is defined as the slope of the standardised logistic function. The Dt and FOM were found to be 5.4, 8.1 and 9.1 mGy and 0.47, 0.51 and 0.38 under the tube voltages of 80, 100 and 120 kVp, respectively, from images reconstructed by the FBP technique. The Dt and FOM values were lower from the images reconstructed by the AIDR 3D in comparison with the FBP technique. The optimal xray peak voltage for the imaging of the PH-5 abdomen phantom by the Aquillion One CT system was found to be at 100 kVp. The images reconstructed by the FBP are more diagnostically effective than that by the AIDR 3D but with a higher dose Dt to the patients.

  3. Bilateral bad pixel and Stokes image reconstruction for microgrid polarimetric imagers

    Science.gov (United States)

    LeMaster, Daniel A.; Ratliff, Bradley M.

    2015-09-01

    Uncorrected or poorly corrected bad pixels reduce the effectiveness of polarimetric clutter suppression. In conventional microgrid processing, bad pixel correction is accomplished as a separate step from Stokes image reconstruction. Here, these two steps are combined to speed processing and provide better estimates of the entire image, including missing samples. A variation on the bilateral filter enables both edge preservation in the Stokes imagery and bad pixel suppression. Understanding the newly presented filter requires two key insights. First, the adaptive nature of the bilateral filter is extended to correct for bad pixels by simply incorporating a bad pixel mask. Second, the bilateral filter for Stokes estimation is the sum of the normalized bilateral filters for estimating each analyzer channel individually. This paper describes the new approach and compares it to our legacy method using simulated imagery.

  4. System and method for three-dimensional image reconstruction using an absolute orientation sensor

    KAUST Repository

    Giancola, Silvio

    2018-01-18

    A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image capture device and records IMU data associated with the image data. The image processor includes one or more processing units and memory for storing instructions that are executed by the one or more processing units, wherein the image processor receives the image data and the IMU data as inputs and utilizes the IMU data to pre-align the first image and the second image, and wherein the image processor utilizes a registration algorithm to register the pre-aligned first and second images.

  5. Efficient discrete cosine transform model-based algorithm for photoacoustic image reconstruction

    Science.gov (United States)

    Zhang, Yan; Wang, Yuanyuan; Zhang, Chen

    2013-06-01

    The model-based algorithm is an effective reconstruction method for photoacoustic imaging (PAI). Compared with the analytical reconstruction algorithms, the model-based algorithm is able to provide a more accurate and high-resolution reconstructed image. However, the relatively heavy computational complexity and huge memory storage requirement often impose restrictions on its applications. We incorporate the discrete cosine transform (DCT) in PAI reconstruction and establish a new photoacoustic model. With this new model, an efficient algorithm is proposed for PAI reconstruction. Relatively significant DCT coefficients of the measured signals are used to reconstruct the image. As a result, the calculation can be saved. The theoretical computation complexity of the proposed algorithm is figured out and it is proved that the proposed method is efficient in calculation. The proposed algorithm is also verified through the numerical simulations and in vitro experiments. Compared with former developed model-based methods, the proposed algorithm is able to provide an equivalent reconstruction with the cost of much less time. From the theoretical analysis and the experiment results, it would be concluded that the model-based PAI reconstruction can be accelerated by using the proposed algorithm, so that the practical applicability of PAI may be enhanced.

  6. Wavelet sparse transform optimization in image reconstruction based on compressed sensing

    Science.gov (United States)

    Ziran, Wei; Huachuang, Wang; Jianlin, Zhang

    2017-06-01

    The high image sparsity is very important to improve the accuracy of compressed sensing reconstruction image, and the wavelet transform can make the image sparse obviously. This paper is the optimization method based on wavelet sparse transform in image reconstruction based on compressed sensing, and we have designed a restraining matrix to optimize the wavelet sparse transform. Firstly, the wavelet coefficients are obtained by wavelet transform of the original signal data, and the wavelet coefficients have a tendency of decreasing gradually. The restraining matrix is used to restrain the small coefficients and is a part of image sparse transform, so as to make the wavelet coefficients more sparse. When the sampling rate is between 0. 15 and 0. 45, the simulation results show that the quality promotion of the reconstructed image is the best, and the peak signal to noise ratio (PSNR) is increased by about 0.5dB to 1dB. At the same time, it is more obvious to improve the reconstruction accuracy of the fingerprint texture image, which to some extent makes up for the shortcomings that reconstruction of texture image by compressed sensing based on the wavelet transform has the low accuracy.

  7. Deep learning methods to guide CT image reconstruction and reduce metal artifacts

    Science.gov (United States)

    Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge

    2017-03-01

    The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.

  8. 3D morphology reconstruction using linear array CCD binocular stereo vision imaging system

    Science.gov (United States)

    Pan, Yu; Wang, Jinjiang

    2018-01-01

    Binocular vision imaging system, which has a small field of view, cannot reconstruct the 3-D shape of the dynamic object. We found a linear array CCD binocular vision imaging system, which uses different calibration and reconstruct methods. On the basis of the binocular vision imaging system, the linear array CCD binocular vision imaging systems which has a wider field of view can reconstruct the 3-D morphology of objects in continuous motion, and the results are accurate. This research mainly introduces the composition and principle of linear array CCD binocular vision imaging system, including the calibration, capture, matching and reconstruction of the imaging system. The system consists of two linear array cameras which were placed in special arrangements and a horizontal moving platform that can pick up objects. The internal and external parameters of the camera are obtained by calibrating in advance. And then using the camera to capture images of moving objects, the results are then matched and 3-D reconstructed. The linear array CCD binocular vision imaging systems can accurately measure the 3-D appearance of moving objects, this essay is of great significance to measure the 3-D morphology of moving objects.

  9. A new approach to solving the prior image constrained compressed sensing (PICCS) with applications in CT image reconstruction

    Science.gov (United States)

    Tang, Yuchao; Zong, Chunxiang

    2017-03-01

    Reduce does exposure in computed tomography (CT) scan has been received much attention in recent years. It is reasonable to reduce the number of projections for reducing does. However, conventional CT image reconstruction methods will lead to streaking artifact due to few-view data. Inspired by the theory of compressive sensing, the total variation minimization method was widely studied in the CT image reconstruction from few-view and limited-angle data. It takes full advantage of the sparsity in the image gradient magnitude. In this paper, we propose a general prior image constrained compressed sensing model and develop an efficient iterative algorithm to solve it. The main idea of our approach is to reformulate the optimization problem as an unconstrained optimization problem with the sum of two convex functions. Then we derive the iterative algorithm by use of the primal dual proximity method. The prior image is reconstructed by a conventional analytic algorithm such as filtered backprojection (FBP) or from a dynamic CT image sequences. We demonstrate the performance of the proposed iterative algorithm in a quite few-view projection data with just 3 percent of the reconstructed image size. The numerical simulation results show that the proposed reconstruction algorithm outperforms the commonly used total variation minimization method.

  10. Quantifying Admissible Undersampling for Sparsity-Exploiting Iterative Image Reconstruction in X-Ray CT

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Heide; Sidky, Emil Y.; Pan, Xiaochuan

    2013-01-01

    Iterative image reconstruction with sparsity-exploiting methods, such as total variation (TV) minimization, investigated in compressive sensing claim potentially large reductions in sampling requirements. Quantifying this claim for computed tomography (CT) is nontrivial, because both full sampling...... of a linear imaging model and address invertibility and stability. In the example application of breast CT, the SSCs are used as reference points of full sampling for quantifying the undersampling admitted by reconstruction through TV-minimization. In numerical simulations, factors affecting admissible...... undersampling are studied. Differences between few-view and few-detector bin reconstruction as well as a relation between object sparsity and admitted undersampling are quantified....

  11. Photon-counting passive 3D image sensing for reconstruction and recognition of partially occluded objects.

    Science.gov (United States)

    Yeom, Seokwon; Javidi, Bahram; Lee, Chae-Wook; Watson, Edward

    2007-11-26

    In this paper, we discuss the reconstruction and the recognition of partially occluded objects using photon counting integral imaging (II). Irradiance scenes are numerically reconstructed for the reference target in three-dimensional (3D) space. Photon counting scenes are estimated for unknown input objects using maximum likelihood estimation (MLE) of Poisson parameter. We propose nonlinear matched filtering in 3D space to recognize partially occluded targets. The recognition performance is substantially improved from the nonlinear matched filtering of elemental images without 3D reconstruction. The discrimination capability is analyzed in terms of Fisher ratio (FR) and receiver operating characteristic (ROC) curves.

  12. A robust state-space kinetics-guided framework for dynamic PET image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Tong, S; Alessio, A M; Kinahan, P E [Department of Radiology, University of Washington, Seattle, WA 98195 (United States); Liu, H; Shi, P, E-mail: saratong@u.washington.edu [Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester, NY 14623 (United States)

    2011-04-21

    Dynamic PET image reconstruction is a challenging issue due to the low SNR and the large quantity of spatio-temporal data. We propose a robust state-space image reconstruction (SSIR) framework for activity reconstruction in dynamic PET. Unlike statistically-based frame-by-frame methods, tracer kinetic modeling is incorporated to provide physiological guidance for the reconstruction, harnessing the temporal information of the dynamic data. Dynamic reconstruction is formulated in a state-space representation, where a compartmental model describes the kinetic processes in a continuous-time system equation, and the imaging data are expressed in a discrete measurement equation. Tracer activity concentrations are treated as the state variables, and are estimated from the dynamic data. Sampled-data H{sub {infinity}} filtering is adopted for robust estimation. H{sub {infinity}} filtering makes no assumptions on the system and measurement statistics, and guarantees bounded estimation error for finite-energy disturbances, leading to robust performance for dynamic data with low SNR and/or errors. This alternative reconstruction approach could help us to deal with unpredictable situations in imaging (e.g. data corruption from failed detector blocks) or inaccurate noise models. Experiments on synthetic phantom and patient PET data are performed to demonstrate feasibility of the SSIR framework, and to explore its potential advantages over frame-by-frame statistical reconstruction approaches.

  13. GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume

    Directory of Open Access Journals (Sweden)

    Xing Zhao

    2009-01-01

    Full Text Available Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation.

  14. Adaptive Statistical Iterative Reconstruction-V Versus Adaptive Statistical Iterative Reconstruction: Impact on Dose Reduction and Image Quality in Body Computed Tomography.

    Science.gov (United States)

    Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo

    2017-09-20

    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 image noise was significantly lower (P 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%.

  15. Total variation regularization in measurement and image space for PET reconstruction

    KAUST Repository

    Burger, M

    2014-09-18

    © 2014 IOP Publishing Ltd. The aim of this paper is to test and analyse a novel technique for image reconstruction in positron emission tomography, which is based on (total variation) regularization on both the image space and the projection space. We formulate our variational problem considering both total variation penalty terms on the image and on an idealized sinogram to be reconstructed from a given Poisson distributed noisy sinogram. We prove existence, uniqueness and stability results for the proposed model and provide some analytical insight into the structures favoured by joint regularization. For the numerical solution of the corresponding discretized problem we employ the split Bregman algorithm and extensively test the approach in comparison to standard total variation regularization on the image. The numerical results show that an additional penalty on the sinogram performs better on reconstructing images with thin structures.

  16. Nonlinear PET parametric image reconstruction with MRI information using kernel method

    Science.gov (United States)

    Gong, Kuang; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

    2017-03-01

    Positron Emission Tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neurology. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information. Previously we have used kernel learning to embed MR information in static PET reconstruction and direct Patlak reconstruction. Here we extend this method to direct reconstruction of nonlinear parameters in a compartment model by using the alternating direction of multiplier method (ADMM) algorithm. Simulation studies show that the proposed method can produce superior parametric images compared with existing methods.

  17. Reconstruction of Computerized Tomography Images on a Cell Broadband Engine using Ray based Interpolation

    DEFF Research Database (Denmark)

    Jørgensen, M. E.; Vinter, Brian

    2009-01-01

    This paper presents a modified version of the filtered backprojection algorithm for reconstruction of images from CT-scanned data [ 2 ]. The algorithm is parallelized and implemented on the Cell Broadband Engine and tested with various densities in data. The original filtered backprojection...... describes a loop through each pixel in the image, locating the nearest rays for the corresponding pixel. The modified version however uses each ray as the center of attention. These are traced through the image, adding to the pixels that are intersected. Due to this modification, the image can...... be reconstructed entirely by the use of integers. To further optimize, the image is divided in sixteen squares and each square is reconstructed by a synergistic processing element (SPE). For the cases where the numbers of SPEs are less than sixteen, a static division of the squares is implemented...

  18. Spectral bidirectional texture function reconstruction by fusing multiple-color and spectral images.

    Science.gov (United States)

    Dong, Wei; Shen, Hui-Liang; Du, Xin; Shao, Si-Jie; Xin, John H

    2016-12-20

    Spectral bidirectional texture function (BTF) is essential for accurate reproduction of material appearance due to its nature of conveying both spatial and spectral information. A practical issue is that the acquisition of raw spectral BTFs is time-consuming. To resolve the limitation, this paper proposes a novel framework for efficient spectral BTF acquisition and reconstruction. The framework acquires red-green-blue (RGB) BTF images and just one spectral image. The full spectral BTFs are reconstructed by fusing the RGB and spectral images based on nonnegative matrix factorization (NMF). Experimental results indicate that the accuracy of spectral reflectance reconstruction is higher than that of existing algorithms. With the reconstructed spectral BTFs, the material appearance can be reproduced with high fidelity under various illumination conditions.

  19. Experimental characterization of the quality of image reconstruction from a chromotomographic system

    Science.gov (United States)

    Dufaud, Kyle J.; Hawks, Michael R.; Tervo, Ryan

    2014-06-01

    A fieldable hyperspectral chromotomographic imager has been developed at the Air Force Institute of Technology to refine component requirements for a space-based system. The imager uses a high speed visible band camera behind a direct-vision prism to simultaneously record two spatial dimensions and the spectral dimension. Capturing all three dimensions simultaneously allows for the hyperspectral imaging of transient events. The prism multiplexes the spectral and spatial information, so a tomographic reconstruction algorithm is required to separate hyperspectral channels. The fixed dispersion of the prism limits the available projections, leading to artifacts in the reconstruction which limit the image quality and spectrometric accuracy of the reconstructions. The amount of degradation is highly dependent on the content of the scene. Experiments were conducted to characterize the image and spectral quality as a function of spatial, spectral, and temporal complexity. We find that in general, image quality degrades as the source bandwidth increases. Spectra estimated from the reconstructed data cube are generally best for point-like sources, and can be highly inaccurate for extended scenes. In other words, the spatial accuracy varies inversely with the spectral width, and the spectral accuracy varies inversely with the spatial width. Experiment results also demonstrate the ability to reconstruct hyperspectral images from transient combustion events.

  20. Reference Information Based Remote Sensing Image Reconstruction with Generalized Nonconvex Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Hongyang Lu

    2016-06-01

    Full Text Available Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1 we propose a nonconvex low-rank approximation for reconstructing RSI; (2 we inject reference prior information to overcome over smoothed edges and texture detail losses; (3 on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.

  1. Computationally rapid method of estimating signal-to-noise ratio for phased array image reconstructions.

    Science.gov (United States)

    Wiens, Curtis N; Kisch, Shawn J; Willig-Onwuachi, Jacob D; McKenzie, Charles A

    2011-10-01

    Measuring signal-to-noise ratio (SNR) for parallel MRI reconstructions is difficult due to spatially dependent noise amplification. Existing approaches for measuring parallel MRI SNR are limited because they are not applicable to all reconstructions, require significant computation time, or rely on repeated image acquisitions. A new SNR estimation approach is proposed, a hybrid of the repeated image acquisitions method detailed in the National Electrical Manufacturers Association (NEMA) standard and the Monte Carlo based pseudo-multiple replica method, in which the difference between images reconstructed from the unaltered acquired data and that same data reconstructed after the addition of calibrated pseudo-noise is used to estimate the noise in the parallel MRI image reconstruction. This new noise estimation method can be used to rapidly compute the pixel-wise SNR of the image generated from any parallel MRI reconstruction of a single acquisition. SNR maps calculated with the new method are validated against existing SNR calculation techniques. Copyright © 2011 Wiley-Liss, Inc.

  2. AN IMAGE-BASED TECHNIQUE FOR 3D BUILDING RECONSTRUCTION USING MULTI-VIEW UAV IMAGES

    Directory of Open Access Journals (Sweden)

    F. Alidoost

    2015-12-01

    Full Text Available Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

  3. An Image-Based Technique for 3d Building Reconstruction Using Multi-View Uav Images

    Science.gov (United States)

    Alidoost, F.; Arefi, H.

    2015-12-01

    Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs) images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM) is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

  4. Improved proton computed tomography by dual modality image reconstruction

    DEFF Research Database (Denmark)

    Hansen, David Christoffer; Bassler, Niels; Petersen, Jørgen B.B.

    2014-01-01

    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...... 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...... 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...

  5. Direct Parametric Image Reconstruction in Reduced Parameter Space for Rapid Multi-Tracer PET Imaging.

    Science.gov (United States)

    Cheng, Xiaoyin; Li, Zhoulei; Liu, Zhen; Navab, Nassir; Huang, Sung-Cheng; Keller, Ulrich; Ziegler, Sibylle; Shi, Kuangyu

    2015-02-12

    The separation of multiple PET tracers within an overlapping scan based on intrinsic differences of tracer pharmacokinetics is challenging, due to limited signal-to-noise ratio (SNR) of PET measurements and high complexity of fitting models. In this study, we developed a direct parametric image reconstruction (DPIR) method for estimating kinetic parameters and recovering single tracer information from rapid multi-tracer PET measurements. This is achieved by integrating a multi-tracer model in a reduced parameter space (RPS) into dynamic image reconstruction. This new RPS model is reformulated from an existing multi-tracer model and contains fewer parameters for kinetic fitting. Ordered-subsets expectation-maximization (OSEM) was employed to approximate log-likelihood function with respect to kinetic parameters. To incorporate the multi-tracer model, an iterative weighted nonlinear least square (WNLS) method was employed. The proposed multi-tracer DPIR (MTDPIR) algorithm was evaluated on dual-tracer PET simulations ([18F]FDG and [11C]MET) as well as on preclinical PET measurements ([18F]FLT and [18F]FDG). The performance of the proposed algorithm was compared to the indirect parameter estimation method with the original dual-tracer model. The respective contributions of the RPS technique and the DPIR method to the performance of the new algorithm were analyzed in detail. For the preclinical evaluation, the tracer separation results were compared with single [18F]FDG scans of the same subjects measured 2 days before the dual-tracer scan. The results of the simulation and preclinical studies demonstrate that the proposed MT-DPIR method can improve the separation of multiple tracers for PET image quantification and kinetic parameter estimations.

  6. Statistical iterative material image reconstruction for spectral CT using a semi-empirical forward model

    Science.gov (United States)

    Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.

    2017-03-01

    In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.

  7. Partial fourier and parallel MR image reconstruction with integrated gradient nonlinearity correction.

    Science.gov (United States)

    Tao, Shengzhen; Trzasko, Joshua D; Shu, Yunhong; Weavers, Paul T; Huston, John; Gray, Erin M; Bernstein, Matt A

    2016-06-01

    To describe how integrated gradient nonlinearity (GNL) correction can be used within noniterative partial Fourier (homodyne) and parallel (SENSE and GRAPPA) MR image reconstruction strategies, and demonstrate that performing GNL correction during, rather than after, these routines mitigates the image blurring and resolution loss caused by postreconstruction image domain based GNL correction. Starting from partial Fourier and parallel magnetic resonance imaging signal models that explicitly account for GNL, noniterative image reconstruction strategies for each accelerated acquisition technique are derived under the same core mathematical assumptions as their standard counterparts. A series of phantom and in vivo experiments on retrospectively undersampled data were performed to investigate the spatial resolution benefit of integrated GNL correction over conventional postreconstruction correction. Phantom and in vivo results demonstrate that the integrated GNL correction reduces the image blurring introduced by the conventional GNL correction, while still correcting GNL-induced coarse-scale geometrical distortion. Images generated from undersampled data using the proposed integrated GNL strategies offer superior depiction of fine image detail, for example, phantom resolution inserts and anatomical tissue boundaries. Noniterative partial Fourier and parallel imaging reconstruction methods with integrated GNL correction reduce the resolution loss that occurs during conventional postreconstruction GNL correction while preserving the computational efficiency of standard reconstruction techniques. Magn Reson Med 75:2534-2544, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  8. A comparison of manual neuronal reconstruction from biocytin histology or 2-photon imaging: morphometry and computer modeling

    National Research Council Canada - National Science Library

    Blackman, Arne V; Grabuschnig, Stefan; Legenstein, Robert; Sjöström, P Jesper

    2014-01-01

    .... Reconstructions are typically created using Neurolucida after biocytin histology (BH). An alternative inexpensive and fast method is to use freeware such as Neuromantic to reconstruct from fluorescence imaging (FI...

  9. Sigma-delta receive beamformer based on cascaded reconstruction for ultrasound imaging application.

    Science.gov (United States)

    Cheong, Jia Hao; Lam, Yvonne Ying Hung; Tiew, Kei Tee; Koh, Liang Mong

    2008-09-01

    A pre-delay reconstruction sigma-delta beamformer (SDBF) was recently proposed to achieve a higher level of integration in ultrasound imaging systems. Nevertheless, the high-order reconstruction filter used in each channel of SDBF makes the beamformer highly complex. The beamformer can be simplified by reconstructing the signal after the delay-and-sum process with only one filter. However, this post-delay reconstruction-based design degrades image quality when dynamic focusing is performed. This paper shows that employing a simple pre-delay filter is sufficient to achieve similar performance as conventional pre-delay reconstruction SDBF, as long as the pre-delay filter provides the required pre-delay signal to-quantization noise ratio (SQNR). Based on this finding, we proposed a cascaded reconstruction beamformer that uses a boxcar filter as the pre-delay filter in each channel. Simulations using real phantom data demonstrate that the proposed beamforming method can achieve a contrast resolution comparable to that of the pre-delay reconstruction beamforming method. In addition, the hardware can be greatly simplified compared with the pre-delay reconstruction beamformers.

  10. Total variation based gradient descent algorithm for sparse-view photoacoustic image reconstruction.

    Science.gov (United States)

    Zhang, Yan; Wang, Yuanyuan; Zhang, Chen

    2012-12-01

    In photoacoustic imaging (PAI), reconstruction from sparse-view sampling data is a remaining challenge in the cases of fast or real-time imaging. In this paper, we present our study on a total variation based gradient descent (TV-GD) algorithm for sparse-view PAI reconstruction. This algorithm involves the total variation (TV) method in compressed sensing (CS) theory. The objective function of the algorithm is modified by adding the TV value of the reconstructed image. With this modification, the reconstructed image could be closer to the real optical energy distribution map. Additionally in the proposed algorithm, the photoacoustic data is processed and the image is updated individually at each detection point. In this way, the calculation with large matrix can be avoided and a more frequent image update can be obtained. Through the numerical simulations, the proposed algorithm is verified and compared with other reconstruction algorithms which have been widely used in PAI. The peak signal-to-noise ratio (PSNR) of the image reconstructed by this algorithm is higher than those by the other algorithms. Additionally, the convergence of the algorithm, the robustness to noise and the tunable parameter are further discussed. The TV-based algorithm is also implemented in the in vitro experiment. The better performance of the proposed method is revealed in the experiments results. From the results, it is seen that the TV-GD algorithm may be a practical and efficient algorithm for sparse-view PAI reconstruction. Copyright © 2012 Elsevier B.V. All rights reserved.

  11. Optimization, evaluation, and comparison of standard algorithms for image reconstruction with the VIP-PET

    Science.gov (United States)

    Mikhaylova, E.; Kolstein, M.; De Lorenzo, G.; Chmeissani, M.

    2014-01-01

    A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project [1]. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head [2]. With unprecedented high channel density (450 channels/cm3) image reconstruction is a challenge. Therefore optimization is needed to find the best algorithm in order to exploit correctly the promising detector potential. The following reconstruction algorithms are evaluated: 2-D Filtered Backprojection (FBP), Ordered Subset Expectation Maximization (OSEM), List-Mode OSEM (LM-OSEM), and the Origin Ensemble (OE) algorithm. The evaluation is based on the comparison of a true image phantom with a set of reconstructed images obtained by each algorithm. This is achieved by calculation of image quality merit parameters such as the bias, the variance and the mean square error (MSE). A systematic optimization of each algorithm is performed by varying the reconstruction parameters, such as the cutoff frequency of the noise filters and the number of iterations. The region of interest (ROI) analysis of the reconstructed phantom is also performed for each algorithm and the results are compared. Additionally, the performance of the image reconstruction methods is compared by calculating the modulation transfer function (MTF). The reconstruction time is also taken into account to choose the optimal algorithm. The analysis is based on GAMOS [3] simulation including the expected CdTe and electronic specifics. PMID:25018777

  12. Impact of iterative reconstruction on image quality of low-dose CT of the lumbar spine.

    Science.gov (United States)

    Alshamari, Muhammed; Geijer, Mats; Norrman, Eva; Lidén, Mats; Krauss, Wolfgang; Jendeberg, Johan; Magnuson, Anders; Geijer, Håkan

    2017-06-01

    Background Iterative reconstruction (IR) is a recent reconstruction algorithm for computed tomography (CT) that can be used instead of the standard algorithm, filtered back projection (FBP), to reduce radiation dose and/or improve image quality. Purpose To evaluate and compare the image quality of low-dose CT of the lumbar spine reconstructed with IR to conventional FBP, without further reduction of radiation dose. Material and Methods Low-dose CT on 55 patients was performed on a Siemens scanner using 120 kV tube voltage, 30 reference mAs, and automatic dose modulation. From raw CT data, lumbar spine CT images were reconstructed with a medium filter (B41f) using FBP and four levels of IR (levels 2-5). Five reviewers scored all images on seven image quality criteria according to the European guidelines on quality criteria for CT, using a five-grade scale. A side-by-side comparison was also performed. Results There was significant improvement in image quality for IR (levels 2-4) compared to FBP. According to visual grading regression, odds ratios of all criteria with 95% confidence intervals for IR2, IR3, IR4, and IR5 were: 1.59 (1.39-1.83), 1.74 (1.51-1.99), 1.68 (1.46-1.93), and 1.08 (0.94-1.23), respectively. In the side-by-side comparison of all reconstructions, images with IR (levels 2-4) received the highest scores. The mean overall CTDIvol was 1.70 mGy (SD 0.46; range, 1.01-3.83 mGy). Image noise decreased in a linear fashion with increased strength of IR. Conclusion Iterative reconstruction at levels 2, 3, and 4 improves image quality of low-dose CT of the lumbar spine compared to FPB.

