Nanomaterial datasets to advance tomography in scanning transmission electron microscopy

PubMed Central

Levin, Barnaby D.A.; Padgett, Elliot; Chen, Chien-Chun; Scott, M.C.; Xu, Rui; Theis, Wolfgang; Jiang, Yi; Yang, Yongsoo; Ophus, Colin; Zhang, Haitao; Ha, Don-Hyung; Wang, Deli; Yu, Yingchao; Abruña, Hector D.; Robinson, Richard D.; Ercius, Peter; Kourkoutis, Lena F.; Miao, Jianwei; Muller, David A.; Hovden, Robert

2016-01-01

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co2P nanocrystal, platinum nanoparticles on a carbon nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data. PMID:27272459

Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography.

PubMed

Galaz-Montoya, Jesús G; Hecksel, Corey W; Baldwin, Philip R; Wang, Eryu; Weaver, Scott C; Schmid, Michael F; Ludtke, Steven J; Chiu, Wah

2016-06-01

Single particle cryo-electron tomography (cryoSPT) extracts features from cryo-electron tomograms, followed by 3D classification, alignment and averaging to generate improved 3D density maps of such features. Robust methods to correct for the contrast transfer function (CTF) of the electron microscope are necessary for cryoSPT to reach its resolution potential. Many factors can make CTF correction for cryoSPT challenging, such as lack of eucentricity of the specimen stage, inherent low dose per image, specimen charging, beam-induced specimen motions, and defocus gradients resulting both from specimen tilting and from unpredictable ice thickness variations. Current CTF correction methods for cryoET make at least one of the following assumptions: that the defocus at the center of the image is the same across the images of a tiltseries, that the particles all lie at the same Z-height in the embedding ice, and/or that the specimen, the cryo-electron microscopy (cryoEM) grid and/or the carbon support are flat. These experimental conditions are not always met. We have developed a CTF correction algorithm for cryoSPT without making any of the aforementioned assumptions. We also introduce speed and accuracy improvements and a higher degree of automation to the subtomogram averaging algorithms available in EMAN2. Using motion-corrected images of isolated virus particles as a benchmark specimen, recorded with a DE20 direct detection camera, we show that our CTF correction and subtomogram alignment routines can yield subtomogram averages close to 4/5 Nyquist frequency of the detector under our experimental conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

Non-rigid alignment in electron tomography in materials science.

PubMed

Printemps, Tony; Bernier, Nicolas; Bleuet, Pierre; Mula, Guido; Hervé, Lionel

2016-09-01

Electron tomography is a key technique that enables the visualization of an object in three dimensions with a resolution of about a nanometre. High-quality 3D reconstruction is possible thanks to the latest compressed sensing algorithms and/or better alignment and preprocessing of the 2D projections. Rigid alignment of 2D projections is routine in electron tomography. However, it cannot correct misalignments induced by (i) deformations of the sample due to radiation damage or (ii) drifting of the sample during the acquisition of an image in scanning transmission electron microscope mode. In both cases, those misalignments can give rise to artefacts in the reconstruction. We propose a simple-to-implement non-rigid alignment technique to correct those artefacts. This technique is particularly suited for needle-shaped samples in materials science. It is initiated by a rigid alignment of the projections and it is then followed by several rigid alignments of different parts of the projections. Piecewise linear deformations are applied to each projection to force them to simultaneously satisfy the rigid alignments of the different parts. The efficiency of this technique is demonstrated on three samples, an intermetallic sample with deformation misalignments due to a high electron dose typical to spectroscopic electron tomography, a porous silicon sample with an extremely thin end particularly sensitive to electron beam and another porous silicon sample that was drifting during image acquisitions. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Two-dimensional ionospheric tomography over the low-latitude Indian region: An intercomparison of ART and MART algorithms

NASA Astrophysics Data System (ADS)

Das, Sukanta Kumar; Shukla, Ashish Kumar

2011-04-01

Single-frequency users of a satellite-based augmentation system (SBAS) rely on ionospheric models to mitigate the delay due to the ionosphere. The ionosphere is the major source of range and range rate errors for users of the Global Positioning System (GPS) who require high-accuracy positioning. The purpose of the present study is to develop a tomography model to reconstruct the total electron content (TEC) over the low-latitude Indian region which lies in the equatorial ionospheric anomaly belt. In the present study, the TEC data collected from the six TEC collection stations along a longitudinal belt of around 77 degrees are used. The main objective of the study is to find out optimum pixel size which supports a better reconstruction of the electron density and hence the TEC over the low-latitude Indian region. Performance of two reconstruction algorithms Algebraic Reconstruction Technique (ART) and Multiplicative Algebraic Reconstruction Technique (MART) is analyzed for different pixel sizes varying from 1 to 6 degrees in latitude. It is found from the analysis that the optimum pixel size is 5° × 50 km over the Indian region using both ART and MART algorithms.

An electron tomography algorithm for reconstructing 3D morphology using surface tangents of projected scattering interfaces

NASA Astrophysics Data System (ADS)

Petersen, T. C.; Ringer, S. P.

2010-03-01

Upon discerning the mere shape of an imaged object, as portrayed by projected perimeters, the full three-dimensional scattering density may not be of particular interest. In this situation considerable simplifications to the reconstruction problem are possible, allowing calculations based upon geometric principles. Here we describe and provide an algorithm which reconstructs the three-dimensional morphology of specimens from tilt series of images for application to electron tomography. Our algorithm uses a differential approach to infer the intersection of projected tangent lines with surfaces which define boundaries between regions of different scattering densities within and around the perimeters of specimens. Details of the algorithm implementation are given and explained using reconstruction calculations from simulations, which are built into the code. An experimental application of the algorithm to a nano-sized Aluminium tip is also presented to demonstrate practical analysis for a real specimen. Program summaryProgram title: STOMO version 1.0 Catalogue identifier: AEFS_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2988 No. of bytes in distributed program, including test data, etc.: 191 605 Distribution format: tar.gz Programming language: C/C++ Computer: PC Operating system: Windows XP RAM: Depends upon the size of experimental data as input, ranging from 200 Mb to 1.5 Gb Supplementary material: Sample output files, for the test run provided, are available. Classification: 7.4, 14 External routines: Dev-C++ ( http://www.bloodshed.net/devcpp.html) Nature of problem: Electron tomography of specimens for which conventional back projection may fail and/or data for which there is a limited angular range. The algorithm does not solve the tomographic back-projection problem but rather reconstructs the local 3D morphology of surfaces defined by varied scattering densities. Solution method: Reconstruction using differential geometry applied to image analysis computations. Restrictions: The code has only been tested with square images and has been developed for only single-axis tilting. Running time: For high quality reconstruction, 5-15 min

FPGA-Based Front-End Electronics for Positron Emission Tomography

PubMed Central

Haselman, Michael; DeWitt, Don; McDougald, Wendy; Lewellen, Thomas K.; Miyaoka, Robert; Hauck, Scott

2010-01-01

Modern Field Programmable Gate Arrays (FPGAs) are capable of performing complex discrete signal processing algorithms with clock rates above 100MHz. This combined with FPGA’s low expense, ease of use, and selected dedicated hardware make them an ideal technology for a data acquisition system for positron emission tomography (PET) scanners. Our laboratory is producing a high-resolution, small-animal PET scanner that utilizes FPGAs as the core of the front-end electronics. For this next generation scanner, functions that are typically performed in dedicated circuits, or offline, are being migrated to the FPGA. This will not only simplify the electronics, but the features of modern FPGAs can be utilizes to add significant signal processing power to produce higher resolution images. In this paper two such processes, sub-clock rate pulse timing and event localization, will be discussed in detail. We show that timing performed in the FPGA can achieve a resolution that is suitable for small-animal scanners, and will outperform the analog version given a low enough sampling period for the ADC. We will also show that the position of events in the scanner can be determined in real time using a statistical positioning based algorithm. PMID:21961085

Alignment Algorithms and Per-Particle CTF Correction for Single Particle Cryo-Electron Tomography

PubMed Central

Galaz-Montoya, Jesús G.; Hecksel, Corey W.; Baldwin, Philip R.; Wang, Eryu; Weaver, Scott C.; Schmid, Michael F.; Ludtke, Steven J.; Chiu, Wah

2016-01-01

Single particle cryo-electron tomography (cryoSPT) extracts features from cryo-electron tomograms, followed by 3D classification, alignment and averaging to generate improved 3D density maps of such features. Robust methods to correct for the contrast transfer function (CTF) of the electron microscope are necessary for cryoSPT to reach its resolution potential. Many factors can make CTF correction for cryoSPT challenging, such as lack of eucentricity of the specimen stage, inherent low dose per image, specimen charging, beam-induced specimen motions, and defocus gradients resulting both from specimen tilting and from unpredictable ice thickness variations. Current CTF correction methods for cryoET make at least one of the following assumptions: that the defocus at the center of the image is the same across the images of a tiltseries, that the particles all lie at the same Z-height in the embedding ice, and/or that the specimen grid and carbon support are flat. These experimental conditions are not always met. We have developed a CTF correction algorithm for cryoSPT without making any of the aforementioned assumptions. We also introduce speed and accuracy improvements and a higher degree of automation to the subtomogram averaging algorithms available in EMAN2. Using motion-corrected images of isolated virus particles as a benchmark specimen, recorded with a DE20 direct detection camera, we show that our CTF correction and subtomogram alignment routines can yield subtomogram averages close to 4/5 Nyquist frequency of the detector under our experimental conditions. PMID:27016284

Sampling limits for electron tomography with sparsity-exploiting reconstructions.

PubMed

Jiang, Yi; Padgett, Elliot; Hovden, Robert; Muller, David A

2018-03-01

Electron tomography (ET) has become a standard technique for 3D characterization of materials at the nano-scale. Traditional reconstruction algorithms such as weighted back projection suffer from disruptive artifacts with insufficient projections. Popularized by compressed sensing, sparsity-exploiting algorithms have been applied to experimental ET data and show promise for improving reconstruction quality or reducing the total beam dose applied to a specimen. Nevertheless, theoretical bounds for these methods have been less explored in the context of ET applications. Here, we perform numerical simulations to investigate performance of ℓ 1 -norm and total-variation (TV) minimization under various imaging conditions. From 36,100 different simulated structures, our results show specimens with more complex structures generally require more projections for exact reconstruction. However, once sufficient data is acquired, dividing the beam dose over more projections provides no improvements-analogous to the traditional dose-fraction theorem. Moreover, a limited tilt range of ±75° or less can result in distorting artifacts in sparsity-exploiting reconstructions. The influence of optimization parameters on reconstructions is also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of generalized singular value decomposition to ionospheric tomography

NASA Astrophysics Data System (ADS)

Bhuyan, K.; Singh, S.; Bhuyan, P.

2004-10-01

The electron density distribution of the low- and mid-latitude ionosphere has been investigated by the computerized tomography technique using a Generalized Singular Value Decomposition (GSVD) based algorithm. Model ionospheric total electron content (TEC) data obtained from the International Reference Ionosphere 2001 and slant relative TEC data measured at a chain of three stations receiving transit satellite transmissions in Alaska, USA are used in this analysis. The issue of optimum efficiency of the GSVD algorithm in the reconstruction of ionospheric structures is being addressed through simulation of the equatorial ionization anomaly (EIA), in addition to its application to investigate complicated ionospheric density irregularities. Results show that the Generalized Cross Validation approach to find the regularization parameter and the corresponding solution gives a very good reconstructed image of the low-latitude ionosphere and the EIA within it. Provided that some minimum norm is fulfilled, the GSVD solution is found to be least affected by considerations, such as pixel size and number of ray paths. The method has also been used to investigate the behaviour of the mid-latitude ionosphere under magnetically quiet and disturbed conditions.

Robust membrane detection based on tensor voting for electron tomography.

PubMed

Martinez-Sanchez, Antonio; Garcia, Inmaculada; Asano, Shoh; Lucic, Vladan; Fernandez, Jose-Jesus

2014-04-01

Electron tomography enables three-dimensional (3D) visualization and analysis of the subcellular architecture at a resolution of a few nanometers. Segmentation of structural components present in 3D images (tomograms) is often necessary for their interpretation. However, it is severely hampered by a number of factors that are inherent to electron tomography (e.g. noise, low contrast, distortion). Thus, there is a need for new and improved computational methods to facilitate this challenging task. In this work, we present a new method for membrane segmentation that is based on anisotropic propagation of the local structural information using the tensor voting algorithm. The local structure at each voxel is then refined according to the information received from other voxels. Because voxels belonging to the same membrane have coherent structural information, the underlying global structure is strengthened. In this way, local information is easily integrated at a global scale to yield segmented structures. This method performs well under low signal-to-noise ratio typically found in tomograms of vitrified samples under cryo-tomography conditions and can bridge gaps present on membranes. The performance of the method is demonstrated by applications to tomograms of different biological samples and by quantitative comparison with standard template matching procedure. Copyright © 2014 Elsevier Inc. All rights reserved.

Combined scanning transmission electron microscopy tilt- and focal series.

PubMed

Dahmen, Tim; Baudoin, Jean-Pierre; Lupini, Andrew R; Kübel, Christian; Slusallek, Philipp; de Jonge, Niels

2014-04-01

In this study, a combined tilt- and focal series is proposed as a new recording scheme for high-angle annular dark-field scanning transmission electron microscopy (STEM) tomography. Three-dimensional (3D) data were acquired by mechanically tilting the specimen, and recording a through-focal series at each tilt direction. The sample was a whole-mount macrophage cell with embedded gold nanoparticles. The tilt-focal algebraic reconstruction technique (TF-ART) is introduced as a new algorithm to reconstruct tomograms from such combined tilt- and focal series. The feasibility of TF-ART was demonstrated by 3D reconstruction of the experimental 3D data. The results were compared with a conventional STEM tilt series of a similar sample. The combined tilt- and focal series led to smaller "missing wedge" artifacts, and a higher axial resolution than obtained for the STEM tilt series, thus improving on one of the main issues of tilt series-based electron tomography.

Vectorization with SIMD extensions speeds up reconstruction in electron tomography.

PubMed

Agulleiro, J I; Garzón, E M; García, I; Fernández, J J

2010-06-01

Electron tomography allows structural studies of cellular structures at molecular detail. Large 3D reconstructions are needed to meet the resolution requirements. The processing time to compute these large volumes may be considerable and so, high performance computing techniques have been used traditionally. This work presents a vector approach to tomographic reconstruction that relies on the exploitation of the SIMD extensions available in modern processors in combination to other single processor optimization techniques. This approach succeeds in producing full resolution tomograms with an important reduction in processing time, as evaluated with the most common reconstruction algorithms, namely WBP and SIRT. The main advantage stems from the fact that this approach is to be run on standard computers without the need of specialized hardware, which facilitates the development, use and management of programs. Future trends in processor design open excellent opportunities for vector processing with processor's SIMD extensions in the field of 3D electron microscopy.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miao, Jianwei; Ercius, Peter; Billinge, S. J. L.

Crystallography has been fundamental to the development of many fields of science over the last century. However, much of our modern science and technology relies on materials with defects and disorders, and their three-dimensional (3D) atomic structures are not accessible to crystallography. One method capable of addressing this major challenge is atomic electron tomography. By combining advanced electron microscopes and detectors with powerful data analysis and tomographic reconstruction algorithms, it is now possible to determine the 3D atomic structure of crystal defects such as grain boundaries, stacking faults, dislocations, and point defects, as well as to precisely localize the 3Dmore » coordinates of individual atoms in materials without assuming crystallinity. In this work, we review the recent advances and the interdisciplinary science enabled by this methodology. We also outline further research needed for atomic electron tomography to address long-standing unresolved problems in the physical sciences.« less

Investigating the performance of wavelet neural networks in ionospheric tomography using IGS data over Europe

NASA Astrophysics Data System (ADS)

Ghaffari Razin, Mir Reza; Voosoghi, Behzad

2017-04-01

Ionospheric tomography is a very cost-effective method which is used frequently to modeling of electron density distributions. In this paper, residual minimization training neural network (RMTNN) is used in voxel based ionospheric tomography. Due to the use of wavelet neural network (WNN) with back-propagation (BP) algorithm in RMTNN method, the new method is named modified RMTNN (MRMTNN). To train the WNN with BP algorithm, two cost functions is defined: total and vertical cost functions. Using minimization of cost functions, temporal and spatial ionospheric variations is studied. The GPS measurements of the international GNSS service (IGS) in the central Europe have been used for constructing a 3-D image of the electron density. Three days (2009.04.15, 2011.07.20 and 2013.06.01) with different solar activity index is used for the processing. To validate and better assess reliability of the proposed method, 4 ionosonde and 3 testing stations have been used. Also the results of MRMTNN has been compared to that of the RMTNN method, international reference ionosphere model 2012 (IRI-2012) and spherical cap harmonic (SCH) method as a local ionospheric model. The comparison of MRMTNN results with RMTNN, IRI-2012 and SCH models shows that the root mean square error (RMSE) and standard deviation of the proposed approach are superior to those of the traditional method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levin, Barnaby D. A.; Padgett, Elliot; Chen, Chien-Chun

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co 2 P nanocrystal, platinum nanoparticles on a carbonmore » nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data.« less

The Ettention software package.

PubMed

Dahmen, Tim; Marsalek, Lukas; Marniok, Nico; Turoňová, Beata; Bogachev, Sviatoslav; Trampert, Patrick; Nickels, Stefan; Slusallek, Philipp

2016-02-01

We present a novel software package for the problem "reconstruction from projections" in electron microscopy. The Ettention framework consists of a set of modular building-blocks for tomographic reconstruction algorithms. The well-known block iterative reconstruction method based on Kaczmarz algorithm is implemented using these building-blocks, including adaptations specific to electron tomography. Ettention simultaneously features (1) a modular, object-oriented software design, (2) optimized access to high-performance computing (HPC) platforms such as graphic processing units (GPU) or many-core architectures like Xeon Phi, and (3) accessibility to microscopy end-users via integration in the IMOD package and eTomo user interface. We also provide developers with a clean and well-structured application programming interface (API) that allows for extending the software easily and thus makes it an ideal platform for algorithmic research while hiding most of the technical details of high-performance computing. Copyright © 2015 Elsevier B.V. All rights reserved.

Design and Construction of Detector and Data Acquisition Elements for Proton Computed Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fermi Research Alliance; Northern Illinois University

2015-07-15

Proton computed tomography (pCT) offers an alternative to x-ray imaging with potential for three-dimensional imaging, reduced radiation exposure, and in-situ imaging. Northern Illinois University (NIU) is developing a second-generation proton computed tomography system with a goal of demonstrating the feasibility of three-dimensional imaging within clinically realistic imaging times. The second-generation pCT system is comprised of a tracking system, a calorimeter, data acquisition, a computing farm, and software algorithms. The proton beam encounters the upstream tracking detectors, the patient or phantom, the downstream tracking detectors, and a calorimeter. The schematic layout of the PCT system is shown. The data acquisition sendsmore » the proton scattering information to an offline computing farm. Major innovations of the second generation pCT project involve an increased data acquisition rate ( MHz range) and development of three-dimensional imaging algorithms. The Fermilab Particle Physics Division and Northern Illinois Center for Accelerator and Detector Development at Northern Illinois University worked together to design and construct the tracking detectors, calorimeter, readout electronics and detector mounting system.« less

Atom probe trajectory mapping using experimental tip shape measurements.

PubMed

Haley, D; Petersen, T; Ringer, S P; Smith, G D W

2011-11-01

Atom probe tomography is an accurate analytical and imaging technique which can reconstruct the complex structure and composition of a specimen in three dimensions. Despite providing locally high spatial resolution, atom probe tomography suffers from global distortions due to a complex projection function between the specimen and detector which is different for each experiment and can change during a single run. To aid characterization of this projection function, this work demonstrates a method for the reverse projection of ions from an arbitrary projection surface in 3D space back to an atom probe tomography specimen surface. Experimental data from transmission electron microscopy tilt tomography are combined with point cloud surface reconstruction algorithms and finite element modelling to generate a mapping back to the original tip surface in a physically and experimentally motivated manner. As a case study, aluminium tips are imaged using transmission electron microscopy before and after atom probe tomography, and the specimen profiles used as input in surface reconstruction methods. This reconstruction method is a general procedure that can be used to generate mappings between a selected surface and a known tip shape using numerical solutions to the electrostatic equation, with quantitative solutions to the projection problem readily achievable in tens of minutes on a contemporary workstation. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.

An electron beam linear scanning mode for industrial limited-angle nano-computed tomography.

PubMed

Wang, Chengxiang; Zeng, Li; Yu, Wei; Zhang, Lingli; Guo, Yumeng; Gong, Changcheng

2018-01-01

Nano-computed tomography (nano-CT), which utilizes X-rays to research the inner structure of some small objects and has been widely utilized in biomedical research, electronic technology, geology, material sciences, etc., is a high spatial resolution and non-destructive research technique. A traditional nano-CT scanning model with a very high mechanical precision and stability of object manipulator, which is difficult to reach when the scanned object is continuously rotated, is required for high resolution imaging. To reduce the scanning time and attain a stable and high resolution imaging in industrial non-destructive testing, we study an electron beam linear scanning mode of nano-CT system that can avoid mechanical vibration and object movement caused by the continuously rotated object. Furthermore, to further save the scanning time and study how small the scanning range could be considered with acceptable spatial resolution, an alternating iterative algorithm based on ℓ 0 minimization is utilized to limited-angle nano-CT reconstruction problem with the electron beam linear scanning mode. The experimental results confirm the feasibility of the electron beam linear scanning mode of nano-CT system.

An electron beam linear scanning mode for industrial limited-angle nano-computed tomography

NASA Astrophysics Data System (ADS)

Wang, Chengxiang; Zeng, Li; Yu, Wei; Zhang, Lingli; Guo, Yumeng; Gong, Changcheng

2018-01-01

Nano-computed tomography (nano-CT), which utilizes X-rays to research the inner structure of some small objects and has been widely utilized in biomedical research, electronic technology, geology, material sciences, etc., is a high spatial resolution and non-destructive research technique. A traditional nano-CT scanning model with a very high mechanical precision and stability of object manipulator, which is difficult to reach when the scanned object is continuously rotated, is required for high resolution imaging. To reduce the scanning time and attain a stable and high resolution imaging in industrial non-destructive testing, we study an electron beam linear scanning mode of nano-CT system that can avoid mechanical vibration and object movement caused by the continuously rotated object. Furthermore, to further save the scanning time and study how small the scanning range could be considered with acceptable spatial resolution, an alternating iterative algorithm based on ℓ0 minimization is utilized to limited-angle nano-CT reconstruction problem with the electron beam linear scanning mode. The experimental results confirm the feasibility of the electron beam linear scanning mode of nano-CT system.

Electronic hardware design of electrical capacitance tomography systems.

PubMed

Saied, I; Meribout, M

2016-06-28

Electrical tomography techniques for process imaging are very prominent for industrial applications, such as the oil and gas industry and chemical refineries, owing to their ability to provide the flow regime of a flowing fluid within a relatively high throughput. Among the various techniques, electrical capacitance tomography (ECT) is gaining popularity due to its non-invasive nature and its capability to differentiate between different phases based on their permittivity distribution. In recent years, several hardware designs have been provided for ECT systems that have improved its resolution of measurements to be around attofarads (aF, 10(-18) F), or the number of channels, that is required to be large for some applications that require a significant amount of data. In terms of image acquisition time, some recent systems could achieve a throughput of a few hundred frames per second, while data processing time could be achieved in only a few milliseconds per frame. This paper outlines the concept and main features of the most recent front-end and back-end electronic circuits dedicated for ECT systems. In this paper, multiple-excitation capacitance polling, a front-end electronic technique, shows promising results for ECT systems to acquire fast data acquisition speeds. A highly parallel field-programmable gate array (FPGA) based architecture for a fast reconstruction algorithm is also described. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

A neural network approach for image reconstruction in electron magnetic resonance tomography.