  13. Optimal image reconstruction intervals for non-invasive coronary angiography with 64-slice CT

    Energy Technology Data Exchange (ETDEWEB)

    Leschka, Sebastian; Husmann, Lars; Desbiolles, Lotus M.; Boehm, Thomas; Marincek, Borut; Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic Radiology, Zurich (Switzerland); Gaemperli, Oliver; Schepis, Tiziano; Koepfli, Pascal [University Hospital Zurich, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiovascular Center, Zurich (Switzerland); University of Zurich, Center for Integrative Human Physiology, Zurich (Switzerland)

    2006-09-15

    The reconstruction intervals providing best image quality for non-invasive coronary angiography with 64-slice computed tomography (CT) were evaluated. Contrast-enhanced, retrospectively electrocardiography (ECG)-gated 64-slice CT coronary angiography was performed in 80 patients (47 male, 33 female; mean age 62.1{+-}10.6 years). Thirteen data sets were reconstructed in 5% increments from 20 to 80% of the R-R interval. Depending on the average heart rate during scanning, patients were grouped as <65 bpm (n=49) and {>=}65 bpm (n=31). Two blinded and independent readers assessed the image quality of each coronary segment with a diameter {>=}1.5 mm using the following scores: 1, no motion artifacts; 2, minor artifacts; 3, moderate artifacts; 4, severe artifacts; and 5, not evaluative. The average heart rate was 63.3{+-}13.1 bpm (range 38-102). Acceptable image quality (scores 1-3) was achieved in 99.1% of all coronary segments (1,162/1,172; mean image quality score 1.55{+-}0.77) in the best reconstruction interval. Best image quality was found at 60% and 65% of the R-R interval for all patients and for each heart rate subgroup, whereas motion artifacts occurred significantly more often (P<0.01) at other reconstruction intervals. At heart rates <65 bpm, acceptable image quality was found in all coronary segments at 60%. At heart rates {>=}65 bpm, the whole coronary artery tree could be visualized with acceptable image quality in 87% (27/31) of the patients at 60%, while ten segments in four patients were rated as non-diagnostic (scores 4-5) at any reconstruction interval. In conclusion, 64-slice CT coronary angiography provides best overall image quality in mid-diastole. At heart rates <65 bpm, diagnostic image quality of all coronary segments can be obtained at a single reconstruction interval of 60%. (orig.)

  14. Importance of the grayscale in early assessment of image quality gains with iterative CT reconstruction

    Science.gov (United States)

    Noo, F.; Hahn, K.; Guo, Z.

    2016-03-01

    Iterative reconstruction methods have become an important research topic in X-ray computed tomography (CT), due to their ability to yield improvements in image quality in comparison with the classical filtered bacprojection method. There are many ways to design an effective iterative reconstruction method. Moreover, for each design, there may be a large number of parameters that can be adjusted. Thus, early assessment of image quality, before clinical deployment, plays a large role in identifying and refining solutions. Currently, there are few publications reporting on early, task-based assessment of image quality achieved with iterative reconstruction methods. We report here on such an assessment, and we illustrate at the same time the importance of the grayscale used for image display when conducting this type of assessment. Our results further support observations made by others that the edge preserving penalty term used in iterative reconstruction is a key ingredient to improving image quality in terms of detection task. Our results also provide a clear demonstration of an implication made in one of our previous publications, namely that the grayscale window plays an important role in image quality comparisons involving iterative CT reconstruction methods.

  15. Systematized methods of surface reconstruction from the serial sectioned images of a cadaver head.

    Science.gov (United States)

    Shin, Dong Sun; Chung, Min Suk; Park, Jin Seo

    2012-01-01

    Three-dimensional models have played important roles in medical simulation and education. Surface models can be manipulated in real time and even online; surface models have significant features for an interactive simulation system. The objective surface models are obtainable from accumulation of each structure's outlines, followed by surface reconstruction. The aim of this research was to suggest the arranged methods of surface reconstruction, which might be applied to building surface models from serial images, such as computed tomographic scans and magnetic resonance images. We used recent state-of-the-art sectioned images of a cadaver head in which several structures were delineated. Four reconstruction methods were regulated according to the structure's morphology: all outlines of a structure are overlapped and singular (method 1), overlapped and not singular (method 2), not overlapped but singular (method 3), and neither overlapped nor singular (method 4). From the trials with various kinds of head structures, we strongly suggested methods 1 and 2, in which volume reconstruction before surface reconstruction accelerated the processing speed on 3D-DOCTOR. So as to use methods 1 and 2, how to make the neighboring outlines overlapped in advance was discussed. The surface models of detailed head structures prepared in this investigation will hopefully contribute to various simulations for clinical practice. The value of the surface models are enhanced if they are placed over the original sectioned images, outlined images, and magnetic resonance images of the same cadaver.

  16. Image reconstruction and scan configurations enabled by optimization-based algorithms in multispectral CT

    Science.gov (United States)

    Chen, Buxin; Zhang, Zheng; Sidky, Emil Y.; Xia, Dan; Pan, Xiaochuan

    2017-11-01

    Optimization-based algorithms for image reconstruction in multispectral (or photon-counting) computed tomography (MCT) remains a topic of active research. The challenge of optimization-based image reconstruction in MCT stems from the inherently non-linear data model that can lead to a non-convex optimization program for which no mathematically exact solver seems to exist for achieving globally optimal solutions. In this work, based upon a non-linear data model, we design a non-convex optimization program, derive its first-order-optimality conditions, and propose an algorithm to solve the program for image reconstruction in MCT. In addition to consideration of image reconstruction for the standard scan configuration, the emphasis is on investigating the algorithm’s potential for enabling non-standard scan configurations with no or minimum hardware modification to existing CT systems, which has potential practical implications for lowered hardware cost, enhanced scanning flexibility, and reduced imaging dose/time in MCT. Numerical studies are carried out for verification of the algorithm and its implementation, and for a preliminary demonstration and characterization of the algorithm in reconstructing images and in enabling non-standard configurations with varying scanning angular range and/or x-ray illumination coverage in MCT.

  17. A physics-based intravascular ultrasound image reconstruction method for lumen segmentation.

    Science.gov (United States)

    Mendizabal-Ruiz, Gerardo; Kakadiaris, Ioannis A

    2016-08-01

    Intravascular ultrasound (IVUS) refers to the medical imaging technique consisting of a miniaturized ultrasound transducer located at the tip of a catheter that can be introduced in the blood vessels providing high-resolution, cross-sectional images of their interior. Current methods for the generation of an IVUS image reconstruction from radio frequency (RF) data do not account for the physics involved in the interaction between the IVUS ultrasound signal and the tissues of the vessel. In this paper, we present a novel method to generate an IVUS image reconstruction based on the use of a scattering model that considers the tissues of the vessel as a distribution of three-dimensional point scatterers. We evaluated the impact of employing the proposed IVUS image reconstruction method in the segmentation of the lumen/wall interface on 40MHz IVUS data using an existing automatic lumen segmentation method. We compared the results with those obtained using the B-mode reconstruction on 600 randomly selected frames from twelve pullback sequences acquired from rabbit aortas and different arteries of swine. Our results indicate the feasibility of employing the proposed IVUS image reconstruction for the segmentation of the lumen. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Radar Imaging of Building Interiors using Sparse Reconstruction

    NARCIS (Netherlands)

    Rossum, W.L. van; Wit, J.J.M. de; Tan, R.G.

    2012-01-01

    At TNO an innovative concept to obtain inside building awareness with stand-off, through-the-wall radar has been developed: SAPPHIRE. The system concept exploits particular phase behavior in the 3D radar data to extract dominant scatterers inside a building. These scatterers can be reconstructed

  19. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL

    2016-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  20. CT imaging of congenital lung lesions: effect of iterative reconstruction on diagnostic performance and radiation dose.

    Science.gov (United States)

    Haggerty, Jay E; Smith, Ethan A; Kunisaki, Shaun M; Dillman, Jonathan R

    2015-07-01

    Different iterative reconstruction techniques are available for use in pediatric computed tomography (CT), but these techniques have not been systematically evaluated in infants. To determine the effect of iterative reconstruction on diagnostic performance, image quality and radiation dose in infants undergoing CT evaluation for congenital lung lesions. A retrospective review of contrast-enhanced chest CT in infants (reconstruction method. CTDIvol was used to calculate size-specific dose estimates (SSDE). CT findings were correlated with intraoperative and histopathological findings. Analysis of variance and the Student's t-test were used to compare image noise measurements and radiation dose estimates between groups. Fifteen CT examinations used filtered back projection (FBP; mean age: 84 days), 15 used adaptive statistical iterative reconstruction (ASiR; mean age: 93 days), and 11 used model-based iterative reconstruction (MBIR; mean age: 98 days). Compared to operative findings, 13/15 (87%), 14/15 (93%) and 11/11 (100%) lesions were correctly characterized using FBP, ASiR and MBIR, respectively. Arterial anatomy was correctly identified in 12/15 (80%) using FBP, 13/15 (87%) using ASiR and 11/11 (100%) using MBIR. Image noise was less for MBIR vs. ASiR (P iterative CT reconstruction techniques while maintaining image quality and lowering radiation dose.

  1. Effect of iterative reconstruction on image quality of low-dose chest computed tomography.

    Science.gov (United States)

    Pavarani, Antonio; Martini, Chiara; Gafa', Veronica; Bini, Paola; Silva, Mario; Ghetti, Caterina; Sverzellati, Nicola

    2016-09-13

    To assess quality and radiologists' preference of low-dose computed tomography (LDCT) reconstructed with filtered back projection (FBP) or Iterative Reconstruction. Thin-section LDCTs (1-mm thick contiguous images; 120 kVp; 30 mAs) of 38 consecutive unselected patients, evaluated for various clinical indications, were reconstructed by four different reconstruction algorithms: FBP and Sinogram-AFfirmed Iterative Reconstruction (SAFIRE) with three different strengths, from 2 to 4 (i.e. S2, S3, S4). The image noise was recorded. Two thoracic radiologists visually compared both anatomic structures (interlobular septa, lung fissures, centrilobular artery, bronchial wall, and small vessels) and lung abnormalities (intralobular reticular opacities, nodules, emphysema, cystic lung disease, decreased-attenuation areas related to constrictive obliterans bronchiolitis, patchy ground-glass opacity, consolidation, and bronchiectasis) using a qualitative four-point scale grading system of the image quality. A lower amount of noise was recorded for LDCTs reformatted with any SAFIRE algorithm, as compared to FBP (P Iterative reconstructions showed lower image noise but did not provide any real improvement for the radiologists' evaluation of thin-section LDCT of the lung.

  2. Development of acoustic model-based iterative reconstruction technique for thick-concrete imaging

    Science.gov (United States)

    Almansouri, Hani; Clayton, Dwight; Kisner, Roger; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector

    2016-02-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.1

  3. Image reconstruction from partial pseudo polar Fourier sampling based on alternating direction total variation minimization

    Science.gov (United States)

    Liu, Qiu-hong; Shu, Fan; Zhang, Wen-kun; Cai, Ai-long; Li, Lei; Yan, Bin

    2013-08-01

    Linear scan Computed Tomography (LCT) has emerged as a promising technique in fields like industrial scanning and security inspection due to its straight-line source trajectory and high scanning speed. However, in practical applications of LCT, the ordinary algorithms suffer from serious artifacts owing to the limited-angle and insufficient data. In this paper, a new method which reconstructs image from partial Fourier data sampled in pseudo polar grid based on alternating direction anisometric total variation minimization has been proposed. The main idea is to reform the image reconstruction problem into solving an under-determined linear equation, and then reconstruct image by applying the popular total variation (TV) minimization to reform an unconstraint optimization by means of augmented Lagrange method and using the alternating minimization method of multiplier (ADMM) which contributes to the fast convergence. The proposed method is practical in the large-scale task of reconstruction due to its algorithmic simplicity and computational efficiency and reconstructs better images. The results of the numerical simulations and pseudo real data reconstructions from the linear scan validate that the proposed method is both efficient and accurate.

  4. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL

    2015-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well s health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  5. Region-Based 4D Tomographic Image Reconstruction: Application to Cardiac X-ray CT

    NARCIS (Netherlands)

    G. Van Eyndhoven (Geert); K.J. Batenburg (Joost); J. Sijbers (Jan)

    2015-01-01

    htmlabstractX-ray computed tomography (CT) is a powerful tool for noninvasive cardiac imaging. However, radiation dose is a major issue. In this paper, we propose an iterative reconstruction method that reduces the radiation dose without compromising image quality. This is achieved by exploiting

  6. Remote Sensing Images Super Resolution Reconstruction Based on Multi-scale Detail Enhancement

    Directory of Open Access Journals (Sweden)

    ZHU Hong

    2016-09-01

    Full Text Available The existing methods are hard to highlight the details after super resolution reconstruction, so it is proposed a super-resolution model frame to enhance the multi-scale details. Firstly, the sequence images are multi-scale deposed to keep the edge structure and the deposed multi-scale image information are differenced. Then, the smoothing information and detail information are interpolated, and a texture detail enhancement function is built to improve the scope of small details. Finally, the coarse-scale image information and small-medium-scale information are confused to get the premier super-resolution reconstruction result, and a local optimizing model is built to further promote the premier image quality. The experiments on the same period and different period remote sensing images show that the objective evaluation index are both largely improved comparing with the interpolation method, traditional total variation(TVmethod,and maximum a posterior(MAP method. The details of the reconstruction image are improved distinctly. The reconstruction image produced using the proposed method provides more high frequency details, and the method proves to be robust and universal for different kinds of satellite remote sensing images.

  7. Algorithms and software for total variation image reconstruction via first-order methods

    DEFF Research Database (Denmark)

    Dahl, Joahim; Hansen, Per Christian; Jensen, Søren Holdt

    2010-01-01

    This paper describes new algorithms and related software for total variation (TV) image reconstruction, more specifically: denoising, inpainting, and deblurring. The algorithms are based on one of Nesterov's first-order methods, tailored to the image processing applications in such a way that...

  8. Three-dimensional photoacoustic tomography through coherent-weighted focal-line-based image reconstruction

    Science.gov (United States)

    Wang, Depeng; Wang, Yuehang; Zhou, Yang; Lovell, Jonathan F.; Xia, Jun

    2017-03-01

    Here, we introduce a new image reconstruction algorithm that combines coherent weighting with focal-line-based three-dimensional image reconstruction. The new algorithm addresses the major limitation of a linear ultrasound transducer array, i.e., the poor elevation resolution, and does not require any modification to the imaging system or the scanning geometry. We first numerically validated our approach through simulation and then experimentally tested it in phantom and in vivo. Both simulation and experimental results proved that the method can significantly improve the elevation resolution (up to 3.4 times in our experiment) and enhance object contrast.

  9. Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm.

    Science.gov (United States)

    Sidky, Emil Y; Jørgensen, Jakob H; Pan, Xiaochuan

    2012-05-21

    The primal-dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1-26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application modeling breast CT with low-intensity x-ray illumination is presented.

  10. Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

    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...

  11. Sparse image reconstruction on the sphere: implications of a new sampling theorem.

    Science.gov (United States)

    McEwen, Jason D; Puy, Gilles; Thiran, Jean-Philippe; Vandergheynst, Pierre; Van De Ville, Dimitri; Wiaux, Yves

    2013-06-01

    We study the impact of sampling theorems on the fidelity of sparse image reconstruction on the sphere. We discuss how a reduction in the number of samples required to represent all information content of a band-limited signal acts to improve the fidelity of sparse image reconstruction, through both the dimensionality and sparsity of signals. To demonstrate this result, we consider a simple inpainting problem on the sphere and consider images sparse in the magnitude of their gradient. We develop a framework for total variation inpainting on the sphere, including fast methods to render the inpainting problem computationally feasible at high resolution. Recently a new sampling theorem on the sphere was developed, reducing the required number of samples by a factor of two for equiangular sampling schemes. Through numerical simulations, we verify the enhanced fidelity of sparse image reconstruction due to the more efficient sampling of the sphere provided by the new sampling theorem.

  12. Model-based reconstruction for illumination variation in face images

    NARCIS (Netherlands)

    Boom, B.J.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2008-01-01

    We propose a novel method to correct for arbitrary illumination variation in the face images. The main purpose is to improve recognition results of face images taken under uncontrolled illumination conditions. We correct the illumination variation in the face images using a face shape model, which

  13. Image reconstruction in a passive element enriched photoacoustic tomography setup

    NARCIS (Netherlands)

    Willemink, Rene

    2010-01-01

    Photoacoustic imaging is a relatively new imaging technology, in which an object is illuminated with optical energy and where in return measurements are taken in the acoustical domain, in order to image the optical absorption distribution inside the object. In this thesis we focus on an experimental

  14. Accurate tissue characterization in low-dose CT imaging with pure iterative reconstruction.

    Science.gov (United States)

    Murphy, Kevin P; McLaughlin, Patrick D; Twomey, Maria; Chan, Vincent E; Moloney, Fiachra; Fung, Adrian J; Chan, Faimee E; Kao, Tafline; O'Neill, Siobhan B; Watson, Benjamin; O'Connor, Owen J; Maher, Michael M

    2017-04-01

    We assess the ability of low-dose hybrid iterative reconstruction (IR) and 'pure' model-based IR (MBIR) images to maintain accurate Hounsfield unit (HU)-determined tissue characterization. Standard-protocol (SP) and low-dose modified-protocol (MP) CTs were contemporaneously acquired in 34 Crohn's disease patients referred for CT. SP image reconstruction was via the manufacturer's recommendations (60% FBP, filtered back projection; 40% ASiR, Adaptive Statistical iterative Reconstruction; SP-ASiR40). MP data sets underwent four reconstructions (100% FBP; 40% ASiR; 70% ASiR; MBIR). Three observers measured tissue volumes using HU thresholds for fat, soft tissue and bone/contrast on each data set. Analysis was via SPSS. Inter-observer agreement was strong for 1530 datapoints (rs > 0.9). MP-MBIR tissue volume measurement was superior to other MP reconstructions and closely correlated with the reference SP-ASiR40 images for all tissue types. MP-MBIR superiority was most marked for fat volume calculation - close SP-ASiR40 and MP-MBIR Bland-Altman plot correlation was seen with the lowest average difference (336 cm(3) ) when compared with other MP reconstructions. Hounsfield unit-determined tissue volume calculations from MP-MBIR images resulted in values comparable to SP-ASiR40 calculations and values that are superior to MP-ASiR images. Accuracy of estimation of volume of tissues (e.g. fat) using segmentation software on low-dose CT images appears optimal when reconstructed with pure IR. © 2016 The Royal Australian and New Zealand College of Radiologists.

  15. Fast 3D Variable-FOV Reconstruction for Parallel Imaging with Localized Sensitivities

    CERN Document Server

    Can, Yiğit Baran; Çukur, Tolga

    2016-01-01

    Several successful iterative approaches have recently been proposed for parallel-imaging reconstructions of variable-density (VD) acquisitions, but they often induce substantial computational burden for non-Cartesian data. Here we propose a generalized variable-FOV PILS reconstruction 3D VD Cartesian and non-Cartesian data. The proposed method separates k-space into non-intersecting annuli based on sampling density, and sets the 3D reconstruction FOV for each annulus based on the respective sampling density. The variable-FOV method is compared against conventional gridding, PILS, and ESPIRiT reconstructions. Results indicate that the proposed method yields better artifact suppression compared to gridding and PILS, and improves noise conditioning relative to ESPIRiT, enabling fast and high-quality reconstructions of 3D datasets.

  16. Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera

    Directory of Open Access Journals (Sweden)

    Yufu Qu

    2018-01-01

    Full Text Available In order to reconstruct three-dimensional (3D structures from an image sequence captured by unmanned aerial vehicles’ camera (UAVs and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth–map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

  17. Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera.

    Science.gov (United States)

    Qu, Yufu; Huang, Jianyu; Zhang, Xuan

    2018-01-14

    In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles' camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth-map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

  18. Electrical CT image reconstruction technique for powder flow in petroleum refinery process

    Science.gov (United States)

    Takei, Masahiro; Doh, Deog-Hee; Ochi, Mitsuaki

    2008-03-01

    A new reconstruction method called sampled pattern matching (SPM) was applied to the image reconstruction of an electrical capacitance computed tomography in powder flow in a vertical pipe for petroleum refinery process. This new method is able to achieve stable convergence without the use of an empirical value. Experiments were carried out using fluid catalytic cracking (FCC) catalysts as powder with two air volume flow rates and four powder volume flow rates to measure the capacitance of a pipe cross section. The SPM method is compared with conventional methods in terms of volume fraction, residual capacitance, and correlation capacitance. Overall, the SPM method proved superior to conventional methods without any empirical value because SPM achieves accurate reconstruction by using an objective function that is calculated as the inner product calculation between the experimental capacitance and the reconstructed image capacitance.

  19. Super Resolution Reconstruction Based on Adaptive Detail Enhancement for ZY-3 Satellite Images

    Science.gov (United States)

    Zhu, Hong; Song, Weidong; Tan, Hai; Wang, Jingxue; Jia, Di

    2016-06-01

    Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

  20. MO-DE-BRA-06: 3D Image Acquisition and Reconstruction Explained with Online Animations

    Energy Technology Data Exchange (ETDEWEB)

    Kesner, A

    2016-06-15

    Purpose: Understanding the principles of 3D imaging and image reconstruction is fundamental to the field of medical imaging. Clinicians, technologists, physicists, patients, students, and inquisitive minds all stand to benefit from greater comprehension of the supporting technologies. To help explain the basic principles of 3D imaging, we developed multi-frame animations that convey the concepts of tomographic imaging. The series of free (gif) animations are accessible online, and provide a multimedia introduction to the main concepts of image reconstruction. Methods: Text and animations were created to convey the principles of analytic tomography in CT, PET, and SPECT. Specific topics covered included: principles of sinograms/image data storage, forward projection, principles of PET acquisitions, and filtered backprojection. A total of 8 animations were created and presented for CT, PET, and digital phantom formats. In addition, a free executable is also provided to allow users to create their own tomographic animations – providing an opportunity for interaction and personalization to help foster user interest. Results: Tutorial text and animations have been posted online, freely available to view or download. The animations are in first position in a google search of “image reconstruction animations”. The website currently receives approximately 200 hits/month, from all over the world, and the usage is growing. Positive feedback has been collected from users. Conclusion: We identified a need for improved teaching tools to help visualize the (temporally variant) concepts of image reconstruction, and have shown that animations can be a useful tool for this aspect of education. Furthermore, posting animations freely on the web has shown to be a good way to maximize their impact in the community. In future endeavors, we hope to expand this animated content, to cover principles of iterative reconstruction, as well as other phenomena relating to imaging.

  1. A New Method for Superresolution Image Reconstruction Based on Surveying Adjustment

    Directory of Open Access Journals (Sweden)

    Jianjun Zhu

    2014-01-01

    Full Text Available A new method for superresolution image reconstruction based on surveying adjustment method is described in this paper. The main idea of such new method is that a sequence of low-resolution images are taken firstly as observations, and then observation equations are established for the superresolution image reconstruction. The gray function of the object surface can be found by using surveying adjustment method from the observation equations. High-resolution pixel value of the corresponding area can be calculated by using the gray function. The results show that the proposed algorithm converges much faster than that of conventional superresolution image reconstruction method. By using the new method, the visual feeling of reconstructed image can be greatly improved compared to that of iterative back projection algorithm, and its peak signal-to-noise ratio can also be improved by nearly 1 dB higher than the projection onto convex sets algorithm. Furthermore, this method can successfully avoid the ill-posed problems in reconstruction process.

  2. Joint reconstruction via coupled Bregman iterations with applications to PET-MR imaging

    Science.gov (United States)

    Rasch, Julian; Brinkmann, Eva-Maria; Burger, Martin

    2018-01-01

    Joint reconstruction has recently attracted a lot of attention, especially in the field of medical multi-modality imaging such as PET-MRI. Most of the developed methods rely on the comparison of image gradients, or more precisely their location, direction and magnitude, to make use of structural similarities between the images. A challenge and still an open issue for most of the methods is to handle images in entirely different scales, i.e. different magnitudes of gradients that cannot be dealt with by a global scaling of the data. We propose the use of generalized Bregman distances and infimal convolutions thereof with regard to the well-known total variation functional. The use of a total variation subgradient respectively the involved vector field rather than an image gradient naturally excludes the magnitudes of gradients, which in particular solves the scaling behavior. Additionally, the presented method features a weighting that allows to control the amount of interaction between channels. We give insights into the general behavior of the method, before we further tailor it to a particular application, namely PET-MRI joint reconstruction. To do so, we compute joint reconstruction results from blurry Poisson data for PET and undersampled Fourier data from MRI and show that we can gain a mutual benefit for both modalities. In particular, the results are superior to the respective separate reconstructions and other joint reconstruction methods.

  3. A comparison framework for temporal image reconstructions in electrical impedance tomography.

    Science.gov (United States)

    Gagnon, Hervé; Grychtol, Bartłomiej; Adler, Andy

    2015-06-01

    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.

  4. THREE-DIMENSIONAL BUILDING RECONSTRUCTION USING IMAGES OBTAINED BY UNMANNED AERIAL VEHICLES

    Directory of Open Access Journals (Sweden)

    C. Wefelscheid

    2012-09-01

    Full Text Available Unmanned Aerial Vehicles (UAVs offer several new possibilities in a wide range of applications. One example is the 3D reconstruction of buildings. In former times this was either restricted by earthbound vehicles to the reconstruction of facades or by air-borne sensors to generate only very coarse building models. This paper describes an approach for fully automatic image-based 3D reconstruction of buildings using UAVs. UAVs are able to observe the whole 3D scene and to capture images of the object of interest from completely different perspectives. The platform used by this work is a Falcon 8 octocopter from Ascending Technologies. A slightly modified high-resolution consumer camera serves as sensor for data acquisition. The final 3D reconstruction is computed offline after image acquisition and follows a reconstruction process originally developed for image sequences obtained by earthbound vehicles. The per- formance of the described method is evaluated on benchmark datasets showing that the achieved accuracy is high and even comparable with Light Detection and Ranging (LIDAR. Additionally, the results of the application of the complete processing-chain starting at image acquisition and ending in a dense surface-mesh are presented and discussed.

  5. Designing sparse sensing matrix for compressive sensing to reconstruct high resolution medical images

    Directory of Open Access Journals (Sweden)

    Vibha Tiwari

    2015-12-01

    Full Text Available Compressive sensing theory enables faithful reconstruction of signals, sparse in domain $ \\Psi $, at sampling rate lesser than Nyquist criterion, while using sampling or sensing matrix $ \\Phi $ which satisfies restricted isometric property. The role played by sensing matrix $ \\Phi $ and sparsity matrix $ \\Psi $ is vital in faithful reconstruction. If the sensing matrix is dense then it takes large storage space and leads to high computational cost. In this paper, effort is made to design sparse sensing matrix with least incurred computational cost while maintaining quality of reconstructed image. The design approach followed is based on sparse block circulant matrix (SBCM with few modifications. The other used sparse sensing matrix consists of 15 ones in each column. The medical images used are acquired from US, MRI and CT modalities. The image quality measurement parameters are used to compare the performance of reconstructed medical images using various sensing matrices. It is observed that, since Gram matrix of dictionary matrix ($ \\Phi \\Psi \\mathrm{} $ is closed to identity matrix in case of proposed modified SBCM, therefore, it helps to reconstruct the medical images of very good quality.