PubMed

Durairaj, D Christopher; Krishna, Murali C; Murugesan, Ramachandran

2007-10-01

An object-oriented, artificial neural network (ANN) based, application system for reconstruction of two-dimensional spatial images in electron magnetic resonance (EMR) tomography is presented. The standard back propagation algorithm is utilized to train a three-layer sigmoidal feed-forward, supervised, ANN to perform the image reconstruction. The network learns the relationship between the 'ideal' images that are reconstructed using filtered back projection (FBP) technique and the corresponding projection data (sinograms). The input layer of the network is provided with a training set that contains projection data from various phantoms as well as in vivo objects, acquired from an EMR imager. Twenty five different network configurations are investigated to test the ability of the generalization of the network. The trained ANN then reconstructs two-dimensional temporal spatial images that present the distribution of free radicals in biological systems. Image reconstruction by the trained neural network shows better time complexity than the conventional iterative reconstruction algorithms such as multiplicative algebraic reconstruction technique (MART). The network is further explored for image reconstruction from 'noisy' EMR data and the results show better performance than the FBP method. The network is also tested for its ability to reconstruct from limited-angle EMR data set.

Accelerating electron tomography reconstruction algorithm ICON with GPU.

PubMed

Chen, Yu; Wang, Zihao; Zhang, Jingrong; Li, Lun; Wan, Xiaohua; Sun, Fei; Zhang, Fa

2017-01-01

Electron tomography (ET) plays an important role in studying in situ cell ultrastructure in three-dimensional space. Due to limited tilt angles, ET reconstruction always suffers from the "missing wedge" problem. With a validation procedure, iterative compressed-sensing optimized NUFFT reconstruction (ICON) demonstrates its power in the restoration of validated missing information for low SNR biological ET dataset. However, the huge computational demand has become a major problem for the application of ICON. In this work, we analyzed the framework of ICON and classified the operations of major steps of ICON reconstruction into three types. Accordingly, we designed parallel strategies and implemented them on graphics processing units (GPU) to generate a parallel program ICON-GPU. With high accuracy, ICON-GPU has a great acceleration compared to its CPU version, up to 83.7×, greatly relieving ICON's dependence on computing resource.

Refinement procedure for the image alignment in high-resolution electron tomography.

PubMed

Houben, L; Bar Sadan, M

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. Copyright © 2011 Elsevier B.V. All rights reserved.

Dynamic Reconstruction Algorithm of Three-Dimensional Temperature Field Measurement by Acoustic Tomography

PubMed Central

Li, Yanqiu; Liu, Shi; Inaki, Schlaberg H.

2017-01-01

Accuracy and speed of algorithms play an important role in the reconstruction of temperature field measurements by acoustic tomography. Existing algorithms are based on static models which only consider the measurement information. A dynamic model of three-dimensional temperature reconstruction by acoustic tomography is established in this paper. A dynamic algorithm is proposed considering both acoustic measurement information and the dynamic evolution information of the temperature field. An objective function is built which fuses measurement information and the space constraint of the temperature field with its dynamic evolution information. Robust estimation is used to extend the objective function. The method combines a tunneling algorithm and a local minimization technique to solve the objective function. Numerical simulations show that the image quality and noise immunity of the dynamic reconstruction algorithm are better when compared with static algorithms such as least square method, algebraic reconstruction technique and standard Tikhonov regularization algorithms. An effective method is provided for temperature field reconstruction by acoustic tomography. PMID:28895930

A novel fully automatic scheme for fiducial marker-based alignment in electron tomography.

PubMed

Han, Renmin; Wang, Liansan; Liu, Zhiyong; Sun, Fei; Zhang, Fa

2015-12-01

Although the topic of fiducial marker-based alignment in electron tomography (ET) has been widely discussed for decades, alignment without human intervention remains a difficult problem. Specifically, the emergence of subtomogram averaging has increased the demand for batch processing during tomographic reconstruction; fully automatic fiducial marker-based alignment is the main technique in this process. However, the lack of an accurate method for detecting and tracking fiducial markers precludes fully automatic alignment. In this paper, we present a novel, fully automatic alignment scheme for ET. Our scheme has two main contributions: First, we present a series of algorithms to ensure a high recognition rate and precise localization during the detection of fiducial markers. Our proposed solution reduces fiducial marker detection to a sampling and classification problem and further introduces an algorithm to solve the parameter dependence of marker diameter and marker number. Second, we propose a novel algorithm to solve the tracking of fiducial markers by reducing the tracking problem to an incomplete point set registration problem. Because a global optimization of a point set registration occurs, the result of our tracking is independent of the initial image position in the tilt series, allowing for the robust tracking of fiducial markers without pre-alignment. The experimental results indicate that our method can achieve an accurate tracking, almost identical to the current best one in IMOD with half automatic scheme. Furthermore, our scheme is fully automatic, depends on fewer parameters (only requires a gross value of the marker diameter) and does not require any manual interaction, providing the possibility of automatic batch processing of electron tomographic reconstruction. Copyright © 2015 Elsevier Inc. All rights reserved.

ODTbrain: a Python library for full-view, dense diffraction tomography.

PubMed

Müller, Paul; Schürmann, Mirjam; Guck, Jochen

2015-11-04

Analyzing the three-dimensional (3D) refractive index distribution of a single cell makes it possible to describe and characterize its inner structure in a marker-free manner. A dense, full-view tomographic data set is a set of images of a cell acquired for multiple rotational positions, densely distributed from 0 to 360 degrees. The reconstruction is commonly realized by projection tomography, which is based on the inversion of the Radon transform. The reconstruction quality of projection tomography is greatly improved when first order scattering, which becomes relevant when the imaging wavelength is comparable to the characteristic object size, is taken into account. This advanced reconstruction technique is called diffraction tomography. While many implementations of projection tomography are available today, there is no publicly available implementation of diffraction tomography so far. We present a Python library that implements the backpropagation algorithm for diffraction tomography in 3D. By establishing benchmarks based on finite-difference time-domain (FDTD) simulations, we showcase the superiority of the backpropagation algorithm over the backprojection algorithm. Furthermore, we discuss how measurment parameters influence the reconstructed refractive index distribution and we also give insights into the applicability of diffraction tomography to biological cells. The present software library contains a robust implementation of the backpropagation algorithm. The algorithm is ideally suited for the application to biological cells. Furthermore, the implementation is a drop-in replacement for the classical backprojection algorithm and is made available to the large user community of the Python programming language.

Electron tomography of HEK293T cells using scanning electron microscope-based scanning transmission electron microscopy.

PubMed

You, Yun-Wen; Chang, Hsun-Yun; Liao, Hua-Yang; Kao, Wei-Lun; Yen, Guo-Ji; Chang, Chi-Jen; Tsai, Meng-Hung; Shyue, Jing-Jong

2012-10-01

Based on a scanning electron microscope operated at 30 kV with a homemade specimen holder and a multiangle solid-state detector behind the sample, low-kV scanning transmission electron microscopy (STEM) is presented with subsequent electron tomography for three-dimensional (3D) volume structure. Because of the low acceleration voltage, the stronger electron-atom scattering leads to a stronger contrast in the resulting image than standard TEM, especially for light elements. Furthermore, the low-kV STEM yields less radiation damage to the specimen, hence the structure can be preserved. In this work, two-dimensional STEM images of a 1-μm-thick cell section with projection angles between ±50° were collected, and the 3D volume structure was reconstructed using the simultaneous iterative reconstructive technique algorithm with the TomoJ plugin for ImageJ, which are both public domain software. Furthermore, the cross-sectional structure was obtained with the Volume Viewer plugin in ImageJ. Although the tilting angle is constrained and limits the resulting structural resolution, slicing the reconstructed volume generated the depth profile of the thick specimen with sufficient resolution to examine cellular uptake of Au nanoparticles, and the final position of these nanoparticles inside the cell was imaged.

Data-driven gradient algorithm for high-precision quantum control

NASA Astrophysics Data System (ADS)

Wu, Re-Bing; Chu, Bing; Owens, David H.; Rabitz, Herschel

2018-04-01

In the quest to achieve scalable quantum information processing technologies, gradient-based optimal control algorithms (e.g., grape) are broadly used for implementing high-precision quantum gates, but their performance is often hindered by deterministic or random errors in the system model and the control electronics. In this paper, we show that grape can be taught to be more effective by jointly learning from the design model and the experimental data obtained from process tomography. The resulting data-driven gradient optimization algorithm (d-grape) can in principle correct all deterministic gate errors, with a mild efficiency loss. The d-grape algorithm may become more powerful with broadband controls that involve a large number of control parameters, while other algorithms usually slow down due to the increased size of the search space. These advantages are demonstrated by simulating the implementation of a two-qubit controlled-not gate.

A new apparatus for electron tomography in the scanning electron microscope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morandi, V., E-mail: morandi@bo.imm.cnr.it; Maccagnani, P.; Masini, L.

2015-06-23

The three-dimensional reconstruction of a microscopic specimen has been obtained by applying the tomographic algorithm to a set of images acquired in a Scanning Electron Microscope. This result was achieved starting from a series of projections obtained by stepwise rotating the sample under the beam raster. The Scanning Electron Microscope was operated in the scanning-transmission imaging mode, where the intensity of the transmitted electron beam is a monotonic function of the local mass-density and thickness of the specimen. The detection strategy has been implemented and tailored in order to maintain the projection requirement over the large tilt range, as requiredmore » by the tomographic workflow. A Si-based electron detector and an eucentric-rotation specimen holder have been specifically developed for the purpose.« less

Correction of absorption-edge artifacts in polychromatic X-ray tomography in a scanning electron microscope for 3D microelectronics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Laloum, D., E-mail: david.laloum@cea.fr; CEA, LETI, MINATEC Campus, 17 rue des Martyrs, 38054 Grenoble Cedex 9; STMicroelectronics, 850 rue Jean Monnet, 38926 Crolles

2015-01-15

X-ray tomography is widely used in materials science. However, X-ray scanners are often based on polychromatic radiation that creates artifacts such as dark streaks. We show this artifact is not always due to beam hardening. It may appear when scanning samples with high-Z elements inside a low-Z matrix because of the high-Z element absorption edge: X-rays whose energy is above this edge are strongly absorbed, violating the exponential decay assumption for reconstruction algorithms and generating dark streaks. A method is proposed to limit the absorption edge effect and is applied on a microelectronic case to suppress dark streaks between interconnections.

Ionospheric-thermospheric UV tomography: 1. Image space reconstruction algorithms

NASA Astrophysics Data System (ADS)

Dymond, K. F.; Budzien, S. A.; Hei, M. A.

2017-03-01

We present and discuss two algorithms of the class known as Image Space Reconstruction Algorithms (ISRAs) that we are applying to the solution of large-scale ionospheric tomography problems. ISRAs have several desirable features that make them useful for ionospheric tomography. In addition to producing nonnegative solutions, ISRAs are amenable to sparse-matrix formulations and are fast, stable, and robust. We present the results of our studies of two types of ISRA: the Least Squares Positive Definite and the Richardson-Lucy algorithms. We compare their performance to the Multiplicative Algebraic Reconstruction and Conjugate Gradient Least Squares algorithms. We then discuss the use of regularization in these algorithms and present our new approach based on regularization to a partial differential equation.

Electron coherent diffraction tomography of a nanocrystal

NASA Astrophysics Data System (ADS)

Dronyak, Roman; Liang, Keng S.; Tsai, Jin-Sheng; Stetsko, Yuri P.; Lee, Ting-Kuo; Chen, Fu-Rong

2010-05-01

Coherent diffractive imaging (CDI) with electron or x-ray sources is a promising technique for investigating the structure of nanoparticles down to the atomic scale. In electron CDI, a two-dimensional reconstruction is demonstrated using highly coherent illumination from a field-emission gun as a source of electrons. In a three-dimensional (3D) electron CDI, we experimentally determine the morphology of a single MgO nanocrystal using the Bragg diffraction geometry. An iterative algorithm is applied to invert the 3D diffraction pattern about a (200) reflection of the nanoparticle measured at an angular range of 1.8°. The results reveal a 3D image of the sample at ˜8 nm resolution, and agree with a simulation. Our work demonstrates an alternative approach to obtain the 3D structure of nanocrystals with an electron microscope.

Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

PubMed

Redman, Joseph S; Natarajan, Yamini; Hou, Jason K; Wang, Jingqi; Hanif, Muzammil; Feng, Hua; Kramer, Jennifer R; Desiderio, Roxanne; Xu, Hua; El-Serag, Hashem B; Kanwal, Fasiha

2017-10-01

Natural language processing is a powerful technique of machine learning capable of maximizing data extraction from complex electronic medical records. We utilized this technique to develop algorithms capable of "reading" full-text radiology reports to accurately identify the presence of fatty liver disease. Abdominal ultrasound, computerized tomography, and magnetic resonance imaging reports were retrieved from the Veterans Affairs Corporate Data Warehouse from a random national sample of 652 patients. Radiographic fatty liver disease was determined by manual review by two physicians and verified with an expert radiologist. A split validation method was utilized for algorithm development. For all three imaging modalities, the algorithms could identify fatty liver disease with >90% recall and precision, with F-measures >90%. These algorithms could be used to rapidly screen patient records to establish a large cohort to facilitate epidemiological and clinical studies and examine the clinic course and outcomes of patients with radiographic hepatic steatosis.

Methodological accuracy of image-based electron density assessment using dual-energy computed tomography.

PubMed

Möhler, Christian; Wohlfahrt, Patrick; Richter, Christian; Greilich, Steffen

2017-06-01

Electron density is the most important tissue property influencing photon and ion dose distributions in radiotherapy patients. Dual-energy computed tomography (DECT) enables the determination of electron density by combining the information on photon attenuation obtained at two different effective x-ray energy spectra. Most algorithms suggested so far use the CT numbers provided after image reconstruction as input parameters, i.e., are imaged-based. To explore the accuracy that can be achieved with these approaches, we quantify the intrinsic methodological and calibration uncertainty of the seemingly simplest approach. In the studied approach, electron density is calculated with a one-parametric linear superposition ('alpha blending') of the two DECT images, which is shown to be equivalent to an affine relation between the photon attenuation cross sections of the two x-ray energy spectra. We propose to use the latter relation for empirical calibration of the spectrum-dependent blending parameter. For a conclusive assessment of the electron density uncertainty, we chose to isolate the purely methodological uncertainty component from CT-related effects such as noise and beam hardening. Analyzing calculated spectrally weighted attenuation coefficients, we find universal applicability of the investigated approach to arbitrary mixtures of human tissue with an upper limit of the methodological uncertainty component of 0.2%, excluding high-Z elements such as iodine. The proposed calibration procedure is bias-free and straightforward to perform using standard equipment. Testing the calibration on five published data sets, we obtain very small differences in the calibration result in spite of different experimental setups and CT protocols used. Employing a general calibration per scanner type and voltage combination is thus conceivable. Given the high suitability for clinical application of the alpha-blending approach in combination with a very small methodological uncertainty, we conclude that further refinement of image-based DECT-algorithms for electron density assessment is not advisable. © 2017 American Association of Physicists in Medicine.

Regional model-based computerized ionospheric tomography using GPS measurements: IONOLAB-CIT

NASA Astrophysics Data System (ADS)

Tuna, Hakan; Arikan, Orhan; Arikan, Feza

2015-10-01

Three-dimensional imaging of the electron density distribution in the ionosphere is a crucial task for investigating the ionospheric effects. Dual-frequency Global Positioning System (GPS) satellite signals can be used to estimate the slant total electron content (STEC) along the propagation path between a GPS satellite and ground-based receiver station. However, the estimated GPS-STEC is very sparse and highly nonuniformly distributed for obtaining reliable 3-D electron density distributions derived from the measurements alone. Standard tomographic reconstruction techniques are not accurate or reliable enough to represent the full complexity of variable ionosphere. On the other hand, model-based electron density distributions are produced according to the general trends of ionosphere, and these distributions do not agree with measurements, especially for geomagnetically active hours. In this study, a regional 3-D electron density distribution reconstruction method, namely, IONOLAB-CIT, is proposed to assimilate GPS-STEC into physical ionospheric models. The proposed method is based on an iterative optimization framework that tracks the deviations from the ionospheric model in terms of F2 layer critical frequency and maximum ionization height resulting from the comparison of International Reference Ionosphere extended to Plasmasphere (IRI-Plas) model-generated STEC and GPS-STEC. The suggested tomography algorithm is applied successfully for the reconstruction of electron density profiles over Turkey, during quiet and disturbed hours of ionosphere using Turkish National Permanent GPS Network.

An algorithm for improving the quality of structural images of turbid media in endoscopic optical coherence tomography

NASA Astrophysics Data System (ADS)

Potlov, A. Yu.; Frolov, S. V.; Proskurin, S. G.

2018-04-01

High-quality OCT structural images reconstruction algorithm for endoscopic optical coherence tomography of biological tissue is described. The key features of the presented algorithm are: (1) raster scanning and averaging of adjacent Ascans and pixels; (2) speckle level minimization. The described algorithm can be used in the gastroenterology, urology, gynecology, otorhinolaryngology for mucous membranes and skin diagnostics in vivo and in situ.

Demonstration of Qubit Operations Below a Rigorous Fault Tolerance Threshold With Gate Set Tomography (Open Access, Publisher’s Version)

DTIC Science & Technology

2017-02-15

Maunz2 Quantum information processors promise fast algorithms for problems inaccessible to classical computers. But since qubits are noisy and error-prone...information processors have been demonstrated experimentally using superconducting circuits1–3, electrons in semiconductors4–6, trapped atoms and...qubit quantum information processor has been realized14, and single- qubit gates have demonstrated randomized benchmarking (RB) infidelities as low as 10

Development of AN Innovative Three-Dimensional Complete Body Screening Device - 3D-CBS

NASA Astrophysics Data System (ADS)

Crosetto, D. B.

2004-07-01

This article describes an innovative technological approach that increases the efficiency with which a large number of particles (photons) can be detected and analyzed. The three-dimensional complete body screening (3D-CBS) combines the functional imaging capability of the Positron Emission Tomography (PET) with those of the anatomical imaging capability of Computed Tomography (CT). The novel techniques provide better images in a shorter time with less radiation to the patient. A primary means of accomplishing this is the use of a larger solid angle, but this requires a new electronic technique capable of handling the increased data rate. This technique, combined with an improved and simplified detector assembly, enables executing complex real-time algorithms and allows more efficiently use of economical crystals. These are the principal features of this invention. A good synergy of advanced techniques in particle detection, together with technological progress in industry (latest FPGA technology) and simple, but cost-effective ideas provide a revolutionary invention. This technology enables over 400 times PET efficiency improvement at once compared to two to three times improvements achieved every five years during the past decades. Details of the electronics are provided, including an IBM PC board with a parallel-processing architecture implemented in FPGA, enabling the execution of a programmable complex real-time algorithm for best detection of photons.

Blur kernel estimation with algebraic tomography technique and intensity profiles of object boundaries

NASA Astrophysics Data System (ADS)

Ingacheva, Anastasia; Chukalina, Marina; Khanipov, Timur; Nikolaev, Dmitry

2018-04-01

Motion blur caused by camera vibration is a common source of degradation in photographs. In this paper we study the problem of finding the point spread function (PSF) of a blurred image using the tomography technique. The PSF reconstruction result strongly depends on the particular tomography technique used. We present a tomography algorithm with regularization adapted specifically for this task. We use the algebraic reconstruction technique (ART algorithm) as the starting algorithm and introduce regularization. We use the conjugate gradient method for numerical implementation of the proposed approach. The algorithm is tested using a dataset which contains 9 kernels extracted from real photographs by the Adobe corporation where the point spread function is known. We also investigate influence of noise on the quality of image reconstruction and investigate how the number of projections influence the magnitude change of the reconstruction error.

Fluorescence laminar optical tomography for brain imaging: system implementation and performance evaluation.

PubMed

Azimipour, Mehdi; Sheikhzadeh, Mahya; Baumgartner, Ryan; Cullen, Patrick K; Helmstetter, Fred J; Chang, Woo-Jin; Pashaie, Ramin

2017-01-01

We present our effort in implementing a fluorescence laminar optical tomography scanner which is specifically designed for noninvasive three-dimensional imaging of fluorescence proteins in the brains of small rodents. A laser beam, after passing through a cylindrical lens, scans the brain tissue from the surface while the emission signal is captured by the epi-fluorescence optics and is recorded using an electron multiplication CCD sensor. Image reconstruction algorithms are developed based on Monte Carlo simulation to model light–tissue interaction and generate the sensitivity matrices. To solve the inverse problem, we used the iterative simultaneous algebraic reconstruction technique. The performance of the developed system was evaluated by imaging microfabricated silicon microchannels embedded inside a substrate with optical properties close to the brain as a tissue phantom and ultimately by scanning brain tissue in vivo. Details of the hardware design and reconstruction algorithms are discussed and several experimental results are presented. The developed system can specifically facilitate neuroscience experiments where fluorescence imaging and molecular genetic methods are used to study the dynamics of the brain circuitries.

A multiresolution inversion for imaging the ionosphere

NASA Astrophysics Data System (ADS)

Yin, Ping; Zheng, Ya-Nan; Mitchell, Cathryn N.; Li, Bo

2017-06-01

Ionospheric tomography has been widely employed in imaging the large-scale ionospheric structures at both quiet and storm times. However, the tomographic algorithms to date have not been very effective in imaging of medium- and small-scale ionospheric structures due to limitations of uneven ground-based data distributions and the algorithm itself. Further, the effect of the density and quantity of Global Navigation Satellite Systems data that could help improve the tomographic results for the certain algorithm remains unclear in much of the literature. In this paper, a new multipass tomographic algorithm is proposed to conduct the inversion using intensive ground GPS observation data and is demonstrated over the U.S. West Coast during the period of 16-18 March 2015 which includes an ionospheric storm period. The characteristics of the multipass inversion algorithm are analyzed by comparing tomographic results with independent ionosonde data and Center for Orbit Determination in Europe total electron content estimates. Then, several ground data sets with different data distributions are grouped from the same data source in order to investigate the impact of the density of ground stations on ionospheric tomography results. Finally, it is concluded that the multipass inversion approach offers an improvement. The ground data density can affect tomographic results but only offers improvements up to a density of around one receiver every 150 to 200 km. When only GPS satellites are tracked there is no clear advantage in increasing the density of receivers beyond this level, although this may change if multiple constellations are monitored from each receiving station in the future.

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

PubMed Central

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

2012-01-01

The primal-dual optimization algorithm developed in Chambolle and Pock (CP), 2011 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 the article, 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. PMID:22538474

Fully Mechanically Controlled Automated Electron Microscopic Tomography

DOE PAGES

Liu, Jinxin; Li, Hongchang; Zhang, Lei; ...