  6. Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Chong Fan

    2017-03-01

    Full Text Available A sub-block algorithm is usually applied in the super-resolution (SR reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

  7. Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images.

    Science.gov (United States)

    Fan, Chong; Chen, Xushuai; Zhong, Lei; Zhou, Min; Shi, Yun; Duan, Yulin

    2017-03-18

    A sub-block algorithm is usually applied in the super-resolution (SR) reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

  8. 4D-CBCT reconstruction using MV portal imaging during volumetric modulated arc therapy.

    Science.gov (United States)

    Kida, Satoshi; Saotome, Naoya; Masutani, Yoshitaka; Yamashita, Hideomi; Ohtomo, Kuni; Nakagawa, Keiichi; Sakumi, Akira; Haga, Akihiro

    2011-09-01

    Recording target motion during treatment is important for verifying the irradiated region. Recently, cone-beam computed tomography (CBCT) reconstruction from portal images acquired during volumetric modulated arc therapy (VMAT), known as VMAT-CBCT, has been investigated. In this study, we developed a four-dimensional (4D) version of the VMAT-CBCT. The MV portal images were sequentially acquired from an electronic portal imaging device. The flex, background, monitor unit, field size, and multi-leaf collimator masking corrections were considered during image reconstruction. A 4D VMAT-CBCT requires a respiratory signal during image acquisition. An image-based phase recognition (IBPR) method was performed using normalised cross correlation to extract a respiratory signal from the series of portal images. Our original IBPR method enabled us to reconstruct 4D VMAT-CBCT with no external devices. We confirmed that 4D VMAT-CBCT was feasible for two patients and in good agreement with in-treatment 4D kV-CBCT. The visibility of the anatomy in 4D VMAT-CBCT reconstruction for lung cancer patients has the potential of using 4D VMAT-CBCT as a tool for verifying relative positions of tumour for each respiratory phase. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  9. Upgrade to iterative image reconstruction (IR) in abdominal MDCT imaging. A clinical study for detailed parameter optimization beyond vendor recommendations using the adaptive statistical iterative reconstruction environment (ASIR)

    Energy Technology Data Exchange (ETDEWEB)

    Mueck, F.G.; Koerner, M.; Scherr, M.K.; Geyer, L.L.; Deak, Z.; Linsenmaier, U.; Reiser, M.; Wirth, S. [Ludwig-Maximilians-Univ. Muenchen (Germany). Inst. fuer Klinische Radiologie

    2012-03-15

    To compare the image quality of dose-reduced 64-row abdominal CT reconstructed at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed with filtered back-projection (FBP) in a clinical setting and upgrade situation. Abdominal baseline examinations (noise index NI = 29; LightSpeed VCT XT, GE) were intra-individually compared to follow-up studies on a CT with an ASIR option (NI = 43; Discovery HD750, GE), n = 42. Standard-kernel images were calculated with ASIR blendings of 0 - 100 % in slice and volume mode, respectively. Three experienced radiologists compared the image quality of these 567 sets to their corresponding full-dose baseline examination (-2: diagnostically inferior, -1: inferior, 0: equal, +1: superior, +2: diagnostically superior). Furthermore, a phantom was scanned. Statistical analysis used the Wilcoxon - the Mann-Whitney U-test and the intra-class correlation (ICC). The mean CTDIvol decreased from 19.7 {+-} 5.5 to 12.2 {+-} 4.7 mGy (p < 0.001). The ICC was 0.861. The total image quality of the dose-reduced ASIR studies was comparable to the baseline at ASIR 50 % in slice (p = 0.18) and ASIR 50 - 100 % in volume mode (p > 0.10). Volume mode performed 73 % slower than slice mode (p < 0.01). After the system upgrade, the vendor recommendation of ASIR 50 % in slice mode allowed for a dose reduction of 38 % in abdominal CT with comparable image quality and time expenditure. However, there is still further dose reduction potential for more complex reconstruction settings. (orig.)

  10. 3D Surface Reconstruction From 2D Binary Images

    Science.gov (United States)

    Raviv, D.; Pao, Y. H.; Loparo, K.

    1987-01-01

    We introduce methods for reconstruction of three dimensional surfaces. They are based on moving the light source relative to an object whose shape is to be determined. Using a camera which is placed above the object and a moving light source, the shadows cast by the object at each angle are recorded and analyzed. In one method, the light source is rotated in a horizontal plane; this method is a simple way to get segmentation between different surfaces. The second method uses a light source which is rotated in a vertical plane. For each section of the object a shadow diagram (Shadowgram) is formed and analyzed to get the third dimension. The Shadowgram has some features which make the reconstruction very simple. By looking at some curves of the Shadowgram, invisible surfaces can be partially reconstructed. The above methods can be combined to achieve simple solutions for problems in the robotics area e.g., the bin-picking problem. A set of experimental results demonstrates the robustness and usefulness of the methods.

  11. Ill-posed problem and regularization in reconstruction of radiobiological parameters from serial tumor imaging data

    Science.gov (United States)

    Chvetsov, Alevei V.; Sandison, George A.; Schwartz, Jeffrey L.; Rengan, Ramesh

    2015-11-01

    The main objective of this article is to improve the stability of reconstruction algorithms for estimation of radiobiological parameters using serial tumor imaging data acquired during radiation therapy. Serial images of tumor response to radiation therapy represent a complex summation of several exponential processes as treatment induced cell inactivation, tumor growth rates, and the rate of cell loss. Accurate assessment of treatment response would require separation of these processes because they define radiobiological determinants of treatment response and, correspondingly, tumor control probability. However, the estimation of radiobiological parameters using imaging data can be considered an inverse ill-posed problem because a sum of several exponentials would produce the Fredholm integral equation of the first kind which is ill posed. Therefore, the stability of reconstruction of radiobiological parameters presents a problem even for the simplest models of tumor response. To study stability of the parameter reconstruction problem, we used a set of serial CT imaging data for head and neck cancer and a simplest case of a two-level cell population model of tumor response. Inverse reconstruction was performed using a simulated annealing algorithm to minimize a least squared objective function. Results show that the reconstructed values of cell surviving fractions and cell doubling time exhibit significant nonphysical fluctuations if no stabilization algorithms are applied. However, after applying a stabilization algorithm based on variational regularization, the reconstruction produces statistical distributions for survival fractions and doubling time that are comparable to published in vitro data. This algorithm is an advance over our previous work where only cell surviving fractions were reconstructed. We conclude that variational regularization allows for an increase in the number of free parameters in our model which enables development of more

  12. Image quality improvements using adaptive statistical iterative reconstruction for evaluating chronic myocardial infarction using iodine density images with spectral CT.

    Science.gov (United States)

    Kishimoto, Junichi; Ohta, Yasutoshi; Kitao, Shinichiro; Watanabe, Tomomi; Ogawa, Toshihide

    2017-10-19

    Single-source dual-energy CT (ssDECT) allows the reconstruction of iodine density images (IDIs) from projection based computing. We hypothesized that adding adaptive statistical iterative reconstruction (ASiR) could improve image quality. The aim of our study was to evaluate the effect and determine the optimal blend percentages of ASiR for IDI of myocardial late iodine enhancement (LIE) in the evaluation of chronic myocardial infarction using ssDECT. A total of 28 patients underwent cardiac LIE using a ssDECT scanner. IDIs between 0 and 100% of ASiR contributions in 10% increments were reconstructed. The signal-to-noise ratio (SNR) of remote myocardia and the contrast-to-noise ratio (CNR) of infarcted myocardia were measured. Transmural extent of infarction was graded using a 5-point scale. The SNR, CNR, and transmural extent were assessed for each ASiR contribution ratio. The transmural extents were compared with MRI as a reference standard. Compared to 0% ASiR, the use of 20-100% ASiR resulted in a reduction of image noise (p ASiR images, reconstruction with 100% ASiR image showed the highest improvement in SNR (229%; p ASiR above 80% showed the highest ratio (73.7%) of accurate transmural extent classification. In conclusion, ASiR intensity of 80-100% in IDIs can improve image quality without changes in signal and maximizes the accuracy of transmural extent in infarcted myocardium.

  13. Prior image guided undersampled dual energy reconstruction with piecewise polynomial function constraint.

    Science.gov (United States)

    Wu, Dufan; Zhang, Li; Li, Liang; Shen, Le; Xing, Yuxiang

    2013-01-01

    Dual energy CT has the ability to give more information about the test object by reconstructing the attenuation factors under different energies. These images under different energies share identical structures but different attenuation factors. By referring to the fully sampled low-energy image, we show that it is possible to greatly reduce the sampling rate of the high-energy image in order to lower dose. To compensate the attenuation factor difference between the two modalities, we use piecewise polynomial fitting to fit the low-energy image to the high-energy image. During the reconstruction, the result is constrained by its distance to the fitted image, and the structural information thus can be preserved. An ASD-POCS-based optimization schedule is proposed to solve the problem, and numerical simulations are taken to verify the algorithm.

  14. Prior Image Guided Undersampled Dual Energy Reconstruction with Piecewise Polynomial Function Constraint

    Directory of Open Access Journals (Sweden)

    Dufan Wu

    2013-01-01

    Full Text Available Dual energy CT has the ability to give more information about the test object by reconstructing the attenuation factors under different energies. These images under different energies share identical structures but different attenuation factors. By referring to the fully sampled low-energy image, we show that it is possible to greatly reduce the sampling rate of the high-energy image in order to lower dose. To compensate the attenuation factor difference between the two modalities, we use piecewise polynomial fitting to fit the low-energy image to the high-energy image. During the reconstruction, the result is constrained by its distance to the fitted image, and the structural information thus can be preserved. An ASD-POCS-based optimization schedule is proposed to solve the problem, and numerical simulations are taken to verify the algorithm.

  15. CT Image Reconstruction by Spatial-Radon Domain Data-Driven Tight Frame Regularization

    CERN Document Server

    Zhan, Ruohan

    2016-01-01

    This paper proposes a spatial-Radon domain CT image reconstruction model based on data-driven tight frames (SRD-DDTF). The proposed SRD-DDTF model combines the idea of joint image and Radon domain inpainting model of \\cite{Dong2013X} and that of the data-driven tight frames for image denoising \\cite{cai2014data}. It is different from existing models in that both CT image and its corresponding high quality projection image are reconstructed simultaneously using sparsity priors by tight frames that are adaptively learned from the data to provide optimal sparse approximations. An alternative minimization algorithm is designed to solve the proposed model which is nonsmooth and nonconvex. Convergence analysis of the algorithm is provided. Numerical experiments showed that the SRD-DDTF model is superior to the model by \\cite{Dong2013X} especially in recovering some subtle structures in the images.

  16. Data Reduction and Image Reconstruction Techniques for Non-redundant Masking

    Science.gov (United States)

    Sallum, S.; Eisner, J.

    2017-11-01

    The technique of non-redundant masking (NRM) transforms a conventional telescope into an interferometric array. In practice, this provides a much better constrained point-spread function than a filled aperture and thus higher resolution than traditional imaging methods. Here, we describe an NRM data reduction pipeline. We discuss strategies for NRM observations regarding dithering patterns and calibrator selection. We describe relevant image calibrations and use example Large Binocular Telescope data sets to show their effects on the scatter in the Fourier measurements. We also describe the various ways to calculate Fourier quantities, and discuss different calibration strategies. We present the results of image reconstructions from simulated observations where we adjust prior images, weighting schemes, and error bar estimation. We compare two imaging algorithms and discuss implications for reconstructing images from real observations. Finally, we explore how the current state of the art compares to next-generation Extremely Large Telescopes.

  17. Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction

    Directory of Open Access Journals (Sweden)

    Hsuan-Ming Huang

    2017-01-01

    Full Text Available Background and Objective. 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. Methods. 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. 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. Conclusions. 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.

  18. Magnetic resonance imaging of double-bundle anterior cruciate ligament reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Poellinger, Alexander; Hamm, Bernd; Asbach, Patrick [Charite, Department of Radiology, Berlin (Germany); Scheffler, Sven [Charite, Department for Orthopaedic Surgery and Traumatology, Center for Musculoskeletal Surgery, Berlin (Germany)

    2009-04-15

    Reconstruction of the anterior cruciate ligament (ACL) using the double-bundle technique is getting highly increasing attention. This surgical approach uses two separate tendon grafts with the intention to reconstruct both anatomic bundles in order to restore the full biomechanical function of the original ligament. With the increasing popularity of this technique, radiologists will be more frequently confronted with patients who underwent this surgical procedure. The aims of this essay are to briefly describe the basic biomechanical and surgical principles and to summarize the magnetic resonance imaging findings of the knee after double-bundle ACL reconstruction. (orig.)

  19. Simultaneous deblurring and iterative reconstruction of CBCT for image guided brain radiosurgery.

    Science.gov (United States)

    Hashemi, SayedMasoud; Song, William Y; Sahgal, Arjun; Lee, Young; Huynh, Christopher; Grouza, Vladimir; Nordström, Håkan; Eriksson, Markus; Dorenlot, Antoine; Régis, Jean Marie; Mainprize, James G; Ruschin, Mark

    2017-04-07

    One of the limiting factors in cone-beam CT (CBCT) image quality is system blur, caused by detector response, x-ray source focal spot size, azimuthal blurring, and reconstruction algorithm. In this work, we develop a novel iterative reconstruction algorithm that improves spatial resolution by explicitly accounting for image unsharpness caused by different factors in the reconstruction formulation. While the model-based iterative reconstruction techniques use prior information about the detector response and x-ray source, our proposed technique uses a simple measurable blurring model. In our reconstruction algorithm, denoted as simultaneous deblurring and iterative reconstruction (SDIR), the blur kernel can be estimated using the modulation transfer function (MTF) slice of the CatPhan phantom or any other MTF phantom, such as wire phantoms. The proposed image reconstruction formulation includes two regularization terms: (1) total variation (TV) and (2) nonlocal regularization, solved with a split Bregman augmented Lagrangian iterative method. The SDIR formulation preserves edges, eases the parameter adjustments to achieve both high spatial resolution and low noise variances, and reduces the staircase effect caused by regular TV-penalized iterative algorithms. The proposed algorithm is optimized for a point-of-care head CBCT unit for image-guided radiosurgery and is tested with CatPhan phantom, an anthropomorphic head phantom, and 6 clinical brain stereotactic radiosurgery cases. Our experiments indicate that SDIR outperforms the conventional filtered back projection and TV penalized simultaneous algebraic reconstruction technique methods (represented by adaptive steepest-descent POCS algorithm, ASD-POCS) in terms of MTF and line pair resolution, and retains the favorable properties of the standard TV-based iterative reconstruction algorithms in improving the contrast and reducing the reconstruction artifacts. It improves the visibility of the high contrast details

  20. Simultaneous deblurring and iterative reconstruction of CBCT for image guided brain radiosurgery

    Science.gov (United States)

    Hashemi, SayedMasoud; Song, William Y.; Sahgal, Arjun; Lee, Young; Huynh, Christopher; Grouza, Vladimir; Nordström, Håkan; Eriksson, Markus; Dorenlot, Antoine; Régis, Jean Marie; Mainprize, James G.; Ruschin, Mark

    2017-04-01

    One of the limiting factors in cone-beam CT (CBCT) image quality is system blur, caused by detector response, x-ray source focal spot size, azimuthal blurring, and reconstruction algorithm. In this work, we develop a novel iterative reconstruction algorithm that improves spatial resolution by explicitly accounting for image unsharpness caused by different factors in the reconstruction formulation. While the model-based iterative reconstruction techniques use prior information about the detector response and x-ray source, our proposed technique uses a simple measurable blurring model. In our reconstruction algorithm, denoted as simultaneous deblurring and iterative reconstruction (SDIR), the blur kernel can be estimated using the modulation transfer function (MTF) slice of the CatPhan phantom or any other MTF phantom, such as wire phantoms. The proposed image reconstruction formulation includes two regularization terms: (1) total variation (TV) and (2) nonlocal regularization, solved with a split Bregman augmented Lagrangian iterative method. The SDIR formulation preserves edges, eases the parameter adjustments to achieve both high spatial resolution and low noise variances, and reduces the staircase effect caused by regular TV-penalized iterative algorithms. The proposed algorithm is optimized for a point-of-care head CBCT unit for image-guided radiosurgery and is tested with CatPhan phantom, an anthropomorphic head phantom, and 6 clinical brain stereotactic radiosurgery cases. Our experiments indicate that SDIR outperforms the conventional filtered back projection and TV penalized simultaneous algebraic reconstruction technique methods (represented by adaptive steepest-descent POCS algorithm, ASD-POCS) in terms of MTF and line pair resolution, and retains the favorable properties of the standard TV-based iterative reconstruction algorithms in improving the contrast and reducing the reconstruction artifacts. It improves the visibility of the high contrast details

  1. Individual thorax geometry reduces position and size differences in reconstructed images of electrical impedance tomography.

    Science.gov (United States)

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2014-01-01

    Due to the ill-posed problem, the electrical impedance within the thorax cannot be exactly reconstructed. The aim of our study was to prove that reconstruction with individual thorax geometry improved the quality of EIT (electrical impedance tomography) images. Seven mechanically ventilated patients with acute respiratory distress syndrome were examined by EIT. The thorax contours were determined from routine computed tomography (CT) images based on automatic threshold filtering. EIT raw data was reconstructed offline with (1) back-projection with circular forward model; (2) GREIT reconstruction method with circular forward model and (3) GREIT with individual thorax geometry. The resulting EIT images were compared to rescaled CT images. The distance between the lung contour and the thorax contour was calculated for each method and the differences to that in CT were denoted as position differences. Shape differences was defined as the ratio of thorax (or lungs) size in EIT and that in rescaled CT. Method (3) has the smallest position differences (6.6 ± 2.8, 5.3 ± 3.3, 2.3 ± 1.4 in pixel, for each reconstruction method respectively; mean ± SD). The thorax and lungs sizes in the transformed CT images were 514 ± 73 and 177 ± 39. Shape differences of thorax were 1.81 ± 0.26, 1.81 ± 0.26, 1.10 ± 0.12 and that of lungs were 1.69 ± 0.45, 1.52 ± 0.45, 1.34 ± 0.35 for each method respectively. The reconstructed images using the GREIT method with individual thorax geometry were more realistic. Improvement of EIT image quality may foster the acceptance of EIT in routine clinical use.

  2. Semi-automated reconstruction of neural processes from large numbers of fluorescence images.

    Directory of Open Access Journals (Sweden)

    Ju Lu

    Full Text Available We introduce a method for large scale reconstruction of complex bundles of neural processes from fluorescent image stacks. We imaged yellow fluorescent protein labeled axons that innervated a whole muscle, as well as dendrites in cerebral cortex, in transgenic mice, at the diffraction limit with a confocal microscope. Each image stack was digitally re-sampled along an orientation such that the majority of axons appeared in cross-section. A region growing algorithm was implemented in the open-source Reconstruct software and applied to the semi-automatic tracing of individual axons in three dimensions. The progression of region growing is constrained by user-specified criteria based on pixel values and object sizes, and the user has full control over the segmentation process. A full montage of reconstructed axons was assembled from the approximately 200 individually reconstructed stacks. Average reconstruction speed is approximately 0.5 mm per hour. We found an error rate in the automatic tracing mode of approximately 1 error per 250 um of axonal length. We demonstrated the capacity of the program by reconstructing the connectome of motor axons in a small mouse muscle.

  3. Aircraft Reconstruction in High Resolution SAR Images Using Deep Shape Prior

    Directory of Open Access Journals (Sweden)

    Dou Fangzheng

    2017-10-01

    Full Text Available Object reconstruction is of vital importance in Synthetic Aperture Radar (SAR image analysis. In this paper, we propose a novel method based on shape prior to reconstruct aircraft in high resolution SAR images. The method mainly contains two stages. In the shape prior modeling stage, a generative deep learning method is used to model deep shape priors; a novel framework is then proposed in the reconstruction stage, which integrates the shape priors in the process of reconstruction. Specifically, to address the issue of object rotation, a novel pose estimation method is proposed to obtain candidate poses, which avoids making an exhaustive search for each pose. In addition, an energy function combining a scattering region term and a shape prior term is proposed; this is optimized via an iterative optimization algorithm to achieve the goal of object reconstruction. To the best of our knowledge, this is the first attempt made to reconstruct objects with complex shapes in SAR images using deep shape priors. Experiments are conducted on the dataset acquired by TerraSAR-X and results demonstrate the accuracy and robustness of the proposed method.

  4. Automatic Texture Reconstruction of 3d City Model from Oblique Images

    Science.gov (United States)

    Kang, Junhua; Deng, Fei; Li, Xinwei; Wan, Fang

    2016-06-01

    In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

  5. AUTOMATIC TEXTURE RECONSTRUCTION OF 3D CITY MODEL FROM OBLIQUE IMAGES

    Directory of Open Access Journals (Sweden)

    J. Kang

    2016-06-01

    Full Text Available In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

  6. Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach.

    Science.gov (United States)

    Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M; El Fakhri, Georges

    2013-10-01

    Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG. The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.

  7. Image Reconstruction in Magnetoacoustic Tomography With Magnetic Induction With Variable Sound Speeds.

    Science.gov (United States)

    Zhang, Wei; Ma, Ren; Zhang, Shunqi; Yin, Tao; Liu, Zhipeng

    2016-12-01

    Acoustic and electrical characteristics of biological tissue are important factors in magnetoacoustic tomography with magnetic induction (MAT-MI). Acoustic inhomogeneity significantly affects the propagations of sound waves. Differences in sound speed lead to distortions of the sound sources in the reconstruction process. The objective of this study is to develop a novel algorithm to reconstruct the sound source distribution in an acoustically inhomogeneous medium. The proposed algorithm is developed on the basis of the finite-difference time-domain method and time-reversal acoustic theory; it combines the relationship among symmetrical transducers with the back-projection algorithm. An acoustically inhomogeneous model with different regions of variable sound speeds is established to validate the proposed algorithm. From the data collected by a rotated focused transducer, first, the sound speed distribution is reconstructed, and then, the sound sources of the model are reconstructed. The reconstructed sound sources are obviously distorted when the speed differences are not considered. In contrast, the proposed algorithm yields reconstructed sound sources that are consistent with the model in terms of shape and size. Thus, the proposed algorithm is capable of accurately reconstructing the acoustic sources distribution in an acoustically inhomogeneous medium. This method provides a solution reducing the influence of acoustic inhomogeneity in MAT-MI. The distributions of sound speed can be obtained during the process of reconstructing the sound source. Consequently, the imaging of the acoustic speed and the electrical conductivity of biological tissues can be implemented simultaneously in MAT-MI.

  8. Noninvasive Vascular Displacement Estimation for Relative Elastic Modulus Reconstruction in Transversal Imaging Planes

    Directory of Open Access Journals (Sweden)

    Chris L. de Korte

    2013-03-01

    Full Text Available Atherosclerotic plaque rupture can initiate stroke or myocardial infarction. Lipid-rich plaques with thin fibrous caps have a higher risk to rupture than fibrotic plaques. Elastic moduli differ for lipid-rich and fibrous tissue and can be reconstructed using tissue displacements estimated from intravascular ultrasound radiofrequency (RF data acquisitions. This study investigated if modulus reconstruction is possible for noninvasive RF acquisitions of vessels in transverse imaging planes using an iterative 2D cross-correlation based displacement estimation algorithm. Furthermore, since it is known that displacements can be improved by compounding of displacements estimated at various beam steering angles, we compared the performance of the modulus reconstruction with and without compounding. For the comparison, simulated and experimental RF data were generated of various vessel-mimicking phantoms. Reconstruction errors were less than 10%, which seems adequate for distinguishing lipid-rich from fibrous tissue. Compounding outperformed single-angle reconstruction: the interquartile range of the reconstructed moduli for the various homogeneous phantom layers was approximately two times smaller. Additionally, the estimated lateral displacements were a factor of 2–3 better matched to the displacements corresponding to the reconstructed modulus distribution. Thus, noninvasive elastic modulus reconstruction is possible for transverse vessel cross sections using this cross-correlation method and is more accurate with compounding.

  9. Noninvasive Vascular Displacement Estimation for Relative Elastic Modulus Reconstruction in Transversal Imaging Planes

    Science.gov (United States)

    Hansen, Hendrik H.G.; Richards, Michael S.; Doyley, Marvin M.; de Korte, Chris L.

    2013-01-01

    Atherosclerotic plaque rupture can initiate stroke or myocardial infarction. Lipid-rich plaques with thin fibrous caps have a higher risk to rupture than fibrotic plaques. Elastic moduli differ for lipid-rich and fibrous tissue and can be reconstructed using tissue displacements estimated from intravascular ultrasound radiofrequency (RF) data acquisitions. This study investigated if modulus reconstruction is possible for noninvasive RF acquisitions of vessels in transverse imaging planes using an iterative 2D cross-correlation based displacement estimation algorithm. Furthermore, since it is known that displacements can be improved by compounding of displacements estimated at various beam steering angles, we compared the performance of the modulus reconstruction with and without compounding. For the comparison, simulated and experimental RF data were generated of various vessel-mimicking phantoms. Reconstruction errors were less than 10%, which seems adequate for distinguishing lipid-rich from fibrous tissue. Compounding outperformed single-angle reconstruction: the interquartile range of the reconstructed moduli for the various homogeneous phantom layers was approximately two times smaller. Additionally, the estimated lateral displacements were a factor of 2–3 better matched to the displacements corresponding to the reconstructed modulus distribution. Thus, noninvasive elastic modulus reconstruction is possible for transverse vessel cross sections using this cross-correlation method and is more accurate with compounding. PMID:23478602

  10. Dummy source digitization algorithm for reconstruction of flexible brachytherapy catheters with biplane images.

    Science.gov (United States)

    Pálvölgyi, Jenö

    2014-03-01

    The traditional brachytherapy catheter reconstruction with biplane images is based on digitizing radio-opaque markers with a pointing device on a film or on a screen. An algorithm to automate digitization of radio-opaque marker coordinates on biplane images is presented. To obtain the marker coordinates in a proper sequence, instead of usual pair of reconstruction images, series of images were taken with insertion of radio-opaque markers consecutively into the catheters. The images were pre-processed to suppress the shield of anatomic structures. The determination of the marker coordinates is based on the detection of characteristic high gradient variation in pre-processed image profiles. The method was tested with six endometrial insertions performed with Simon-Norman catheters using our version of Heyman packing. 28 catheters of six treatment fractions were digitized, typically 10 markers per catheter. To obtain the marker coordinates, adjustment of two threshold levels on the pre-processed images were needed. The coordinates of the radio-opaque markers on the biplane projection images were obtained without positive or negative artefact. THE DUMMY SOURCE COORDINATES ON THE BIPLANE IMAGES WERE DIGITIZED IN A PROPER SEQUENCE: from the catheters' tip towards the end of the catheters. After the three-dimensional reconstruction of the catheters from the digitized coordinates, the geometry file was imported by the brachytherapy planning system for dose calculation. The method has the advantage to eliminate manual digitization of the dummy sources.

  11. High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional neural network

    Science.gov (United States)

    Dimitrievski, Martin; Goossens, Bart; Veelaert, Peter; Philips, Wilfried

    2017-09-01

    Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot's point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

  12. A review of breast tomosynthesis. Part II. Image reconstruction, processing and analysis, and advanced applications

    Science.gov (United States)

    Sechopoulos, Ioannis

    2013-01-01

    Many important post-acquisition aspects of breast tomosynthesis imaging can impact its clinical performance. Chief among them is the reconstruction algorithm that generates the representation of the three-dimensional breast volume from the acquired projections. But even after reconstruction, additional processes, such as artifact reduction algorithms, computer aided detection and diagnosis, among others, can also impact the performance of breast tomosynthesis in the clinical realm. In this two part paper, a review of breast tomosynthesis research is performed, with an emphasis on its medical physics aspects. In the companion paper, the first part of this review, the research performed relevant to the image acquisition process is examined. This second part will review the research on the post-acquisition aspects, including reconstruction, image processing, and analysis, as well as the advanced applications being investigated for breast tomosynthesis. PMID:23298127

  13. In vivo three-dimensional reconstruction of the cornea from confocal microscopy images.

    Science.gov (United States)

    Scarpa, Fabio; Fiorin, Diego; Ruggeri, Alfredo

    2007-01-01

    Confocal microscopy can provide sequences of images from all cornea layers in a rapid, in vivo and non invasive way. These images are useful to extract important clinical information on cornea state of health. We address the problem of obtaining a 3-dimensional (3D) reconstruction of the cornea starting from a confocal microscope sequence, from endothelium to epithelium. A registration procedure, based on normalized correlation, is applied to each image, because eye movements normally occur during acquisition of the sequence and shifts in x-y plane take place in the sequence of images. Information on shifts along x and y directions comes from registration process, shift along z direction comes from the instrument itself. A 2D image stack is reconstructed by taking into account shifts along x, y, and z directions. If data are missing, we reconstruct them by taking lines from adjacent images and interpolating them. After reconstruction, it is possible to display and analyze corneal structures in the 3D volume and obtain slices in the x, y, or z direction.

  14. Near-infrared optical imaging of human brain based on the semi-3D reconstruction algorithm

    Science.gov (United States)

    Liu, Ming; Meng, Wei; Qin, Zhuanping; Zhou, Xiaoqing; Zhao, Huijuan; Gao, Feng

    2013-03-01

    In the non-invasive brain imaging with near-infrared light, precise head model is of great significance to the forward model and the image reconstruction. To deal with the individual difference of human head tissues and the problem of the irregular curvature, in this paper, we extracted head structure with Mimics software from the MRI image of a volunteer. This scheme makes it possible to assign the optical parameters to every layer of the head tissues reasonably and solve the diffusion equation with the finite-element analysis. During the solution of the inverse problem, a semi-3D reconstruction algorithm is adopted to trade off the computation cost and accuracy between the full 3-D and the 2-D reconstructions. In this scheme, the changes in the optical properties of the inclusions are assumed either axially invariable or confined to the imaging plane, while the 3-D nature of the photon migration is still retained. This therefore leads to a 2-D inverse issue with the matched 3-D forward model. Simulation results show that comparing to the 3-D reconstruction algorithm, the Semi-3D reconstruction algorithm cut 27% the calculation time consumption.

  15. Upgrade to iterative image reconstruction (IR) in abdominal MDCT imaging: a clinical study for detailed parameter optimization beyond vendor recommendations using the adaptive statistical iterative reconstruction environment (ASIR).

    Science.gov (United States)

    Mueck, F G; Körner, M; Scherr, M K; Geyer, L L; Deak, Z; Linsenmaier, U; Reiser, M; Wirth, S

    2012-03-01

    To compare the image quality of dose-reduced 64-row abdominal CT reconstructed at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed with filtered back-projection (FBP) in a clinical setting and upgrade situation. Abdominal baseline examinations (noise index NI = 29; LightSpeed VCT XT, GE) were intra-individually compared to follow-up studies on a CT with an ASIR option (NI = 43; Discovery HD750, GE), n = 42. Standard-kernel images were calculated with ASIR blendings of 0 - 100 % in slice and volume mode, respectively. Three experienced radiologists compared the image quality of these 567 sets to their corresponding full-dose baseline examination (- 2: diagnostically inferior, - 1: inferior, 0: equal, + 1: superior, + 2: diagnostically superior). Furthermore, a phantom was scanned. Statistical analysis used the Wilcoxon - the Mann-Whitney U-test and the intra-class correlation (ICC). The mean CTDIvol decreased from 19.7 ± 5.5 to 12.2 ± 4.7 mGy (p ASIR studies was comparable to the baseline at ASIR 50 % in slice (p = 0.18) and ASIR 50 - 100 % in volume mode (p > 0.10). Volume mode performed 73 % slower than slice mode (p ASIR 50 % in slice mode allowed for a dose reduction of 38 % in abdominal CT with comparable image quality and time expenditure. However, there is still further dose reduction potential for more complex reconstruction settings. © Georg Thieme Verlag KG Stuttgart · New York.

  16. Super-resolution image reconstruction applied to an active millimeter wave imaging system based on compressive sensing

    Science.gov (United States)

    Alkuş, Ümit; Şengün Ermeydan, Esra; Şahin, Asaf Behzat; ćankaya, Ä.°lyas; Altan, Hakan

    2017-10-01

    The development of passive and active millimeter wave imaging systems is progressing rapidly fueled by the need for many applications in the area of security and defense. Imaging schemes that may either utilize array detectors or single detectors in scan architectures offer suffer from poor resolution due to the longer wavelengths used and the limits of the optical system in terms of lens and mirror dimensions. In order to overcome this limit, super-resolution techniques can be employed to enhance the resolution of the imaging system. Here, a form of this technique based on oversampling is applied to reconstruct the image of a target which is acquired using compressive sensing based on scanning the image plane using randomly patterned masks with fixed pixel sizes. The mm-wave stand-off imaging system uses a 93 GHz center frequency source and heterodyne sub-harmonic receiver place in a bi-static configuration to image a target in reflection mode. The image of the target is projected onto a mechanically scanned spatial light modulator (SLM), which is a patterned two-dimensional mask that is translated along one axis. In order to improve the resolution of the image, the masks are shifted by half the pixel size (2.5mm). To enhance the resolution of the image, the patterns are shifted by smaller steps, thereby each pixel is oversampled and the resulting new pattern and detected intensity is fed into the CS algorithm to reconstruct the image of the target. After the image reconstruction process, sharper edges are observed for a circular object of 12mm diameter compared to the image acquired by whole pixel step scanning.

  17. Ensuring convergence in total-variation-based reconstruction for accurate microcalcification imaging in breast X-ray CT

    CERN Document Server

    Jørgensen, Jakob H; Pan, Xiaochuan

    2011-01-01

    Breast X-ray CT imaging is being considered in screening as an extension to mammography. As a large fraction of the population will be exposed to radiation, low-dose imaging is essential. Iterative image reconstruction based on solving an optimization problem, such as Total-Variation minimization, shows potential for reconstruction from sparse-view data. For iterative methods it is important to ensure convergence to an accurate solution, since important image features, such as presence of microcalcifications indicating breast cancer, may not be visible in a non-converged reconstruction, and this can have clinical significance. To prevent excessively long computational times, which is a practical concern for the large image arrays in CT, it is desirable to keep the number of iterations low, while still ensuring a sufficiently accurate reconstruction for the specific imaging task. This motivates the study of accurate convergence criteria for iterative image reconstruction. In simulation studies with a realistic...

  18. CT imaging of congenital lung lesions: effect of iterative reconstruction on diagnostic performance and radiation dose

    Energy Technology Data Exchange (ETDEWEB)

    Haggerty, Jay E.; Smith, Ethan A.; Dillman, Jonathan R. [University of Michigan Health System, Section of Pediatric Radiology, Department of Radiology, C.S. Mott Children' s Hospital, Ann Arbor, MI (United States); Kunisaki, Shaun M. [University of Michigan Health System, Section of Pediatric Surgery, Department of Surgery, C.S. Mott Children' s Hospital, Ann Arbor, MI (United States)

    2015-07-15

    Different iterative reconstruction techniques are available for use in pediatric computed tomography (CT), but these techniques have not been systematically evaluated in infants. To determine the effect of iterative reconstruction on diagnostic performance, image quality and radiation dose in infants undergoing CT evaluation for congenital lung lesions. A retrospective review of contrast-enhanced chest CT in infants (<1 year) with congenital lung lesions was performed. CT examinations were reviewed to document the type of lung lesion, vascular anatomy, image noise measurements and image reconstruction method. CTDI{sub vol} was used to calculate size-specific dose estimates (SSDE). CT findings were correlated with intraoperative and histopathological findings. Analysis of variance and the Student's t-test were used to compare image noise measurements and radiation dose estimates between groups. Fifteen CT examinations used filtered back projection (FBP; mean age: 84 days), 15 used adaptive statistical iterative reconstruction (ASiR; mean age: 93 days), and 11 used model-based iterative reconstruction (MBIR; mean age: 98 days). Compared to operative findings, 13/15 (87%), 14/15 (93%) and 11/11 (100%) lesions were correctly characterized using FBP, ASiR and MBIR, respectively. Arterial anatomy was correctly identified in 12/15 (80%) using FBP, 13/15 (87%) using ASiR and 11/11 (100%) using MBIR. Image noise was less for MBIR vs. ASiR (P < 0.0001). Mean SSDE was different among groups (P = 0.003; FBP = 7.35 mGy, ASiR = 1.89 mGy, MBIR = 1.49 mGy). Congenital lung lesions can be adequately characterized in infants using iterative CT reconstruction techniques while maintaining image quality and lowering radiation dose. (orig.)

  19. A photoacoustic imaging reconstruction method based on directional total variation with adaptive directivity.

    Science.gov (United States)

    Wang, Jin; Zhang, Chen; Wang, Yuanyuan

    2017-05-30

    In photoacoustic tomography (PAT), total variation (TV) based iteration algorithm is reported to have a good performance in PAT image reconstruction. However, classical TV based algorithm fails to preserve the edges and texture details of the image because it is not sensitive to the direction of the image. Therefore, it is of great significance to develop a new PAT reconstruction algorithm to effectively solve the drawback of TV. In this paper, a directional total variation with adaptive directivity (DDTV) model-based PAT image reconstruction algorithm, which weightedly sums the image gradients based on the spatially varying directivity pattern of the image is proposed to overcome the shortcomings of TV. The orientation field of the image is adaptively estimated through a gradient-based approach. The image gradients are weighted at every pixel based on both its anisotropic direction and another parameter, which evaluates the estimated orientation field reliability. An efficient algorithm is derived to solve the iteration problem associated with DDTV and possessing directivity of the image adaptively updated for each iteration step. Several texture images with various directivity patterns are chosen as the phantoms for the numerical simulations. The 180-, 90- and 30-view circular scans are conducted. Results obtained show that the DDTV-based PAT reconstructed algorithm outperforms the filtered back-projection method (FBP) and TV algorithms in the quality of reconstructed images with the peak signal-to-noise rations (PSNR) exceeding those of TV and FBP by about 10 and 18 dB, respectively, for all cases. The Shepp-Logan phantom is studied with further discussion of multimode scanning, convergence speed, robustness and universality aspects. In-vitro experiments are performed for both the sparse-view circular scanning and linear scanning. The results further prove the effectiveness of the DDTV, which shows better results than that of the TV with sharper image edges and

  20. Multi-view 3D reconstruction with volumetric registration in a freehand ultrasound imaging system

    Science.gov (United States)

    Yu, Honggang; Pattichis, Marios S.; Goens, M. Beth

    2006-03-01

    In this paper, we describe a new freehand ultrasound imaging system for reconstructing the left ventricle from 2D echocardiography slices. An important contribution of the proposed system is its ability to reconstruct from multiple standard views. The multi-view reconstruction procedure results in significant reduction in reconstruction error over single view reconstructions. The system uses object-based 3D volumetric registration, allowing for arbitrary rigid object movements in inter-view acquisition. Furthermore, a new segmentation procedure that combines level set methods with gradient vector flow(GVF) is used for automatically segmenting the 2D ultrasound images, in which low level of contrast, high level of speckle noise, and weak boundaries are common. The new segmentation approach is shown to be robust to these artifacts and is found to converge to the boundary from a wider range of initial conditions than competitive methods. The proposed system has been validated on a physical, 3D ultrasound calibration phantom and evaluated on one actual cardiac echocardiography data set. In the phantom experiment, two calibrated volumetric egg-shape objects were scanned from the top and side windows and reconstructed using the new method. The volume error was measured to be less than 4%. In a real heart data set experiment, qualitative results of 3D surface reconstruction from parasternal and apical views appear significantly improved over single view reconstructions. The estimated volumes from the 3D reconstructions were also found to be in agreement with the manual clinical measurements from 2D slices. Further extension of this work is to compare the quantitative results with more accuracy MRI data.

  1. High-order noise analysis for low dose iterative image reconstruction methods: ASIR, IRIS, and MBAI

    Science.gov (United States)

    Do, Synho; Singh, Sarabjeet; Kalra, Mannudeep K.; Karl, W. Clem; Brady, Thomas J.; Pien, Homer

    2011-03-01

    Iterative reconstruction techniques (IRTs) has been shown to suppress noise significantly in low dose CT imaging. However, medical doctors hesitate to accept this new technology because visual impression of IRT images are different from full-dose filtered back-projection (FBP) images. Most common noise measurements such as the mean and standard deviation of homogeneous region in the image that do not provide sufficient characterization of noise statistics when probability density function becomes non-Gaussian. In this study, we measure L-moments of intensity values of images acquired at 10% of normal dose and reconstructed by IRT methods of two state-of-art clinical scanners (i.e., GE HDCT and Siemens DSCT flash) by keeping dosage level identical to each other. The high- and low-dose scans (i.e., 10% of high dose) were acquired from each scanner and L-moments of noise patches were calculated for the comparison.

  2. Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

    Science.gov (United States)

    Lavoie, Benjamin R; Okoniewski, Michal; Fear, Elise C

    2016-01-01

    We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.

  3. Study on infrared image super-resolution reconstruction based on an improved POCS algorithm

    Science.gov (United States)

    Dai, Shaosheng; Cui, Junjie; Zhang, Dezhou; Liu, Qin; Zhang, Xiaoxiao

    2017-04-01

    Aiming at the disadvantages of the traditional projection onto convex sets of blurry edges and lack of image details, this paper proposes an improved projection onto convex sets (POCS) method to enhance the quality of image super-resolution reconstruction (SRR). In traditional POCS method, bilinear interpolation easily blurs the image. In order to improve the initial estimation of high-resolution image (HRI) during reconstruction of POCS algorithm, the initial estimation of HRI is obtained through iterative curvature-based interpolation (ICBI) instead of bilinear interpolation. Compared with the traditional POCS algorithm, the experimental results in subjective evaluation and objective evaluation demonstrate the effectiveness of the proposed method. The visual effect is improved significantly and image detail information is preserved better. Project supported by the National Natural Science Foundation of China (Nos. 61275099, 61671094) and the Natural Science Foundation of Chongqing Science and Technology Commission (No. CSTC2015JCYJA40032).

  4. Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

    Directory of Open Access Journals (Sweden)

    Benjamin R Lavoie

    Full Text Available We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.

  5. STEREO RECONSTRUCTION OF ATMOSPHERIC CLOUD SURFACES FROM FISH-EYE CAMERA IMAGES

    Directory of Open Access Journals (Sweden)

    G. Katai-Urban

    2016-06-01

    Full Text Available In this article a method for reconstructing atmospheric cloud surfaces using a stereo camera system is presented. The proposed camera system utilizes fish-eye lenses in a flexible wide baseline camera setup. The entire workflow from the camera calibration to the creation of the 3D point set is discussed, but the focus is mainly on cloud segmentation and on the image processing steps of stereo reconstruction. Speed requirements, geometric limitations, and possible extensions of the presented method are also covered. After evaluating the proposed method on artificial cloud images, this paper concludes with results and discussion of possible applications for such systems.

  6. Restoration of the analytically reconstructed OpenPET images by the method of convex projections

    Energy Technology Data Exchange (ETDEWEB)

    Tashima, Hideaki; Murayama, Hideo; Yamaya, Taiga [National Institute of Radiological Sciences, Chiba (Japan); Katsunuma, Takayuki; Suga, Mikio [Chiba Univ. (Japan). Graduate School of Engineering; Kinouchi, Shoko [National Institute of Radiological Sciences, Chiba (Japan); Chiba Univ. (Japan). Graduate School of Engineering; Obi, Takashi [Tokyo Institute of Technology (Japan). Interdisciplinary Graduate School of Science and Engineering; Kudo, Hiroyuki [Tsukuba Univ. (Japan). Graduate School of Systems and Information Engineering

    2011-07-01

    We have proposed the OpenPET geometry which has gaps between detector rings and physically opened field-of-view. The image reconstruction of the OpenPET is classified into an incomplete problem because it does not satisfy the Orlov's condition. Even so, the simulation and experimental studies have shown that applying iterative methods such as the maximum likelihood expectation maximization (ML-EM) algorithm successfully reconstruct images in the gap area. However, the imaging process of the iterative methods in the OpenPET imaging is not clear. Therefore, the aim of this study is to analytically analyze the OpenPET imaging and estimate implicit constraints involved in the iterative methods. To apply explicit constraints in the OpenPET imaging, we used the method of convex projections for restoration of the images reconstructed by the analytical way in which low-frequency components are lost. Numerical simulations showed that the similar restoration effects are involved both in the ML-EM and the method of convex projections. Therefore, the iterative methods have advantageous effect of restoring lost frequency components of the OpenPET imaging. (orig.)

  7. Effect of masking phase-only holograms on the quality of reconstructed images.

    Science.gov (United States)

    Deng, Yuanbo; Chu, Daping

    2016-04-20

    A phase-only hologram modulates the phase of the incident light and diffracts it efficiently with low energy loss because of the minimum absorption. Much research attention has been focused on how to generate phase-only holograms, and little work has been done to understand the effect and limitation of their partial implementation, possibly due to physical defects and constraints, in particular as in the practical situations where a phase-only hologram is confined or needs to be sliced or tiled. The present study simulates the effect of masking phase-only holograms on the quality of reconstructed images in three different scenarios with different filling factors, filling positions, and illumination intensity profiles. Quantitative analysis confirms that the width of the image point spread function becomes wider and the image quality decreases, as expected, when the filling factor decreases, and the image quality remains the same for different filling positions as well. The width of the image point spread function as derived from different filling factors shows a consistent behavior to that as measured directly from the reconstructed image, especially as the filling factor becomes small. Finally, mask profiles of different shapes and intensity distributions are shown to have more complicated effects on the image point spread function, which in turn affects the quality and textures of the reconstructed image.

  8. Image quality of CT angiography with model-based iterative reconstruction in young children with congenital heart disease: comparison with filtered back projection and adaptive statistical iterative reconstruction.

    Science.gov (United States)

    Son, Sung Sil; Choo, Ki Seok; Jeon, Ung Bae; Jeon, Gye Rok; Nam, Kyung Jin; Kim, Tae Un; Yeom, Jeong A; Hwang, Jae Yeon; Jeong, Dong Wook; Lim, Soo Jin

    2015-06-01

    To retrospectively evaluate the image quality of CT angiography (CTA) reconstructed by model-based iterative reconstruction (MBIR) and to compare this with images obtained by filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) in newborns and infants with congenital heart disease (CHD). Thirty-seven children (age 4.8 ± 3.7 months; weight 4.79 ± 0.47 kg) with suspected CHD underwent CTA on a 64detector MDCT without ECG gating (80 kVp, 40 mA using tube current modulation). Total dose length product was recorded in all patients. Images were reconstructed using FBP, ASIR, and MBIR. Objective image qualities (density, noise) were measured in the great vessels and heart chambers. The contrast-to-noise ratio (CNR) was calculated by measuring the density and noise of myocardial walls. Two radiologists evaluated images for subjective noise, diagnostic confidence, and sharpness at the level prior to the first branch of the main pulmonary artery. Images were compared with respect to reconstruction method, and reconstruction times were measured. Images from all patients were diagnostic, and the effective dose was 0.22 mSv. The objective image noise of MBIR was significantly lower than those of FBP and ASIR in the great vessels and heart chambers (P 0.05). Mean CNR values were 8.73 for FBP, 14.54 for ASIR, and 22.95 for MBIR. In addition, the subjective image noise of MBIR was significantly lower than those of the others (P ASIR had the highest score for diagnostic confidence (P reconstruction times were 5.1 ± 2.3 s for FBP and ASIR and 15.1 ± 2.4 min for MBIR. While CTA with MBIR in newborns and infants with CHD can reduce image noise and improve CNR more than other methods, it is more time-consuming than the other methods.

  9. A pseudo-discrete algebraic reconstruction technique (PDART) prior image-based suppression of high density artifacts in computed tomography

    Science.gov (United States)

    Pua, Rizza; Park, Miran; Wi, Sunhee; Cho, Seungryong

    2016-12-01

    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.

  10. Multishot cartesian turbo spin-echo diffusion imaging using iterative POCSMUSE Reconstruction.

    Science.gov (United States)

    Zhang, Zhe; Zhang, Bing; Li, Ming; Liang, Xue; Chen, Xiaodong; Liu, Renyuan; Zhang, Xin; Guo, Hua

    2017-07-01

    To report a diffusion imaging technique insensitive to off-resonance artifacts and motion-induced ghost artifacts using multishot Cartesian turbo spin-echo (TSE) acquisition and iterative POCS-based reconstruction of multiplexed sensitivity encoded magnetic resonance imaging (MRI) (POCSMUSE) for phase correction. Phase insensitive diffusion preparation was used to deal with the violation of the Carr-Purcell-Meiboom-Gill (CPMG) conditions of TSE diffusion-weighted imaging (DWI), followed by a multishot Cartesian TSE readout for data acquisition. An iterative diffusion phase correction method, iterative POCSMUSE, was developed and implemented to eliminate the ghost artifacts in multishot TSE DWI. The in vivo human brain diffusion images (from one healthy volunteer and 10 patients) using multishot Cartesian TSE were acquired at 3T and reconstructed using iterative POCSMUSE, and compared with single-shot and multishot echo-planar imaging (EPI) results. These images were evaluated by two radiologists using visual scores (considering both image quality and distortion levels) from 1 to 5. The proposed iterative POCSMUSE reconstruction was able to correct the ghost artifacts in multishot DWI. The ghost-to-signal ratio of TSE DWI using iterative POCSMUSE (0.0174 ± 0.0024) was significantly (P iterative POCSMUSE reconstruction can provide high-quality diffusion images insensitive to motion-induced ghost artifacts and off-resonance related artifacts such as chemical shifts and susceptibility-induced image distortions. 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:167-174. © 2016 International Society for Magnetic Resonance in Medicine.

  11. STEP: Self-supporting tailored k-space estimation for parallel imaging reconstruction.

    Science.gov (United States)

    Zhou, Zechen; Wang, Jinnan; Balu, Niranjan; Li, Rui; Yuan, Chun

    2016-02-01

    A new subspace-based iterative reconstruction method, termed Self-supporting Tailored k-space Estimation for Parallel imaging reconstruction (STEP), is presented and evaluated in comparison to the existing autocalibrating method SPIRiT and calibrationless method SAKE. In STEP, two tailored schemes including k-space partition and basis selection are proposed to promote spatially variant signal subspace and incorporated into a self-supporting structured low rank model to enforce properties of locality, sparsity, and rank deficiency, which can be formulated into a constrained optimization problem and solved by an iterative algorithm. Simulated and in vivo datasets were used to investigate the performance of STEP in terms of overall image quality and detail structure preservation. The advantage of STEP on image quality is demonstrated by retrospectively undersampled multichannel Cartesian data with various patterns. Compared with SPIRiT and SAKE, STEP can provide more accurate reconstruction images with less residual aliasing artifacts and reduced noise amplification in simulation and in vivo experiments. In addition, STEP has the capability of combining compressed sensing with arbitrary sampling trajectory. Using k-space partition and basis selection can further improve the performance of parallel imaging reconstruction with or without calibration signals. © 2015 Wiley Periodicals, Inc.

  12. Influence of adaptive statistical iterative reconstruction algorithm on image quality in coronary computed tomography angiography.

    Science.gov (United States)

    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 ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR.

  13. Quantitative cardiac SPECT reconstruction with reduced image degradation due to patient anatomy

    Energy Technology Data Exchange (ETDEWEB)

    Tsui, B.M.W.; Zhao, X.D.; Gregoriou, G.K.; Lalush, D.S.; Frey, E.C.; Johnston, R.E.; McCartney, W.H. (Univ. of North Carolina, Chapel Hill, NC (United States))

    1994-12-01

    Patient anatomy has complicated effects on cardiac SPECT images. The authors investigated reconstruction methods which substantially reduced these effects for improved image quality. A 3D mathematical cardiac-torso (MCAT) phantom which models the anatomical structures in the thorax region were used in the study. The phantom was modified to simulate variations in patient anatomy including regions of natural thinning along the myocardium, body size, diaphragmatic shape, gender, and size and shape of breasts for female patients. Distributions of attenuation coefficients and Tl-201 uptake in different organs in a normal patient were also simulated. Emission projection data were generated from the phantoms including effects of attenuation and detector response. The authors have observed the attenuation-induced artifacts caused by patient anatomy in the conventional FBP reconstructed images. Accurate attenuation compensation using iterative reconstruction algorithms and attenuation maps substantially reduced the image artifacts and improved quantitative accuracy. They conclude that reconstruction methods which accurately compensate for non-uniform attenuation can substantially reduce image degradation caused by variations in patient anatomy in cardiac SPECT.