2016-07-11

Knowledge of three-dimensional (3D) structures of each individual particles of asymmetric and flexible proteins is essential in understanding those proteins' functions; but their structures are difficult to determine. Electron tomography (ET) provides a tool for imaging a single and unique biological object from a series of tilted angles, but it is challenging to image a single protein for three-dimensional (3D) reconstruction due to the imperfect mechanical control capability of the specimen goniometer under both a medium to high magnification (approximately 50,000-160,000×) and an optimized beam coherence condition. Here, we report a fully mechanical control method for automating ET data acquisitionmore » without using beam tilt/shift processes. This method could reduce the accumulation of beam tilt/shift that used to compensate the error from the mechanical control, but downgraded the beam coherence. Our method was developed by minimizing the error of the target object center during the tilting process through a closed-loop proportional-integral (PI) control algorithm. The validations by both negative staining (NS) and cryo-electron microscopy (cryo-EM) suggest that this method has a comparable capability to other ET methods in tracking target proteins while maintaining optimized beam coherence conditions for imaging.« less

Three-dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization

NASA Astrophysics Data System (ADS)

Wang, Sicheng; Huang, Sixun; Xiang, Jie; Fang, Hanxian; Feng, Jian; Wang, Yu

2016-12-01

Ionospheric tomography is based on the observed slant total electron content (sTEC) along different satellite-receiver rays to reconstruct the three-dimensional electron density distributions. Due to incomplete measurements provided by the satellite-receiver geometry, it is a typical ill-posed problem, and how to overcome the ill-posedness is still a crucial content of research. In this paper, Tikhonov regularization method is used and the model function approach is applied to determine the optimal regularization parameter. This algorithm not only balances the weights between sTEC observations and background electron density field but also converges globally and rapidly. The background error covariance is given by multiplying background model variance and location-dependent spatial correlation, and the correlation model is developed by using sample statistics from an ensemble of the International Reference Ionosphere 2012 (IRI2012) model outputs. The Global Navigation Satellite System (GNSS) observations in China are used to present the reconstruction results, and measurements from two ionosondes are used to make independent validations. Both the test cases using artificial sTEC observations and actual GNSS sTEC measurements show that the regularization method can effectively improve the background model outputs.

Synthetic Incoherence via Scanned Gaussian Beams

PubMed Central

Levine, Zachary H.

2006-01-01

Tomography, in most formulations, requires an incoherent signal. For a conventional transmission electron microscope, the coherence of the beam often results in diffraction effects that limit the ability to perform a 3D reconstruction from a tilt series with conventional tomographic reconstruction algorithms. In this paper, an analytic solution is given to a scanned Gaussian beam, which reduces the beam coherence to be effectively incoherent for medium-size (of order 100 voxels thick) tomographic applications. The scanned Gaussian beam leads to more incoherence than hollow-cone illumination. PMID:27274945

Analysis and an image recovery algorithm for ultrasonic tomography system

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1994-01-01

The problem of an ultrasonic reflectivity tomography is similar to that of a spotlight-mode aircraft Synthetic Aperture Radar (SAR) system. The analysis for a circular path spotlight mode SAR in this paper leads to the insight of the system characteristics. It indicates that such a system when operated in a wide bandwidth is capable of achieving the ultimate resolution; one quarter of the wavelength of the carrier frequency. An efficient processing algorithm based on the exact two dimensional spectrum is presented. The results of simulation indicate that the impulse responses meet the predicted resolution performance. Compared to an algorithm previously developed for the ultrasonic reflectivity tomography, the throughput rate of this algorithm is about ten times higher.

CatSim: a new computer assisted tomography simulation environment

NASA Astrophysics Data System (ADS)

De Man, Bruno; Basu, Samit; Chandra, Naveen; Dunham, Bruce; Edic, Peter; Iatrou, Maria; McOlash, Scott; Sainath, Paavana; Shaughnessy, Charlie; Tower, Brendon; Williams, Eugene

2007-03-01

We present a new simulation environment for X-ray computed tomography, called CatSim. CatSim provides a research platform for GE researchers and collaborators to explore new reconstruction algorithms, CT architectures, and X-ray source or detector technologies. The main requirements for this simulator are accurate physics modeling, low computation times, and geometrical flexibility. CatSim allows simulating complex analytic phantoms, such as the FORBILD phantoms, including boxes, ellipsoids, elliptical cylinders, cones, and cut planes. CatSim incorporates polychromaticity, realistic quantum and electronic noise models, finite focal spot size and shape, finite detector cell size, detector cross-talk, detector lag or afterglow, bowtie filtration, finite detector efficiency, non-linear partial volume, scatter (variance-reduced Monte Carlo), and absorbed dose. We present an overview of CatSim along with a number of validation experiments.

Prototype of a Muon Tomography Station with GEM detectors for Detection of Shielded Nuclear Contraband

NASA Astrophysics Data System (ADS)

Staib, Michael; Bhopatkar, Vallary; Bittner, William; Hohlmann, Marcus; Locke, Judson; Twigger, Jessie; Gnanvo, Kondo

2012-03-01

Muon tomography for homeland security aims at detecting well-shielded nuclear contraband in cargo and imaging it in 3D. The technique exploits multiple scattering of atmospheric cosmic ray muons, which is stronger in dense, high-Z materials, e.g. enriched uranium, than in low-Z and medium-Z shielding materials. We have constructed and are operating a compact Muon Tomography Station (MTS) that tracks muons with eight 30 cm x 30 cm Triple Gas Electron Multiplier (GEM) detectors placed on the sides of a cubic-foot imaging volume. A point-of-closest-approach algorithm applied to reconstructed incident and exiting tracks is used to create a tomographic reconstruction of the material within the active volume. We discuss the performance of this MTS prototype including characterization and commissioning of the GEM detectors and the data acquisition systems. We also present experimental tomographic images of small high-Z objects including depleted uranium with and without shielding and discuss the performance of material discrimination using this method.

RF tomography of metallic objects in free space: preliminary results

NASA Astrophysics Data System (ADS)

Li, Jia; Ewing, Robert L.; Berdanier, Charles; Baker, Christopher

2015-05-01

RF tomography has great potential in defense and homeland security applications. A distributed sensing research facility is under development at Air Force Research Lab. To develop a RF tomographic imaging system for the facility, preliminary experiments have been performed in an indoor range with 12 radar sensors distributed on a circle of 3m radius. Ultra-wideband pulses are used to illuminate single and multiple metallic targets. The echoes received by distributed sensors were processed and combined for tomography reconstruction. Traditional matched filter algorithm and truncated singular value decomposition (SVD) algorithm are compared in terms of their complexity, accuracy, and suitability for distributed processing. A new algorithm is proposed for shape reconstruction, which jointly estimates the object boundary and scatter points on the waveform's propagation path. The results show that the new algorithm allows accurate reconstruction of object shape, which is not available through the matched filter and truncated SVD algorithms.

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

PubMed Central

Wang, Kun; Su, Richard; Oraevsky, Alexander A; Anastasio, Mark A

2012-01-01

Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely, a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications. PMID:22864062

An Efficient Image Recovery Algorithm for Diffraction Tomography Systems

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1993-01-01

A diffraction tomography system has potential application in ultrasonic medical imaging area. It is capable of achieving imagery with the ultimate resolution of one quarter the wavelength by collecting ultrasonic backscattering data from a circular array of sensors and reconstructing the object reflectivity using a digital image recovery algorithm performed by a computer. One advantage of such a system is that is allows a relatively lower frequency wave to penetrate more deeply into the object and still achieve imagery with a reasonable resolution. An efficient image recovery algorithm for the diffraction tomography system was originally developed for processing a wide beam spaceborne SAR data...

IPET and FETR: Experimental Approach for Studying Molecular Structure Dynamics by Cryo-Electron Tomography of a Single-Molecule Structure

PubMed Central

Zhang, Lei; Ren, Gang

2012-01-01

The dynamic personalities and structural heterogeneity of proteins are essential for proper functioning. Structural determination of dynamic/heterogeneous proteins is limited by conventional approaches of X-ray and electron microscopy (EM) of single-particle reconstruction that require an average from thousands to millions different molecules. Cryo-electron tomography (cryoET) is an approach to determine three-dimensional (3D) reconstruction of a single and unique biological object such as bacteria and cells, by imaging the object from a series of tilting angles. However, cconventional reconstruction methods use large-size whole-micrographs that are limited by reconstruction resolution (lower than 20 Å), especially for small and low-symmetric molecule (<400 kDa). In this study, we demonstrated the adverse effects from image distortion and the measuring tilt-errors (including tilt-axis and tilt-angle errors) both play a major role in limiting the reconstruction resolution. Therefore, we developed a “focused electron tomography reconstruction” (FETR) algorithm to improve the resolution by decreasing the reconstructing image size so that it contains only a single-instance protein. FETR can tolerate certain levels of image-distortion and measuring tilt-errors, and can also precisely determine the translational parameters via an iterative refinement process that contains a series of automatically generated dynamic filters and masks. To describe this method, a set of simulated cryoET images was employed; to validate this approach, the real experimental images from negative-staining and cryoET were used. Since this approach can obtain the structure of a single-instance molecule/particle, we named it individual-particle electron tomography (IPET) as a new robust strategy/approach that does not require a pre-given initial model, class averaging of multiple molecules or an extended ordered lattice, but can tolerate small tilt-errors for high-resolution single “snapshot” molecule structure determination. Thus, FETR/IPET provides a completely new opportunity for a single-molecule structure determination, and could be used to study the dynamic character and equilibrium fluctuation of macromolecules. PMID:22291925

Applications of emerging transmission electron microscopy technology in PCD research and diagnosis.

PubMed

Shoemark, Amelia

2017-01-01

Primary Ciliary Dyskinesia (PCD) is a heterogeneous genetic condition characterized by dysfunction of motile cilia. Patients suffer from chronic infection and inflammation of the upper and lower respiratory tract. Diagnosis of PCD is confirmed by identification of a hallmark defect of ciliary ultrastructure or by identification of biallelic pathogenic mutations in a known PCD gene. Since the first description of PCD in 1976, assessment of ciliary ultrastructure by transmission electron microscopy (TEM) has been central to diagnosis and research. Electron tomography is a technique whereby a series of transmission electron micrographs are collected at different angles and reconstructed into a single 3D model of a specimen. Electron tomography provides improved spatial information and resolution compared to a single micrograph. Research by electron tomography has revealed new insight into ciliary ultrastructure and consequently ciliary function at a molecular and cellular level. Gene discovery studies in PCD have utilized electron tomography to define the structural consequences of variants in cilia genes. Modern transmission electron microscopes capable of electron tomography are increasingly being installed in clinical laboratories. This presents the possibility for the use of tomography technique in a diagnostic setting. This review describes the electron tomography technique, the contribution tomography has made to the understanding of basic cilia structure and function and finally the potential of the technique for use in PCD diagnosis.

Preliminary Analysis of Double Shell Tomography Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pascucci, V

2009-01-16

In this project we have collaborated with LLNL scientists Dr. Peer-Timo Bremer while performing our research work on algorithmic solutions for geometric processing, image segmentation and data streaming. The main deliverable has been a 3D viewer for high-resolution imaging data with particular focus on the presentation of orthogonal slices of the double shell tomography dataset. Basic probing capabilities allow querying single voxels in the data to study in detail the information presented to the user and compensate for the intrinsic filtering and imprecision due to visualization based on colormaps. On the algorithmic front we have studied the possibility of usingmore » of non-local means filtering algorithm to achieve noise removal from tomography data. In particular we have developed a prototype that implements an accelerated version of the algorithm that may be able to take advantage of the multi-resolution sub-sampling of the ViSUS format. We have achieved promising results. Future plans include the full integration of the non-local means algorithm in the ViSUS frameworks and testing if the accelerated method will scale properly from 2D images to 3D tomography data.« less

Magnetospheric Radio Tomography: Observables, Algorithms, and Experimental Analysis

NASA Technical Reports Server (NTRS)

Cummer, Steven

2005-01-01

This grant supported research towards developing magnetospheric electron density and magnetic field remote sensing techniques via multistatic radio propagation and tomographic image reconstruction. This work was motivated by the need to better develop the basic technique of magnetospheric radio tomography, which holds substantial promise as a technology uniquely capable of imaging magnetic field and electron density in the magnetosphere on large scales with rapid cadence. Such images would provide an unprecedented and needed view into magnetospheric processes. By highlighting the systems-level interconnectedness of different regions, our understanding of space weather processes and ability to predict them would be dramatically enhanced. Three peer-reviewed publications and 5 conference presentations have resulted from this work, which supported 1 PhD student and 1 postdoctoral researcher. One more paper is in progress and will be submitted shortly. Because the main results of this research have been published or are soon to be published in refereed journal articles listed in the reference section of this document, we provide here an overview of the research and accomplishments without describing all of the details that are contained in the articles.

Static and dynamic structural characterization of nanomaterial catalysts

NASA Astrophysics Data System (ADS)

Masiel, Daniel Joseph

Heterogeneous catalysts systems are pervasive in industry, technology and academia. These systems often involve nanostructured transition metal particles that have crucial interfaces with either their supports or solid products. Understanding the nature of these interfaces as well as the structure of the catalysts and support materials themselves is crucial for the advancement of catalysis in general. Recent developments in the field of transmission electron microscopy (TEM) including dynamic transmission electron microscopy (DTEM), electron tomography, and in situ techniques stand poised to provide fresh insight into nanostructured catalyst systems. Several electron microscopy techniques are applied in this study to elucidate the mechanism of silica nanocoil growth and to discern the role of the support material and catalyst size in carbon dioxide and steam reforming of methane. The growth of silica nanocoils by faceted cobalt nanoparticles is a process that was initially believed to take place via a vapor-liquid-solid growth mechanism similar to other nanowire growth techniques. The extensive TEM work described here suggests that the process may instead occur via transport of silicate and silica species over the nanoparticle surface. Electron tomography studies of the interface between the catalyst particles and the wire indicate that they grow from edges between facets. Studies on reduction of the Co 3O4 nanoparticle precursors to the faceted pure cobalt catalysts were carried out using DTEM and in situ heating. Supported catalyst systems for methane reforming were studied using dark field scanning TEM to better understand sintering effects and the increased activity of Ni/Co catalysts supported by carbon nanotubes. Several novel electron microscopy techniques are described including annular dark field DTEM and a metaheuristic algorithm for solving the phase problem of coherent diffractive imaging. By inserting an annular dark field aperture into the back focal plane of the objective lens in a DTEM, time-resolved dark field images can be produced that have vastly improved contrast for supported catalyst materials compared to bright field DTEM imaging. A new algorithm called swarm optimized phase retrieval is described that uses a population-based approach to solve for the missing phases of diffraction data from discrete particles.

Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements

NASA Astrophysics Data System (ADS)

Norberg, Johannes; Virtanen, Ilkka I.; Roininen, Lassi; Vierinen, Juha; Orispää, Mikko; Kauristie, Kirsti; Lehtinen, Markku S.

2016-04-01

We validate two-dimensional ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. Our tomography method is based on Bayesian statistical inversion with prior distribution given by its mean and covariance. We employ ionosonde measurements for the choice of the prior mean and covariance parameters and use the Gaussian Markov random fields as a sparse matrix approximation for the numerical computations. This results in a computationally efficient tomographic inversion algorithm with clear probabilistic interpretation. We demonstrate how this method works with simultaneous beacon satellite and ionosonde measurements obtained in northern Scandinavia. The performance is compared with results obtained with a zero-mean prior and with the prior mean taken from the International Reference Ionosphere 2007 model. In validating the results, we use EISCAT ultra-high-frequency incoherent scatter radar measurements as the ground truth for the ionization profile shape. We find that in comparison to the alternative prior information sources, ionosonde measurements improve the reconstruction by adding accurate information about the absolute value and the altitude distribution of electron density. With an ionosonde at continuous disposal, the presented method enhances stand-alone near-real-time ionospheric tomography for the given conditions significantly.

An algorithm for localization of optical disturbances in turbid media using time-resolved diffuse optical tomography

NASA Astrophysics Data System (ADS)

Potlov, A. Yu.; Frolov, S. V.; Proskurin, S. G.

2018-04-01

Optical structure disturbances localization algorithm for time-resolved diffuse optical tomography of biological objects is described. The key features of the presented algorithm are: the initial approximation for the spatial distribution of the optical characteristics based on the Homogeneity Index and the assumption that all the absorbing and scattering inhomogeneities in an investigated object are spherical and have the same absorption and scattering coefficients. The described algorithm can be used in the brain structures diagnosis, in traumatology and optical mammography.

Ionospheric Asymmetry Evaluation using Tomography to Assess the Effectiveness of Radio Occultation Data Inversion

NASA Astrophysics Data System (ADS)

Shaikh, M. M.; Notarpietro, R.; Yin, P.; Nava, B.

2013-12-01

The Multi-Instrument Data Analysis System (MIDAS) algorithm is based on the oceanographic imaging techniques first applied to do the imaging of 2D slices of the ionosphere. The first version of MIDAS (version 1.0) was able to deal with any line-integral data such as GPS-ground or GPS-LEO differential-phase data or inverted ionograms. The current version extends tomography into four dimensional (lat, long, height and time) spatial-temporal mapping that combines all observations simultaneously in a single inversion with the minimum of a priori assumptions about the form of the ionospheric electron-concentration distribution. This work is an attempt to investigate the Radio Occultation (RO) data assimilation into MIDAS by assessing the ionospheric asymmetry and its impact on RO data inversion, when the Onion-peeling algorithm is used. Ionospheric RO data from COSMIC mission, specifically data collected during 24 September 2011 storm over mid-latitudes, has been used for the data assimilation. Using output electron density data from Midas (with/without RO assimilation) and ideal RO geometries, we tried to assess ionospheric asymmetry. It has been observed that the level of asymmetry was significantly increased when the storm was active. This was due to the increased ionization, which in turn produced large gradients along occulted ray path in the ionosphere. The presence of larger gradients was better observed when Midas was used with RO assimilated data. A very good correlation has been found between the evaluated asymmetry and errors related to the inversion products, when the inversion is performed considering standard techniques based on the assumption of spherical symmetry of the ionosphere. Errors are evaluated considering the peak electron density (NmF2) estimate and the Vertical TEC (VTEC) evaluation. This work highlights the importance of having a tool which should be able to state the effectiveness of Radio Occultation data inversion considering standard algorithms, like Onion-peeling, which are based on ionospheric spherical symmetry assumption. The outcome of this work will lead to find a better inversion algorithm which will deal with the ionospheric asymmetry in more realistic way. This is foreseen as a task for future research. This work has been done under the framework of TRANSMIT project (ITN Marie Curie Actions - GA No. 264476).

Real-time management of faulty electrodes in electrical impedance tomography.

PubMed

Hartinger, Alzbeta E; Guardo, Robert; Adler, Andy; Gagnon, Hervé

2009-02-01

Completely or partially disconnected electrodes are a fairly common occurrence in many electrical impedance tomography (EIT) clinical applications. Several factors can contribute to electrode disconnection: patient movement, perspiration, manipulations by clinical staff, and defective electrode leads or electronics. By corrupting several measurements, faulty electrodes introduce significant image artifacts. In order to properly manage faulty electrodes, it is necessary to: 1) account for invalid data in image reconstruction algorithms and 2) automatically detect faulty electrodes. This paper presents a two-part approach for real-time management of faulty electrodes based on the principle of voltage-current reciprocity. The first part allows accounting for faulty electrodes in EIT image reconstruction without a priori knowledge of which electrodes are at fault. The method properly weights each measurement according to its compliance with the principle of voltage-current reciprocity. Results show that the algorithm is able to automatically determine the valid portion of the data and use it to calculate high-quality images. The second part of the approach allows automatic real-time detection of at least one faulty electrode with 100% sensitivity and two faulty electrodes with 80% sensitivity enabling the clinical staff to fix the problem as soon as possible to minimize data loss.

Imaging the topside ionosphere and plasmasphere with ionospheric tomography using COSMIC GPS TEC

NASA Astrophysics Data System (ADS)

Pinto Jayawardena, Talini S.; Chartier, Alex T.; Spencer, Paul; Mitchell, Cathryn N.

2016-01-01

GPS-based ionospheric tomography is a well-known technique for imaging the total electron content (TEC) between GPS satellites and receivers. However, as an integral measurement of electron concentration, TEC typically encompasses both the ionosphere and plasmasphere, masking signatures from the topside ionosphere-plasmasphere due to the dominant ionosphere. Imaging these regions requires a technique that isolates TEC in the topside ionosphere-plasmasphere. Multi-Instrument Data Analysis System (MIDAS) employs tomography to image the electron distribution in the ionosphere. Its implementation for regions beyond is yet to be seen due to the different dynamics present above the ionosphere. This paper discusses the extension of MIDAS to image these altitudes using GPS phase-based TEC measurements and follows the work by Spencer and Mitchell (2011). Plasma is constrained to dipole field lines described by Euler potentials, resulting in a distribution symmetrical about the geomagnetic equator. A simulation of an empirical plasmaspheric model by Gallagher et al. (1988) is used to verify the technique by comparing reconstructions of the simulation with the empirical model. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) is used as GPS receiver locations. The verification is followed by a validation of the modified MIDAS algorithm, where the regions' TEC is reconstructed from COSMIC GPS phase measurements and qualitatively compared with previous studies using Jason-1 and COSMIC data. Results show that MIDAS can successfully image features/trends of the topside ionosphere-plasmasphere observed in other studies, with deviations in absolute TEC attributed to differences in data set properties and the resolution of the images.

Two-dimensional imaging of gas temperature and concentration based on hyperspectral tomography

NASA Astrophysics Data System (ADS)

Xin, Ming-yuan; Jin, Xing; Wang, Guang-yu; Song, Junling

2016-10-01

Two-dimensional imaging of gas temperature and concentration is realized by hyperspectral tomography, which has the characteristics of using multi-wavelengths absorption spectral information, so that the imaging could be accomplished in a small number of projections and viewing angles. A temperature and concentration model is established to simulate the combustion conditions and a total number of 10 near-infrared absorption spectral information of H2O is used. An improved simulated annealing algorithm by adjusting search step is performed the main search algorithm for the tomography. By adding random errors into the absorption area information, the stability of the algorithm is tested, and the results are compared with the reconstructions provided by algebraic reconstruction technique which takes advantage of 2 spectral information contents in imaging. The results show that the two methods perform equivalent in low-level noise environment, but at high-level, hyperspectral tomography turns out to be more stable.

Tomography and the Herglotz-Wiechert inverse formulation

NASA Astrophysics Data System (ADS)

Nowack, Robert L.

1990-04-01

In this paper, linearized tomography and the Herglotz-Wiechert inverse formulation are compared. Tomographic inversions for 2-D or 3-D velocity structure use line integrals along rays and can be written in terms of Radon transforms. For radially concentric structures, Radon transforms are shown to reduce to Abel transforms. Therefore, for straight ray paths, the Abel transform of travel-time is a tomographic algorithm specialized to a one-dimensional radially concentric medium. The Herglotz-Wiechert formulation uses seismic travel-time data to invert for one-dimensional earth structure and is derived using exact ray trajectories by applying an Abel transform. This is of historical interest since it would imply that a specialized tomographic-like algorithm has been used in seismology since the early part of the century (see Herglotz, 1907; Wiechert, 1910). Numerical examples are performed comparing the Herglotz-Wiechert algorithm and linearized tomography along straight rays. Since the Herglotz-Wiechert algorithm is applicable under specific conditions, (the absence of low velocity zones) to non-straight ray paths, the association with tomography may prove to be useful in assessing the uniqueness of tomographic results generalized to curved ray geometries.

On a gas electron multiplier based synthetic diagnostic for soft x-ray tomography on WEST with focus on impurity transport studies

NASA Astrophysics Data System (ADS)

Jardin, A.; Mazon, D.; Malard, P.; O'Mullane, M.; Chernyshova, M.; Czarski, T.; Malinowski, K.; Kasprowicz, G.; Wojenski, A.; Pozniak, K.