  14. Analysis of stability of tomographic reconstruction of x-ray medical images

    Directory of Open Access Journals (Sweden)

    Л. А. Булавін

    2017-09-01

    Full Text Available Slice reconstruction in X-ray computed tomography is reduced to the solution of integral equations, or a system of algebraic equations in discrete case. It is considered to be an ill-posed problem due to the inconsistencies in the number of equations and variables and due to errors in the experimental data. Therefore, determination of the best method of the slice reconstruction is of great interest. Furthermore, all available methods give approximate results. The aim of this article was two-fold: i to compare two methods of image reconstruction, viz. inverse projection and variation, using the numerical experiment; ii to obtain the relationship between image accuracy and experimental error. It appeared that the image obtained by inverse projection is unstable: there was no convergence of the approximate image to the accurate one, when the experimental error reached zero. In turn, the image obtained by variational method was accurate at zero experimental error. Finally, the latter showed better slice reconstruction, despite the low number of projections and the experimental errors.

  15. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy.

    Directory of Open Access Journals (Sweden)

    Chae Young Lee

    Full Text Available The purposes of this study were to optimize a proton computed tomography system (pCT for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy.

  16. Sparse image reconstruction of targets in multilayered dielectric media using total variation minimization

    Science.gov (United States)

    Zhang, Wenji; Hoorfar, Ahmad

    2017-05-01

    In this paper, we present a sparse image reconstruction approach for radar imaging through multilayered media with total variation minimization (TVM). The approach is well suited for high-resolution imaging for both ground penetrating radar (GPR) and through-the-wall radar imaging (TWRI) applications. The multilayered media Green's function is incorporated in the imaging algorithm to efficiently model the wave propagation in the multilayered environment. For GPR imaging, the multilayered subsurface Green's function is derived in closed form with saddle point method, which is significantly less time consuming than numerical methods. For through-the-wall radar imaging, where the first and last layers are freespace, a far field approximation of the Green's function in analytical form is used to model the wave propagation through single or multilayered building walls. The TVM minimizes the gradient of the image resulting in excellent edge preservation and shape reconstruction of the image. Representative examples are presented to show high quality imaging results with limited data under various subsurface and through-the-wall imaging scenarios.

  17. Imaging Features of AlloDerm® Used in Postmastectomy Breast Reconstructions

    Directory of Open Access Journals (Sweden)

    Christine U Lee

    2014-01-01

    Full Text Available The purpose of this pictorial essay is to demonstrate the imaging features (ultrasound, mammogram, and magnetic resonance imaging (MRI of AlloDerm® (LifeCell Corp.; Branchburg, NJ, an acellular dermal matrix sometimes used in both primary and reconstructive breast surgeries. AlloDerm® is derived from cadaveric dermis and provides an immunologically inert scaffold in tissue reconstruction. Since there is little literature on the imaging of this substance, radiologists may be unfamiliar with its appearance in breast imaging. For this manuscript, ex vivo and in vivo images of AlloDerm® in postmastectomy patients were evaluated using different imaging modalities. The appearance of AlloDerm® can vary based on length of time postsurgery and incorporation into the host. AlloDerm® appears as an isodense to glandular tissue on a mammogram and isoechoic to glandular tissue on ultrasound imaging. On MRI, in comparison with normal breast parenchyma, AlloDerm® is hyperintense on T2-weighted imaging and isointense on T1-weighted imaging and demonstrates mild enhancement. To the best of the authors′ knowledge, this is the first multimodality imaging description of AlloDerm® used in postmastectomy patients. The conformation of AlloDerm® at surgical placement and the degree of host cell migration and neoangiogenesis are factors to take into consideration when performing diagnostic evaluations; and, familiarity with the various imaging appearances of AlloDerm® can be helpful to exclude residual or recurrent disease.

  18. 3D reconstruction of SEM images by use of optical photogrammetry software.

    Science.gov (United States)

    Eulitz, Mona; Reiss, Gebhard

    2015-08-01

    Reconstruction of the three-dimensional (3D) surface of an object to be examined is widely used for structure analysis in science and many biological questions require information about their true 3D structure. For Scanning Electron Microscopy (SEM) there has been no efficient non-destructive solution for reconstruction of the surface morphology to date. The well-known method of recording stereo pair images generates a 3D stereoscope reconstruction of a section, but not of the complete sample surface. We present a simple and non-destructive method of 3D surface reconstruction from SEM samples based on the principles of optical close range photogrammetry. In optical close range photogrammetry a series of overlapping photos is used to generate a 3D model of the surface of an object. We adapted this method to the special SEM requirements. Instead of moving a detector around the object, the object itself was rotated. A series of overlapping photos was stitched and converted into a 3D model using the software commonly used for optical photogrammetry. A rabbit kidney glomerulus was used to demonstrate the workflow of this adaption. The reconstruction produced a realistic and high-resolution 3D mesh model of the glomerular surface. The study showed that SEM micrographs are suitable for 3D reconstruction by optical photogrammetry. This new approach is a simple and useful method of 3D surface reconstruction and suitable for various applications in research and teaching. Copyright © 2015 Elsevier Inc. All rights reserved.

  19. Sparse Image Reconstruction on the Sphere: Analysis and Synthesis.

    Science.gov (United States)

    Wallis, Christopher G R; Wiaux, Yves; McEwen, Jason D

    2017-11-01

    We develop techniques to solve ill-posed inverse problems on the sphere by sparse regularization, exploiting sparsity in both axisymmetric and directional scale-discretized wavelet space. Denoising, inpainting, and deconvolution problems and combinations thereof, are considered as examples. Inverse problems are solved in both the analysis and synthesis settings, with a number of different sampling schemes. The most effective approach is that with the most restricted solution-space, which depends on the interplay between the adopted sampling scheme, the selection of the analysis/synthesis problem, and any weighting of the l1 norm appearing in the regularization problem. More efficient sampling schemes on the sphere improve reconstruction fidelity by restricting the solution-space and also by improving sparsity in wavelet space. We apply the technique to denoise Planck 353-GHz observations, improving the ability to extract the structure of Galactic dust emission, which is important for studying Galactic magnetism.

  20. Clinical evaluation of PET image reconstruction using a spatial resolution model

    DEFF Research Database (Denmark)

    Andersen, Flemming Littrup; Klausen, Thomas Levin; Loft, Annika

    2013-01-01

    reconstructed on 336×336-matrices using: (R1) standard AW-OSEM (4 iter, 8 subsets, 4mm Gaussian) and (R2) AW-OSEM with PSF (3 iter, 21 subsets, 2mm). Blinded and randomised reading of R1- and R2-PET images was performed. Individual lesions were located and counted independently on both sets of images......PURPOSE: PET image resolution is variable across the measured field-of-view and described by the point spread function (PSF). When accounting for the PSF during PET image reconstruction image resolution is improved and partial volume effects are reduced. Here, we evaluate the effect of PSF......-based reconstruction on lesion quantification in routine clinical whole-body (WB) PET/CT imaging. MATERIALS AND METHODS: 41 oncology patients were referred for a WB-PET/CT examination (Biograph 40 TruePoint). Emission data were acquired at 2.5min/bed at 1hpi of 400 MBq [18F]-FDG. Attenuation-corrected PET images were...

  1. Task-based data-acquisition optimization for sparse image reconstruction systems

    Science.gov (United States)

    Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.

    2017-03-01

    Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.

  2. An estimation method of MR signal parameters for improved image reconstruction in unilateral scanner.

    Science.gov (United States)

    Bergman, Elad; Yeredor, Arie; Nevo, Uri

    2013-12-01

    Unilateral NMR devices are used in various applications including non-destructive testing and well logging, but are not used routinely for imaging. This is mainly due to the inhomogeneous magnetic field (B0) in these scanners. This inhomogeneity results in low sensitivity and further forces the use of the slow single point imaging scan scheme. Improving the measurement sensitivity is therefore an important factor as it can improve image quality and reduce imaging times. Short imaging times can facilitate the use of this affordable and portable technology for various imaging applications. This work presents a statistical signal-processing method, designed to fit the unique characteristics of imaging with a unilateral device. The method improves the imaging capabilities by improving the extraction of image information from the noisy data. This is done by the use of redundancy in the acquired MR signal and by the use of the noise characteristics. Both types of data were incorporated into a Weighted Least Squares estimation approach. The method performance was evaluated with a series of imaging acquisitions applied on phantoms. Images were extracted from each measurement with the proposed method and were compared to the conventional image reconstruction. All measurements showed a significant improvement in image quality based on the MSE criterion - with respect to gold standard reference images. An integration of this method with further improvements may lead to a prominent reduction in imaging times aiding the use of such scanners in imaging application. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. Scan time reduction in {sup 23}Na-Magnetic Resonance Imaging using the chemical shift imaging sequence. Evaluation of an iterative reconstruction method

    Energy Technology Data Exchange (ETDEWEB)

    Weingaertner, Sebastian; Konstandin, Simon; Schad, Lothar R. [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine; Wetterling, Friedrich [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine; Dublin Univ. (Ireland) Trinity Inst. of Neuroscience; Fatar, Marc [Heidelberg Univ., Mannheim (Germany). Dept. of Neurology; Neumaier-Probst, Eva [Heidelberg Univ., Mannheim (Germany). Dept. of Neuroradiology

    2015-07-01

    To evaluate potential scan time reduction in {sup 23}Na-Magnetic Resonance Imaging with the chemical shift imaging sequence (CSI) using undersampled data of high-quality datasets, reconstructed with an iterative constrained reconstruction, compared to reduced resolution or reduced signal-to-noise ratio. CSI {sup 23}Na-images were retrospectively undersampled and reconstructed with a constrained reconstruction scheme. The results were compared to conventional methods of scan time reduction. The constrained reconstruction scheme used a phase constraint and a finite object support, which was extracted from a spatially registered {sup 1}H-image acquired with a double-tuned coil. The methods were evaluated using numerical simulations, phantom images and in-vivo images of a healthy volunteer and a patient who suffered from cerebral ischemic stroke. The constrained reconstruction scheme showed improved image quality compared to a decreased number of averages, images with decreased resolution or circular undersampling with weighted averaging for any undersampling factor. Brain images of a stroke patient, which were reconstructed from three-fold undersampled k-space data, resulted in only minor differences from the original image (normalized root means square error < 12%) and an almost identical delineation of the stroke region (mismatch < 6%). The acquisition of undersampled {sup 23}Na-CSI images enables up to three-fold scan time reduction with improved image quality compared to conventional methods of scan time saving.

  4. The influence of hologram aperture on speckle noise in the reconstructed image of digital holography and its reduction

    Science.gov (United States)

    Cai, Xiao-ou; Wang, Hui

    2008-01-01

    Based on the whole process of the recording and reconstruction of digital holography, we study the formation cause of speckle noise in its reconstructed image and acquire the conclusion that the small size of hologram aperture diffraction aggravates the speckle noise of reconstructed image and the speckle noise has been one of primary noise sources in the reconstruction process. In order to reduce the speckle noise resulting from little hologram aperture diffraction, we set an appropriate aperture function matching the recording parameter and aperture size of hologram and deconvolve the reconstructed image with it. The validity has been proved in theory and experiment. Therefore, it offers a brand-new thought and practical way to reduce the speckle noise in the reconstructed image of digital holography.

  5. Direct Reconstruction of CT-Based Attenuation Correction Images for PET With Cluster-Based Penalties

    Science.gov (United States)

    Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Kinahan, Paul E.

    2017-03-01

    Extremely low-dose (LD) CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This paper explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air + background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the root mean squared error (RMSE) by roughly two times compared with a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared with a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-LD CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

  6. Applicator reconstruction in MRI 3D image-based dose planning of brachytherapy for cervical cancer.

    Science.gov (United States)

    Haack, Søren; Nielsen, Søren Kynde; Lindegaard, Jacob Christian; Gelineck, John; Tanderup, Kari

    2009-05-01

    To elaborate a method for applicator reconstruction for MRI-based brachytherapy for cervical cancer. Custom-made plastic catheters with a copper sulphate solution were made for insertion in the source channels of MR-CT compatible applicators: plastic and titanium tandem ring applicators, and titanium needles. The applicators were CT and MR scanned in a phantom for accurate 3D assessment of applicator visibility and geometry. A reconstruction method was developed and evaluated in 19 patient MR examinations with ring applicator (plastic: 14, titanium: 5). MR applicator reconstruction uncertainties related to inter-observer variation were evaluated. The catheters were visible in the plastic applicator on T1-weighted images in phantom and in 14/14 clinical applications. On T2-weighted images, the catheters appeared weaker but still visible in phantom and in 13/14 MR clinical applications. In the titanium applicator, the catheters could not be separated from the artifacts from the applicator itself. However, these artifacts could be used to localize both titanium ring applicator (5/5 clinical applications) and needles (6/6 clinical applications). Standard deviations of inter-observer differences were below 2 mm in all directions. 3D applicator reconstruction based on MR imaging could be performed for plastic and titanium applicators. Plastic applicators proved well to be suited for MRI-based reconstruction. For improved practicability of titanium applicator reconstruction, development of MR applicator markers is essential. Reconstruction of titanium applicator and needles at 1.5 T MR requires geometric evaluations in phantoms before using the applicator in patients.

  7. A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

    Science.gov (United States)

    McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.

    2017-06-01

    Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

  8. A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images.

    Science.gov (United States)

    McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; Connell, Dylan O'; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J

    2017-06-07

    Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of 'partial' imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

  9. A regularization-free Young's modulus reconstruction algorithm for ultrasound elasticity imaging.

    Science.gov (United States)

    Pan, Xiaochang; Gao, Jing; Shao, Jinhua; Luo, Jianwen; Bai, Jing

    2013-01-01

    Ultrasound elasticity imaging aims to reconstruct the distribution of elastic modulus (e.g., Young's modulus) within biological tissues, since the value of elastic modulus is often related to pathological changes. Currently, most elasticity imaging algorithms face a challenge of choosing the value of the regularization constant. We propose a more applicable algorithm without the need of any regularization. This algorithm is not only simple to use, but has a relatively high accuracy. Our method comprises of a nonrigid registration technique and tissue incompressibility assumption to estimate the two-dimensional (2D) displacement field, and finite element method (FEM) to reconstruct the Young's modulus distribution. Simulation and phantom experiments are performed to evaluate the algorithm. Simulation and phantom results showed that the proposed algorithm can reconstruct the Young's modulus with an accuracy of 63∼85%.

  10. Motion tolerant iterative reconstruction algorithm for cone-beam helical CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu [Hitachi Medical Corporation, Chiba-ken (Japan). CT System Div.

    2011-07-01

    We have developed a new advanced iterative reconstruction algorithm for cone-beam helical CT. The features of this algorithm are: (a) it uses separable paraboloidal surrogate (SPS) technique as a foundation for reconstruction to reduce noise and cone-beam artifact, (b) it uses a view weight in the back-projection process to reduce motion artifact. To confirm the improvement of our proposed algorithm over other existing algorithm, such as Feldkamp-Davis-Kress (FDK) or SPS algorithm, we compared the motion artifact reduction, image noise reduction (standard deviation of CT number), and cone-beam artifact reduction on simulated and clinical data set. Our results demonstrate that the proposed algorithm dramatically reduces motion artifacts compared with the SPS algorithm, and decreases image noise compared with the FDK algorithm. In addition, the proposed algorithm potentially improves time resolution of iterative reconstruction. (orig.)

  11. High-performance image reconstruction in fluorescence tomography on desktop computers and graphics hardware.

    Science.gov (United States)

    Freiberger, Manuel; Egger, Herbert; Liebmann, Manfred; Scharfetter, Hermann

    2011-11-01

    Image reconstruction in fluorescence optical tomography is a three-dimensional nonlinear ill-posed problem governed by a system of partial differential equations. In this paper we demonstrate that a combination of state of the art numerical algorithms and a careful hardware optimized implementation allows to solve this large-scale inverse problem in a few seconds on standard desktop PCs with modern graphics hardware. In particular, we present methods to solve not only the forward but also the non-linear inverse problem by massively parallel programming on graphics processors. A comparison of optimized CPU and GPU implementations shows that the reconstruction can be accelerated by factors of about 15 through the use of the graphics hardware without compromising the accuracy in the reconstructed images.

  12. High-performance image reconstruction in fluorescence tomography on desktop computers and graphics hardware

    Science.gov (United States)

    Freiberger, Manuel; Egger, Herbert; Liebmann, Manfred; Scharfetter, Hermann

    2011-01-01

    Image reconstruction in fluorescence optical tomography is a three-dimensional nonlinear ill-posed problem governed by a system of partial differential equations. In this paper we demonstrate that a combination of state of the art numerical algorithms and a careful hardware optimized implementation allows to solve this large-scale inverse problem in a few seconds on standard desktop PCs with modern graphics hardware. In particular, we present methods to solve not only the forward but also the non-linear inverse problem by massively parallel programming on graphics processors. A comparison of optimized CPU and GPU implementations shows that the reconstruction can be accelerated by factors of about 15 through the use of the graphics hardware without compromising the accuracy in the reconstructed images. PMID:22076279

  13. Radial differential interior tomography and its image reconstruction with differentiated backprojection and projection onto convex sets.

    Science.gov (United States)

    Tang, Shaojie; Tang, Xiangyang

    2013-09-01

    Interior tomography has been recognized as one of the most effective approaches in computed tomography (CT) to reduce radiation dose rendered to patients. In this work, the authors propose and evaluate an imaging method of radial differential interior tomography. In interior tomography, an x-ray beam is collimated to only irradiate the region of interest (ROI) with suspected lesions while the surrounding area∕volume of normal tissues∕organs is spared. In the proposed imaging method of radial differential interior tomography, the outcome is a ROI image that has gone through a radial differential filtering. The image reconstruction algorithm for the radial differential interior tomography is kept in the fashion of differentiated backprojection and projection onto convex sets, but the required a priori knowledge in a small round area becomes zero and may be more readily available in practice. Using the projection data simulated by computer and acquired by CT scanner, the authors evaluate and verify the performance of the proposed radial differential interior tomography method and its associated image reconstruction algorithm. The preliminary results show that the proposed imaging method can generate an image that is the radial differentiation of a conventional tomographic image and is robust over noise that inevitably exist in practice. It is believed that the proposed imaging method may find its utility in advanced clinical applications wherein a ROI-based image processing and analysis is required for lesion visualization, characterization, and diagnosis.

  14. Efficient stereo image geometrical reconstruction at arbitrary camera settings from a single calibration.

    Science.gov (United States)

    Ji, Songbai; Fan, Xiaoyao; Roberts, David W; Paulsen, Keith D

    2014-01-01

    Camera calibration is central to obtaining a quantitative image-to-physical-space mapping from stereo images acquired in the operating room (OR). A practical challenge for cameras mounted to the operating microscope is maintenance of image calibration as the surgeon's field-of-view is repeatedly changed (in terms of zoom and focal settings) throughout a procedure. Here, we present an efficient method for sustaining a quantitative image-to-physical space relationship for arbitrary image acquisition settings (S) without the need for camera re-calibration. Essentially, we warp images acquired at S into the equivalent data acquired at a reference setting, S(0), using deformation fields obtained with optical flow by successively imaging a simple phantom. Closed-form expressions for the distortions were derived from which 3D surface reconstruction was performed based on the single calibration at S(0). The accuracy of the reconstructed surface was 1.05 mm and 0.59 mm along and perpendicular to the optical axis of the operating microscope on average, respectively, for six phantom image pairs, and was 1.26 mm and 0.71 mm for images acquired with a total of 47 arbitrary settings during three clinical cases. The technique is presented in the context of stereovision; however, it may also be applicable to other types of video image acquisitions (e.g., endoscope) because it does not rely on any a priori knowledge about the camera system itself, suggesting the method is likely of considerable significance.

  15. Image reconstruction for digital breast tomosynthesis (DBT) by using projection-angle-dependent filter functions

    Energy Technology Data Exchange (ETDEWEB)

    Park, Yeonok; Park, Chulkyu; Cho, Hyosung; Je, Uikyu; Hong, Daeki; Lee, Minsik; Cho, Heemoon; Choi, Sungil; Koo, Yangseo [Yonsei University, Wonju (Korea, Republic of)

    2014-09-15

    Digital breast tomosynthesis (DBT) is considered in clinics as a standard three-dimensional imaging modality, allowing the earlier detection of cancer. It typically acquires only 10-30 projections over a limited angle range of 15 - 60 .deg. with a stationary detector and typically uses a computationally-efficient filtered-backprojection (FBP) algorithm for image reconstruction. However, a common FBP algorithm yields poor image quality resulting from the loss of average image value and the presence of severe image artifacts due to the elimination of the dc component of the image by the ramp filter and to the incomplete data, respectively. As an alternative, iterative reconstruction methods are often used in DBT to overcome these difficulties, even though they are still computationally expensive. In this study, as a compromise, we considered a projection-angle dependent filtering method in which one-dimensional geometry-adapted filter kernels are computed with the aid of a conjugate-gradient method and are incorporated into the standard FBP framework. We implemented the proposed algorithm and performed systematic simulation works to investigate the imaging characteristics. Our results indicate that the proposed method is superior to a conventional FBP method for DBT imaging and has a comparable computational cost, while preserving good image homogeneity and edge sharpening with no serious image artifacts.

  16. Progress toward the development and testing of source reconstruction methods for NIF neutron imaging.

    Science.gov (United States)

    Loomis, E N; Grim, G P; Wilde, C; Wilson, D C; Morgan, G; Wilke, M; Tregillis, I; Merrill, F; Clark, D; Finch, J; Fittinghoff, D; Bower, D

    2010-10-01

    Development of analysis techniques for neutron imaging at the National Ignition Facility is an important and difficult task for the detailed understanding of high-neutron yield inertial confinement fusion implosions. Once developed, these methods must provide accurate images of the hot and cold fuels so that information about the implosion, such as symmetry and areal density, can be extracted. One method under development involves the numerical inversion of the pinhole image using knowledge of neutron transport through the pinhole aperture from Monte Carlo simulations. In this article we present results of source reconstructions based on simulated images that test the methods effectiveness with regard to pinhole misalignment.

  17. Image reconstruction of mMR PET data using the open source software STIR

    Energy Technology Data Exchange (ETDEWEB)

    Markiewicz, Pawel [Centre for Medical Image Computing, University College London, London (United Kingdom); Thielemans, Kris [Institute of Nuclear Medicine, University College London, London (United Kingdom); Burgos, Ninon [Centre for Medical Image Computing, University College London, London (United Kingdom); Manber, Richard [Institute of Nuclear Medicine, University College London, London (United Kingdom); Jiao, Jieqing [Centre for Medical Image Computing, University College London, London (United Kingdom); Barnes, Anna [Institute of Nuclear Medicine, University College London, London (United Kingdom); Atkinson, David [Centre for Medical Imaging, University College London, London (United Kingdom); Arridge, Simon R [Centre for Medical Image Computing, University College London, London (United Kingdom); Hutton, Brian F [Institute of Nuclear Medicine, University College London, London (United Kingdom); Ourselin, Sébastien [Centre for Medical Image Computing, University College London, London (United Kingdom); Dementia Research Centre, University College London, London (United Kingdom)

    2014-07-29

    Simultaneous PET and MR acquisitions have now become possible with the new hybrid Biograph Molecular MR (mMR) scanner from Siemens. The purpose of this work is to create a platform for mMR 3D and 4D PET image reconstruction which would be freely accessible to the community as well as fully adjustable in order to obtain optimal images for a given research task in PET imaging. The proposed platform is envisaged to prove useful in developing novel and robust image bio-markers which could then be adapted for use on the mMR scanner.

  18. B-Spline potential function for maximum a-posteriori image reconstruction in fluorescence microscopy

    Directory of Open Access Journals (Sweden)

    Shilpa Dilipkumar

    2015-03-01

    Full Text Available An iterative image reconstruction technique employing B-Spline potential function in a Bayesian framework is proposed for fluorescence microscopy images. B-splines are piecewise polynomials with smooth transition, compact support and are the shortest polynomial splines. Incorporation of the B-spline potential function in the maximum-a-posteriori reconstruction technique resulted in improved contrast, enhanced resolution and substantial background reduction. The proposed technique is validated on simulated data as well as on the images acquired from fluorescence microscopes (widefield, confocal laser scanning fluorescence and super-resolution 4Pi microscopy. A comparative study of the proposed technique with the state-of-art maximum likelihood (ML and maximum-a-posteriori (MAP with quadratic potential function shows its superiority over the others. B-Spline MAP technique can find applications in several imaging modalities of fluorescence microscopy like selective plane illumination microscopy, localization microscopy and STED.

  19. 3D Reconstruction of Tree-Crown Based on the UAV Aerial Images

    Directory of Open Access Journals (Sweden)

    Chao Xu

    2015-01-01

    Full Text Available The algorithm for 3D reconstruction of tree-crown is presented with the UAV aerial images from a mountainous area in China. Considering the fact that the aerial images consist of little tree-crown texture and contour information, a feature area extraction method is proposed based on watershed segmentation, and the local area correlation coefficient is calculated to match the feature areas, in order to fully extract the characteristics that can reflect the structure of tree-crown. Then, the depth of feature points is calculated using the stereo vision theory. Finally, the L-system theory is applied to construct the 3D model of tree. The experiments are conducted with the tree-crown images from UAV aerial images manually. The experiment result showed that the method proposed in this paper can fully extract and match the feature points of tree-crown that can reconstruct the 3D model of the tree-crown correctly.

  20. Monte Carlo evaluation of the Filtered Back Projection method for image reconstruction in proton computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Cirrone, G.A.P., E-mail: cirrone@lns.infn.it [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Bucciolini, M. [Department of ' Fisiopatologia Clinica' , University of Florence, V.le Morgagni 85, I-50134 Florence (Italy); Bruzzi, M. [Energetic Department, University of Florence, Via S. Marta 3, I-50139 Florence (Italy); Candiano, G. [Laboratorio di Tecnologie Oncologiche HSR, Giglio Contrada, Pietrapollastra-Pisciotto, 90015 Cefalu, Palermo (Italy); Civinini, C. [National Institute for Nuclear Physics INFN, Section of Florence, Via G. Sansone 1, Sesto Fiorentino, I-50019 Florence (Italy); Cuttone, G. [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Guarino, P. [Nuclear Engineering Department, University of Palermo, Via... Palermo (Italy); Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Lo Presti, D. [Physics Department, University of Catania, Via S. Sofia 64, I-95123, Catania (Italy); Mazzaglia, S.E. [Laboratori Nazionali del Sud - National Instiute for Nuclear Physics INFN (INFN-LNS), Via S.Sofia 64, 95100 Catania (Italy); Pallotta, S. [Department of ' Fisiopatologia Clinica' , University of Florence, V.le Morgagni 85, I-50134 Florence (Italy); Randazzo, N. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); Sipala, V. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); Physics Department, University of Catania, Via S. Sofia 64, I-95123, Catania (Italy); Stancampiano, C. [National Institute for Nuclear Physics INFN, Section of Catania, Via S.Sofia 64, 95123 Catania (Italy); and others

    2011-12-01

    In this paper the use of the Filtered Back Projection (FBP) Algorithm, in order to reconstruct tomographic images using the high energy (200-250 MeV) proton beams, is investigated. The algorithm has been studied in detail with a Monte Carlo approach and image quality has been analysed and compared with the total absorbed dose. A proton Computed Tomography (pCT) apparatus, developed by our group, has been fully simulated to exploit the power of the Geant4 Monte Carlo toolkit. From the simulation of the apparatus, a set of tomographic images of a test phantom has been reconstructed using the FBP at different absorbed dose values. The images have been evaluated in terms of homogeneity, noise, contrast, spatial and density resolution.