2017-08-01

The tokamak WEST aims at testing ITER divertor high heat flux component technology in long pulse operation. Unfortunately, heavy impurities like tungsten (W) sputtered from the plasma facing components can pollute the plasma core by radiation cooling in the soft x-ray (SXR) range, which is detrimental for the energy confinement and plasma stability. SXR diagnostics give valuable information to monitor impurities and study their transport. The WEST SXR diagnostic is composed of two new cameras based on the Gas Electron Multiplier (GEM) technology. The WEST GEM cameras will be used for impurity transport studies by performing 2D tomographic reconstructions with spectral resolution in tunable energy bands. In this paper, we characterize the GEM spectral response and investigate W density reconstruction thanks to a synthetic diagnostic recently developed and coupled with a tomography algorithm based on the minimum Fisher information (MFI) inversion method. The synthetic diagnostic includes the SXR source from a given plasma scenario, the photoionization, electron cloud transport and avalanche in the detection volume using Magboltz, and tomographic reconstruction of the radiation from the GEM signal. Preliminary studies of the effect of transport on the W ionization equilibrium and on the reconstruction capabilities are also presented.

Quantification of choroidal neovascularization vessel length using optical coherence tomography angiography

NASA Astrophysics Data System (ADS)

Gao, Simon S.; Liu, Li; Bailey, Steven T.; Flaxel, Christina J.; Huang, David; Li, Dengwang; Jia, Yali

2016-07-01

Quantification of choroidal neovascularization (CNV) as visualized by optical coherence tomography angiography (OCTA) may have importance clinically when diagnosing or tracking disease. Here, we present an automated algorithm to quantify the vessel skeleton of CNV as vessel length. Initial segmentation of the CNV on en face angiograms was achieved using saliency-based detection and thresholding. A level set method was then used to refine vessel edges. Finally, a skeleton algorithm was applied to identify vessel centerlines. The algorithm was tested on nine OCTA scans from participants with CNV and comparisons of the algorithm's output to manual delineation showed good agreement.

The sensitivity and negative predictive value of a pediatric cervical spine clearance algorithm that minimizes computerized tomography.

PubMed

Arbuthnot, Mary; Mooney, David P

2017-01-01

It is crucial to identify cervical spine injuries while minimizing ionizing radiation. This study analyzes the sensitivity and negative predictive value of a pediatric cervical spine clearance algorithm. We performed a retrospective review of all children <21years old who were admitted following blunt trauma and underwent cervical spine clearance utilizing our institution's cervical spine clearance algorithm over a 10-year period. Age, gender, International Classification of Diseases 9th Edition diagnosis codes, presence or absence of cervical collar on arrival, Injury Severity Score, and type of cervical spine imaging obtained were extracted from the trauma registry and electronic medical record. Descriptive statistics were used and the sensitivity and negative predictive value of the algorithm were calculated. Approximately 125,000 children were evaluated in the Emergency Department and 11,331 were admitted. Of the admitted children, 1023 patients arrived in a cervical collar without advanced cervical spine imaging and were evaluated using the cervical spine clearance algorithm. Algorithm sensitivity was 94.4% and the negative predictive value was 99.9%. There was one missed injury, a spinous process tip fracture in a teenager maintained in a collar. Our algorithm was associated with a low missed injury rate and low CT utilization rate, even in children <3years old. IV. Published by Elsevier Inc.

Digital algorithm for dispersion correction in optical coherence tomography for homogeneous and stratified media.

PubMed

Marks, Daniel L; Oldenburg, Amy L; Reynolds, J Joshua; Boppart, Stephen A

2003-01-10

The resolution of optical coherence tomography (OCT) often suffers from blurring caused by material dispersion. We present a numerical algorithm for computationally correcting the effect of material dispersion on OCT reflectance data for homogeneous and stratified media. This is experimentally demonstrated by correcting the image of a polydimethyl siloxane microfludic structure and of glass slides. The algorithm can be implemented using the fast Fourier transform. With broad spectral bandwidths and highly dispersive media or thick objects, dispersion correction becomes increasingly important.

Digital Algorithm for Dispersion Correction in Optical Coherence Tomography for Homogeneous and Stratified Media

NASA Astrophysics Data System (ADS)

Marks, Daniel L.; Oldenburg, Amy L.; Reynolds, J. Joshua; Boppart, Stephen A.

2003-01-01

The resolution of optical coherence tomography (OCT) often suffers from blurring caused by material dispersion. We present a numerical algorithm for computationally correcting the effect of material dispersion on OCT reflectance data for homogeneous and stratified media. This is experimentally demonstrated by correcting the image of a polydimethyl siloxane microfludic structure and of glass slides. The algorithm can be implemented using the fast Fourier transform. With broad spectral bandwidths and highly dispersive media or thick objects, dispersion correction becomes increasingly important.

Recent advances in electron tomography: TEM and HAADF-STEM tomography for materials science and semiconductor applications.

PubMed

Kübel, Christian; Voigt, Andreas; Schoenmakers, Remco; Otten, Max; Su, David; Lee, Tan-Chen; Carlsson, Anna; Bradley, John

2005-10-01

Electron tomography is a well-established technique for three-dimensional structure determination of (almost) amorphous specimens in life sciences applications. With the recent advances in nanotechnology and the semiconductor industry, there is also an increasing need for high-resolution three-dimensional (3D) structural information in physical sciences. In this article, we evaluate the capabilities and limitations of transmission electron microscopy (TEM) and high-angle-annular-dark-field scanning transmission electron microscopy (HAADF-STEM) tomography for the 3D structural characterization of partially crystalline to highly crystalline materials. Our analysis of catalysts, a hydrogen storage material, and different semiconductor devices shows that features with a diameter as small as 1-2 nm can be resolved in three dimensions by electron tomography. For partially crystalline materials with small single crystalline domains, bright-field TEM tomography provides reliable 3D structural information. HAADF-STEM tomography is more versatile and can also be used for high-resolution 3D imaging of highly crystalline materials such as semiconductor devices.

Angle Statistics Reconstruction: a robust reconstruction algorithm for Muon Scattering Tomography

NASA Astrophysics Data System (ADS)

Stapleton, M.; Burns, J.; Quillin, S.; Steer, C.

2014-11-01

Muon Scattering Tomography (MST) is a technique for using the scattering of cosmic ray muons to probe the contents of enclosed volumes. As a muon passes through material it undergoes multiple Coulomb scattering, where the amount of scattering is dependent on the density and atomic number of the material as well as the path length. Hence, MST has been proposed as a means of imaging dense materials, for instance to detect special nuclear material in cargo containers. Algorithms are required to generate an accurate reconstruction of the material density inside the volume from the muon scattering information and some have already been proposed, most notably the Point of Closest Approach (PoCA) and Maximum Likelihood/Expectation Maximisation (MLEM) algorithms. However, whilst PoCA-based algorithms are easy to implement, they perform rather poorly in practice. Conversely, MLEM is a complicated algorithm to implement and computationally intensive and there is currently no published, fast and easily-implementable algorithm that performs well in practice. In this paper, we first provide a detailed analysis of the source of inaccuracy in PoCA-based algorithms. We then motivate an alternative method, based on ideas first laid out by Morris et al, presenting and fully specifying an algorithm that performs well against simulations of realistic scenarios. We argue this new algorithm should be adopted by developers of Muon Scattering Tomography as an alternative to PoCA.

Reduced projection angles for binary tomography with particle aggregation.

PubMed

Al-Rifaie, Mohammad Majid; Blackwell, Tim

This paper extends particle aggregate reconstruction technique (PART), a reconstruction algorithm for binary tomography based on the movement of particles. PART supposes that pixel values are particles, and that particles diffuse through the image, staying together in regions of uniform pixel value known as aggregates. In this work, a variation of this algorithm is proposed and a focus is placed on reducing the number of projections and whether this impacts the reconstruction of images. The algorithm is tested on three phantoms of varying sizes and numbers of forward projections and compared to filtered back projection, a random search algorithm and to SART, a standard algebraic reconstruction method. It is shown that the proposed algorithm outperforms the aforementioned algorithms on small numbers of projections. This potentially makes the algorithm attractive in scenarios where collecting less projection data are inevitable.

Interferometric tomography of continuous fields with incomplete projections

NASA Technical Reports Server (NTRS)

Cha, Soyoung S.; Sun, Hogwei

1988-01-01

Interferometric tomography in the presence of an opaque object is investigated. The developed iterative algorithm does not need to augment the missing information. It is based on the successive reconstruction of the difference field, the difference between the object field to be reconstructed and its estimate, only in the difined region. The application of the algorithm results in stable convergence.

Algorithms for bioluminescence tomography incorporating anatomical information and reconstruction of tissue optical properties

PubMed Central

Naser, Mohamed A.; Patterson, Michael S.

2010-01-01

Reconstruction algorithms are presented for a two-step solution of the bioluminescence tomography (BLT) problem. In the first step, a priori anatomical information provided by x-ray computed tomography or by other methods is used to solve the continuous wave (cw) diffuse optical tomography (DOT) problem. A Taylor series expansion approximates the light fluence rate dependence on the optical properties of each region where first and second order direct derivatives of the light fluence rate with respect to scattering and absorption coefficients are obtained and used for the reconstruction. In the second step, the reconstructed optical properties at different wavelengths are used to calculate the Green’s function of the system. Then an iterative minimization solution based on the L1 norm shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. This provides an efficient BLT reconstruction algorithm with the ability to determine relative source magnitudes and positions in the presence of noise. PMID:21258486

Magnetic resonance electrical impedance tomography (MREIT): simulation study of J-substitution algorithm.

PubMed

Kwon, Ohin; Woo, Eung Je; Yoon, Jeong-Rock; Seo, Jin Keun

2002-02-01

We developed a new image reconstruction algorithm for magnetic resonance electrical impedance tomography (MREIT). MREIT is a new EIT imaging technique integrated into magnetic resonance imaging (MRI) system. Based on the assumption that internal current density distribution is obtained using magnetic resonance imaging (MRI) technique, the new image reconstruction algorithm called J-substitution algorithm produces cross-sectional static images of resistivity (or conductivity) distributions. Computer simulations show that the spatial resolution of resistivity image is comparable to that of MRI. MREIT provides accurate high-resolution cross-sectional resistivity images making resistivity values of various human tissues available for many biomedical applications.

Multi-Scale Correlative Tomography of a Li-Ion Battery Composite Cathode

PubMed Central

Moroni, Riko; Börner, Markus; Zielke, Lukas; Schroeder, Melanie; Nowak, Sascha; Winter, Martin; Manke, Ingo; Zengerle, Roland; Thiele, Simon

2016-01-01

Focused ion beam/scanning electron microscopy tomography (FIB/SEMt) and synchrotron X-ray tomography (Xt) are used to investigate the same lithium manganese oxide composite cathode at the same specific spot. This correlative approach allows the investigation of three central issues in the tomographic analysis of composite battery electrodes: (i) Validation of state-of-the-art binary active material (AM) segmentation: Although threshold segmentation by standard algorithms leads to very good segmentation results, limited Xt resolution results in an AM underestimation of 6 vol% and severe overestimation of AM connectivity. (ii) Carbon binder domain (CBD) segmentation in Xt data: While threshold segmentation cannot be applied for this purpose, a suitable classification method is introduced. Based on correlative tomography, it allows for reliable ternary segmentation of Xt data into the pore space, CBD, and AM. (iii) Pore space analysis in the micrometer regime: This segmentation technique is applied to an Xt reconstruction with several hundred microns edge length, thus validating the segmentation of pores within the micrometer regime for the first time. The analyzed cathode volume exhibits a bimodal pore size distribution in the ranges between 0–1 μm and 1–12 μm. These ranges can be attributed to different pore formation mechanisms. PMID:27456201

Diffuse optical tomography for breast cancer imaging guided by computed tomography: A feasibility study.

PubMed

Baikejiang, Reheman; Zhang, Wei; Li, Changqing

2017-01-01

Diffuse optical tomography (DOT) has attracted attentions in the last two decades due to its intrinsic sensitivity in imaging chromophores of tissues such as hemoglobin, water, and lipid. However, DOT has not been clinically accepted yet due to its low spatial resolution caused by strong optical scattering in tissues. Structural guidance provided by an anatomical imaging modality enhances the DOT imaging substantially. Here, we propose a computed tomography (CT) guided multispectral DOT imaging system for breast cancer imaging. To validate its feasibility, we have built a prototype DOT imaging system which consists of a laser at the wavelength of 650 nm and an electron multiplying charge coupled device (EMCCD) camera. We have validated the CT guided DOT reconstruction algorithms with numerical simulations and phantom experiments, in which different imaging setup parameters, such as projection number of measurements and width of measurement patch, have been investigated. Our results indicate that an air-cooling EMCCD camera is good enough for the transmission mode DOT imaging. We have also found that measurements at six angular projections are sufficient for DOT to reconstruct the optical targets with 2 and 4 times absorption contrast when the CT guidance is applied. Finally, we have described our future research plan on integration of a multispectral DOT imaging system into a breast CT scanner.

Role of radionuclide imaging for diagnosis of device and prosthetic valve infections

PubMed Central

Sarrazin, Jean-François; Philippon, François; Trottier, Mikaël; Tessier, Michel

2016-01-01

Cardiovascular implantable electronic device (CIED) infection and prosthetic valve endocarditis (PVE) remain a diagnostic challenge. Cardiac imaging plays an important role in the diagnosis and management of patients with CIED infection or PVE. Over the past few years, cardiac radionuclide imaging has gained a key role in the diagnosis of these patients, and in assessing the need for surgery, mainly in the most difficult cases. Both 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) and radiolabelled white blood cell single-photon emission computed tomography/computed tomography (WBC SPECT/CT) have been studied in these situations. In their 2015 guidelines for the management of infective endocarditis, the European Society of Cardiology incorporated cardiac nuclear imaging as part of their diagnostic algorithm for PVE, but not CIED infection since the data were judged insufficient at the moment. This article reviews the actual knowledge and recent studies on the use of 18F-FDG PET/CT and WBC SPECT/CT in the context of CIED infection and PVE, and describes the technical aspects of cardiac radionuclide imaging. It also discusses their accepted and potential indications for the diagnosis and management of CIED infection and PVE, the limitations of these tests, and potential areas of future research. PMID:27721936

Investigation of the reconstruction accuracy of guided wave tomography using full waveform inversion

NASA Astrophysics Data System (ADS)

Rao, Jing; Ratassepp, Madis; Fan, Zheng

2017-07-01

Guided wave tomography is a promising tool to accurately determine the remaining wall thicknesses of corrosion damages, which are among the major concerns for many industries. Full Waveform Inversion (FWI) algorithm is an attractive guided wave tomography method, which uses a numerical forward model to predict the waveform of guided waves when propagating through corrosion defects, and an inverse model to reconstruct the thickness map from the ultrasonic signals captured by transducers around the defect. This paper discusses the reconstruction accuracy of the FWI algorithm on plate-like structures by using simulations as well as experiments. It was shown that this algorithm can obtain a resolution of around 0.7 wavelengths for defects with smooth depth variations from the acoustic modeling data, and about 1.5-2 wavelengths from the elastic modeling data. Further analysis showed that the reconstruction accuracy is also dependent on the shape of the defect. It was demonstrated that the algorithm maintains the accuracy in the case of multiple defects compared to conventional algorithms based on Born approximation.

Feasibility study for mega-electron-volt electron beam tomography.

PubMed

Hampel, U; Bärtling, Y; Hoppe, D; Kuksanov, N; Fadeev, S; Salimov, R

2012-09-01

Electron beam tomography is a promising imaging modality for the study of fast technical processes. But for many technical objects of interest x rays of several hundreds of keV energy are required to achieve sufficient material penetration. In this article we report on a feasibility study for fast electron beam computed tomography with a 1 MeV electron beam. The experimental setup comprises an electrostatic accelerator with beam optics, transmission target, and a single x-ray detector. We employed an inverse fan-beam tomography approach with radiographic projections being generated from the linearly moving x-ray source. Angular projections were obtained by rotating the object.

Using Machine Learning and Natural Language Processing Algorithms to Automate the Evaluation of Clinical Decision Support in Electronic Medical Record Systems.

PubMed

Szlosek, Donald A; Ferrett, Jonathan

2016-01-01

As the number of clinical decision support systems (CDSSs) incorporated into electronic medical records (EMRs) increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. The authors use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an EMR system, and they compare it against manual evaluation. Modeled after the EMR system EPIC at Maine Medical Center, we developed a dummy data set containing physician notes in free text for 3,621 artificial patients records undergoing a head computed tomography (CT) scan for mild traumatic brain injury after the incorporation of an electronic best practice approach. We validated the accuracy of the Best Practice Advisories (BPA) using three machine learning algorithms-C-Support Vector Classification (SVC), Decision Tree Classifier (DecisionTreeClassifier), k-nearest neighbors classifier (KNeighborsClassifier)-by comparing their accuracy for adjudicating the occurrence of a mild traumatic brain injury against manual review. We then used the best of the three algorithms to evaluate the effectiveness of the BPA, and we compared the algorithm's evaluation of the BPA to that of manual review. The electronic best practice approach was found to have a sensitivity of 98.8 percent (96.83-100.0), specificity of 10.3 percent, PPV = 7.3 percent, and NPV = 99.2 percent when reviewed manually by abstractors. Though all the machine learning algorithms were observed to have a high level of prediction, the SVC displayed the highest with a sensitivity 93.33 percent (92.49-98.84), specificity of 97.62 percent (96.53-98.38), PPV = 50.00, NPV = 99.83. The SVC algorithm was observed to have a sensitivity of 97.9 percent (94.7-99.86), specificity 10.30 percent, PPV 7.25 percent, and NPV 99.2 percent for evaluating the best practice approach, after accounting for 17 cases (0.66 percent) where the patient records had to be reviewed manually due to the NPL systems inability to capture the proper diagnosis. CDSSs incorporated into EMRs can be evaluated in an automatic fashion by using NLP and machine learning techniques.

Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography.

PubMed

Liu, Li; Gao, Simon S; Bailey, Steven T; Huang, David; Li, Dengwang; Jia, Yali

2015-09-01

Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area.

X-Ray Radiography of Gas Turbine Ceramics.

DTIC Science & Technology

1979-10-20

Microfocus X-ray equipment. 1a4ihe definition of equipment concepts for a computer assisted tomography ( CAT ) system; and 4ffthe development of a CAT ...were obtained from these test coupons using Microfocus X-ray and image en- hancement techniques. A Computer Assisted Tomography ( CAT ) design concept...monitor. Computer reconstruction algorithms were investigated with respect to CAT and a preferred approach was determined. An appropriate CAT algorithm

Sparse-view proton computed tomography using modulated proton beams.

PubMed

Lee, Jiseoc; Kim, Changhwan; Min, Byungjun; Kwak, Jungwon; Park, Seyjoon; Lee, Se Byeong; Park, Sungyong; Cho, Seungryong

2015-02-01

Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT. Proton projection images were acquired using the modulated proton beams and the EBT2 film as an intensity detector. Four electron-density cylinders representing normal soft tissues and bone were used as imaged object and scanned at 40 views that are equally separated over 360°. Digitized film images were converted to water-equivalent thickness by use of an empirically derived conversion curve. For improving the image quality, a deconvolution-based image deblurring with an empirically acquired point spread function was employed. They have implemented iterative image reconstruction algorithms such as adaptive steepest descent-projection onto convex sets (ASD-POCS), superiorization method-projection onto convex sets (SM-POCS), superiorization method-expectation maximization (SM-EM), and expectation maximization-total variation minimization (EM-TV). Performance of the four image reconstruction algorithms was analyzed and compared quantitatively via contrast-to-noise ratio (CNR) and root-mean-square-error (RMSE). Objects of higher electron density have been reconstructed more accurately than those of lower density objects. The bone, for example, has been reconstructed within 1% error. EM-based algorithms produced an increased image noise and RMSE as the iteration reaches about 20, while the POCS-based algorithms showed a monotonic convergence with iterations. The ASD-POCS algorithm outperformed the others in terms of CNR, RMSE, and the accuracy of the reconstructed relative stopping power in the region of lung and soft tissues. The four iterative algorithms, i.e., ASD-POCS, SM-POCS, SM-EM, and EM-TV, have been developed and applied for proton CT image reconstruction. Although it still seems that the images need to be improved for practical applications to the treatment planning, proton CT imaging by use of the modulated beams in sparse-view sampling has demonstrated its feasibility.

A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy

DOE PAGES

Pryor, Alan; Ophus, Colin; Miao, Jianwei

2017-10-25

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. In this paper, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditionalmore » multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic, using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic.« less

A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy.

PubMed

Pryor, Alan; Ophus, Colin; Miao, Jianwei

2017-01-01

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. Here, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditional multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic , using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic .

A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pryor, Alan; Ophus, Colin; Miao, Jianwei

Simulation of atomic-resolution image formation in scanning transmission electron microscopy can require significant computation times using traditional methods. A recently developed method, termed plane-wave reciprocal-space interpolated scattering matrix (PRISM), demonstrates potential for significant acceleration of such simulations with negligible loss of accuracy. In this paper, we present a software package called Prismatic for parallelized simulation of image formation in scanning transmission electron microscopy (STEM) using both the PRISM and multislice methods. By distributing the workload between multiple CUDA-enabled GPUs and multicore processors, accelerations as high as 1000 × for PRISM and 15 × for multislice are achieved relative to traditionalmore » multislice implementations using a single 4-GPU machine. We demonstrate a potentially important application of Prismatic, using it to compute images for atomic electron tomography at sufficient speeds to include in the reconstruction pipeline. Prismatic is freely available both as an open-source CUDA/C++ package with a graphical user interface and as a Python package, PyPrismatic.« less

An iterative three-dimensional electron density imaging algorithm using uncollimated compton scattered x rays from a polyenergetic primary pencil beam.

PubMed

Van Uytven, Eric; Pistorius, Stephen; Gordon, Richard

2007-01-01

X-ray film-screen mammography is currently the gold standard for detecting breast cancer. However, one disadvantage is that it projects a three-dimensional (3D) object onto a two-dimensional (2D) image, reducing contrast between small lesions and layers of normal tissue. Another limitation is its reduced sensitivity in women with mammographically dense breasts. Computed tomography (CT) produces a 3D image yet has had a limited role in mammography due to its relatively high dose, low resolution, and low contrast. As a first step towards implementing quantitative 3D mammography, which may improve the ability to detect and specify breast tumors, we have developed an analytical technique that can use Compton scatter to obtain 3D information of an object from a single projection. Imaging material with a pencil beam of polychromatic x rays produces a characteristic scattered photon spectrum at each point on the detector plane. A comparable distribution may be calculated using a known incident x-ray energy spectrum, beam shape, and an initial estimate of the object's 3D mass attenuation and electron density. Our iterative minimization algorithm changes the initially arbitrary electron density voxel matrix to reduce regular differences between the analytically predicted and experimentally measured spectra at each point on the detector plane. The simulated electron density converges to that of the object as the differences are minimized. The reconstruction algorithm has been validated using simulated data produced by the EGSnrc Monte Carlo code system. We applied the imaging algorithm to a cylindrically symmetric breast tissue phantom containing multiple inhomogeneities. A preliminary ROC analysis scores greater than 0.96, which indicate that under the described simplifying conditions, this approach shows promise in identifying and localizing inhomogeneities which simulate 0.5 mm calcifications with an image voxel resolution of 0.25 cm and at a dose comparable to mammography.

Interior tomography in microscopic CT with image reconstruction constrained by full field of view scan at low spatial resolution

NASA Astrophysics Data System (ADS)

Luo, Shouhua; Shen, Tao; Sun, Yi; Li, Jing; Li, Guang; Tang, Xiangyang

2018-04-01

In high resolution (microscopic) CT applications, the scan field of view should cover the entire specimen or sample to allow complete data acquisition and image reconstruction. However, truncation may occur in projection data and results in artifacts in reconstructed images. In this study, we propose a low resolution image constrained reconstruction algorithm (LRICR) for interior tomography in microscopic CT at high resolution. In general, the multi-resolution acquisition based methods can be employed to solve the data truncation problem if the project data acquired at low resolution are utilized to fill up the truncated projection data acquired at high resolution. However, most existing methods place quite strict restrictions on the data acquisition geometry, which greatly limits their utility in practice. In the proposed LRICR algorithm, full and partial data acquisition (scan) at low and high resolutions, respectively, are carried out. Using the image reconstructed from sparse projection data acquired at low resolution as the prior, a microscopic image at high resolution is reconstructed from the truncated projection data acquired at high resolution. Two synthesized digital phantoms, a raw bamboo culm and a specimen of mouse femur, were utilized to evaluate and verify performance of the proposed LRICR algorithm. Compared with the conventional TV minimization based algorithm and the multi-resolution scout-reconstruction algorithm, the proposed LRICR algorithm shows significant improvement in reduction of the artifacts caused by data truncation, providing a practical solution for high quality and reliable interior tomography in microscopic CT applications. The proposed LRICR algorithm outperforms the multi-resolution scout-reconstruction method and the TV minimization based reconstruction for interior tomography in microscopic CT.

Acoustic Inversion in Optoacoustic Tomography: A Review

PubMed Central

Rosenthal, Amir; Ntziachristos, Vasilis; Razansky, Daniel

2013-01-01

Optoacoustic tomography enables volumetric imaging with optical contrast in biological tissue at depths beyond the optical mean free path by the use of optical excitation and acoustic detection. The hybrid nature of optoacoustic tomography gives rise to two distinct inverse problems: The optical inverse problem, related to the propagation of the excitation light in tissue, and the acoustic inverse problem, which deals with the propagation and detection of the generated acoustic waves. Since the two inverse problems have different physical underpinnings and are governed by different types of equations, they are often treated independently as unrelated problems. From an imaging standpoint, the acoustic inverse problem relates to forming an image from the measured acoustic data, whereas the optical inverse problem relates to quantifying the formed image. This review focuses on the acoustic aspects of optoacoustic tomography, specifically acoustic reconstruction algorithms and imaging-system practicalities. As these two aspects are intimately linked, and no silver bullet exists in the path towards high-performance imaging, we adopt a holistic approach in our review and discuss the many links between the two aspects. Four classes of reconstruction algorithms are reviewed: time-domain (so called back-projection) formulae, frequency-domain formulae, time-reversal algorithms, and model-based algorithms. These algorithms are discussed in the context of the various acoustic detectors and detection surfaces which are commonly used in experimental studies. We further discuss the effects of non-ideal imaging scenarios on the quality of reconstruction and review methods that can mitigate these effects. Namely, we consider the cases of finite detector aperture, limited-view tomography, spatial under-sampling of the acoustic signals, and acoustic heterogeneities and losses. PMID:24772060

High reliability - low noise radionuclide signature identification algorithms for border security applications

NASA Astrophysics Data System (ADS)

Lee, Sangkyu

Illicit trafficking and smuggling of radioactive materials and special nuclear materials (SNM) are considered as one of the most important recent global nuclear threats. Monitoring the transport and safety of radioisotopes and SNM are challenging due to their weak signals and easy shielding. Great efforts worldwide are focused at developing and improving the detection technologies and algorithms, for accurate and reliable detection of radioisotopes of interest in thus better securing the borders against nuclear threats. In general, radiation portal monitors enable detection of gamma and neutron emitting radioisotopes. Passive or active interrogation techniques, present and/or under the development, are all aimed at increasing accuracy, reliability, and in shortening the time of interrogation as well as the cost of the equipment. Equally important efforts are aimed at advancing algorithms to process the imaging data in an efficient manner providing reliable "readings" of the interiors of the examined volumes of various sizes, ranging from cargos to suitcases. The main objective of this thesis is to develop two synergistic algorithms with the goal to provide highly reliable - low noise identification of radioisotope signatures. These algorithms combine analysis of passive radioactive detection technique with active interrogation imaging techniques such as gamma radiography or muon tomography. One algorithm consists of gamma spectroscopy and cosmic muon tomography, and the other algorithm is based on gamma spectroscopy and gamma radiography. The purpose of fusing two detection methodologies per algorithm is to find both heavy-Z radioisotopes and shielding materials, since radionuclides can be identified with gamma spectroscopy, and shielding materials can be detected using muon tomography or gamma radiography. These combined algorithms are created and analyzed based on numerically generated images of various cargo sizes and materials. In summary, the three detection methodologies are fused into two algorithms with mathematical functions providing: reliable identification of radioisotopes in gamma spectroscopy; noise reduction and precision enhancement in muon tomography; and the atomic number and density estimation in gamma radiography. It is expected that these new algorithms maybe implemented at portal scanning systems with the goal to enhance the accuracy and reliability in detecting nuclear materials inside the cargo containers.

A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.

PubMed

De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc

2010-09-01

In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.

Wavelet tree structure based speckle noise removal for optical coherence tomography

NASA Astrophysics Data System (ADS)

Yuan, Xin; Liu, Xuan; Liu, Yang

2018-02-01

We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.

Development of seismic tomography software for hybrid supercomputers

NASA Astrophysics Data System (ADS)

Nikitin, Alexandr; Serdyukov, Alexandr; Duchkov, Anton

2015-04-01

Seismic tomography is a technique used for computing velocity model of geologic structure from first arrival travel times of seismic waves. The technique is used in processing of regional and global seismic data, in seismic exploration for prospecting and exploration of mineral and hydrocarbon deposits, and in seismic engineering for monitoring the condition of engineering structures and the surrounding host medium. As a consequence of development of seismic monitoring systems and increasing volume of seismic data, there is a growing need for new, more effective computational algorithms for use in seismic tomography applications with improved performance, accuracy and resolution. To achieve this goal, it is necessary to use modern high performance computing systems, such as supercomputers with hybrid architecture that use not only CPUs, but also accelerators and co-processors for computation. The goal of this research is the development of parallel seismic tomography algorithms and software package for such systems, to be used in processing of large volumes of seismic data (hundreds of gigabytes and more). These algorithms and software package will be optimized for the most common computing devices used in modern hybrid supercomputers, such as Intel Xeon CPUs, NVIDIA Tesla accelerators and Intel Xeon Phi co-processors. In this work, the following general scheme of seismic tomography is utilized. Using the eikonal equation solver, arrival times of seismic waves are computed based on assumed velocity model of geologic structure being analyzed. In order to solve the linearized inverse problem, tomographic matrix is computed that connects model adjustments with travel time residuals, and the resulting system of linear equations is regularized and solved to adjust the model. The effectiveness of parallel implementations of existing algorithms on target architectures is considered. During the first stage of this work, algorithms were developed for execution on supercomputers using multicore CPUs only, with preliminary performance tests showing good parallel efficiency on large numerical grids. Porting of the algorithms to hybrid supercomputers is currently ongoing.

Minimal-scan filtered backpropagation algorithms for diffraction tomography.

PubMed

Pan, X; Anastasio, M A

1999-12-01

The filtered backpropagation (FBPP) algorithm, originally developed by Devaney [Ultrason. Imaging 4, 336 (1982)], has been widely used for reconstructing images in diffraction tomography. It is generally known that the FBPP algorithm requires scattered data from a full angular range of 2 pi for exact reconstruction of a generally complex-valued object function. However, we reveal that one needs scattered data only over the angular range 0 < or = phi < or = 3 pi/2 for exact reconstruction of a generally complex-valued object function. Using this insight, we develop and analyze a family of minimal-scan filtered backpropagation (MS-FBPP) algorithms, which, unlike the FBPP algorithm, use scattered data acquired from view angles over the range 0 < or = phi < or = 3 pi/2. We show analytically that these MS-FBPP algorithms are mathematically identical to the FBPP algorithm. We also perform computer simulation studies for validation, demonstration, and comparison of these MS-FBPP algorithms. The numerical results in these simulation studies corroborate our theoretical assertions.

Fourier domain preconditioned conjugate gradient algorithm for atmospheric tomography.

PubMed

Yang, Qiang; Vogel, Curtis R; Ellerbroek, Brent L

2006-07-20

By 'atmospheric tomography' we mean the estimation of a layered atmospheric turbulence profile from measurements of the pupil-plane phase (or phase gradients) corresponding to several different guide star directions. We introduce what we believe to be a new Fourier domain preconditioned conjugate gradient (FD-PCG) algorithm for atmospheric tomography, and we compare its performance against an existing multigrid preconditioned conjugate gradient (MG-PCG) approach. Numerical results indicate that on conventional serial computers, FD-PCG is as accurate and robust as MG-PCG, but it is from one to two orders of magnitude faster for atmospheric tomography on 30 m class telescopes. Simulations are carried out for both natural guide stars and for a combination of finite-altitude laser guide stars and natural guide stars to resolve tip-tilt uncertainty.

Comparisons of hybrid radiosity-diffusion model and diffusion equation for bioluminescence tomography in cavity cancer detection

NASA Astrophysics Data System (ADS)

Chen, Xueli; Yang, Defu; Qu, Xiaochao; Hu, Hao; Liang, Jimin; Gao, Xinbo; Tian, Jie

2012-06-01

Bioluminescence tomography (BLT) has been successfully applied to the detection and therapeutic evaluation of solid cancers. However, the existing BLT reconstruction algorithms are not accurate enough for cavity cancer detection because of neglecting the void problem. Motivated by the ability of the hybrid radiosity-diffusion model (HRDM) in describing the light propagation in cavity organs, an HRDM-based BLT reconstruction algorithm was provided for the specific problem of cavity cancer detection. HRDM has been applied to optical tomography but is limited to simple and regular geometries because of the complexity in coupling the boundary between the scattering and void region. In the provided algorithm, HRDM was first applied to three-dimensional complicated and irregular geometries and then employed as the forward light transport model to describe the bioluminescent light propagation in tissues. Combining HRDM with the sparse reconstruction strategy, the cavity cancer cells labeled with bioluminescent probes can be more accurately reconstructed. Compared with the diffusion equation based reconstruction algorithm, the essentiality and superiority of the HRDM-based algorithm were demonstrated with simulation, phantom and animal studies. An in vivo gastric cancer-bearing nude mouse experiment was conducted, whose results revealed the ability and feasibility of the HRDM-based algorithm in the biomedical application of gastric cancer detection.

Comparisons of hybrid radiosity-diffusion model and diffusion equation for bioluminescence tomography in cavity cancer detection.

PubMed

Chen, Xueli; Yang, Defu; Qu, Xiaochao; Hu, Hao; Liang, Jimin; Gao, Xinbo; Tian, Jie

2012-06-01

Bioluminescence tomography (BLT) has been successfully applied to the detection and therapeutic evaluation of solid cancers. However, the existing BLT reconstruction algorithms are not accurate enough for cavity cancer detection because of neglecting the void problem. Motivated by the ability of the hybrid radiosity-diffusion model (HRDM) in describing the light propagation in cavity organs, an HRDM-based BLT reconstruction algorithm was provided for the specific problem of cavity cancer detection. HRDM has been applied to optical tomography but is limited to simple and regular geometries because of the complexity in coupling the boundary between the scattering and void region. In the provided algorithm, HRDM was first applied to three-dimensional complicated and irregular geometries and then employed as the forward light transport model to describe the bioluminescent light propagation in tissues. Combining HRDM with the sparse reconstruction strategy, the cavity cancer cells labeled with bioluminescent probes can be more accurately reconstructed. Compared with the diffusion equation based reconstruction algorithm, the essentiality and superiority of the HRDM-based algorithm were demonstrated with simulation, phantom and animal studies. An in vivo gastric cancer-bearing nude mouse experiment was conducted, whose results revealed the ability and feasibility of the HRDM-based algorithm in the biomedical application of gastric cancer detection.

HAADF-STEM atom counting in atom probe tomography specimens: Towards quantitative correlative microscopy.

PubMed

Lefebvre, W; Hernandez-Maldonado, D; Moyon, F; Cuvilly, F; Vaudolon, C; Shinde, D; Vurpillot, F

2015-12-01

The geometry of atom probe tomography tips strongly differs from standard scanning transmission electron microscopy foils. Whereas the later are rather flat and thin (<20 nm), tips display a curved surface and a significantly larger thickness. As far as a correlative approach aims at analysing the same specimen by both techniques, it is mandatory to explore the limits and advantages imposed by the particular geometry of atom probe tomography specimens. Based on simulations (electron probe propagation and image simulations), the possibility to apply quantitative high angle annular dark field scanning transmission electron microscopy to of atom probe tomography specimens has been tested. The influence of electron probe convergence and the benefice of deconvolution of electron probe point spread function electron have been established. Atom counting in atom probe tomography specimens is for the first time reported in this present work. It is demonstrated that, based on single projections of high angle annular dark field imaging, significant quantitative information can be used as additional input for refining the data obtained by correlative analysis of the specimen in APT, therefore opening new perspectives in the field of atomic scale tomography. Copyright © 2015 Elsevier B.V. All rights reserved.

Physically corrected forward operators for induced emission tomography: a simulation study

NASA Astrophysics Data System (ADS)

Viganò, Nicola Roberto; Solé, Vicente Armando

2018-03-01

X-ray emission tomography techniques over non-radioactive materials allow one to investigate different and important aspects of the matter that are usually not addressable with the standard x-ray transmission tomography, such as density, chemical composition and crystallographic information. However, the quantitative reconstruction of these investigated properties is hindered by additional problems, including the self-attenuation of the emitted radiation. Work has been done in the past, especially concerning x-ray fluorescence tomography, but this has always focused on solving very specific problems. The novelty of this work resides in addressing the problem of induced emission tomography from a much wider perspective, introducing a unified discrete representation that can be used to modify existing algorithms to reconstruct the data of the different types of experiments. The direct outcome is a clear and easy mathematical description of the implementation details of such algorithms, despite small differences in geometry and other practical aspects, but also the possibility to express the reconstruction as a minimization problem, allowing the use of variational methods, and a more flexible modeling of the noise involved in the detection process. In addition, we look at the results of a few selected simulated data reconstructions that describe the effect of physical corrections like the self-attenuation, and the response to noise of the adapted reconstruction algorithms.

Multiscale solvers and systematic upscaling in computational physics

NASA Astrophysics Data System (ADS)

Brandt, A.

2005-07-01

Multiscale algorithms can overcome the scale-born bottlenecks that plague most computations in physics. These algorithms employ separate processing at each scale of the physical space, combined with interscale iterative interactions, in ways which use finer scales very sparingly. Having been developed first and well known as multigrid solvers for partial differential equations, highly efficient multiscale techniques have more recently been developed for many other types of computational tasks, including: inverse PDE problems; highly indefinite (e.g., standing wave) equations; Dirac equations in disordered gauge fields; fast computation and updating of large determinants (as needed in QCD); fast integral transforms; integral equations; astrophysics; molecular dynamics of macromolecules and fluids; many-atom electronic structures; global and discrete-state optimization; practical graph problems; image segmentation and recognition; tomography (medical imaging); fast Monte-Carlo sampling in statistical physics; and general, systematic methods of upscaling (accurate numerical derivation of large-scale equations from microscopic laws).

Resolution Study of a Hyperspectral Sensor using Computed Tomography in the Presence of Noise

DTIC Science & Technology

2012-06-14

diffraction efficiency is dependent on wavelength. Compared to techniques developed by later work, simple algebraic reconstruction techniques were used...spectral di- mension, using computed tomography (CT) techniques with only a finite number of diverse images. CTHIS require a reconstruction algorithm in...many frames are needed to reconstruct the spectral cube of a simple object using a theoretical lower bound. In this research a new algorithm is derived

Wavelet methods in multi-conjugate adaptive optics

NASA Astrophysics Data System (ADS)

Helin, T.; Yudytskiy, M.

2013-08-01

The next generation ground-based telescopes rely heavily on adaptive optics for overcoming the limitation of atmospheric turbulence. In the future adaptive optics modalities, like multi-conjugate adaptive optics (MCAO), atmospheric tomography is the major mathematical and computational challenge. In this severely ill-posed problem, a fast and stable reconstruction algorithm is needed that can take into account many real-life phenomena of telescope imaging. We introduce a novel reconstruction method for the atmospheric tomography problem and demonstrate its performance and flexibility in the context of MCAO. Our method is based on using locality properties of compactly supported wavelets, both in the spatial and frequency domains. The reconstruction in the atmospheric tomography problem is obtained by solving the Bayesian MAP estimator with a conjugate-gradient-based algorithm. An accelerated algorithm with preconditioning is also introduced. Numerical performance is demonstrated on the official end-to-end simulation tool OCTOPUS of European Southern Observatory.

FPGA-Based Pulse Pile-Up Correction With Energy and Timing Recovery.

PubMed

Haselman, M D; Pasko, J; Hauck, S; Lewellen, T K; Miyaoka, R S

2012-10-01

Modern field programmable gate arrays (FPGAs) are capable of performing complex discrete signal processing algorithms with clock rates well above 100 MHz. This, combined with FPGA's low expense, ease of use, and selected dedicated hardware make them an ideal technology for a data acquisition system for a positron emission tomography (PET) scanner. The University of Washington is producing a high-resolution, small-animal PET scanner that utilizes FPGAs as the core of the front-end electronics. For this scanner, functions that are typically performed in dedicated circuits, or offline, are being migrated to the FPGA. This will not only simplify the electronics, but the features of modern FPGAs can be utilized to add significant signal processing power to produce higher quality images. In this paper we report on an all-digital pulse pile-up correction algorithm that has been developed for the FPGA. The pile-up mitigation algorithm will allow the scanner to run at higher count rates without incurring large data losses due to the overlapping of scintillation signals. This correction technique utilizes a reference pulse to extract timing and energy information for most pile-up events. Using pulses acquired from a Zecotech Photonics MAPD-N with an LFS-3 scintillator, we show that good timing and energy information can be achieved in the presence of pile-up utilizing a moderate amount of FPGA resources.

Teleseismic tomography for imaging Earth's upper mantle

NASA Astrophysics Data System (ADS)

Aktas, Kadircan

Teleseismic tomography is an important imaging tool in earthquake seismology, used to characterize lithospheric structure beneath a region of interest. In this study I investigate three different tomographic techniques applied to real and synthetic teleseismic data, with the aim of imaging the velocity structure of the upper mantle. First, by applying well established traveltime tomographic techniques to teleseismic data from southern Ontario, I obtained high-resolution images of the upper mantle beneath the lower Great Lakes. Two salient features of the 3D models are: (1) a patchy, NNW-trending low-velocity region, and (2) a linear, NE-striking high-velocity anomaly. I interpret the high-velocity anomaly as a possible relict slab associated with ca. 1.25 Ga subduction, whereas the low-velocity anomaly is interpreted as a zone of alteration and metasomatism associated with the ascent of magmas that produced the Late Cretaceous Monteregian plutons. The next part of the thesis is concerned with adaptation of existing full-waveform tomographic techniques for application to teleseismic body-wave observations. The method used here is intended to be complementary to traveltime tomography, and to take advantage of efficient frequency-domain methodologies that have been developed for inverting large controlled-source datasets. Existing full-waveform acoustic modelling and inversion codes have been modified to handle plane waves impinging from the base of the lithospheric model at a known incidence angle. A processing protocol has been developed to prepare teleseismic observations for the inversion algorithm. To assess the validity of the acoustic approximation, the processing procedure and modelling-inversion algorithm were tested using synthetic seismograms computed using an elastic Kirchhoff integral method. These tests were performed to evaluate the ability of the frequency-domain full-waveform inversion algorithm to recover topographic variations of the Moho under a variety of realistic scenarios. Results show that frequency-domain full-waveform tomography is generally successful in recovering both sharp and discontinuous features. Thirdly, I developed a new method for creating an initial background velocity model for the inversion algorithm, which is sufficiently close to the true model so that convergence is likely to be achieved. I adapted a method named Deformable Layer Tomography (DLT), which adjusts interfaces between layers rather than velocities within cells. I applied this method to a simple model comprising a single uniform crustal layer and a constant-velocity mantle, separated by an irregular Moho interface. A series of tests was performed to evaluate the sensitivity of the DLT algorithm; the results show that my algorithm produces useful results within a realistic range of incident-wave obliquity, incidence angle and signal-to-noise level. Keywords. Teleseismic tomography, full waveform tomography, deformable layer tomography, lower Great Lakes, crust and upper mantle.

Regularization iteration imaging algorithm for electrical capacitance tomography

NASA Astrophysics Data System (ADS)

Tong, Guowei; Liu, Shi; Chen, Hongyan; Wang, Xueyao

2018-03-01

The image reconstruction method plays a crucial role in real-world applications of the electrical capacitance tomography technique. In this study, a new cost function that simultaneously considers the sparsity and low-rank properties of the imaging targets is proposed to improve the quality of the reconstruction images, in which the image reconstruction task is converted into an optimization problem. Within the framework of the split Bregman algorithm, an iterative scheme that splits a complicated optimization problem into several simpler sub-tasks is developed to solve the proposed cost function efficiently, in which the fast-iterative shrinkage thresholding algorithm is introduced to accelerate the convergence. Numerical experiment results verify the effectiveness of the proposed algorithm in improving the reconstruction precision and robustness.

Acceptance test of a commercially available software for automatic image registration of computed tomography (CT), magnetic resonance imaging (MRI) and 99mTc-methoxyisobutylisonitrile (MIBI) single-photon emission computed tomography (SPECT) brain images.

PubMed

Loi, Gianfranco; Dominietto, Marco; Manfredda, Irene; Mones, Eleonora; Carriero, Alessandro; Inglese, Eugenio; Krengli, Marco; Brambilla, Marco

2008-09-01

This note describes a method to characterize the performances of image fusion software (Syntegra) with respect to accuracy and robustness. Computed tomography (CT), magnetic resonance imaging (MRI), and single-photon emission computed tomography (SPECT) studies were acquired from two phantoms and 10 patients. Image registration was performed independently by two couples composed of one radiotherapist and one physicist by means of superposition of anatomic landmarks. Each couple performed jointly and saved the registration. The two solutions were averaged to obtain the gold standard registration. A new set of estimators was defined to identify translation and rotation errors in the coordinate axes, independently from point position in image field of view (FOV). Algorithms evaluated were local correlation (LC) for CT-MRI, normalized mutual information (MI) for CT-MRI, and CT-SPECT registrations. To evaluate accuracy, estimator values were compared to limiting values for the algorithms employed, both in phantoms and in patients. To evaluate robustness, different alignments between images taken from a sample patient were produced and registration errors determined. LC algorithm resulted accurate in CT-MRI registrations in phantoms, but exceeded limiting values in 3 of 10 patients. MI algorithm resulted accurate in CT-MRI and CT-SPECT registrations in phantoms; limiting values were exceeded in one case in CT-MRI and never reached in CT-SPECT registrations. Thus, the evaluation of robustness was restricted to the algorithm of MI both for CT-MRI and CT-SPECT registrations. The algorithm of MI proved to be robust: limiting values were not exceeded with translation perturbations up to 2.5 cm, rotation perturbations up to 10 degrees and roto-translational perturbation up to 3 cm and 5 degrees.

Automatic characterization and segmentation of human skin using three-dimensional optical coherence tomography

NASA Astrophysics Data System (ADS)

Hori, Yasuaki; Yasuno, Yoshiaki; Sakai, Shingo; Matsumoto, Masayuki; Sugawara, Tomoko; Madjarova, Violeta; Yamanari, Masahiro; Makita, Shuichi; Yasui, Takeshi; Araki, Tsutomu; Itoh, Masahide; Yatagai, Toyohiko

2006-03-01

A set of fully automated algorithms that is specialized for analyzing a three-dimensional optical coherence tomography (OCT) volume of human skin is reported. The algorithm set first determines the skin surface of the OCT volume, and a depth-oriented algorithm provides the mean epidermal thickness, distribution map of the epidermis, and a segmented volume of the epidermis. Subsequently, an en face shadowgram is produced by an algorithm to visualize the infundibula in the skin with high contrast. The population and occupation ratio of the infundibula are provided by a histogram-based thresholding algorithm and a distance mapping algorithm. En face OCT slices at constant depths from the sample surface are extracted, and the histogram-based thresholding algorithm is again applied to these slices, yielding a three-dimensional segmented volume of the infundibula. The dermal attenuation coefficient is also calculated from the OCT volume in order to evaluate the skin texture. The algorithm set examines swept-source OCT volumes of the skins of several volunteers, and the results show the high stability, portability and reproducibility of the algorithm.