  1. Efficient methodologies for system matrix modelling in iterative image reconstruction for rotating high-resolution PET

    Energy Technology Data Exchange (ETDEWEB)

    Ortuno, J E; Kontaxakis, G; Rubio, J L; Santos, A [Departamento de Ingenieria Electronica (DIE), Universidad Politecnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain); Guerra, P [Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid (Spain)], E-mail: juanen@die.upm.es

    2010-04-07

    A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries.

  2. Fused analytical and iterative reconstruction (AIR) via modified proximal forward-backward splitting: a FDK-based iterative image reconstruction example for CBCT.

    Science.gov (United States)

    Gao, Hao

    2016-10-07

    This work is to develop a general framework, namely analytical iterative reconstruction (AIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality and reconstruction efficiency. Specifically, AIR is established based on the modified proximal forward-backward splitting (PFBS) algorithm, and its connection to the filtered data fidelity with sparsity regularization is discussed. As a result, AIR decouples data fidelity and image regularization with a two-step iterative scheme, during which an AR-projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR-projection step, the image is projected to the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is then weighted together with previous image iterate to form next image iterate. Intuitively since the eigenvalues of AR-projection operator are close to the unity, PFBS based AIR has a fast convergence. Such an advantage is rigorously established through convergence analysis and numerical computation of convergence rate. The proposed AIR method is validated in the setting of circular cone-beam CT with AR being FDK and total-variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half-fan artifacts.

  3. Fused analytical and iterative reconstruction (AIR) via modified proximal forward-backward splitting: a FDK-based iterative image reconstruction example for CBCT

    Science.gov (United States)

    Gao, Hao

    2016-10-01

    This work is to develop a general framework, namely analytical iterative reconstruction (AIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality and reconstruction efficiency. Specifically, AIR is established based on the modified proximal forward-backward splitting (PFBS) algorithm, and its connection to the filtered data fidelity with sparsity regularization is discussed. As a result, AIR decouples data fidelity and image regularization with a two-step iterative scheme, during which an AR-projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR-projection step, the image is projected to the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is then weighted together with previous image iterate to form next image iterate. Intuitively since the eigenvalues of AR-projection operator are close to the unity, PFBS based AIR has a fast convergence. Such an advantage is rigorously established through convergence analysis and numerical computation of convergence rate. The proposed AIR method is validated in the setting of circular cone-beam CT with AR being FDK and total-variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half-fan artifacts.

  4. Breast Microcalcification Detection Using Super-Resolution Ultrasound Image Reconstruction

    Science.gov (United States)

    2010-09-01

    imag- ing for breast microcalcification detection. Breast microcalcifications can be seen in malignant cancerous masses. We construct a numerical... cancers detected by mam- mography, and approximately 95% of all DCIS is diagnosed because of mammographically detected microcalcifications . Breast ...detection using numerical breast phantoms. Microcalcifications can be found in different breast tissues, such as cancerous masses or cysts. We build two

  5. Page 1 Image acquisition & surface reconstruction using active ...

    Indian Academy of Sciences (India)

    and equipped with Vicon V17.5–105M motorized zoom lenses. High-precision stepper-motor rotational units are used to control independent pan, tilt, and vergence angles. The imaging system is controlled by a Sun Microsystems 3/160 workstation. 4.1 Implementation details. For the left and the right cameras, calibrated ...

  6. Paediatric cardiac CT examinations: impact of the iterative reconstruction method ASIR on image quality - preliminary findings

    Energy Technology Data Exchange (ETDEWEB)

    Mieville, Frederic A. [University Hospital Center and University of Lausanne, Institute of Radiation Physics, Lausanne (Switzerland); University Hospital Center and University of Lausanne, Institute of Radiation Physics - Medical Radiology, Lausanne (Switzerland); Gudinchet, Francois; Rizzo, Elena [University Hospital Center and University of Lausanne, Department of Radiology, Lausanne (Switzerland); Ou, Phalla; Brunelle, Francis [Necker Children' s Hospital, Department of Radiology, Paris (France); Bochud, Francois O.; Verdun, Francis R. [University Hospital Center and University of Lausanne, Institute of Radiation Physics, Lausanne (Switzerland)

    2011-09-15

    Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI{sub vol} 4.8-7.9 mGy, DLP 37.1-178.9 mGy.cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. The best image quality for all clinical images was obtained with 20% and 40% ASIR (p < 0.001) whereas with ASIR above 50%, image quality significantly decreased (p < 0.001). With 100% ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone. (orig.)

  7. System and method for image reconstruction, analysis, and/or de-noising

    KAUST Repository

    Laleg-Kirati, Taous-Meriem

    2015-11-12

    A method and system can analyze, reconstruct, and/or denoise an image. The method and system can include interpreting a signal as a potential of a Schrödinger operator, decomposing the signal into squared eigenfunctions, reducing a design parameter of the Schrödinger operator, analyzing discrete spectra of the Schrödinger operator and combining the analysis of the discrete spectra to construct the image.

  8. Cardiac Magnetic Resonance Imaging by Retrospective Gating : Mathematical Modelling and Reconstruction Algorithms

    NARCIS (Netherlands)

    Roerdink, J.B.T.M.; Zwaan, M.

    1993-01-01

    This paper is concerned with some mathematical aspects of magnetic resonance imaging (MRI) of the beating human heart. In particular we investigate the so-called retrospective gating technique which is a non-triggered technique for data acquisition and reconstruction of (approximately) periodically

  9. Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method

    Science.gov (United States)

    Baikejiang, Reheman; Zhao, Yue; Fite, Brett Z.; Ferrara, Katherine W.; Li, Changqing

    2017-05-01

    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.

  10. Computed Tomography Radiation Dose Reduction: Effect of Different Iterative Reconstruction Algorithms on Image Quality

    NARCIS (Netherlands)

    Willemink, M.J.; Takx, R.A.P.; Jong, P.A. de; Budde, R.P.; Bleys, R.L.; Das, M.; Wildberger, J.E.; Prokop, M.; Buls, N.; Mey, J. de; Leiner, T.; Schilham, A.M.

    2014-01-01

    We evaluated the effects of hybrid and model-based iterative reconstruction (IR) algorithms from different vendors at multiple radiation dose levels on image quality of chest phantom scans.A chest phantom was scanned on state-of-the-art computed tomography scanners from 4 vendors at 4 dose levels

  11. Vascular fluorescence casting and imaging cryomicrotomy for computerized three-dimensional renal arterial reconstruction

    NARCIS (Netherlands)

    Lagerveld, Brunolf W.; ter Wee, Rene D.; de La Rosette, Jean J. M. C. H.; Spaan, Jos A. E.; Wijkstra, Hessel

    2007-01-01

    OBJECTIVES To assess the combined use of a casting technique, cryomicrotomy imaging, and three-dimensional (3D) computer analysis as a method for visualizing and reconstructing the arterial vascular tree in a porcine renal model. MATERIAL AND METHODS The arterial branches of two porcine kidneys were

  12. A tensor-based dictionary learning approach to tomographic image reconstruction

    DEFF Research Database (Denmark)

    Soltani, Sara; Kilmer, Misha E.; Hansen, Per Christian

    2016-01-01

    with sparsity constraints. The reconstruction problem is formulated in a convex optimization framework by looking for a solution with a sparse representation in the tensor dictionary. Numerical results show that our tensor formulation leads to very sparse representations of both the training images...

  13. Segmentation, Reconstruction, and Analysis of Blood Thrombus Formation in 3D 2-Photon Microscopy Images

    Directory of Open Access Journals (Sweden)

    Xu Zhiliang

    2010-01-01

    Full Text Available We study the problem of segmenting, reconstructing, and analyzing the structure growth of thrombi (clots in blood vessels in vivo based on 2-photon microscopic image data. First, we develop an algorithm for segmenting clots in 3D microscopic images based on density-based clustering and methods for dealing with imaging artifacts. Next, we apply the union-of-balls (or alpha-shape algorithm to reconstruct the boundary of clots in 3D. Finally, we perform experimental studies and analysis on the reconstructed clots and obtain quantitative data of thrombus growth and structures. We conduct experiments on laser-induced injuries in vessels of two types of mice (the wild type and the type with low levels of coagulation factor VII and analyze and compare the developing clot structures based on their reconstructed clots from image data. The results we obtain are of biomedical significance. Our quantitative analysis of the clot composition leads to better understanding of the thrombus development, and is valuable to the modeling and verification of computational simulation of thrombogenesis.

  14. Three-dimensional reconstruction of intracoronary ultrasound images. Rationale, approaches, problems, and directions

    OpenAIRE

    Roelandt, Jos; Mario, Carlo; Pandian, Natesa; Wenguang, L.; Keane, David; Slager, Cornelis; Feyter, Pim; Serruys, Patrick

    1994-01-01

    textabstractAlthough intracoronary ultrasonography allows detailed tomographic imaging of the arterial wall, it fails to provide data on the structural architecture and longitudinal extent of arterial disease. This information is essential for decision making during therapeutic interventions. Three-dimensional reconstruction techniques offer visualization of the complex longitudinal architecture of atherosclerotic plaques in composite display. Progress in computer hardware and software techno...

  15. Connections model for tomographic images reconstruction; Modelo conexionista para reconstrucao de imagens tomograficas

    Energy Technology Data Exchange (ETDEWEB)

    Rodrigues, R.G.S.; Pela, C.A.; Roque, S.F. A.C. [Departamento de Fisica e Matematica (FFCLRP) USP. Av. Bandeirantes, 3900- 14040- 901- Ribeirao Preto, Sao Paulo (Brazil)

    1998-12-31

    This paper shows an artificial neural network with an adequately topology for tomographic image reconstruction. The associated error function is derived and the learning algorithm is make. The simulated results are presented and demonstrate the existence of a generalized solution for nets with linear activation function. (Author)

  16. Tunnel Effect in CNNs: Image Reconstruction From Max-Switch Locations

    DEFF Research Database (Denmark)

    de La Roche Saint Andre, Matthieu; Rieger, Laura; Hannemose, Morten

    2016-01-01

    In this paper, we show that reconstruction of an image passed through a neural network is possible, using only the locations of the max pool activations. This was demonstrated with an architecture consisting of an encoder and a decoder. The decoder is a mirrored version of the encoder, where conv...

  17. Non-Cartesian Parallel Imaging Reconstruction of Undersampled IDEAL Spiral 13C CSI Data

    DEFF Research Database (Denmark)

    Hansen, Rie Beck; Hanson, Lars G.; Ardenkjær-Larsen, Jan Henrik

    scan times based on spatial information inherent to each coil element. In this work, we explored the combination of non-cartesian parallel imaging reconstruction and spatially undersampled IDEAL spiral CSI1 acquisition for efficient encoding of multiple chemical shifts within a large FOV with high...

  18. Image quality in children with low-radiation chest CT using adaptive statistical iterative reconstruction and model-based iterative reconstruction.

    Science.gov (United States)

    Sun, Jihang; Peng, Yun; Duan, Xiaomin; Yu, Tong; Zhang, Qifeng; Liu, Yong; Hu, Di

    2014-01-01

    To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR) and a full model-based iterative reconstruction (MBIR) algorithm. Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years) who received low-dose chest CT scans were included. Age-dependent noise index (NI) was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP), and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV), muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR) was calculated. In terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP. Compared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.

  19. Image quality in children with low-radiation chest CT using adaptive statistical iterative reconstruction and model-based iterative reconstruction.

    Directory of Open Access Journals (Sweden)

    Jihang Sun

    Full Text Available OBJECTIVE: To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR and a full model-based iterative reconstruction (MBIR algorithm. METHODS: Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years who received low-dose chest CT scans were included. Age-dependent noise index (NI was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP, and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV, muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR was calculated. RESULT: In terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP. CONCLUSION: Compared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.

  20. 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)

  1. Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

    Energy Technology Data Exchange (ETDEWEB)

    Solomon, Justin, E-mail: justin.solomon@duke.edu [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Samei, Ehsan [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Biomedical Engineering and Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina 27705 (United States)

    2014-09-15

    Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

  2. Ensuring convergence in total-variation-based reconstruction for accurate microcalcification imaging in breast X-ray CT

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Heide; Sidky, Emil Y.; Pan, Xiaochuan

    2011-01-01

    , shows potential for reconstruction from sparse-view data. For iterative methods it is important to ensure convergence to an accurate solution, since important diagnostic image features, such as presence of microcalcifications indicating breast cancer, may not be visible in a non-converged reconstruction....... This motivates the study of accurate convergence criteria for iterative image reconstruction. In simulation studies with a realistic breast phantom with microcalcifications we investigate the issue of ensuring sufficiently converged solution for reliable reconstruction. Our results show that it can......Breast X-ray CT imaging is being considered in screening as an extension to mammography. As a large fraction of the population will be exposed to radiation, low·dose imaging is essential. Iterative image reconstruction based on solving an optimization problem, such as Total-Variation minimization...

  3. Analysis of acetabular orientation and femoral anteversion using images of three-dimensional reconstructed bone models.

    Science.gov (United States)

    Park, Jaeyeong; Kim, Jun-Young; Kim, Hyun Deok; Kim, Young Cheol; Seo, Anna; Je, Minkyu; Mun, Jong Uk; Kim, Bia; Park, Il Hyung; Kim, Shin-Yoon

    2017-05-01

    Radiographic measurements using two-dimensional (2D) plain radiographs or planes from computed tomography (CT) scans have several drawbacks, while measurements using images of three-dimensional (3D) reconstructed bone models can provide more consistent anthropometric information. We compared the consistency of results using measurements based on images of 3D reconstructed bone models (3D measurements) with those using planes from CT scans (measurements using 2D slice images). Ninety-six of 561 patients who had undergone deep vein thrombosis-CT between January 2013 and November 2014 were randomly selected. We evaluated measurements using 2D slice images and 3D measurements. The images used for 3D reconstruction of bone models were obtained and measured using [Formula: see text] and [Formula: see text] (Materialize, Leuven, Belgium). The mean acetabular inclination, acetabular anteversion and femoral anteversion values on 2D slice images were 42.01[Formula: see text], 18.64[Formula: see text] and 14.44[Formula: see text], respectively, while those using images of 3D reconstructed bone models were 52.80[Formula: see text], 14.98[Formula: see text] and 17.26[Formula: see text]. Intra-rater reliabilities for acetabular inclination, acetabular anteversion, and femoral anteversion on 2D slice images were 0.55, 0.81, and 0.85, respectively, while those for 3D measurements were 0.98, 0.99, and 0.98. Inter-rater reliabilities for acetabular inclination, acetabular anteversion and femoral anteversion on 2D slice images were 0.48, 0.86, and 0.84, respectively, while those for 3D measurements were 0.97, 0.99, and 0.97. The differences between the two measurements are explained by the use of different tools. However, more consistent measurements were possible using the images of 3D reconstructed bone models. Therefore, 3D measurement can be a good alternative to measurement using 2D slice images.

  4. A fast method based on NESTA to accurately reconstruct CT image from highly undersampled projection measurements.

    Science.gov (United States)

    He, Zhijie; Qiao, Quanbang; Li, Jun; Huang, Meiping; Zhu, Shouping; Huang, Liyu

    2016-11-22

    The CT image reconstruction algorithm based compressed sensing (CS) can be formulated as an optimization problem that minimizes the total-variation (TV) term constrained by the data fidelity and image nonnegativity. There are a lot of solutions to this problem, but the computational efficiency and reconstructed image quality of these methods still need to be improved. To investigate a faster and more accurate mathematical algorithm to settle TV term minimization problem of CT image reconstruction. A Nesterov's algorithm (NESTA) is a fast and accurate algorithm for solving TV minimization problem, which can be ascribed to the use of most notably Nesterov's smoothing technique and a subtle averaging of sequences of iterates, which has been shown to improve the convergence properties of standard gradient-descent algorithms. In order to demonstrate the superior performance of NESTA on computational efficiency and image quality, a comparison with Simultaneous Algebraic Reconstruction Technique-TV (SART-TV) and Split-Bregman (SpBr) algorithm is made using a digital phantom study and two physical phantom studies from highly undersampled projection measurements. With only 25% of conventional full-scan dose and, NESTA method reduces the average CT number error from 51.76HU to 9.98HU on Shepp-Logan phantom and reduces the average CT number error from 50.13HU to 0.32HU on Catphan 600 phantom. On an anthropomorphic head phantom, the average CT number error is reduced from 84.21HU to 1.01HU in the central uniform area. To the best of our knowledge this is the first work that apply the NESTA method into CT reconstruction based CS. Research shows that this method is of great potential, further studies and optimization are necessary.

  5. Mandibular Defect Reconstruction with the Help of Mirror Imaging Coupled with Laser Stereolithographic Modeling Technique

    Directory of Open Access Journals (Sweden)

    Jing-Wei Lee

    2007-01-01

    Full Text Available With the advent of microsurgery, composite defect in the mandible can be repaired with various forms of osteocutaneous free flaps. However, it is difficult to accurately reconstruct a large defect in the mandible when not enough mandibular reference blueprints remain. This case report describes a large ameloblastoma at the left lower molar region and ascending ramus of the mandible in a 53-year-old male patient. Before surgery, spiral computed tomography scanning of the whole skull of the patient was performed. Using three-dimensional reconstruction and mirror imaging coupled with laser stereolithographic technique, a complete mandibular biomodel with idealized shape was fabricated. A titanium reconstruction plate was made using the biomodel as a guide. The tumor mass together with the left mandible from the second premolar to the condylar head area was resected en bloc. The large mandibular defect was then reconstructed with the precontoured titanium plate and three segments of vascularized fibular bone graft fixed along the plate. The temporomandibular joint was restored with temporalis muscle as an interpositional disc replacement. The complex defect in the mandible was thus repaired with satisfactory functioning and esthetic result. We suggest that with the help of mirror imaging coupled with laser stereolithographic technique, a precontoured titanium plate can be made for the reconstruction of large mandibular defects. [J Formos Med Assoc 2007;106(3:244-250

  6. Evaluation of Algebraic Iterative Image Reconstruction Methods for Tetrahedron Beam Computed Tomography Systems

    Directory of Open Access Journals (Sweden)

    Joshua Kim

    2013-01-01

    Full Text Available Tetrahedron beam computed tomography (TBCT performs volumetric imaging using a stack of fan beams generated by a multiple pixel X-ray source. While the TBCT system was designed to overcome the scatter and detector issues faced by cone beam computed tomography (CBCT, it still suffers the same large cone angle artifacts as CBCT due to the use of approximate reconstruction algorithms. It has been shown that iterative reconstruction algorithms are better able to model irregular system geometries and that algebraic iterative algorithms in particular have been able to reduce cone artifacts appearing at large cone angles. In this paper, the SART algorithm is modified for the use with the different TBCT geometries and is tested using both simulated projection data and data acquired using the TBCT benchtop system. The modified SART reconstruction algorithms were able to mitigate the effects of using data generated at large cone angles and were also able to reconstruct CT images without the introduction of artifacts due to either the longitudinal or transverse truncation in the data sets. Algebraic iterative reconstruction can be especially useful for dual-source dual-detector TBCT, wherein the cone angle is the largest in the center of the field of view.

  7. Three-dimensional image reconstruction of distribution of Pnmt+ cell-derived cells in murine heart.

    Science.gov (United States)

    Ni, Haibo; Wang, Yange; Crawford, William; Zhang, Shanzhuo; Cheng, Longxian; Zhang, Henggui; Lei, Ming

    2017-09-26

    Elucidating the function of specific cell types in a highly complex multicellular system such as the heart often requires detailed anatomic reconstruction. We recently described a distinctive class of phenylethanolamine n-methyltransferase (Pnmt+) cell-derived cardiomyocytes (PdCMs), a new cardiomyocyte population with a potential endocrine role. In this dataset, a 3D reconstruction was carried out to visualise the distribution of PdCMs throughout the murine heart. Rigid registration (stiff rotation and translation) was applied to properly align the fused heart slice images based on landmarks using TrakEM2, an open source plug-in in Fiji. The registered slices were then analysed and reconstructed using MATLAB (MATLAB®. Version 8.3.0.532). The final reconstructed 3D volume was 561×866×48 pixels (corresponding to spatial resolutions of 5.8, 8.9 and 2.5 mm in the x-, y- and z-direction respectively), and visualised in Paraview. The reconstruction allows for detailed analyses of morphology, projections and cellular features of different cell types, enabling further geometrical and topological analyses. Image data can be accessed and viewed through Figshare.

  8. Challenges in using GPUs for the reconstruction of digital hologram images

    Science.gov (United States)

    Reid, I. D.; Nebrensky, J. J.; Hobson, P. R.

    2012-06-01

    In-line holographic imaging is used for small particulates, such as cloud or spray droplets, marine plankton, and alluvial sediments, and enables a true 3D object field to be recorded at high resolution over a considerable depth. To reconstruct a digital hologram a 2D FFT must be calculated for every depth slice desired in the replayed image volume. A typical in-line hologram of ~ 100 micrometre-sized particles over a depth of a few hundred millimetres will require O(1000) 2D FFT operations to be performed on an hologram of typically a few million pixels. In previous work we have reported on our experiences with reconstruction on a computational grid. In this paper we discuss the technical challenges in making efficient use of the NVIDIA Tesla and Fermi GPU systems and show how our reconstruction code was optimised for near real-time video slice reconstruction with holograms as large as 4K by 4K pixels. We also consider the implications for grid and cloud computing approaches to hologram replay, and the extent to which a GPU can replace these approaches, when the important step of locating focussed objects within a reconstructed volume is included.

  9. 300 GHz imaging with 8 meter stand-off distance and one-dimensional synthetic image reconstruction

    DEFF Research Database (Denmark)

    Keil, Andreas; Quast, Holger; Loeffler, Torsten

    2011-01-01

    of mirrors with effective aperture of 0.5 × 0.5 meter. Information about range and reflectivity of the object are obtained using an active FMCW (frequency modulated continuous wave) radar operation principle. Data acquisition time for one line is as short as 1 ms. Synthetic image reconstruction is achieved......An active system for stand-off imaging operating in a frequency range from 234 GHz to 306 GHz is presented. Imaging is achieved by combining a line array consisting of 8 emitters and 16 detectors with a scanning cylindrical mirror system. A stand-off distance of 7-8 m is achieved using a system...

  10. Image Reconstruction from Under sampled Fourier Data Using the Polynomial Annihilation Transform

    Energy Technology Data Exchange (ETDEWEB)

    Archibald, Richard K. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gelb, Anne [Arizona State Univ., Mesa, AZ (United States); Platte, Rodrigo [Arizona State Univ., Mesa, AZ (United States)

    2015-09-09

    Fourier samples are collected in a variety of applications including magnetic resonance imaging and synthetic aperture radar. The data are typically under-sampled and noisy. In recent years, l1 regularization has received considerable attention in designing image reconstruction algorithms from under-sampled and noisy Fourier data. The underlying image is assumed to have some sparsity features, that is, some measurable features of the image have sparse representation. The reconstruction algorithm is typically designed to solve a convex optimization problem, which consists of a fidelity term penalized by one or more l1 regularization terms. The Split Bregman Algorithm provides a fast explicit solution for the case when TV is used for the l1l1 regularization terms. Due to its numerical efficiency, it has been widely adopted for a variety of applications. A well known drawback in using TV as an l1 regularization term is that the reconstructed image will tend to default to a piecewise constant image. This issue has been addressed in several ways. Recently, the polynomial annihilation edge detection method was used to generate a higher order sparsifying transform, and was coined the “polynomial annihilation (PA) transform.” This paper adapts the Split Bregman Algorithm for the case when the PA transform is used as the l1 regularization term. In so doing, we achieve a more accurate image reconstruction method from under-sampled and noisy Fourier data. Our new method compares favorably to the TV Split Bregman Algorithm, as well as to the popular TGV combined with shearlet approach.

  11. Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography.

    Science.gov (United States)

    Huy, Tran Quang; Tue, Huynh Huu; Long, Ton That; Duc-Tan, Tran

    2017-05-25

    A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared to the current gold-standard X-ray mammography. Based on inverse scattering technique, ultrasound tomography uses some material properties such as sound contrast or attenuation to detect small targets. The Distorted Born Iterative Method (DBIM) based on first-order Born approximation is an efficient diffraction tomography approach. One of the challenges for a high quality reconstruction is to obtain many measurements from the number of transmitters and receivers. Given the fact that biomedical images are often sparse, the compressed sensing (CS) technique could be therefore effectively applied to ultrasound tomography by reducing the number of transmitters and receivers, while maintaining a high quality of image reconstruction. There are currently several work on CS that dispose randomly distributed locations for the measurement system. However, this random configuration is relatively difficult to implement in practice. Instead of it, we should adopt a methodology that helps determine the locations of measurement devices in a deterministic way. For this, we develop the novel DCS-DBIM algorithm that is highly applicable in practice. Inspired of the exploitation of the deterministic compressed sensing technique (DCS) introduced by the authors few years ago with the image reconstruction process implemented using l 1 regularization. Simulation results of the proposed approach have demonstrated its high performance, with the normalized error approximately 90% reduced, compared to the conventional approach, this new approach can save half of number of measurements and only uses two iterations. Universal image quality index is also evaluated in order to prove the efficiency of the proposed approach. Numerical simulation results

  12. Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

    Science.gov (United States)

    Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

    2017-05-01

    Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other

  13. Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies.

    Science.gov (United States)

    Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

    2017-05-07

    Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18 F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans-each containing 1/8th of the total number of events-were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18 F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other

  14. MAP-MRF-Based Super-Resolution Reconstruction Approach for Coded Aperture Compressive Temporal Imaging

    Directory of Open Access Journals (Sweden)

    Tinghua Zhang

    2018-02-01

    Full Text Available Coded Aperture Compressive Temporal Imaging (CACTI can afford low-cost temporal super-resolution (SR, but limits are imposed by noise and compression ratio on reconstruction quality. To utilize inter-frame redundant information from multiple observations and sparsity in multi-transform domains, a robust reconstruction approach based on maximum a posteriori probability and Markov random field (MAP-MRF model for CACTI is proposed. The proposed approach adopts a weighted 3D neighbor system (WNS and the coordinate descent method to perform joint estimation of model parameters, to achieve the robust super-resolution reconstruction. The proposed multi-reconstruction algorithm considers both total variation (TV and ℓ 2 , 1 norm in wavelet domain to address the minimization problem for compressive sensing, and solves it using an accelerated generalized alternating projection algorithm. The weighting coefficient for different regularizations and frames is resolved by the motion characteristics of pixels. The proposed approach can provide high visual quality in the foreground and background of a scene simultaneously and enhance the fidelity of the reconstruction results. Simulation results have verified the efficacy of our new optimization framework and the proposed reconstruction approach.