Three-dimensional photoacoustic tomography based on graphics-processing-unit-accelerated finite element method.

PubMed

Peng, Kuan; He, Ling; Zhu, Ziqiang; Tang, Jingtian; Xiao, Jiaying

2013-12-01

Compared with commonly used analytical reconstruction methods, the frequency-domain finite element method (FEM) based approach has proven to be an accurate and flexible algorithm for photoacoustic tomography. However, the FEM-based algorithm is computationally demanding, especially for three-dimensional cases. To enhance the algorithm's efficiency, in this work a parallel computational strategy is implemented in the framework of the FEM-based reconstruction algorithm using a graphic-processing-unit parallel frame named the "compute unified device architecture." A series of simulation experiments is carried out to test the accuracy and accelerating effect of the improved method. The results obtained indicate that the parallel calculation does not change the accuracy of the reconstruction algorithm, while its computational cost is significantly reduced by a factor of 38.9 with a GTX 580 graphics card using the improved method.

Image reconstruction algorithms for electrical capacitance tomography based on ROF model using new numerical techniques

NASA Astrophysics Data System (ADS)

Chen, Jiaoxuan; Zhang, Maomao; Liu, Yinyan; Chen, Jiaoliao; Li, Yi

2017-03-01

Electrical capacitance tomography (ECT) is a promising technique applied in many fields. However, the solutions for ECT are not unique and highly sensitive to the measurement noise. To remain a good shape of reconstructed object and endure a noisy data, a Rudin-Osher-Fatemi (ROF) model with total variation regularization is applied to image reconstruction in ECT. Two numerical methods, which are simplified augmented Lagrangian (SAL) and accelerated alternating direction method of multipliers (AADMM), are innovatively introduced to try to solve the above mentioned problems in ECT. The effect of the parameters and the number of iterations for different algorithms, and the noise level in capacitance data are discussed. Both simulation and experimental tests were carried out to validate the feasibility of the proposed algorithms, compared to the Landweber iteration (LI) algorithm. The results show that the SAL and AADMM algorithms can handle a high level of noise and the AADMM algorithm outperforms other algorithms in identifying the object from its background.

Improved bioluminescence and fluorescence reconstruction algorithms using diffuse optical tomography, normalized data, and optimized selection of the permissible source region

PubMed Central

Naser, Mohamed A.; Patterson, Michael S.

2011-01-01

Reconstruction algorithms are presented for two-step solutions of the bioluminescence tomography (BLT) and the fluorescence tomography (FT) problems. In the first step, a continuous wave (cw) diffuse optical tomography (DOT) algorithm is used to reconstruct the tissue optical properties assuming known anatomical information provided by x-ray computed tomography or other methods. Minimization problems are formed based on L1 norm objective functions, where normalized values for the light fluence rates and the corresponding Green’s functions are used. Then an iterative minimization solution shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. Throughout this process the permissible region shrinks from the entire object to just a few points. The optimum reconstructed bioluminescence and fluorescence distributions are chosen to be the results of the iteration corresponding to the permissible region where the objective function has its global minimum This provides efficient BLT and FT reconstruction algorithms without the need for a priori information about the bioluminescence sources or the fluorophore concentration. Multiple small sources and large distributed sources can be reconstructed with good accuracy for the location and the total source power for BLT and the total number of fluorophore molecules for the FT. For non-uniform distributed sources, the size and magnitude become degenerate due to the degrees of freedom available for possible solutions. However, increasing the number of data points by increasing the number of excitation sources can improve the accuracy of reconstruction for non-uniform fluorophore distributions. PMID:21326647

Quantum control and quantum tomography on neutral atom qudits

NASA Astrophysics Data System (ADS)

Sosa Martinez, Hector

Neutral atom systems are an appealing platform for the development and testing of quantum control and measurement techniques. This dissertation presents experimental investigations of control and measurement tools using as a testbed the 16-dimensional hyperfine manifold associated with the electronic ground state of cesium atoms. On the control side, we present an experimental realization of a protocol to implement robust unitary transformations in the presence of static and dynamic perturbations. We also present an experimental realization of inhomogeneous quantum control. Specifically, we demonstrate our ability to perform two different unitary transformations on atoms that see different light shifts from an optical addressing field. On the measurement side, we present experimental realizations of quantum state and process tomography. The state tomography project encompasses a comprehensive evaluation of several measurement strategies and state estimation algorithms. Our experimental results show that in the presence of experimental imperfections, there is a clear tradeoff between accuracy, efficiency and robustness in the reconstruction. The process tomography project involves an experimental demonstration of efficient reconstruction by using a set of intelligent probe states. Experimental results show that we are able to reconstruct unitary maps in Hilbert spaces with dimension ranging from d=4 to d=16. To the best of our knowledge, this is the first time that a unitary process in d=16 is successfully reconstructed in the laboratory.

Application of IRI-Plas in Ionospheric Tomography and HF Communication Studies with Assimilation of GPS-TEC

NASA Astrophysics Data System (ADS)

Arikan, Feza; Gulyaeva, Tamara; Sezen, Umut; Arikan, Orhan; Toker, Cenk; Hakan Tuna, MR.; Erdem, Esra

2016-07-01

International Reference Ionosphere is the most acknowledged climatic model of ionosphere that provides electron density profile and hourly, monthly median values of critical layer parameters of the ionosphere for a desired location, date and time between 60 to 2,000 km altitude. IRI is also accepted as the International Standard Ionosphere model. Recently, the IRI model is extended to the Global Positioning System (GPS) satellite orbital range of 20,000 km. The new version is called IRI-Plas and it can be obtained from http://ftp.izmiran.ru/pub/izmiran /SPIM/. A user-friendly online version is also provided at www.ionolab.org as a space weather service. Total Electron Content (TEC), which is defined as the line integral of electron density on a given ray path, is an observable parameter that can be estimated from earth based GPS receivers in a cost-effective manner as GPS-TEC. One of the most important advantages of IRI-Plas is the possible input of GPS-TEC to update the background deterministic ionospheric model to the current ionospheric state. This option is highly useful in regional and global tomography studies and HF link assessments. IONOLAB group currently implements IRI-Plas as a background model and updates the ionospheric state using GPS-TEC in IONOLAB-CIT and IONOLAB-RAY algorithms. The improved state of ionosphere allows the most reliable 4-D imaging of electron density profiles and HF and satellite communication link simulations.This study is supported by TUBITAK 115E915 and joint TUBITAK 114E092 and AS CR 14/001.

Iterative methods for tomography problems: implementation to a cross-well tomography problem

NASA Astrophysics Data System (ADS)

Karadeniz, M. F.; Weber, G. W.

2018-01-01

The velocity distribution between two boreholes is reconstructed by cross-well tomography, which is commonly used in geology. In this paper, iterative methods, Kaczmarz’s algorithm, algebraic reconstruction technique (ART), and simultaneous iterative reconstruction technique (SIRT), are implemented to a specific cross-well tomography problem. Convergence to the solution of these methods and their CPU time for the cross-well tomography problem are compared. Furthermore, these three methods for this problem are compared for different tolerance values.

Direct integration of the inverse Radon equation for X-ray computed tomography.

PubMed

Libin, E E; Chakhlov, S V; Trinca, D

2016-11-22

A new mathematical appoach using the inverse Radon equation for restoration of images in problems of linear two-dimensional x-ray tomography is formulated. In this approach, Fourier transformation is not used, and it gives the chance to create the practical computing algorithms having more reliable mathematical substantiation. Results of software implementation show that for especially for low number of projections, the described approach performs better than standard X-ray tomographic reconstruction algorithms.

Iterative reconstruction methods in atmospheric tomography: FEWHA, Kaczmarz and Gradient-based algorithm

NASA Astrophysics Data System (ADS)

Ramlau, R.; Saxenhuber, D.; Yudytskiy, M.

2014-07-01

The problem of atmospheric tomography arises in ground-based telescope imaging with adaptive optics (AO), where one aims to compensate in real-time for the rapidly changing optical distortions in the atmosphere. Many of these systems depend on a sufficient reconstruction of the turbulence profiles in order to obtain a good correction. Due to steadily growing telescope sizes, there is a strong increase in the computational load for atmospheric reconstruction with current methods, first and foremost the MVM. In this paper we present and compare three novel iterative reconstruction methods. The first iterative approach is the Finite Element- Wavelet Hybrid Algorithm (FEWHA), which combines wavelet-based techniques and conjugate gradient schemes to efficiently and accurately tackle the problem of atmospheric reconstruction. The method is extremely fast, highly flexible and yields superior quality. Another novel iterative reconstruction algorithm is the three step approach which decouples the problem in the reconstruction of the incoming wavefronts, the reconstruction of the turbulent layers (atmospheric tomography) and the computation of the best mirror correction (fitting step). For the atmospheric tomography problem within the three step approach, the Kaczmarz algorithm and the Gradient-based method have been developed. We present a detailed comparison of our reconstructors both in terms of quality and speed performance in the context of a Multi-Object Adaptive Optics (MOAO) system for the E-ELT setting on OCTOPUS, the ESO end-to-end simulation tool.

A multistage selective weighting method for improved microwave breast tomography.

PubMed

Shahzad, Atif; O'Halloran, Martin; Jones, Edward; Glavin, Martin

2016-12-01

Microwave tomography has shown potential to successfully reconstruct the dielectric properties of the human breast, thereby providing an alternative to other imaging modalities used in breast imaging applications. Considering the costly forward solution and complex iterative algorithms, computational complexity becomes a major bottleneck in practical applications of microwave tomography. In addition, the natural tendency of microwave inversion algorithms to reward high contrast breast tissue boundaries, such as the skin-adipose interface, usually leads to a very slow reconstruction of the internal tissue structure of human breast. This paper presents a multistage selective weighting method to improve the reconstruction quality of breast dielectric properties and minimize the computational cost of microwave breast tomography. In the proposed two stage approach, the skin layer is approximated using scaled microwave measurements in the first pass of the inversion algorithm; a numerical skin model is then constructed based on the estimated skin layer and the assumed dielectric properties of the skin tissue. In the second stage of the algorithm, the skin model is used as a priori information to reconstruct the internal tissue structure of the breast using a set of temporal scaling functions. The proposed method is evaluated on anatomically accurate MRI-derived breast phantoms and a comparison with the standard single-stage technique is presented. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Miniature modified Faraday cup for micro electron beams

DOEpatents

Teruya, Alan T.; Elmer, John W.; Palmer, Todd A.; Walton, Chris C.

2008-05-27

A micro beam Faraday cup assembly includes a refractory metal layer with an odd number of thin, radially positioned traces in this refractory metal layer. Some of the radially positioned traces are located at the edge of the micro modified Faraday cup body and some of the radially positioned traces are located in the central portion of the micro modified Faraday cup body. Each set of traces is connected to a separate data acquisition channel to form multiple independent diagnostic networks. The data obtained from the two diagnostic networks are combined and inputted into a computed tomography algorithm to reconstruct the beam shape, size, and power density distribution.

Three-dimensional ophthalmic optical coherence tomography with a refraction correction algorithm

NASA Astrophysics Data System (ADS)

Zawadzki, Robert J.; Leisser, Christoph; Leitgeb, Rainer; Pircher, Michael; Fercher, Adolf F.

2003-10-01

We built an optical coherence tomography (OCT) system with a rapid scanning optical delay (RSOD) line, which allows probing full axial eye length. The system produces Three-dimensional (3D) data sets that are used to generate 3D tomograms of the model eye. The raw tomographic data were processed by an algorithm, which is based on Snell"s law to correct the interface positions. The Zernike polynomials representation of the interfaces allows quantitative wave aberration measurements. 3D images of our results are presented to illustrate the capabilities of the system and the algorithm performance. The system allows us to measure intra-ocular distances.

Total variation iterative constraint algorithm for limited-angle tomographic reconstruction of non-piecewise-constant structures

NASA Astrophysics Data System (ADS)

Krauze, W.; Makowski, P.; Kujawińska, M.

2015-06-01

Standard tomographic algorithms applied to optical limited-angle tomography result in the reconstructions that have highly anisotropic resolution and thus special algorithms are developed. State of the art approaches utilize the Total Variation (TV) minimization technique. These methods give very good results but are applicable to piecewise constant structures only. In this paper, we propose a novel algorithm for 3D limited-angle tomography - Total Variation Iterative Constraint method (TVIC) which enhances the applicability of the TV regularization to non-piecewise constant samples, like biological cells. This approach consists of two parts. First, the TV minimization is used as a strong regularizer to create a sharp-edged image converted to a 3D binary mask which is then iteratively applied in the tomographic reconstruction as a constraint in the object domain. In the present work we test the method on a synthetic object designed to mimic basic structures of a living cell. For simplicity, the test reconstructions were performed within the straight-line propagation model (SIRT3D solver from the ASTRA Tomography Toolbox), but the strategy is general enough to supplement any algorithm for tomographic reconstruction that supports arbitrary geometries of plane-wave projection acquisition. This includes optical diffraction tomography solvers. The obtained reconstructions present resolution uniformity and general shape accuracy expected from the TV regularization based solvers, but keeping the smooth internal structures of the object at the same time. Comparison between three different patterns of object illumination arrangement show very small impact of the projection acquisition geometry on the image quality.

Noninvasive coronary artery angiography using electron beam computed tomography

NASA Astrophysics Data System (ADS)

Rumberger, John A.; Rensing, Benno J.; Reed, Judd E.; Ritman, Erik L.; Sheedy, Patrick F., II

1996-04-01

Electron beam computed tomography (EBCT), also known as ultrafast-CT or cine-CT, uses a unique scanning architecture which allows for multiple high spatial resolution electrocardiographic triggered images of the beating heart. A recent study has demonstrated the feasibility of qualitative comparisons between EBCT derived 3D coronary angiograms and invasive angiography. Stenoses of the proximal portions of the left anterior descending and right coronary arteries were readily identified, but description of atherosclerotic narrowing in the left circumflex artery (and distal epicardial disease) was not possible with any degree of confidence. Although these preliminary studies support the notion that this approach has potential, the images overall were suboptimal for clinical application as an adjunct to invasive angiography. Furthermore, these studies did not examine different methods of EBCT scan acquisition, tomographic slice thicknesses, extent of scan overlap, or other segmentation, thresholding, and interpolation algorithms. Our laboratory has initiated investigation of these aspects and limitations of EBCT coronary angiography. Specific areas of research include defining effects of cardiac orientation; defining the effects of tomographic slice thickness and intensity (gradient) versus positional (shaped based) interpolation; and defining applicability of imaging each of the major epicardial coronary arteries for quantitative definition of vessel size, cross-sectional area, taper, and discrete vessel narrowing.

Impedance computed tomography using an adaptive smoothing coefficient algorithm.

PubMed

Suzuki, A; Uchiyama, A

2001-01-01

In impedance computed tomography, a fixed coefficient regularization algorithm has been frequently used to improve the ill-conditioning problem of the Newton-Raphson algorithm. However, a lot of experimental data and a long period of computation time are needed to determine a good smoothing coefficient because a good smoothing coefficient has to be manually chosen from a number of coefficients and is a constant for each iteration calculation. Thus, sometimes the fixed coefficient regularization algorithm distorts the information or fails to obtain any effect. In this paper, a new adaptive smoothing coefficient algorithm is proposed. This algorithm automatically calculates the smoothing coefficient from the eigenvalue of the ill-conditioned matrix. Therefore, the effective images can be obtained within a short computation time. Also the smoothing coefficient is automatically adjusted by the information related to the real resistivity distribution and the data collection method. In our impedance system, we have reconstructed the resistivity distributions of two phantoms using this algorithm. As a result, this algorithm only needs one-fifth the computation time compared to the fixed coefficient regularization algorithm. When compared to the fixed coefficient regularization algorithm, it shows that the image is obtained more rapidly and applicable in real-time monitoring of the blood vessel.

An Energy-Based Three-Dimensional Segmentation Approach for the Quantitative Interpretation of Electron Tomograms

PubMed Central

Bartesaghi, Alberto; Sapiro, Guillermo; Subramaniam, Sriram

2006-01-01

Electron tomography allows for the determination of the three-dimensional structures of cells and tissues at resolutions significantly higher than that which is possible with optical microscopy. Electron tomograms contain, in principle, vast amounts of information on the locations and architectures of large numbers of subcellular assemblies and organelles. The development of reliable quantitative approaches for the analysis of features in tomograms is an important problem, and a challenging prospect due to the low signal-to-noise ratios that are inherent to biological electron microscopic images. This is, in part, a consequence of the tremendous complexity of biological specimens. We report on a new method for the automated segmentation of HIV particles and selected cellular compartments in electron tomograms recorded from fixed, plastic-embedded sections derived from HIV-infected human macrophages. Individual features in the tomogram are segmented using a novel robust algorithm that finds their boundaries as global minimal surfaces in a metric space defined by image features. The optimization is carried out in a transformed spherical domain with the center an interior point of the particle of interest, providing a proper setting for the fast and accurate minimization of the segmentation energy. This method provides tools for the semi-automated detection and statistical evaluation of HIV particles at different stages of assembly in the cells and presents opportunities for correlation with biochemical markers of HIV infection. The segmentation algorithm developed here forms the basis of the automated analysis of electron tomograms and will be especially useful given the rapid increases in the rate of data acquisition. It could also enable studies of much larger data sets, such as those which might be obtained from the tomographic analysis of HIV-infected cells from studies of large populations. PMID:16190467

Tomography by iterative convolution - Empirical study and application to interferometry

NASA Technical Reports Server (NTRS)

Vest, C. M.; Prikryl, I.

1984-01-01

An algorithm for computer tomography has been developed that is applicable to reconstruction from data having incomplete projections because an opaque object blocks some of the probing radiation as it passes through the object field. The algorithm is based on iteration between the object domain and the projection (Radon transform) domain. Reconstructions are computed during each iteration by the well-known convolution method. Although it is demonstrated that this algorithm does not converge, an empirically justified criterion for terminating the iteration when the most accurate estimate has been computed is presented. The algorithm has been studied by using it to reconstruct several different object fields with several different opaque regions. It also has been used to reconstruct aerodynamic density fields from interferometric data recorded in wind tunnel tests.

Total variation-based neutron computed tomography

NASA Astrophysics Data System (ADS)

Barnard, Richard C.; Bilheux, Hassina; Toops, Todd; Nafziger, Eric; Finney, Charles; Splitter, Derek; Archibald, Rick

2018-05-01

We perform the neutron computed tomography reconstruction problem via an inverse problem formulation with a total variation penalty. In the case of highly under-resolved angular measurements, the total variation penalty suppresses high-frequency artifacts which appear in filtered back projections. In order to efficiently compute solutions for this problem, we implement a variation of the split Bregman algorithm; due to the error-forgetting nature of the algorithm, the computational cost of updating can be significantly reduced via very inexact approximate linear solvers. We present the effectiveness of the algorithm in the significantly low-angular sampling case using synthetic test problems as well as data obtained from a high flux neutron source. The algorithm removes artifacts and can even roughly capture small features when an extremely low number of angles are used.

Polyquant CT: direct electron and mass density reconstruction from a single polyenergetic source

NASA Astrophysics Data System (ADS)

Mason, Jonathan H.; Perelli, Alessandro; Nailon, William H.; Davies, Mike E.

2017-11-01

Quantifying material mass and electron density from computed tomography (CT) reconstructions can be highly valuable in certain medical practices, such as radiation therapy planning. However, uniquely parameterising the x-ray attenuation in terms of mass or electron density is an ill-posed problem when a single polyenergetic source is used with a spectrally indiscriminate detector. Existing approaches to single source polyenergetic modelling often impose consistency with a physical model, such as water-bone or photoelectric-Compton decompositions, which will either require detailed prior segmentation or restrictive energy dependencies, and may require further calibration to the quantity of interest. In this work, we introduce a data centric approach to fitting the attenuation with piecewise-linear functions directly to mass or electron density, and present a segmentation-free statistical reconstruction algorithm for exploiting it, with the same order of complexity as other iterative methods. We show how this allows both higher accuracy in attenuation modelling, and demonstrate its superior quantitative imaging, with numerical chest and metal implant data, and validate it with real cone-beam CT measurements.

Cone-beam reconstruction for the two-circles-plus-one-line trajectory

NASA Astrophysics Data System (ADS)

Lu, Yanbin; Yang, Jiansheng; Emerson, John W.; Mao, Heng; Zhou, Tie; Si, Yuanzheng; Jiang, Ming

2012-05-01

The Kodak Image Station In-Vivo FX has an x-ray module with cone-beam configuration for radiographic imaging but lacks the functionality of tomography. To introduce x-ray tomography into the system, we choose the two-circles-plus-one-line trajectory by mounting one translation motor and one rotation motor. We establish a reconstruction algorithm by applying the M-line reconstruction method. Numerical studies and preliminary physical phantom experiment demonstrate the feasibility of the proposed design and reconstruction algorithm.

Computerized tomography platform using beta rays

NASA Astrophysics Data System (ADS)

Paetkau, Owen; Parsons, Zachary; Paetkau, Mark

2017-12-01

A computerized tomography (CT) system using a 0.1 μCi Sr-90 beta source, Geiger counter, and low density foam samples was developed. A simple algorithm was used to construct images from the data collected with the beta CT scanner. The beta CT system is analogous to X-ray CT as both types of radiation are sensitive to density variations. This system offers a platform for learning opportunities in an undergraduate laboratory, covering topics such as image reconstruction algorithms, radiation exposure, and the energy dependence of absorption.

Progress and opportunities in EELS and EDS tomography.

PubMed

Collins, Sean M; Midgley, Paul A

2017-09-01

Electron tomography using energy loss and X-ray spectroscopy in the electron microscope continues to develop in rapidly evolving and diverse directions, enabling new insight into the three-dimensional chemistry and physics of nanoscale volumes. Progress has been made recently in improving reconstructions from EELS and EDS signals in electron tomography by applying compressed sensing methods, characterizing new detector technologies in detail, deriving improved models of signal generation, and exploring machine learning approaches to signal processing. These disparate threads can be brought together in a cohesive framework in terms of a model-based approach to analytical electron tomography. Models incorporate information on signal generation and detection as well as prior knowledge of structures in the spectrum image data. Many recent examples illustrate the flexibility of this approach and its feasibility for addressing challenges in non-linear or limited signals in EELS and EDS tomography. Further work in combining multiple imaging and spectroscopy modalities, developing synergistic data acquisition, processing, and reconstruction approaches, and improving the precision of quantitative spectroscopic tomography will expand the frontiers of spatial resolution, dose limits, and maximal information recovery. Copyright © 2017 Elsevier B.V. All rights reserved.

Formation of bimetallic clusters in superfluid helium nanodroplets analysed by atomic resolution electron tomography

PubMed Central

Haberfehlner, Georg; Thaler, Philipp; Knez, Daniel; Volk, Alexander; Hofer, Ferdinand; Ernst, Wolfgang E.; Kothleitner, Gerald

2015-01-01

Structure, shape and composition are the basic parameters responsible for properties of nanoscale materials, distinguishing them from their bulk counterparts. To reveal these in three dimensions at the nanoscale, electron tomography is a powerful tool. Advancing electron tomography to atomic resolution in an aberration-corrected transmission electron microscope remains challenging and has been demonstrated only a few times using strong constraints or extensive filtering. Here we demonstrate atomic resolution electron tomography on silver/gold core/shell nanoclusters grown in superfluid helium nanodroplets. We reveal morphology and composition of a cluster identifying gold- and silver-rich regions in three dimensions and we estimate atomic positions without using any prior information and with minimal filtering. The ability to get full three-dimensional information down to the atomic scale allows understanding the growth and deposition process of the nanoclusters and demonstrates an approach that may be generally applicable to all types of nanoscale materials. PMID:26508471

Cryo-scanning transmission electron tomography of vitrified cells.

PubMed

Wolf, Sharon Grayer; Houben, Lothar; Elbaum, Michael

2014-04-01

Cryo-electron tomography (CET) of fully hydrated, vitrified biological specimens has emerged as a vital tool for biological research. For cellular studies, the conventional imaging modality of transmission electron microscopy places stringent constraints on sample thickness because of its dependence on phase coherence for contrast generation. Here we demonstrate the feasibility of using scanning transmission electron microscopy for cryo-tomography of unstained vitrified specimens (CSTET). We compare CSTET and CET for the imaging of whole bacteria and human tissue culture cells, finding favorable contrast and detail in the CSTET reconstructions. Particularly at high sample tilts, the CSTET signals contain more informative data than energy-filtered CET phase contrast images, resulting in improved depth resolution. Careful control over dose delivery permits relatively high cumulative exposures before the onset of observable beam damage. The increase in acceptable specimen thickness broadens the applicability of electron cryo-tomography.

Secondary signal imaging (SSI) electron tomography (SSI-ET): A new three-dimensional metrology for mesoscale specimens in transmission electron microscope.

PubMed

Han, Chang Wan; Ortalan, Volkan

2015-09-01

We have demonstrated a new electron tomography technique utilizing the secondary signals (secondary electrons and backscattered electrons) for ultra thick (a few μm) specimens. The Monte Carlo electron scattering simulations reveal that the amount of backscattered electrons generated by 200 and 300keV incident electrons is a monotonic function of the sample thickness and this causes the thickness contrast satisfying the projection requirement for the tomographic reconstruction. Additional contribution of the secondary electrons emitted from the edges of the specimens enhances the visibility of the surface features. The acquired SSI tilt series of the specimen having mesoscopic dimensions are successfully reconstructed verifying that this new technique, so called the secondary signal imaging electron tomography (SSI-ET), can directly be utilized for 3D structural analysis of mesoscale structures. Published by Elsevier Ltd.

Database tomography for commercial application

NASA Technical Reports Server (NTRS)

Kostoff, Ronald N.; Eberhart, Henry J.

1994-01-01

Database tomography is a method for extracting themes and their relationships from text. The algorithms, employed begin with word frequency and word proximity analysis and build upon these results. When the word 'database' is used, think of medical or police records, patents, journals, or papers, etc. (any text information that can be computer stored). Database tomography features a full text, user interactive technique enabling the user to identify areas of interest, establish relationships, and map trends for a deeper understanding of an area of interest. Database tomography concepts and applications have been reported in journals and presented at conferences. One important feature of the database tomography algorithm is that it can be used on a database of any size, and will facilitate the users ability to understand the volume of content therein. While employing the process to identify research opportunities it became obvious that this promising technology has potential applications for business, science, engineering, law, and academe. Examples include evaluating marketing trends, strategies, relationships and associations. Also, the database tomography process would be a powerful component in the area of competitive intelligence, national security intelligence and patent analysis. User interests and involvement cannot be overemphasized.

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

PubMed

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

2014-07-01

A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project [1]. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head [2]. With unprecedented high channel density (450 channels/cm 3 ) 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.

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

PubMed

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

Model-based sensor-less wavefront aberration correction in optical coherence tomography.

PubMed

Verstraete, Hans R G W; Wahls, Sander; Kalkman, Jeroen; Verhaegen, Michel

2015-12-15

Several sensor-less wavefront aberration correction methods that correct nonlinear wavefront aberrations by maximizing the optical coherence tomography (OCT) signal are tested on an OCT setup. A conventional coordinate search method is compared to two model-based optimization methods. The first model-based method takes advantage of the well-known optimization algorithm (NEWUOA) and utilizes a quadratic model. The second model-based method (DONE) is new and utilizes a random multidimensional Fourier-basis expansion. The model-based algorithms achieve lower wavefront errors with up to ten times fewer measurements. Furthermore, the newly proposed DONE method outperforms the NEWUOA method significantly. The DONE algorithm is tested on OCT images and shows a significantly improved image quality.

BPF-type region-of-interest reconstruction for parallel translational computed tomography.

PubMed

Wu, Weiwen; Yu, Hengyong; Wang, Shaoyu; Liu, Fenglin

2017-01-01

The objective of this study is to present and test a new ultra-low-cost linear scan based tomography architecture. Similar to linear tomosynthesis, the source and detector are translated in opposite directions and the data acquisition system targets on a region-of-interest (ROI) to acquire data for image reconstruction. This kind of tomographic architecture was named parallel translational computed tomography (PTCT). In previous studies, filtered backprojection (FBP)-type algorithms were developed to reconstruct images from PTCT. However, the reconstructed ROI images from truncated projections have severe truncation artefact. In order to overcome this limitation, we in this study proposed two backprojection filtering (BPF)-type algorithms named MP-BPF and MZ-BPF to reconstruct ROI images from truncated PTCT data. A weight function is constructed to deal with data redundancy for multi-linear translations modes. Extensive numerical simulations are performed to evaluate the proposed MP-BPF and MZ-BPF algorithms for PTCT in fan-beam geometry. Qualitative and quantitative results demonstrate that the proposed BPF-type algorithms cannot only more accurately reconstruct ROI images from truncated projections but also generate high-quality images for the entire image support in some circumstances.

Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography

NASA Technical Reports Server (NTRS)

Xu, Feng; Deshpande, Manohar

2012-01-01

Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.

Correlated Light and Electron Microscopy/Electron Tomography of Mitochondria In Situ

PubMed Central

Perkins, Guy A.; Sun, Mei G.; Frey, Terrence G.

2009-01-01

Three-dimensional light microscopy and three-dimensional electron microscopy (electron tomography) separately provide very powerful tools to study cellular structure and physiology, including the structure and physiology of mitochondria. Fluorescence microscopy allows one to study processes in live cells with specific labels and stains that follow the movement of labeled proteins and changes within cellular compartments but does not have sufficient resolution to define the ultrastructure of intracellular organelles such as mitochondria. Electron microscopy and electron tomography provide the highest resolution currently available to study mitochondrial ultrastructure but cannot follow processes in living cells. We describe the combination of these two techniques in which fluorescence confocal microscopy is used to study structural and physiologic changes in mitochondria within apoptotic HeLa cells to define the apoptotic timeframe. Cells can then be selected at various stages of the apoptotic timeframe for examination at higher resolution by electron microscopy and electron tomography. This is a form of “virtual” 4-dimensional electron microscopy that has revealed interesting structural changes in the mitochondria of HeLa cells during apoptosis. The same techniques can be applied, with modification, to study other dynamic processes within cells in other experimental contexts. PMID:19348881

Vertical structure of medium-scale traveling ionospheric disturbances

NASA Astrophysics Data System (ADS)

Ssessanga, Nicholas; Kim, Yong Ha; Kim, Eunsol

2015-11-01

We develop an algorithm of computerized ionospheric tomography (CIT) to infer information on the vertical and horizontal structuring of electron density during nighttime medium-scale traveling ionospheric disturbances (MSTIDs). To facilitate digital CIT we have adopted total electron contents (TEC) from a dense Global Positioning System (GPS) receiver network, GEONET, which contains more than 1000 receivers. A multiplicative algebraic reconstruction technique was utilized with a calibrated IRI-2012 model as an initial solution. The reconstructed F2 peak layer varied in altitude with average peak-to-peak amplitude of ~52 km. In addition, the F2 peak layer anticorrelated with TEC variations. This feature supports a theory in which nighttime MSTID is composed of oscillating electric fields due to conductivity variations. Moreover, reconstructed TEC variations over two stations were reasonably close to variations directly derived from the measured TEC data set. Our tomographic analysis may thus help understand three-dimensional structure of MSTIDs in a quantitative way.

Mathematics of Computed Tomography

NASA Astrophysics Data System (ADS)

Hawkins, William Grant

A review of the applications of the Radon transform is presented, with emphasis on emission computed tomography and transmission computed tomography. The theory of the 2D and 3D Radon transforms, and the effects of attenuation for emission computed tomography are presented. The algebraic iterative methods, their importance and limitations are reviewed. Analytic solutions of the 2D problem the convolution and frequency filtering methods based on linear shift invariant theory, and the solution of the circular harmonic decomposition by integral transform theory--are reviewed. The relation between the invisible kernels, the inverse circular harmonic transform, and the consistency conditions are demonstrated. The discussion and review are extended to the 3D problem-convolution, frequency filtering, spherical harmonic transform solutions, and consistency conditions. The Cormack algorithm based on reconstruction with Zernike polynomials is reviewed. An analogous algorithm and set of reconstruction polynomials is developed for the spherical harmonic transform. The relations between the consistency conditions, boundary conditions and orthogonal basis functions for the 2D projection harmonics are delineated and extended to the 3D case. The equivalence of the inverse circular harmonic transform, the inverse Radon transform, and the inverse Cormack transform is presented. The use of the number of nodes of a projection harmonic as a filter is discussed. Numerical methods for the efficient implementation of angular harmonic algorithms based on orthogonal functions and stable recursion are presented. The derivation of a lower bound for the signal-to-noise ratio of the Cormack algorithm is derived.

Postinjection single photon transmission tomography with ordered-subset algorithms for whole-body PET imaging

NASA Astrophysics Data System (ADS)

Bai, Chuanyong; Kinahan, P. E.; Brasse, D.; Comtat, C.; Townsend, D. W.

2002-02-01

We have evaluated the penalized ordered-subset transmission reconstruction (OSTR) algorithm for postinjection single photon transmission scanning. The OSTR algorithm of Erdogan and Fessler (1999) uses a more accurate model for transmission tomography than ordered-subsets expectation-maximization (OSEM) when OSEM is applied to the logarithm of the transmission data. The OSTR algorithm is directly applicable to postinjection transmission scanning with a single photon source, as emission contamination from the patient mimics the effect, in the original derivation of OSTR, of random coincidence contamination in a positron source transmission scan. Multiple noise realizations of simulated postinjection transmission data were reconstructed using OSTR, filtered backprojection (FBP), and OSEM algorithms. Due to the nonspecific task performance, or multiple uses, of the transmission image, multiple figures of merit were evaluated, including image noise, contrast, uniformity, and root mean square (rms) error. We show that: 1) the use of a three-dimensional (3-D) regularizing image roughness penalty with OSTR improves the tradeoffs in noise, contrast, and rms error relative to the use of a two-dimensional penalty; 2) OSTR with a 3-D penalty has improved tradeoffs in noise, contrast, and rms error relative to FBP or OSEM; and 3) the use of image standard deviation from a single realization to estimate the true noise can be misleading in the case of OSEM. We conclude that using OSTR with a 3-D penalty potentially allows for shorter postinjection transmission scans in single photon transmission tomography in positron emission tomography (PET) relative to FBP or OSEM reconstructed images with the same noise properties. This combination of singles+OSTR is particularly suitable for whole-body PET oncology imaging.

Hybrid radiosity-SP3 equation based bioluminescence tomography reconstruction for turbid medium with low- and non-scattering regions

NASA Astrophysics Data System (ADS)

Chen, Xueli; Zhang, Qitan; Yang, Defu; Liang, Jimin

2014-01-01

To provide an ideal solution for a specific problem of gastric cancer detection in which low-scattering regions simultaneously existed with both the non- and high-scattering regions, a novel hybrid radiosity-SP3 equation based reconstruction algorithm for bioluminescence tomography was proposed in this paper. In the algorithm, the third-order simplified spherical harmonics approximation (SP3) was combined with the radiosity equation to describe the bioluminescent light propagation in tissues, which provided acceptable accuracy for the turbid medium with both low- and non-scattering regions. The performance of the algorithm was evaluated with digital mouse based simulations and a gastric cancer-bearing mouse based in situ experiment. Primary results demonstrated the feasibility and superiority of the proposed algorithm for the turbid medium with low- and non-scattering regions.

Statistical reconstruction for cosmic ray muon tomography.

PubMed

Schultz, Larry J; Blanpied, Gary S; Borozdin, Konstantin N; Fraser, Andrew M; Hengartner, Nicolas W; Klimenko, Alexei V; Morris, Christopher L; Orum, Chris; Sossong, Michael J

2007-08-01

Highly penetrating cosmic ray muons constantly shower the earth at a rate of about 1 muon per cm2 per minute. We have developed a technique which exploits the multiple Coulomb scattering of these particles to perform nondestructive inspection without the use of artificial radiation. In prior work [1]-[3], we have described heuristic methods for processing muon data to create reconstructed images. In this paper, we present a maximum likelihood/expectation maximization tomographic reconstruction algorithm designed for the technique. This algorithm borrows much from techniques used in medical imaging, particularly emission tomography, but the statistics of muon scattering dictates differences. We describe the statistical model for multiple scattering, derive the reconstruction algorithm, and present simulated examples. We also propose methods to improve the robustness of the algorithm to experimental errors and events departing from the statistical model.

Regional regularization method for ECT based on spectral transformation of Laplacian

NASA Astrophysics Data System (ADS)

Guo, Z. H.; Kan, Z.; Lv, D. C.; Shao, F. Q.

2016-10-01

Image reconstruction in electrical capacitance tomography is an ill-posed inverse problem, and regularization techniques are usually used to solve the problem for suppressing noise. An anisotropic regional regularization algorithm for electrical capacitance tomography is constructed using a novel approach called spectral transformation. Its function is derived and applied to the weighted gradient magnitude of the sensitivity of Laplacian as a regularization term. With the optimum regional regularizer, the a priori knowledge on the local nonlinearity degree of the forward map is incorporated into the proposed online reconstruction algorithm. Simulation experimentations were performed to verify the capability of the new regularization algorithm to reconstruct a superior quality image over two conventional Tikhonov regularization approaches. The advantage of the new algorithm for improving performance and reducing shape distortion is demonstrated with the experimental data.

Cone Beam X-Ray Luminescence Tomography Imaging Based on KA-FEM Method for Small Animals.

PubMed

Chen, Dongmei; Meng, Fanzhen; Zhao, Fengjun; Xu, Cao

2016-01-01

Cone beam X-ray luminescence tomography can realize fast X-ray luminescence tomography imaging with relatively low scanning time compared with narrow beam X-ray luminescence tomography. However, cone beam X-ray luminescence tomography suffers from an ill-posed reconstruction problem. First, the feasibility of experiments with different penetration and multispectra in small animal has been tested using nanophosphor material. Then, the hybrid reconstruction algorithm with KA-FEM method has been applied in cone beam X-ray luminescence tomography for small animals to overcome the ill-posed reconstruction problem, whose advantage and property have been demonstrated in fluorescence tomography imaging. The in vivo mouse experiment proved the feasibility of the proposed method.

Quantitative X-ray fluorescence computed tomography for low-Z samples using an iterative absorption correction algorithm

NASA Astrophysics Data System (ADS)

Huang, Rong; Limburg, Karin; Rohtla, Mehis

2017-05-01

X-ray fluorescence computed tomography is often used to measure trace element distributions within low-Z samples, using algorithms capable of X-ray absorption correction when sample self-absorption is not negligible. Its reconstruction is more complicated compared to transmission tomography, and therefore not widely used. We describe in this paper a very practical iterative method that uses widely available transmission tomography reconstruction software for fluorescence tomography. With this method, sample self-absorption can be corrected not only for the absorption within the measured layer but also for the absorption by material beyond that layer. By combining tomography with analysis for scanning X-ray fluorescence microscopy, absolute concentrations of trace elements can be obtained. By using widely shared software, we not only minimized the coding, took advantage of computing efficiency of fast Fourier transform in transmission tomography software, but also thereby accessed well-developed data processing tools coming with well-known and reliable software packages. The convergence of the iterations was also carefully studied for fluorescence of different attenuation lengths. As an example, fish eye lenses could provide valuable information about fish life-history and endured environmental conditions. Given the lens's spherical shape and sometimes the short distance from sample to detector for detecting low concentration trace elements, its tomography data are affected by absorption related to material beyond the measured layer but can be reconstructed well with our method. Fish eye lens tomography results are compared with sliced lens 2D fluorescence mapping with good agreement, and with tomography providing better spatial resolution.

Rapid data processing for ultrafast X-ray computed tomography using scalable and modular CUDA based pipelines

NASA Astrophysics Data System (ADS)

Frust, Tobias; Wagner, Michael; Stephan, Jan; Juckeland, Guido; Bieberle, André

2017-10-01

Ultrafast X-ray tomography is an advanced imaging technique for the study of dynamic processes basing on the principles of electron beam scanning. A typical application case for this technique is e.g. the study of multiphase flows, that is, flows of mixtures of substances such as gas-liquidflows in pipelines or chemical reactors. At Helmholtz-Zentrum Dresden-Rossendorf (HZDR) a number of such tomography scanners are operated. Currently, there are two main points limiting their application in some fields. First, after each CT scan sequence the data of the radiation detector must be downloaded from the scanner to a data processing machine. Second, the current data processing is comparably time-consuming compared to the CT scan sequence interval. To enable online observations or use this technique to control actuators in real-time, a modular and scalable data processing tool has been developed, consisting of user-definable stages working independently together in a so called data processing pipeline, that keeps up with the CT scanner's maximal frame rate of up to 8 kHz. The newly developed data processing stages are freely programmable and combinable. In order to achieve the highest processing performance all relevant data processing steps, which are required for a standard slice image reconstruction, were individually implemented in separate stages using Graphics Processing Units (GPUs) and NVIDIA's CUDA programming language. Data processing performance tests on different high-end GPUs (Tesla K20c, GeForce GTX 1080, Tesla P100) showed excellent performance. Program Files doi:http://dx.doi.org/10.17632/65sx747rvm.1 Licensing provisions: LGPLv3 Programming language: C++/CUDA Supplementary material: Test data set, used for the performance analysis. Nature of problem: Ultrafast computed tomography is performed with a scan rate of up to 8 kHz. To obtain cross-sectional images from projection data computer-based image reconstruction algorithms must be applied. The objective of the presented program is to reconstruct a data stream of around 1.3 GB s-1 in a minimum time period. Thus, the program allows to go into new fields of application and to use in the future even more compute-intensive algorithms, especially for data post-processing, to improve the quality of data analysis. Solution method: The program solves the given problem using a two-step process: first, by a generic, expandable and widely applicable template library implementing the streaming paradigm (GLADOS); second, by optimized processing stages for ultrafast computed tomography implementing the required algorithms in a performance-oriented way using CUDA (RISA). Thereby, task-parallelism between the processing stages as well as data parallelism within one processing stage is realized.

Speckle contrast optical tomography: A new method for deep tissue three-dimensional tomography of blood flow

PubMed Central

Varma, Hari M.; Valdes, Claudia P.; Kristoffersen, Anna K.; Culver, Joseph P.; Durduran, Turgut

2014-01-01

A novel tomographic method based on the laser speckle contrast, speckle contrast optical tomography (SCOT) is introduced that allows us to reconstruct three dimensional distribution of blood flow in deep tissues. This method is analogous to the diffuse optical tomography (DOT) but for deep tissue blood flow. We develop a reconstruction algorithm based on first Born approximation to generate three dimensional distribution of flow using the experimental data obtained from tissue simulating phantoms. PMID:24761306

Entropic Comparison of Atomic-Resolution Electron Tomography of Crystals and Amorphous Materials.

PubMed

Collins, S M; Leary, R K; Midgley, P A; Tovey, R; Benning, M; Schönlieb, C-B; Rez, P; Treacy, M M J

2017-10-20

Electron tomography bears promise for widespread determination of the three-dimensional arrangement of atoms in solids. However, it remains unclear whether methods successful for crystals are optimal for amorphous solids. Here, we explore the relative difficulty encountered in atomic-resolution tomography of crystalline and amorphous nanoparticles. We define an informational entropy to reveal the inherent importance of low-entropy zone-axis projections in the reconstruction of crystals. In turn, we propose considerations for optimal sampling for tomography of ordered and disordered materials.

Mapping chemicals in air using an environmental CAT scanning system: evaluation of algorithms

NASA Astrophysics Data System (ADS)

Samanta, A.; Todd, L. A.

A new technique is being developed which creates near real-time maps of chemical concentrations in air for environmental and occupational environmental applications. This technique, we call Environmental CAT Scanning, combines the real-time measuring technique of open-path Fourier transform infrared spectroscopy with the mapping capabilitites of computed tomography to produce two-dimensional concentration maps. With this system, a network of open-path measurements is obtained over an area; measurements are then processed using a tomographic algorithm to reconstruct the concentrations. This research focussed on the process of evaluating and selecting appropriate reconstruction algorithms, for use in the field, by using test concentration data from both computer simultation and laboratory chamber studies. Four algorithms were tested using three types of data: (1) experimental open-path data from studies that used a prototype opne-path Fourier transform/computed tomography system in an exposure chamber; (2) synthetic open-path data generated from maps created by kriging point samples taken in the chamber studies (in 1), and; (3) synthetic open-path data generated using a chemical dispersion model to create time seires maps. The iterative algorithms used to reconstruct the concentration data were: Algebraic Reconstruction Technique without Weights (ART1), Algebraic Reconstruction Technique with Weights (ARTW), Maximum Likelihood with Expectation Maximization (MLEM) and Multiplicative Algebraic Reconstruction Technique (MART). Maps were evaluated quantitatively and qualitatively. In general, MART and MLEM performed best, followed by ARTW and ART1. However, algorithm performance varied under different contaminant scenarios. This study showed the importance of using a variety of maps, particulary those generated using dispersion models. The time series maps provided a more rigorous test of the algorithms and allowed distinctions to be made among the algorithms. A comprehensive evaluation of algorithms, for the environmental application of tomography, requires the use of a battery of test concentration data before field implementation, which models reality and tests the limits of the algorithms.

Multi-contrast imaging of human posterior eye by Jones matrix optical coherence tomography

NASA Astrophysics Data System (ADS)

Yasuno, Yoshiaki

2017-04-01

A multi-contrast imaging of pathologic posterior eyes is demonstrated by Jones matrix optical coherence tomography (Jones matrix OCT). The Jones matrix OCT provides five tomographies, which includes scattering, local attenuation, birefringence, polarization uniformity, and optical coherence angiography, by a single scan. The hardware configuration, algorithms of the Jones matrix OCT as well as its application to ophthalmology is discussed.