  15. Consequences of random and systematic reconstruction uncertainties in 3D image based brachytherapy in cervical cancer.

    Science.gov (United States)

    Tanderup, Kari; Hellebust, Taran Paulsen; Lang, Stefan; Granfeldt, Jørgen; Pötter, Richard; Lindegaard, Jacob Christian; Kirisits, Christian

    2008-11-01

    The purpose of this study was to evaluate the impact of random and systematic applicator reconstruction uncertainties on DVH parameters in brachytherapy for cervical cancer. Dose plans were analysed for 20 cervical cancer patients with MRI based brachytherapy. Uncertainty of applicator reconstruction was modelled by translating and rotating the applicator. Changes in DVH parameters per mm of applicator displacement were evaluated for GTV, CTV, bladder, rectum, and sigmoid. These data were used to derive patient population based estimates of delivered dose relative to expected dose. Deviations of DVH parameters depend on direction of reconstruction uncertainty. The most sensitive organs are rectum and bladder where mean DVH parameter shifts are 5-6% per mm applicator displacement in ant-post direction. For other directions and other DVH parameters, mean shifts are below 4% per mm. By avoiding systematic reconstruction errors, uncertainties on DVH parameters can be kept below 10% in 90% of a patient population. Systematic errors of a few millimetres can lead to significant deviations. Comprehensive quality control of afterloader, applicators and imaging procedures should be applied to prevent systematic errors in applicator reconstruction. Random errors should be minimised by using small slice thickness. With careful reconstruction procedures, reliable DVH parameters for target and OAR's can be obtained.

  16. Image Quality in Oncologic Chest Computerized Tomography With Iterative Reconstruction: A Phantom Study.

    Science.gov (United States)

    Jensen, Kristin; Aaløkken, Trond Mogens; Tingberg, Anders; Fosse, Erik; Martinsen, Anne Catrine T

    2016-01-01

    The purpose of this study was to validate iterative reconstruction technique in oncologic chest computed tomography (CT). An anthropomorphic thorax phantom with 4 simulated tumors was scanned on a 64-slice CT scanner with 2 different iterative reconstruction techniques: one model based (MBIR) and one hybrid (ASiR). Dose levels of 14.9, 11.1, 6.7, and 0.6 mGy were used, and all images were reconstructed with filtered back projection (FBP) and both iterative reconstruction algorithms. Hounsfield units (HU) and absolute noise were measured in the tumors, lung, heart, diaphragm, and muscle. Contrast-to-noise ratios (CNRs) and signal-to-noise ratios (SNRs) were calculated. Model-based iterative reconstruction (MBIR) increased CNRs of the tumors (21.1-192.2) and SNRs in the lung (-49.0-165.6) and heart (3.1-8.5) at all dose levels compared with FBP (CNR, 1.1-23.0; SNR, -7.5-31.6 and 0.2-1.1) and with adaptive statistical iterative reconstruction (CNR, 1.2-33.2; SNR, -7.3-37.7 and 0.2-1.5). At the lowest dose level (0.6 mGy), MBIR reduced the cupping artifact (HU range: 17.0 HU compared with 31.4-32.2). An HU shift in the negative direction was seen with MBIR. Quantitative image quality parameters in oncologic chest CT are improved with MBIR compared with FBP and simpler iterative reconstruction algorithms. Artifacts at low doses are reduced. A shift in HU values was shown; thus, absolute HU values should be used with care.

  17. Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Qiaofeng; Sawatzky, Alex; Anastasio, Mark A., E-mail: anastasio@wustl.edu [Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130 (United States); Yang, Deshan [Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri 63110 (United States); Tan, Jun [Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390 (United States)

    2016-04-15

    Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated

  18. The optimal monochromatic spectral computed tomographic imaging plus adaptive statistical iterative reconstruction algorithm can improve the superior mesenteric vessel image quality.

    Science.gov (United States)

    Yin, Xiao-Ping; Zuo, Zi-Wei; Xu, Ying-Jin; Wang, Jia-Ning; Liu, Huai-Jun; Liang, Guang-Lu; Gao, Bu-Lang

    2017-04-01

    To investigate the effect of the optimal monochromatic spectral computed tomography (CT) plus adaptive statistical iterative reconstruction on the improvement of the image quality of the superior mesenteric artery and vein. The gemstone spectral CT angiographic data of 25 patients were reconstructed in the following three groups: 70KeV, the optimal monochromatic imaging, and the optimal monochromatic plus 40%iterative reconstruction mode. The CT value, image noises (IN), background CT value and noises, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image scores of the vessels and surrounding tissues were analyzed. In the 70KeV, the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group, the mean scores of image quality were 3.86, 4.24 and 4.25 for the superior mesenteric artery and 3.46, 3.78 and 3.81 for the superior mesenteric vein, respectively. The image quality scores for the optimal monochromatic and the optimal monochromatic plus 40% iterative reconstruction groups were significantly greater than for the 70KeV group (Piterative reconstruction group than in the 70KeV group. The optimal monochromatic plus 40% iterative reconstruction group had significantly (Piterative reconstruction using low-contrast agent dosage and low injection rate can significantly improve the image quality of the superior mesenteric artery and vein. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. MO-DE-202-02: Advances in Image Registration and Reconstruction for Image-Guided Neurosurgery

    Energy Technology Data Exchange (ETDEWEB)

    Siewerdsen, J. [Johns Hopkins University (United States)

    2016-06-15

    At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guided neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504

  20. Assessment of the impact of modeling axial compression on PET image reconstruction.

    Science.gov (United States)

    Belzunce, Martin A; Reader, Andrew J

    2017-10-01

    To comprehensively evaluate both the acceleration and image-quality impacts of axial compression and its degree of modeling in fully 3D PET image reconstruction. Despite being used since the very dawn of 3D PET reconstruction, there are still no extensive studies on the impact of axial compression and its degree of modeling during reconstruction on the end-point reconstructed image quality. In this work, an evaluation of the impact of axial compression on the image quality is performed by extensively simulating data with span values from 1 to 121. In addition, two methods for modeling the axial compression in the reconstruction were evaluated. The first method models the axial compression in the system matrix, while the second method uses an unmatched projector/backprojector, where the axial compression is modeled only in the forward projector. The different system matrices were analyzed by computing their singular values and the point response functions for small subregions of the FOV. The two methods were evaluated with simulated and real data for the Biograph mMR scanner. For the simulated data, the axial compression with span values lower than 7 did not show a decrease in the contrast of the reconstructed images. For span 11, the standard sinogram size of the mMR scanner, losses of contrast in the range of 5-10 percentage points were observed when measured for a hot lesion. For higher span values, the spatial resolution was degraded considerably. However, impressively, for all span values of 21 and lower, modeling the axial compression in the system matrix compensated for the spatial resolution degradation and obtained similar contrast values as the span 1 reconstructions. Such approaches have the same processing times as span 1 reconstructions, but they permit significant reduction in storage requirements for the fully 3D sinograms. For higher span values, the system has a large condition number and it is therefore difficult to recover accurately the higher

  1. Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

    Science.gov (United States)

    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 reconstructed using 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.

  2. A novel weighted total difference based image reconstruction algorithm for few-view computed tomography.

    Directory of Open Access Journals (Sweden)

    Wei Yu

    Full Text Available In practical applications of computed tomography (CT imaging, due to the risk of high radiation dose imposed on the patients, it is desired that high quality CT images can be accurately reconstructed from limited projection data. While with limited projections, the images reconstructed often suffer severe artifacts and the edges of the objects are blurred. In recent years, the compressed sensing based reconstruction algorithm has attracted major attention for CT reconstruction from a limited number of projections. In this paper, to eliminate the streak artifacts and preserve the edge structure information of the object, we present a novel iterative reconstruction algorithm based on weighted total difference (WTD minimization, and demonstrate the superior performance of this algorithm. The WTD measure enforces both the sparsity and the directional continuity in the gradient domain, while the conventional total difference (TD measure simply enforces the gradient sparsity horizontally and vertically. To solve our WTD-based few-view CT reconstruction model, we use the soft-threshold filtering approach. Numerical experiments are performed to validate the efficiency and the feasibility of our algorithm. For a typical slice of FORBILD head phantom, using 40 projections in the experiments, our algorithm outperforms the TD-based algorithm with more than 60% gains in terms of the root-mean-square error (RMSE, normalized root mean square distance (NRMSD and normalized mean absolute distance (NMAD measures and with more than 10% gains in terms of the peak signal-to-noise ratio (PSNR measure. While for the experiments of noisy projections, our algorithm outperforms the TD-based algorithm with more than 15% gains in terms of the RMSE, NRMSD and NMAD measures and with more than 4% gains in terms of the PSNR measure. The experimental results indicate that our algorithm achieves better performance in terms of suppressing streak artifacts and preserving the edge

  3. A Web simulation of medical image reconstruction and processing as an educational tool.

    Science.gov (United States)

    Papamichail, Dimitrios; Pantelis, Evaggelos; Papagiannis, Panagiotis; Karaiskos, Pantelis; Georgiou, Evangelos

    2015-02-01

    Web educational resources integrating interactive simulation tools provide students with an in-depth understanding of the medical imaging process. The aim of this work was the development of a purely Web-based, open access, interactive application, as an ancillary learning tool in graduate and postgraduate medical imaging education, including a systematic evaluation of learning effectiveness. The pedagogic content of the educational Web portal was designed to cover the basic concepts of medical imaging reconstruction and processing, through the use of active learning and motivation, including learning simulations that closely resemble actual tomographic imaging systems. The user can implement image reconstruction and processing algorithms under a single user interface and manipulate various factors to understand the impact on image appearance. A questionnaire for pre- and post-training self-assessment was developed and integrated in the online application. The developed Web-based educational application introduces the trainee in the basic concepts of imaging through textual and graphical information and proceeds with a learning-by-doing approach. Trainees are encouraged to participate in a pre- and post-training questionnaire to assess their knowledge gain. An initial feedback from a group of graduate medical students showed that the developed course was considered as effective and well structured. An e-learning application on medical imaging integrating interactive simulation tools was developed and assessed in our institution.

  4. Processing of MRI images weighted in TOF for blood vessels analysis: 3-D reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez D, J.; Cordova F, T. [Universidad de Guanajuato, Campus Leon, Departamento de Ingenieria Fisica, Loma del Bosque No. 103, Lomas del Campestre, 37150 Leon, Guanajuato (Mexico); Cruz A, I., E-mail: hernandezdj.gto@gmail.com [CONACYT, Centro de Investigacion en Matematicas, A. C., Jalisco s/n, Col. Valenciana, 36000 Guanajuato, Gto. (Mexico)

    2015-10-15

    This paper presents a novel presents an approach based on differences of intensities for the identification of vascular structures in medical images from MRI studies of type time of flight method (TOF). The plating method hypothesis gave high intensities belonging to the vascular system image type TOF can be segmented by thresholding of the histogram. The enhanced vascular structures is performed using the filter Vesselness, upon completion of a decision based on fuzzy thresholding minimizes error in the selection of vascular structures. It will give a brief introduction to the vascular system problems and how the images have helped diagnosis, is summarized the physical history of the different imaging modalities and the evolution of digital images with computers. Segmentation and 3-D reconstruction became image type time of flight; these images are typically used in medical diagnosis of cerebrovascular diseases. The proposed method has less error in segmentation and reconstruction of volumes related to the vascular system, clear images and less noise compared with edge detection methods. (Author)

  5. Image-Based Reconstruction and Analysis of Dynamic Scenes in a Landslide Simulation Facility

    Science.gov (United States)

    Scaioni, M.; Crippa, J.; Longoni, L.; Papini, M.; Zanzi, L.

    2017-12-01

    The application of image processing and photogrammetric techniques to dynamic reconstruction of landslide simulations in a scaled-down facility is described. Simulations are also used here for active-learning purpose: students are helped understand how physical processes happen and which kinds of observations may be obtained from a sensor network. In particular, the use of digital images to obtain multi-temporal information is presented. On one side, using a multi-view sensor set up based on four synchronized GoPro 4 Black® cameras, a 4D (3D spatial position and time) reconstruction of the dynamic scene is obtained through the composition of several 3D models obtained from dense image matching. The final textured 4D model allows one to revisit in dynamic and interactive mode a completed experiment at any time. On the other side, a digital image correlation (DIC) technique has been used to track surface point displacements from the image sequence obtained from the camera in front of the simulation facility. While the 4D model may provide a qualitative description and documentation of the experiment running, DIC analysis output quantitative information such as local point displacements and velocities, to be related to physical processes and to other observations. All the hardware and software equipment adopted for the photogrammetric reconstruction has been based on low-cost and open-source solutions.

  6. A Novel Kernel-Based Regularization Technique for PET Image Reconstruction

    Directory of Open Access Journals (Sweden)

    Abdelwahhab Boudjelal

    2017-06-01

    Full Text Available Positron emission tomography (PET is an imaging technique that generates 3D detail of physiological processes at the cellular level. The technique requires a radioactive tracer, which decays and releases a positron that collides with an electron; consequently, annihilation photons are emitted, which can be measured. The purpose of PET is to use the measurement of photons to reconstruct the distribution of radioisotopes in the body. Currently, PET is undergoing a revamp, with advancements in data measurement instruments and the computing methods used to create the images. These computer methods are required to solve the inverse problem of “image reconstruction from projection”. This paper proposes a novel kernel-based regularization technique for maximum-likelihood expectation-maximization ( κ -MLEM to reconstruct the image. Compared to standard MLEM, the proposed algorithm is more robust and is more effective in removing background noise, whilst preserving the edges; this suppresses image artifacts, such as out-of-focus slice blur.

  7. Deterministic Compressive Sampling for High-Quality Image Reconstruction of Ultrasound Tomography

    CERN Document Server

    Quang-Huy, Tran; Tue, Huynh Huu; Linh-Trung, Nguyen

    2015-01-01

    A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared to the current gold-standard X-ray mammography. Based on inverse scattering technique, ultrasound tomography uses some material properties such as sound contrast or attenuation to detect small targets. The Distorted Born Iterative Method (DBIM) based on first-order Born approximation is an efficient diffraction tomography approach. Compressed Sensing (CS) technique was applied to the detection geometry configuration of ultrasound tomography as a powerful tool for improved image reconstruction quality. However, this configuration is very difficult to implement in practice. Inspired of easier hardware implementation of deterministic CS, in this paper, we propose the chaos measurements in the detection geometry configuration and the image reconstruction process is implemen...

  8. Computed Tomographic Image Analysis Based on FEM Performance Comparison of Segmentation on Knee Joint Reconstruction

    Directory of Open Access Journals (Sweden)

    Seong-Wook Jang

    2014-01-01

    Full Text Available The demand for an accurate and accessible image segmentation to generate 3D models from CT scan data has been increasing as such models are required in many areas of orthopedics. In this paper, to find the optimal image segmentation to create a 3D model of the knee CT data, we compared and validated segmentation algorithms based on both objective comparisons and finite element (FE analysis. For comparison purposes, we used 1 model reconstructed in accordance with the instructions of a clinical professional and 3 models reconstructed using image processing algorithms (Sobel operator, Laplacian of Gaussian operator, and Canny edge detection. Comparison was performed by inspecting intermodel morphological deviations with the iterative closest point (ICP algorithm, and FE analysis was performed to examine the effects of the segmentation algorithm on the results of the knee joint movement analysis.

  9. Multiscale vision model for event detection and reconstruction in two-photon imaging data

    DEFF Research Database (Denmark)

    Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke

    2014-01-01

    on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities.......Reliable detection of calcium waves in multiphoton imaging data is challenging because of the low signal-to-noise ratio and because of the unpredictability of the time and location of these spontaneous events. This paper describes our approach to calcium wave detection and reconstruction based...

  10. DIEP Flap Breast Reconstruction Using 3-dimensional Surface Imaging and a Printed Mold

    Directory of Open Access Journals (Sweden)

    Koichi Tomita, MD, PhD

    2015-03-01

    Full Text Available Summary: Recent advances in 3-dimensional (3D surface imaging technologies allow for digital quantification of complex breast tissue. We performed 11 unilateral breast reconstructions with deep inferior epigastric artery perforator (DIEP flaps (5 immediate, 6 delayed using 3D surface imaging for easier surgery planning and 3D-printed molds for shaping the breast neoparenchyma. A single- or double-pedicle flap was preoperatively planned according to the estimated tissue volume required and estimated total flap volume. The DIEP flap was then intraoperatively shaped with a 3D-printed mold that was based on a horizontally inverted shape of the contralateral breast. Cosmetic outcomes were assessed as satisfactory, as confirmed by the postoperative 3D measurements of bilateral breasts. We believe that DIEP flap reconstruction assisted with 3D surface imaging and a 3D-printed mold is a simple and quick method for rebuilding a symmetric breast.

  11. Accelerating image reconstruction in dual-head PET system by GPU and symmetry properties.

    Directory of Open Access Journals (Sweden)

    Cheng-Ying Chou

    Full Text Available Positron emission tomography (PET is an important imaging modality in both clinical usage and research studies. We have developed a compact high-sensitivity PET system that consisted of two large-area panel PET detector heads, which produce more than 224 million lines of response and thus request dramatic computational demands. In this work, we employed a state-of-the-art graphics processing unit (GPU, NVIDIA Tesla C2070, to yield an efficient reconstruction process. Our approaches ingeniously integrate the distinguished features of the symmetry properties of the imaging system and GPU architectures, including block/warp/thread assignments and effective memory usage, to accelerate the computations for ordered subset expectation maximization (OSEM image reconstruction. The OSEM reconstruction algorithms were implemented employing both CPU-based and GPU-based codes, and their computational performance was quantitatively analyzed and compared. The results showed that the GPU-accelerated scheme can drastically reduce the reconstruction time and thus can largely expand the applicability of the dual-head PET system.

  12. Reconstruction of Cochlea Based on Micro-CT and Histological Images of the Human Inner Ear

    Directory of Open Access Journals (Sweden)

    Christos Bellos

    2014-01-01

    Full Text Available The study of the normal function and pathology of the inner ear has unique difficulties as it is inaccessible during life and, so, conventional techniques of pathologic studies such as biopsy and surgical excision are not feasible, without further impairing function. Mathematical modelling is therefore particularly attractive as a tool in researching the cochlea and its pathology. The first step towards efficient mathematical modelling is the reconstruction of an accurate three dimensional (3D model of the cochlea that will be presented in this paper. The high quality of the histological images is being exploited in order to extract several sections of the cochlea that are not visible on the micro-CT (mCT images (i.e., scala media, spiral ligament, and organ of Corti as well as other important sections (i.e., basilar membrane, Reissner membrane, scala vestibule, and scala tympani. The reconstructed model is being projected in the centerline of the coiled cochlea, extracted from mCT images, and represented in the 3D space. The reconstruction activities are part of the SIFEM project, which will result in the delivery of an infrastructure, semantically interlinking various tools and libraries (i.e., segmentation, reconstruction, and visualization tools with the clinical knowledge, which is represented by existing data, towards the delivery of a robust multiscale model of the inner ear.

  13. Enhanced imaging colonoscopy facilitates dense motion-based 3D reconstruction.

    Science.gov (United States)

    Alcantarilla, Pablo F; Bartoli, Adrien; Chadebecq, Francois; Tilmant, Christophe; Lepilliez, Vincent

    2013-01-01

    We propose a novel approach for estimating a dense 3D model of neoplasia in colonoscopy using enhanced imaging endoscopy modalities. Estimating a dense 3D model of neoplasia is important to make 3D measurements and to classify the superficial lesions in standard frameworks such as the Paris classification. However, it is challenging to obtain decent dense 3D models using computer vision techniques such as Structure-from-Motion due to the lack of texture in conventional (white light) colonoscopy. Therefore, we propose to use enhanced imaging endoscopy modalities such as Narrow Band Imaging and chromoendoscopy to facilitate the 3D reconstruction process. Thanks to the use of these enhanced endoscopy techniques, visualization is improved, resulting in more reliable feature tracks and 3D reconstruction results. We first build a sparse 3D model of neoplasia using Structure-from-Motion from enhanced endoscopy imagery. Then, the sparse reconstruction is densified using a Multi-View Stereo approach, and finally the dense 3D point cloud is transformed into a mesh by means of Poisson surface reconstruction. The obtained dense 3D models facilitate classification of neoplasia in the Paris classification, in which the 3D size and the shape of the neoplasia play a major role in the diagnosis.

  14. Comparison of mammographic image quality in various methods of reconstructive breast surgery

    Energy Technology Data Exchange (ETDEWEB)

    Lindbichler, F. [University Hospital, Graz (Austria). Dept. of Radiology; Hoflehner, H. [University Hospital, Graz (Austria). Dept. of Plastic and Reconstructive Surgery; Schmidt, F. [University Hospital, Graz (Austria). Dept. of Radiology; Pierer, G.R. [University Hospital, Graz (Austria). Dept. of Plastic and Reconstructive Surgery; Raith, J. [University Hospital, Graz (Austria). Dept. of Radiology; Umschaden, J. [University Hospital, Graz (Austria). Dept. of Plastic and Reconstructive Surgery; Preidler, K.W. [University Hospital, Graz (Austria). Dept. of Radiology

    1996-12-01

    The purpose of our study was to evaluate mammographic image quality of various methods of reconstructive breast surgery with specific reference to the possibility of diagnosis of recurrent tumors. A total of 39 patients who underwent breast reconstruction following modified radical mastectomy were subject to clinical and mammographic examination. Three groups were formed: (a) autonomous tissue reconstruction (TRAM-flap; n=9), (b) submuscular silicon gel prostheses (n=21), and (c) supramuscular silicon gel prostheses (n=9). Mammographic images quality of the groups was compared by two radiologists working together using a point system where five specific criteria were valued and scored. The result was tabulated into three quality levels: good, acceptable, and limited. Mammograms were assessed as good, acceptable, or limited, respectively, as follows: group I: 7 (77.8%), 1 (11.1%), 1 (11.1%); group II; 4 (19%), 11 (52.4%), 6 (28.6%); group III: 3 (33.3%), 4 (44.5%), 2 (22.2%). The TRAM-flap method of reconstruction displays a high degree of mammographic image quality and therefore is preferable with respect to early diagnosis of recurrent tumors. (orig.)

  15. Comparison of mammographic image quality in various methods of reconstructive breast surgery.

    Science.gov (United States)

    Lindbichler, F; Hoflehner, H; Schmidt, F; Pierer, G R; Raith, J; Umschaden, J; Preidler, K W

    1996-01-01

    The purpose of our study was to evaluate mammographic image quality of various methods of reconstructive breast surgery with specific reference to the possibility of diagnosis of recurrent tumors. A total of 39 patients who underwent breast reconstruction following modified radical mastectomy were subject to clinical and mammographic examination. Three groups were formed: (a) autonomous tissue reconstruction (TRAM-flap; n = 9), (b) submuscular silicon gel prostheses (n = 21), and (c) supramuscular silicon gel prostheses (n = 9). Mammographic image quality of the groups was compared by two radiologists working together using a point system where five specific criteria were valued and scored. The result was tabulated into three quality levels: good, acceptable, and limited. Mammograms were assessed as good, acceptable, or limited, respectively, as follows: group I: 7 (77.8%), 1 (11.1%), 1 (11.1%); group II: 4 (19%), 11 (52.4%), 6 (28.6%); group III: 3 (33.3%), 4 (44.5%), 2 (22.2%). The TRAM-flap method of reconstruction displays a high degree of mammographic image quality and therefore is preferable with respect to early diagnosis of recurrent tumors.

  16. Effect of hybrid iterative reconstruction technique on quantitative and qualitative image analysis at 256-slice prospective gating cardiac CT.

    Science.gov (United States)

    Utsunomiya, Daisuke; Weigold, Wm Guy; Weissman, Gaby; Taylor, Allen J

    2012-06-01

    To evaluate the effect of hybrid iterative reconstruction on qualitative and quantitative parameters at 256-slice cardiac CT. Prospective cardiac CT images from 20 patients were analysed. Paired image sets were created using 3 reconstructions, i.e. filtered back projection (FBP) and moderate- and high-level iterative reconstructions. Quantitative parameters including CT-attenuation, noise, and contrast-to-noise ratio (CNR) were determined in both proximal- and distal coronary segments. Image quality was graded on a 4-point scale. Coronary CT attenuation values were similar for FBP, moderate- and high-level iterative reconstruction at 293 ± 74-, 290 ± 75-, and 283 ± 78 Hounsfield units (HU), respectively. CNR was significantly higher with moderate- and high-level iterative reconstructions (10.9 ± 3.5 and 18.4 ± 6.2, respectively) than FBP (8.2 ± 2.5) as was the visual grading of proximal vessels. Visualisation of distal vessels was better with high-level iterative reconstruction than FBP. The mean number of assessable segments among 289 segments was 245, 260, and 267 for FBP, moderate- and high-level iterative reconstruction, respectively; the difference between FBP and high-level iterative reconstruction was significant. Interobserver agreement was significantly higher for moderate- and high-level iterative reconstruction than FBP. Cardiac CT using hybrid iterative reconstruction yields higher CNR and better image quality than FBP. • Cardiac CT helps clinicians to assess patients with coronary artery disease • Hybrid iterative reconstruction provides improved cardiac CT image quality • Hybrid iterative reconstruction improves the number of assessable coronary segments • Hybrid iterative reconstruction improves interobserver agreement on cardiac CT.

  17. New Image Reconstruction Methods for Accelerated Quantitative Parameter Mapping and Magnetic Resonance Angiography

    Science.gov (United States)

    Velikina, J. V.; Samsonov, A. A.

    2016-02-01

    Advanced MRI techniques often require sampling in additional (non-spatial) dimensions such as time or parametric dimensions, which significantly elongate scan time. Our purpose was to develop novel iterative image reconstruction methods to reduce amount of acquired data in such applications using prior knowledge about signal in the extra dimensions. The efforts have been made to accelerate two applications, namely, time resolved contrast enhanced MR angiography and T1 mapping. Our result demonstrate that significant acceleration (up to 27x times) may be achieved using our proposed iterative reconstruction techniques.

  18. Reconstructed imaging of acoustic cloak using time-lapse reversal method

    Science.gov (United States)

    Zhou, Chen; Cheng, Ying; Xu, Jian-yi; Li, Bo; Liu, Xiao-jun

    2014-08-01

    We proposed and investigated a solution to the inverse acoustic cloak problem, an anti-stealth technology to make cloaks visible, using the time-lapse reversal (TLR) method. The TLR method reconstructs the image of an unknown acoustic cloak by utilizing scattered acoustic waves. Compared to previous anti-stealth methods, the TLR method can determine not only the existence of a cloak but also its exact geometric information like definite shape, size, and position. Here, we present the process for TLR reconstruction based on time reversal invariance. This technology may have potential applications in detecting various types of cloaks with different geometric parameters.

  19. Rapid reconstruction of 3D neuronal morphology from light microscopy images with augmented rayburst sampling.

    Directory of Open Access Journals (Sweden)

    Xing Ming

    Full Text Available Digital reconstruction of three-dimensional (3D neuronal morphology from light microscopy images provides a powerful technique for analysis of neural circuits. It is time-consuming to manually perform this process. Thus, efficient computer-assisted approaches are preferable. In this paper, we present an innovative method for the tracing and reconstruction of 3D neuronal morphology from light microscopy images. The method uses a prediction and refinement strategy that is based on exploration of local neuron structural features. We extended the rayburst sampling algorithm to a marching fashion, which starts from a single or a few seed points and marches recursively forward along neurite branches to trace and reconstruct the whole tree-like structure. A local radius-related but size-independent hemispherical sampling was used to predict the neurite centerline and detect branches. Iterative rayburst sampling was performed in the orthogonal plane, to refine the centerline location and to estimate the local radius. We implemented the method in a cooperative 3D interactive visualization-assisted system named flNeuronTool. The source code in C++ and the binaries are freely available at http://sourceforge.net/projects/flneurontool/. We validated and evaluated the proposed method using synthetic data and real datasets from the Digital Reconstruction of Axonal and Dendritic Morphology (DIADEM challenge. Then, flNeuronTool was applied to mouse brain images acquired with the Micro-Optical Sectioning Tomography (MOST system, to reconstruct single neurons and local neural circuits. The results showed that the system achieves a reasonable balance between fast speed and acceptable accuracy, which is promising for interactive applications in neuronal image analysis.

  20. Preoperative implant selection for unilateral breast reconstruction using 3D imaging with the Microsoft Kinect sensor.

    Science.gov (United States)

    Pöhlmann, Stefanie T L; Harkness, Elaine; Taylor, Christopher J; Gandhi, Ashu; Astley, Susan M

    2017-08-01

    This study aimed to investigate whether breast volume measured preoperatively using a Kinect 3D sensor could be used to determine the most appropriate implant size for reconstruction. Ten patients underwent 3D imaging before and after unilateral implant-based reconstruction. Imaging used seven configurations, varying patient pose and Kinect location, which were compared regarding suitability for volume measurement. Four methods of defining the breast boundary for automated volume calculation were compared, and repeatability assessed over five repetitions. The most repeatable breast boundary annotation used an ellipse to track the inframammary fold and a plane describing the chest wall (coefficient of repeatability: 70 ml). The most reproducible imaging position comparing pre- and postoperative volume measurement of the healthy breast was achieved for the sitting patient with elevated arms and Kinect centrally positioned (coefficient of repeatability: 141 ml). Optimal implant volume was calculated by correcting used implant volume by the observed postoperative asymmetry. It was possible to predict implant size using a linear model derived from preoperative volume measurement of the healthy breast (coefficient of determination R(2) = 0.78, standard error of prediction 120 ml). Mastectomy specimen weight and experienced surgeons' choice showed similar predictive ability (both: R(2) = 0.74, standard error: 141/142 ml). A leave one-out validation showed that in 61% of cases, 3D imaging could predict implant volume to within 10%; however for 17% of cases it was >30%. This technology has the potential to facilitate reconstruction surgery planning and implant procurement to maximise symmetry after unilateral reconstruction. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  1. Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method.

    Directory of Open Access Journals (Sweden)

    Xingjian Yu

    Full Text Available In this paper, a total variation (TV minimization strategy is proposed to overcome the problem of sparse spatial resolution and large amounts of noise in low dose positron emission tomography (PET imaging reconstruction. Two types of objective function were established based on two statistical models of measured PET data, least-square (LS TV for the Gaussian distribution and Poisson-TV for the Poisson distribution. To efficiently obtain high quality reconstructed images, the alternating direction method (ADM is used to solve these objective functions. As compared with the iterative shrinkage/thresholding (IST based algorithms, the proposed ADM can make full use of the TV constraint and its convergence rate is faster. The performance of the proposed approach is validated through comparisons with the expectation-maximization (EM method using synthetic and experimental biological data. In the comparisons, the results of both LS-TV and Poisson-TV are taken into consideration to find which models are more suitable for PET imaging, in particular low-dose PET. To evaluate the results quantitatively, we computed bias, variance, and the contrast recovery coefficient (CRC and drew profiles of the reconstructed images produced by the different methods. The results show that both Poisson-TV and LS-TV can provide a high visual quality at a low dose level. The bias and variance of the proposed LS-TV and Poisson-TV methods are 20% to 74% less at all counting levels than those of the EM method. Poisson-TV gives the best performance in terms of high-accuracy reconstruction with the lowest bias and variance as compared to the ground truth (14.3% less bias and 21.9% less variance. In contrast, LS-TV gives the best performance in terms of the high contrast of the reconstruction with the highest CRC.

  2. Improving three-dimensional reconstruction of buildings from web-harvested images using forensic clues

    Science.gov (United States)

    Milani, Simone; Tronca, Enrico

    2017-01-01

    During the past years, research has focused on the reconstruction of three-dimensional point cloud models from unordered and uncalibrated sets of images. Most of the proposed solutions rely on the structure-from-motion algorithm, and their performances significantly degrade whenever exchangeable image file format information about focal lengths is missing or corrupted. We propose a preprocessing strategy that permits estimating the focal lengths of a camera more accurately. The basic idea is to cluster the input images into separate subsets according to an array of interpolation-related multimedia forensic clues. This operation permits having a more robust estimate and improving the accuracy of the final model.

  3. Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image

    Directory of Open Access Journals (Sweden)

    YiNan Zhang

    2017-01-01

    Full Text Available Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template layer and two convolutional layers. The bicubic interpolation template layer is prefixed by mathematics deduction, and two convolutional layers learn from training samples. For saving training medical images, a SIFT feature-based transfer learning method is proposed. Not only can medical images be used to train the proposed method, but also other types of images can be added into training dataset selectively. In empirical experiments, results of eight distinctive medical images show improvement of image quality and time reduction. Further, the proposed method also produces slightly sharper edges than other deep learning approaches in less time and it is projected that the hybrid architecture of prefixed template layer and unfixed hidden layers has potentials in other applications.

  4. Thermoacoustic image reconstruction based on layered tissue model

    Science.gov (United States)

    Bayıntır, Hazel; Elmas, Demet; Idemen, Mithat; Uzun, Banu; Karaman, Mustafa

    2017-03-01

    We derived analytical forward and inverse solution of thermoacoustic wave equation for inhomogeneous multi- layered planar and cylindrical mediums with the source distribution existing in all layers. These solutions are applicable for imaging of organs such as breast and brain, whose structures are suitable for multi-layer modelling. For qualitative testing and comparison of the point-spread-functions associated with the homogeneous and layered solutions, we performed numerical simulations. Our simulation results show that the conventional inverse solution based on homogeneous medium assumption, as expected, produces incorrect locations of point sources and significantly increased side lobes, whereas our inverse solution involving the multi-layered medium produces point sources at the correct locations with lower side lobes.

  5. Four-dimensional dose reconstruction through in vivo phase matching of cine images of electronic portal imaging device.

    Science.gov (United States)

    Yoon, Jihyung; Jung, Jae Won; Kim, Jong Oh; Yi, Byong Yong; Yeo, Inhwan

    2016-07-01

    A method is proposed to reconstruct a four-dimensional (4D) dose distribution using phase matching of measured cine images to precalculated images of electronic portal imaging device (EPID). (1) A phantom, designed to simulate a tumor in lung (a polystyrene block with a 3 cm diameter embedded in cork), was placed on a sinusoidally moving platform with an amplitude of 1 cm and a period of 4 s. Ten-phase 4D computed tomography (CT) images of the phantom were acquired. A planning target volume (PTV) was created by adding a margin of 1 cm around the internal target volume of the tumor. (2) Three beams were designed, which included a static beam, a theoretical dynamic beam, and a planning-optimized dynamic beam (PODB). While the theoretical beam was made by manually programming a simplistic sliding leaf motion, the planning-optimized beam was obtained from treatment planning. From the three beams, three-dimensional (3D) doses on the phantom were calculated; 4D dose was calculated by means of the ten phase images (integrated over phases afterward); serving as "reference" images, phase-specific EPID dose images under the lung phantom were also calculated for each of the ten phases. (3) Cine EPID images were acquired while the beams were irradiated to the moving phantom. (4) Each cine image was phase-matched to a phase-specific CT image at which common irradiation occurred by intercomparing the cine image with the reference images. (5) Each cine image was used to reconstruct dose in the phase-matched CT image, and the reconstructed doses were summed over all phases. (6) The summation was compared with forwardly calculated 4D and 3D dose distributions. Accounting for realistic situations, intratreatment breathing irregularity was simulated by assuming an amplitude of 0.5 cm for the phantom during a portion of breathing trace in which the phase matching could not be performed. Intertreatment breathing irregularity between the time of treatment and the time of planning CT was

  6. System calibration and image reconstruction for a new small-animal SPECT system

    Science.gov (United States)

    Chen, Yi-Chun

    A novel small-animal SPECT imager, FastSPECT II, was recently developed at the Center for Gamma-Ray Imaging. FastSPECT II consists of two rings of eight modular scintillation cameras and list-mode data-acquisition electronics that enable stationary and dynamic imaging studies. The instrument is equipped with exchangeable aperture assemblies and adjustable camera positions for selections of magnifications, pinhole sizes, and fields of view (FOVs). The purpose of SPECT imaging is to recover the radiotracer distribution in the object from the measured image data. Accurate knowledge of the imaging system matrix (referred to as H) is essential for image reconstruction. To assure that all of the system physics is contained in the matrix, experimental calibration methods for the individual cameras and the whole imaging system were developed and carefully performed. The average spatial resolution over the FOV of FastSPECT II in its low-magnification (2.4X) configuration is around 2.4 mm, computed from the Fourier crosstalk matrix. The system sensitivity measured with a 99mTc point source at the center of the FOV is about 267 cps/MBq. The system detectability was evaluated by computing the ideal-observer performance on SKE/BKE (signal-known-exactly/background-known-exactly) detection tasks. To reduce the system-calibration time and achieve finer reconstruction grids, two schemes for interpolating H were implemented and compared: these are centroid interpolation with Gaussian fitting and Fourier interpolation. Reconstructed phantom and mouse-cardiac images demonstrated the effectiveness of the H-matrix interpolation. Tomographic reconstruction can be formulated as a linear inverse problem and solved using statistical-estimation techniques. Several iterative reconstruction algorithms were introduced, including maximum-likelihood expectation-maximization (ML-EM) and its ordered-subsets (OS) version, and some least-squares (LS) and weighted-least-squares (WLS) algorithms such

  7. A pseudo-discrete algebraic reconstruction technique (PDART) prior image-based suppression of high density artifacts in computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    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.

  8. High fidelity system modeling for high quality image reconstruction in clinical CT.

    Directory of Open Access Journals (Sweden)

    Synho Do

    Full Text Available Today, while many researchers focus on the improvement of the regularization term in IR algorithms, they pay less concern to the improvement of the fidelity term. In this paper, we hypothesize that improving the fidelity term will further improve IR image quality in low-dose scanning, which typically causes more noise. The purpose of this paper is to systematically test and examine the role of high-fidelity system models using raw data in the performance of iterative image reconstruction approach minimizing energy functional. We first isolated the fidelity term and analyzed the importance of using focal spot area modeling, flying focal spot location modeling, and active detector area modeling as opposed to just flying focal spot motion. We then compared images using different permutations of all three factors. Next, we tested the ability of the fidelity terms to retain signals upon application of the regularization term with all three factors. We then compared the differences between images generated by the proposed method and Filtered-Back-Projection. Lastly, we compared images of low-dose in vivo data using Filtered-Back-Projection, Iterative Reconstruction in Image Space, and the proposed method using raw data. The initial comparison of difference maps of images constructed showed that the focal spot area model and the active detector area model also have significant impacts on the quality of images produced. Upon application of the regularization term, images generated using all three factors were able to substantially decrease model mismatch error, artifacts, and noise. When the images generated by the proposed method were tested, conspicuity greatly increased, noise standard deviation decreased by 90% in homogeneous regions, and resolution also greatly improved. In conclusion, the improvement of the fidelity term to model clinical scanners is essential to generating higher quality images in low-dose imaging.

  9. Image quality of ct angiography using model-based iterative reconstruction in infants with congenital heart disease: Comparison with filtered back projection and hybrid iterative reconstruction.

    Science.gov (United States)

    Jia, Qianjun; Zhuang, Jian; Jiang, Jun; Li, Jiahua; Huang, Meiping; Liang, Changhong

    2017-01-01

    To compare the image quality, rate of coronary artery visualization and diagnostic accuracy of 256-slice multi-detector computed tomography angiography (CTA) with prospective electrocardiographic (ECG) triggering at a tube voltage of 80kVp between 3 reconstruction algorithms (filtered back projection (FBP), hybrid iterative reconstruction (iDose(4)) and iterative model reconstruction (IMR)) in infants with congenital heart disease (CHD). Fifty-one infants with CHD who underwent cardiac CTA in our institution between December 2014 and March 2015 were included. The effective radiation doses were calculated. Imaging data were reconstructed using the FBP, iDose(4) and IMR algorithms. Parameters of objective image quality (noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR)); subjective image quality (overall image quality, image noise and margin sharpness); coronary artery visibility; and diagnostic accuracy for the three algorithms were measured and compared. The mean effective radiation dose was 0.61±0.32 mSv. Compared to FBP and iDose(4), IMR yielded significantly lower noise (Preconstruction algorithm provided significantly increased objective and subjective image quality compared with the FBP and iDose(4) algorithms. However, IMR did not improve the diagnostic accuracy or coronary artery visualization compared with iDose(4). Copyright © 2016. Published by Elsevier Ireland Ltd.

  10. Comparison of the image qualities of filtered back-projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction for CT venography at 80 kVp.

    Science.gov (United States)

    Kim, Jin Hyeok; Choo, Ki Seok; Moon, Tae Yong; Lee, Jun Woo; Jeon, Ung Bae; Kim, Tae Un; Hwang, Jae Yeon; Yun, Myeong-Ja; Jeong, Dong Wook; Lim, Soo Jin

    2016-07-01

    To evaluate the subjective and objective qualities of computed tomography (CT) venography images at 80 kVp using model-based iterative reconstruction (MBIR) and to compare these with those of filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) using the same CT data sets. Forty-four patients (mean age: 56.1 ± 18.1) who underwent 80 kVp CT venography (CTV) for the evaluation of deep vein thrombosis (DVT) during 4 months were enrolled in this retrospective study. The same raw data were reconstructed using FBP, ASIR, and MBIR. Objective and subjective image analysis were performed at the inferior vena cava (IVC), femoral vein, and popliteal vein. The mean CNR of MBIR was significantly greater than those of FBP and ASIR and images reconstructed using MBIR had significantly lower objective image noise (p ASIR (p ASIR regarding subjective and objective image qualities. • MBIR provides superior image quality compared with FBP and ASIR • CTV at 80kVp with MBIR improves diagnostic confidence in diagnosing DVT • CTV at 80kVp with MBIR presents better image quality with low radiation.

  11. Iterative image reconstruction for sparse-view CT using normal-dose image induced total variation prior.

    Directory of Open Access Journals (Sweden)

    Jing Huang

    Full Text Available X-ray computed tomography (CT iterative image reconstruction from sparse-view projection data has been an important research topic for radiation reduction in clinic. In this paper, to relieve the requirement of misalignment reduction operation of the prior image constrained compressed sensing (PICCS approach introduced by Chen et al, we present an iterative image reconstruction approach for sparse-view CT using a normal-dose image induced total variation (ndiTV prior. The associative objective function of the present approach is constructed under the penalized weighed least-square (PWLS criteria, which contains two terms, i.e., the weighted least-square (WLS fidelity and the ndiTV prior, and is referred to as "PWLS-ndiTV". Specifically, the WLS fidelity term is built based on an accurate relationship between the variance and mean of projection data in the presence of electronic background noise. The ndiTV prior term is designed to reduce the influence of the misalignment between the desired- and prior- image by using a normal-dose image induced non-local means (ndiNLM filter. Subsequently, a modified steepest descent algorithm is adopted to minimize the associative objective function. Experimental results on two different digital phantoms and an anthropomorphic torso phantom show that the present PWLS-ndiTV approach for sparse-view CT image reconstruction can achieve noticeable gains over the existing similar approaches in terms of noise reduction, resolution-noise tradeoff, and low-contrast object detection.

  12. ANALYSIS OF MOBILE LASER SCANNING DATA AND MULTI-VIEW IMAGE RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    C. Briese

    2012-07-01

    Full Text Available The combination of laser scanning (LS, active, direct 3D measurement of the object surface and photogrammetry (high geometric and radiometric resolution is widely applied for object reconstruction (e.g. architecture, topography, monitoring, archaeology. Usually the results are a coloured point cloud or a textured mesh. The geometry is typically generated from the laser scanning point cloud and the radiometric information is the result of image acquisition. In the last years, next to significant developments in static (terrestrial LS and kinematic LS (airborne and mobile LS hardware and software, research in computer vision and photogrammetry lead to advanced automated procedures in image orientation and image matching. These methods allow a highly automated generation of 3D geometry just based on image data. Founded on advanced feature detector techniques (like SIFT (Scale Invariant Feature Transform very robust techniques for image orientation were established (cf. Bundler. In a subsequent step, dense multi-view stereo reconstruction algorithms allow the generation of very dense 3D point clouds that represent the scene geometry (cf. Patch-based Multi-View Stereo (PMVS2. Within this paper the usage of mobile laser scanning (MLS and simultaneously acquired image data for an advanced integrated scene reconstruction is studied. For the analysis the geometry of a scene is generated by both techniques independently. Then, the paper focuses on the quality assessment of both techniques. This includes a quality analysis of the individual surface models and a comparison of the direct georeferencing of the images using positional and orientation data of the on board GNSS-INS system and the indirect georeferencing of the imagery by automatic image orientation. For the practical evaluation a dataset from an archaeological monument is utilised. Based on the gained knowledge a discussion of the results is provided and a future strategy for the integration of

  13. TV-constrained incremental algorithms for low-intensity CT image reconstruction

    DEFF Research Database (Denmark)

    Rose, Sean D.; Andersen, Martin S.; Sidky, Emil Y.

    2015-01-01

    Low-dose X-ray computed tomography (CT) has garnered much recent interest as it provides a method to lower patient dose and simultaneously reduce scan time. In non-medical applications the possibility of preventing sample damage makes low-dose CT desirable. Reconstruction in low-dose CT poses...... a significant challenge due to the high level of noise in the data. Here we propose an iterative method for reconstruction which minimizes the transmission Poisson likelihood subject to a total-variation constraint. This formulation accommodates efficient methods of parameter selection because the choice of TV...... constraint can be guided by an image reconstructed by filtered backprojection (FBP). We apply our algorithm to low-dose synchrotron X-ray CT data from the Advanced Photon Source (APS) at Argonne National Labs (ANL) to demonstrate its potential utility. We find that the algorithm provides a means of edge...

  14. MR imaging appearances of soft tissue flaps following reconstructive surgery of the lower extremity

    Energy Technology Data Exchange (ETDEWEB)

    Magerkurth, Olaf [Dept. of Radiology, Hospital Baden, Baden (Switzerland); Girish, Gandikota; Jacobson, Jon A.; Kim, Sung Moon; Brigido, Monica; Dong, Qian; Jamadar, David A. [Dept. of Radiology, University of Michigan Hospitals, Ann Arbor (United States)

    2015-02-15

    MR imaging appearances of different types of reconstructive muscle flaps following reconstructive surgery of the lower extremity with associated post-surgical changes due to altered anatomy, radiation, and potential complications, can be challenging. A multidisciplinary therapeutic approach to tumors allows for limb salvage therapy in a majority of the patients. Decision-making for specific types of soft tissue reconstruction is based on the body region affected, as well as the size and complexity of the defect. Hematomas and infections are early complications that can jeopardize flap viability. The local recurrence of a tumor within six months after a complete resection with confirmed tumor-free margins and adjuvant radiation therapy is rare. Identification of a new lesion similar to the initial tumor favors a finding of tumor recurrence.

  15. Image super-resolution reconstruction based on regularization technique and guided filter

    Science.gov (United States)

    Huang, De-tian; Huang, Wei-qin; Gu, Pei-ting; Liu, Pei-zhong; Luo, Yan-min

    2017-06-01

    In order to improve the accuracy of sparse representation coefficients and the quality of reconstructed images, an improved image super-resolution algorithm based on sparse representation is presented. In the sparse coding stage, the autoregressive (AR) regularization and the non-local (NL) similarity regularization are introduced to improve the sparse coding objective function. A group of AR models which describe the image local structures are pre-learned from the training samples, and one or several suitable AR models can be adaptively selected for each image patch to regularize the solution space. Then, the image non-local redundancy is obtained by the NL similarity regularization to preserve edges. In the process of computing the sparse representation coefficients, the feature-sign search algorithm is utilized instead of the conventional orthogonal matching pursuit algorithm to improve the accuracy of the sparse coefficients. To restore image details further, a global error compensation model based on weighted guided filter is proposed to realize error compensation for the reconstructed images. Experimental results demonstrate that compared with Bicubic, L1SR, SISR, GR, ANR, NE + LS, NE + NNLS, NE + LLE and A + (16 atoms) methods, the proposed approach has remarkable improvement in peak signal-to-noise ratio, structural similarity and subjective visual perception.

  16. Imaging and reconstruction of cell cortex structures near the cell surface

    Science.gov (United States)

    Jin, Luhong; Zhou, Xiaoxu; Xiu, Peng; Luo, Wei; Huang, Yujia; Yu, Feng; Kuang, Cuifang; Sun, Yonghong; Liu, Xu; Xu, Yingke

    2017-11-01

    Total internal reflection fluorescence microscopy (TIRFM) provides high optical sectioning capability and superb signal-to-noise ratio for imaging of cell cortex structures. The development of multi-angle (MA)-TIRFM permits high axial resolution imaging and reconstruction of cellular structures near the cell surface. Cytoskeleton is composed of a network of filaments, which are important for maintenance of cell function. The high-resolution imaging and quantitative analysis of filament organization would contribute to our understanding of cytoskeleton regulation in cell. Here, we used a custom-developed MA-TIRFM setup, together with stochastic photobleaching and single molecule localization method, to enhance the lateral resolution of TIRFM imaging to about 100 nm. In addition, we proposed novel methods to perform filament segmentation and 3D reconstruction from MA-TIRFM images. Furthermore, we applied these methods to study the 3D localization of cortical actin and microtubule structures in U373 cancer cells. Our results showed that cortical actins localize ∼ 27 nm closer to the plasma membrane when compared with microtubules. We found that treatment of cells with chemotherapy drugs nocodazole and cytochalasin B disassembles cytoskeletal network and induces the reorganization of filaments towards the cell periphery. In summary, this study provides feasible approaches for 3D imaging and analyzing cell surface distribution of cytoskeletal network. Our established microscopy platform and image analysis toolkits would facilitate the study of cytoskeletal network in cells.

  17. 3D PET image reconstruction based on Maximum Likelihood Estimation Method (MLEM) algorithm

    CERN Document Server

    Słomski, Artur; Bednarski, Tomasz; Białas, Piotr; Czerwiński, Eryk; Kapłon, Łukasz; Kochanowski, Andrzej; Korcyl, Grzegorz; Kowal, Jakub; Kowalski, Paweł; Kozik, Tomasz; Krzemień, Wojciech; Molenda, Marcin; Moskal, Paweł; Niedźwiecki, Szymon; Pałka, Marek; Pawlik, Monika; Raczyński, Lech; Salabura, Piotr; Gupta-Sharma, Neha; Silarski, Michał; Smyrski, Jerzy; Strzelecki, Adam; Wiślicki, Wojciech; Zieliński, Marcin; Zoń, Natalia

    2015-01-01

    Positron emission tomographs (PET) do not measure an image directly. Instead, they measure at the boundary of the field-of-view (FOV) of PET tomograph a sinogram that consists of measurements of the sums of all the counts along the lines connecting two detectors. As there is a multitude of detectors build-in typical PET tomograph structure, there are many possible detector pairs that pertain to the measurement. The problem is how to turn this measurement into an image (this is called imaging). Decisive improvement in PET image quality was reached with the introduction of iterative reconstruction techniques. This stage was reached already twenty years ago (with the advent of new powerful computing processors). However, three dimensional (3D) imaging remains still a challenge. The purpose of the image reconstruction algorithm is to process this imperfect count data for a large number (many millions) of lines-of-responce (LOR) and millions of detected photons to produce an image showing the distribution of the l...

  18. PHOTOGRAMMETRIC ANALYSIS OF HISTORICAL IMAGE REPOSITORIES FOR VIRTUAL RECONSTRUCTION IN THE FIELD OF DIGITAL HUMANITIES

    Directory of Open Access Journals (Sweden)

    F. Maiwald

    2017-02-01

    Full Text Available Historical photographs contain high density of information and are of great importance as sources in humanities research. In addition to the semantic indexing of historical images based on metadata, it is also possible to reconstruct geometric information about the depicted objects or the camera position at the time of the recording by employing photogrammetric methods. The approach presented here is intended to investigate (semi- automated photogrammetric reconstruction methods for heterogeneous collections of historical (city photographs and photographic documentation for the use in the humanities, urban research and history sciences. From a photogrammetric point of view, these images are mostly digitized photographs. For a photogrammetric evaluation, therefore, the characteristics of scanned analog images with mostly unknown camera geometry, missing or minimal object information and low radiometric and geometric resolution have to be considered. In addition, these photographs have not been created specifically for documentation purposes and so the focus of these images is often not on the object to be evaluated. The image repositories must therefore be subjected to a preprocessing analysis of their photogrammetric usability. Investigations are carried out on the basis of a repository containing historical images of the Kronentor ("crown gate" of the Dresden Zwinger. The initial step was to assess the quality and condition of available images determining their appropriateness for generating three-dimensional point clouds from historical photos using a structure-from-motion evaluation (SfM. Then, the generated point clouds were assessed by comparing them with current measurement data of the same object.