A new computerized ionosphere tomography model using the mapping function and an application to the study of seismic-ionosphere disturbance

NASA Astrophysics Data System (ADS)

Kong, Jian; Yao, Yibin; Liu, Lei; Zhai, Changzhi; Wang, Zemin

2016-08-01

A new algorithm for ionosphere tomography using the mapping function is proposed in this paper. First, the new solution splits the integration process into four layers along the observation ray, and then, the single-layer model (SLM) is applied to each integration part using a mapping function. Next, the model parameters are estimated layer by layer with the Kalman filtering method by introducing the scale factor (SF) γ to solve the ill-posed problem. Finally, the inversed images of different layers are combined into the final CIT image. We utilized simulated data from 23 IGS GPS stations around Europe to verify the estimation accuracy of the new algorithm; the results show that the new CIT model has better accuracy than the SLM in dense data areas and the CIT residuals are more closely grouped. The stability of the new algorithm is discussed by analyzing model accuracy under different error levels (the max errors are 5TECU, 10TECU, 15TECU, respectively). In addition, the key preset parameter, SFγ , which is given by the International Reference Ionosphere model (IRI2012). The experiment is designed to test the sensitivity of the new algorithm to SF variations. The results show that the IRI2012 is capable of providing initial SF values. Also in this paper, the seismic-ionosphere disturbance (SID) of the 2011 Japan earthquake is studied using the new CIT algorithm. Combined with the TEC time sequence of Sat.15, we find that the SID occurrence time and reaction area are highly related to the main shock time and epicenter. According to CIT images, there is a clear vertical electron density upward movement (from the 150-km layer to the 450-km layer) during this SID event; however, the peak value areas in the different layers were different, which means that the horizontal movement velocity is not consistent among the layers. The potential physical triggering mechanism is also discussed in this paper. Compared with the SLM, the RMS of the new CIT model is improved by 16.78%, while the CIT model could provide the three-dimensional variation in the ionosphere.

4D electron tomography.

PubMed

Kwon, Oh-Hoon; Zewail, Ahmed H

2010-06-25

Electron tomography provides three-dimensional (3D) imaging of noncrystalline and crystalline equilibrium structures, as well as elemental volume composition, of materials and biological specimens, including those of viruses and cells. We report the development of 4D electron tomography by integrating the fourth dimension (time resolution) with the 3D spatial resolution obtained from a complete tilt series of 2D projections of an object. The different time frames of tomograms constitute a movie of the object in motion, thus enabling studies of nonequilibrium structures and transient processes. The method was demonstrated using carbon nanotubes of a bracelet-like ring structure for which 4D tomograms display different modes of motion, such as breathing and wiggling, with resonance frequencies up to 30 megahertz. Applications can now make use of the full space-time range with the nanometer-femtosecond resolution of ultrafast electron tomography.

4D Electron Tomography

NASA Astrophysics Data System (ADS)

Kwon, Oh-Hoon; Zewail, Ahmed H.

2010-06-01

Electron tomography provides three-dimensional (3D) imaging of noncrystalline and crystalline equilibrium structures, as well as elemental volume composition, of materials and biological specimens, including those of viruses and cells. We report the development of 4D electron tomography by integrating the fourth dimension (time resolution) with the 3D spatial resolution obtained from a complete tilt series of 2D projections of an object. The different time frames of tomograms constitute a movie of the object in motion, thus enabling studies of nonequilibrium structures and transient processes. The method was demonstrated using carbon nanotubes of a bracelet-like ring structure for which 4D tomograms display different modes of motion, such as breathing and wiggling, with resonance frequencies up to 30 megahertz. Applications can now make use of the full space-time range with the nanometer-femtosecond resolution of ultrafast electron tomography.

LASER BIOLOGY AND MEDICINE: Visualisation of details of a complicated inner structure of model objects by the method of diffusion optical tomography

NASA Astrophysics Data System (ADS)

Tret'yakov, Evgeniy V.; Shuvalov, Vladimir V.; Shutov, I. V.

2002-11-01

An approximate algorithm is tested for solving the problem of diffusion optical tomography in experiments on the visualisation of details of the inner structure of strongly scattering model objects containing scattering and semitransparent inclusions, as well as absorbing inclusions located inside other optical inhomogeneities. The stability of the algorithm to errors is demonstrated, which allows its use for a rapid (2 — 3 min) image reconstruction of the details of objects with a complicated inner structure.

XDesign: an open-source software package for designing X-ray imaging phantoms and experiments.

PubMed

Ching, Daniel J; Gürsoy, Dogˇa

2017-03-01

The development of new methods or utilization of current X-ray computed tomography methods is impeded by the substantial amount of expertise required to design an X-ray computed tomography experiment from beginning to end. In an attempt to make material models, data acquisition schemes and reconstruction algorithms more accessible to researchers lacking expertise in some of these areas, a software package is described here which can generate complex simulated phantoms and quantitatively evaluate new or existing data acquisition schemes and image reconstruction algorithms for targeted applications.

XDesign: An open-source software package for designing X-ray imaging phantoms and experiments

DOE PAGES

Ching, Daniel J.; Gursoy, Dogˇa

2017-02-21

Here, the development of new methods or utilization of current X-ray computed tomography methods is impeded by the substantial amount of expertise required to design an X-ray computed tomography experiment from beginning to end. In an attempt to make material models, data acquisition schemes and reconstruction algorithms more accessible to researchers lacking expertise in some of these areas, a software package is described here which can generate complex simulated phantoms and quantitatively evaluate new or existing data acquisition schemes and image reconstruction algorithms for targeted applications.

Motion-compensated cone beam computed tomography using a conjugate gradient least-squares algorithm and electrical impedance tomography imaging motion data.

PubMed

Pengpen, T; Soleimani, M

2015-06-13

Cone beam computed tomography (CBCT) is an imaging modality that has been used in image-guided radiation therapy (IGRT). For applications such as lung radiation therapy, CBCT images are greatly affected by the motion artefacts. This is mainly due to low temporal resolution of CBCT. Recently, a dual modality of electrical impedance tomography (EIT) and CBCT has been proposed, in which the high temporal resolution EIT imaging system provides motion data to a motion-compensated algebraic reconstruction technique (ART)-based CBCT reconstruction software. High computational time associated with ART and indeed other variations of ART make it less practical for real applications. This paper develops a motion-compensated conjugate gradient least-squares (CGLS) algorithm for CBCT. A motion-compensated CGLS offers several advantages over ART-based methods, including possibilities for explicit regularization, rapid convergence and parallel computations. This paper for the first time demonstrates motion-compensated CBCT reconstruction using CGLS and reconstruction results are shown in limited data CBCT considering only a quarter of the full dataset. The proposed algorithm is tested using simulated motion data in generic motion-compensated CBCT as well as measured EIT data in dual EIT-CBCT imaging. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Meaning of Interior Tomography

PubMed Central

Wang, Ge; Yu, Hengyong

2013-01-01

The classic imaging geometry for computed tomography is for collection of un-truncated projections and reconstruction of a global image, with the Fourier transform as the theoretical foundation that is intrinsically non-local. Recently, interior tomography research has led to theoretically exact relationships between localities in the projection and image spaces and practically promising reconstruction algorithms. Initially, interior tomography was developed for x-ray computed tomography. Then, it has been elevated as a general imaging principle. Finally, a novel framework known as “omni-tomography” is being developed for grand fusion of multiple imaging modalities, allowing tomographic synchrony of diversified features. PMID:23912256

Tunable diode laser absorption spectroscopy-based tomography system for on-line monitoring of two-dimensional distributions of temperature and H2O mole fraction.

PubMed

Xu, Lijun; Liu, Chang; Jing, Wenyang; Cao, Zhang; Xue, Xin; Lin, Yuzhen

2016-01-01

To monitor two-dimensional (2D) distributions of temperature and H2O mole fraction, an on-line tomography system based on tunable diode laser absorption spectroscopy (TDLAS) was developed. To the best of the authors' knowledge, this is the first report on a multi-view TDLAS-based system for simultaneous tomographic visualization of temperature and H2O mole fraction in real time. The system consists of two distributed feedback (DFB) laser diodes, a tomographic sensor, electronic circuits, and a computer. The central frequencies of the two DFB laser diodes are at 7444.36 cm(-1) (1343.3 nm) and 7185.6 cm(-1) (1391.67 nm), respectively. The tomographic sensor is used to generate fan-beam illumination from five views and to produce 60 ray measurements. The electronic circuits not only provide stable temperature and precise current controlling signals for the laser diodes but also can accurately sample the transmitted laser intensities and extract integrated absorbances in real time. Finally, the integrated absorbances are transferred to the computer, in which the 2D distributions of temperature and H2O mole fraction are reconstructed by using a modified Landweber algorithm. In the experiments, the TDLAS-based tomography system was validated by using asymmetric premixed flames with fixed and time-varying equivalent ratios, respectively. The results demonstrate that the system is able to reconstruct the profiles of the 2D distributions of temperature and H2O mole fraction of the flame and effectively capture the dynamics of the combustion process, which exhibits good potential for flame monitoring and on-line combustion diagnosis.

Tunable diode laser absorption spectroscopy-based tomography system for on-line monitoring of two-dimensional distributions of temperature and H2O mole fraction

NASA Astrophysics Data System (ADS)

Xu, Lijun; Liu, Chang; Jing, Wenyang; Cao, Zhang; Xue, Xin; Lin, Yuzhen

2016-01-01

To monitor two-dimensional (2D) distributions of temperature and H2O mole fraction, an on-line tomography system based on tunable diode laser absorption spectroscopy (TDLAS) was developed. To the best of the authors' knowledge, this is the first report on a multi-view TDLAS-based system for simultaneous tomographic visualization of temperature and H2O mole fraction in real time. The system consists of two distributed feedback (DFB) laser diodes, a tomographic sensor, electronic circuits, and a computer. The central frequencies of the two DFB laser diodes are at 7444.36 cm-1 (1343.3 nm) and 7185.6 cm-1 (1391.67 nm), respectively. The tomographic sensor is used to generate fan-beam illumination from five views and to produce 60 ray measurements. The electronic circuits not only provide stable temperature and precise current controlling signals for the laser diodes but also can accurately sample the transmitted laser intensities and extract integrated absorbances in real time. Finally, the integrated absorbances are transferred to the computer, in which the 2D distributions of temperature and H2O mole fraction are reconstructed by using a modified Landweber algorithm. In the experiments, the TDLAS-based tomography system was validated by using asymmetric premixed flames with fixed and time-varying equivalent ratios, respectively. The results demonstrate that the system is able to reconstruct the profiles of the 2D distributions of temperature and H2O mole fraction of the flame and effectively capture the dynamics of the combustion process, which exhibits good potential for flame monitoring and on-line combustion diagnosis.

Tunable diode laser absorption spectroscopy-based tomography system for on-line monitoring of two-dimensional distributions of temperature and H{sub 2}O mole fraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Lijun, E-mail: lijunxu@buaa.edu.cn; Liu, Chang; Jing, Wenyang

2016-01-15

To monitor two-dimensional (2D) distributions of temperature and H{sub 2}O mole fraction, an on-line tomography system based on tunable diode laser absorption spectroscopy (TDLAS) was developed. To the best of the authors’ knowledge, this is the first report on a multi-view TDLAS-based system for simultaneous tomographic visualization of temperature and H{sub 2}O mole fraction in real time. The system consists of two distributed feedback (DFB) laser diodes, a tomographic sensor, electronic circuits, and a computer. The central frequencies of the two DFB laser diodes are at 7444.36 cm{sup −1} (1343.3 nm) and 7185.6 cm{sup −1} (1391.67 nm), respectively. The tomographicmore » sensor is used to generate fan-beam illumination from five views and to produce 60 ray measurements. The electronic circuits not only provide stable temperature and precise current controlling signals for the laser diodes but also can accurately sample the transmitted laser intensities and extract integrated absorbances in real time. Finally, the integrated absorbances are transferred to the computer, in which the 2D distributions of temperature and H{sub 2}O mole fraction are reconstructed by using a modified Landweber algorithm. In the experiments, the TDLAS-based tomography system was validated by using asymmetric premixed flames with fixed and time-varying equivalent ratios, respectively. The results demonstrate that the system is able to reconstruct the profiles of the 2D distributions of temperature and H{sub 2}O mole fraction of the flame and effectively capture the dynamics of the combustion process, which exhibits good potential for flame monitoring and on-line combustion diagnosis.« less

Whole-cell imaging of the budding yeast Saccharomyces cerevisiae by high-voltage scanning transmission electron tomography.

PubMed

Murata, Kazuyoshi; Esaki, Masatoshi; Ogura, Teru; Arai, Shigeo; Yamamoto, Yuta; Tanaka, Nobuo

2014-11-01

Electron tomography using a high-voltage electron microscope (HVEM) provides three-dimensional information about cellular components in sections thicker than 1 μm, although in bright-field mode image degradation caused by multiple inelastic scattering of transmitted electrons limit the attainable resolution. Scanning transmission electron microscopy (STEM) is believed to give enhanced contrast and resolution compared to conventional transmission electron microscopy (CTEM). Samples up to 1 μm in thickness have been analyzed with an intermediate-voltage electron microscope because inelastic scattering is not a critical limitation, and probe broadening can be minimized. Here, we employed STEM at 1 MeV high-voltage to extend the useful specimen thickness for electron tomography, which we demonstrate by a seamless tomographic reconstruction of a whole, budding Saccharomyces cerevisiae yeast cell, which is ~3 μm in thickness. High-voltage STEM tomography, especially in the bright-field mode, demonstrated sufficiently enhanced contrast and intensity, compared to CTEM tomography, to permit segmentation of major organelles in the whole cell. STEM imaging also reduced specimen shrinkage during tilt-series acquisition. The fidelity of structural preservation was limited by cytoplasmic extraction, and the spatial resolution was limited by the relatively large convergence angle of the scanning probe. However, the new technique has potential to solve longstanding problems of image blurring in biological specimens beyond 1 μm in thickness, and may facilitate new research in cellular structural biology. Copyright © 2014 Elsevier B.V. All rights reserved.

A new Mumford-Shah total variation minimization based model for sparse-view x-ray computed tomography image reconstruction.

PubMed

Chen, Bo; Bian, Zhaoying; Zhou, Xiaohui; Chen, Wensheng; Ma, Jianhua; Liang, Zhengrong

2018-04-12

Total variation (TV) minimization for the sparse-view x-ray computer tomography (CT) reconstruction has been widely explored to reduce radiation dose. However, due to the piecewise constant assumption for the TV model, the reconstructed images often suffer from over-smoothness on the image edges. To mitigate this drawback of TV minimization, we present a Mumford-Shah total variation (MSTV) minimization algorithm in this paper. The presented MSTV model is derived by integrating TV minimization and Mumford-Shah segmentation. Subsequently, a penalized weighted least-squares (PWLS) scheme with MSTV is developed for the sparse-view CT reconstruction. For simplicity, the proposed algorithm is named as 'PWLS-MSTV.' To evaluate the performance of the present PWLS-MSTV algorithm, both qualitative and quantitative studies were conducted by using a digital XCAT phantom and a physical phantom. Experimental results show that the present PWLS-MSTV algorithm has noticeable gains over the existing algorithms in terms of noise reduction, contrast-to-ratio measure and edge-preservation.

Pulse Phase Dynamic Thermal Tomography Investigation on the Defects of the Solid-Propellant Missile Engine Cladding Layer

NASA Astrophysics Data System (ADS)

Peng, Wei; Wang, Fei; Liu, Jun-yan; Xiao, Peng; Wang, Yang; Dai, Jing-min

2018-04-01

Pulse phase dynamic thermal tomography (PP-DTT) was introduced as a nondestructive inspection technique to detect the defects of the solid-propellant missile engine cladding layer. One-dimensional thermal wave mathematical model stimulated by pulse signal was developed and employed to investigate the thermal wave transmission characteristics. The pulse phase algorithm was used to extract the thermal wave characteristic of thermal radiation. Depth calibration curve was obtained by fuzzy c-means algorithm. Moreover, PP-DTT, a depth-resolved photothermal imaging modality, was employed to enable three-dimensional (3D) visualization of cladding layer defects. The comparison experiment between PP-DTT and classical dynamic thermal tomography was investigated. The results showed that PP-DTT can reconstruct the 3D topography of defects in a high quality.

Evaluation of a computer-aided detection algorithm for timely diagnosis of small acute intracranial hemorrhage on computed tomography in a critical care environment

NASA Astrophysics Data System (ADS)

Lee, Joon K.; Chan, Tao; Liu, Brent J.; Huang, H. K.

2009-02-01

Detection of acute intracranial hemorrhage (AIH) is a primary task in the interpretation of computed tomography (CT) brain scans of patients suffering from acute neurological disturbances or after head trauma. Interpretation can be difficult especially when the lesion is inconspicuous or the reader is inexperienced. We have previously developed a computeraided detection (CAD) algorithm to detect small AIH. One hundred and thirty five small AIH CT studies from the Los Angeles County (LAC) + USC Hospital were identified and matched by age and sex with one hundred and thirty five normal studies. These cases were then processed using our AIH CAD system to evaluate the efficacy and constraints of the algorithm.

Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

PubMed Central

Srinivasan, Pratul P.; Kim, Leo A.; Mettu, Priyatham S.; Cousins, Scott W.; Comer, Grant M.; Izatt, Joseph A.; Farsiu, Sina

2014-01-01

We present a novel fully automated algorithm for the detection of retinal diseases via optical coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of oriented gradient descriptors as feature vectors of a support vector machine based classifier. The spectral domain OCT data sets used for cross-validation consisted of volumetric scans acquired from 45 subjects: 15 normal subjects, 15 patients with dry age-related macular degeneration (AMD), and 15 patients with diabetic macular edema (DME). Our classifier correctly identified 100% of cases with AMD, 100% cases with DME, and 86.67% cases of normal subjects. This algorithm is a potentially impactful tool for the remote diagnosis of ophthalmic diseases. PMID:25360373

Electrical conductivity imaging using gradient B, decomposition algorithm in magnetic resonance electrical impedance tomography (MREIT).

PubMed

Park, Chunjae; Kwon, Ohin; Woo, Eung Je; Seo, Jin Keun

2004-03-01

In magnetic resonance electrical impedance tomography (MREIT), we try to visualize cross-sectional conductivity (or resistivity) images of a subject. We inject electrical currents into the subject through surface electrodes and measure the z component Bz of the induced internal magnetic flux density using an MRI scanner. Here, z is the direction of the main magnetic field of the MRI scanner. We formulate the conductivity image reconstruction problem in MREIT from a careful analysis of the relationship between the injection current and the induced magnetic flux density Bz. Based on the novel mathematical formulation, we propose the gradient Bz decomposition algorithm to reconstruct conductivity images. This new algorithm needs to differentiate Bz only once in contrast to the previously developed harmonic Bz algorithm where the numerical computation of (inverted delta)2Bz is required. The new algorithm, therefore, has the important advantage of much improved noise tolerance. Numerical simulations with added random noise of realistic amounts show the feasibility of the algorithm in practical applications and also its robustness against measurement noise.

Metal-induced streak artifact reduction using iterative reconstruction algorithms in x-ray computed tomography image of the dentoalveolar region.

PubMed

Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia

2013-02-01

The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.

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

PubMed

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.

Three-dimensional structural dynamics and fluctuations of DNA-nanogold conjugates by individual-particle electron tomography

NASA Astrophysics Data System (ADS)

Zhang, Lei; Lei, Dongsheng; Smith, Jessica M.; Zhang, Meng; Tong, Huimin; Zhang, Xing; Lu, Zhuoyang; Liu, Jiankang; Alivisatos, A. Paul; Ren, Gang

2016-03-01

DNA base pairing has been used for many years to direct the arrangement of inorganic nanocrystals into small groupings and arrays with tailored optical and electrical properties. The control of DNA-mediated assembly depends crucially on a better understanding of three-dimensional structure of DNA-nanocrystal-hybridized building blocks. Existing techniques do not allow for structural determination of these flexible and heterogeneous samples. Here we report cryo-electron microscopy and negative-staining electron tomography approaches to image, and three-dimensionally reconstruct a single DNA-nanogold conjugate, an 84-bp double-stranded DNA with two 5-nm nanogold particles for potential substrates in plasmon-coupling experiments. By individual-particle electron tomography reconstruction, we obtain 14 density maps at ~2-nm resolution. Using these maps as constraints, we derive 14 conformations of dsDNA by molecular dynamics simulations. The conformational variation is consistent with that from liquid solution, suggesting that individual-particle electron tomography could be an expected approach to study DNA-assembling and flexible protein structure and dynamics.

Fast and accurate metrology of multi-layered ceramic materials by an automated boundary detection algorithm developed for optical coherence tomography data

PubMed Central

Ekberg, Peter; Su, Rong; Chang, Ernest W.; Yun, Seok Hyun; Mattsson, Lars

2014-01-01

Optical coherence tomography (OCT) is useful for materials defect analysis and inspection with the additional possibility of quantitative dimensional metrology. Here, we present an automated image-processing algorithm for OCT analysis of roll-to-roll multilayers in 3D manufacturing of advanced ceramics. It has the advantage of avoiding filtering and preset modeling, and will, thus, introduce a simplification. The algorithm is validated for its capability of measuring the thickness of ceramic layers, extracting the boundaries of embedded features with irregular shapes, and detecting the geometric deformations. The accuracy of the algorithm is very high, and the reliability is better than 1 µm when evaluating with the OCT images using the same gauge block step height reference. The method may be suitable for industrial applications to the rapid inspection of manufactured samples with high accuracy and robustness. PMID:24562018

Automated segmentation algorithm for detection of changes in vaginal epithelial morphology using optical coherence tomography

NASA Astrophysics Data System (ADS)

Chitchian, Shahab; Vincent, Kathleen L.; Vargas, Gracie; Motamedi, Massoud

2012-11-01

We have explored the use of optical coherence tomography (OCT) as a noninvasive tool for assessing the toxicity of topical microbicides, products used to prevent HIV, by monitoring the integrity of the vaginal epithelium. A novel feature-based segmentation algorithm using a nearest-neighbor classifier was developed to monitor changes in the morphology of vaginal epithelium. The two-step automated algorithm yielded OCT images with a clearly defined epithelial layer, enabling differentiation of normal and damaged tissue. The algorithm was robust in that it was able to discriminate the epithelial layer from underlying stroma as well as residual microbicide product on the surface. This segmentation technique for OCT images has the potential to be readily adaptable to the clinical setting for noninvasively defining the boundaries of the epithelium, enabling quantifiable assessment of microbicide-induced damage in vaginal tissue.

Development of PET projection data correction algorithm

NASA Astrophysics Data System (ADS)

Bazhanov, P. V.; Kotina, E. D.

2017-12-01

Positron emission tomography is modern nuclear medicine method used in metabolism and internals functions examinations. This method allows to diagnosticate treatments on their early stages. Mathematical algorithms are widely used not only for images reconstruction but also for PET data correction. In this paper random coincidences and scatter correction algorithms implementation are considered, as well as algorithm of PET projection data acquisition modeling for corrections verification.

In-situ straining and time-resolved electron tomography data acquisition in a transmission electron microscope.

PubMed

Hata, S; Miyazaki, S; Gondo, T; Kawamoto, K; Horii, N; Sato, K; Furukawa, H; Kudo, H; Miyazaki, H; Murayama, M

2017-04-01

This paper reports the preliminary results of a new in-situ three-dimensional (3D) imaging system for observing plastic deformation behavior in a transmission electron microscope (TEM) as a directly relevant development of the recently reported straining-and-tomography holder [Sato K et al. (2015) Development of a novel straining holder for transmission electron microscopy compatible with single tilt-axis electron tomography. Microsc. 64: 369-375]. We designed an integrated system using the holder and newly developed straining and image-acquisition software and then developed an experimental procedure for in-situ straining and time-resolved electron tomography (ET) data acquisition. The software for image acquisition and 3D visualization was developed based on the commercially available ET software TEMographyTM. We achieved time-resolved 3D visualization of nanometer-scale plastic deformation behavior in a Pb-Sn alloy sample, thus demonstrating the capability of this system for potential applications in materials science. © The Author 2016. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Gaussian process tomography for soft x-ray spectroscopy at WEST without equilibrium information

NASA Astrophysics Data System (ADS)

Wang, T.; Mazon, D.; Svensson, J.; Li, D.; Jardin, A.; Verdoolaege, G.

2018-06-01

Gaussian process tomography (GPT) is a recently developed tomography method based on the Bayesian probability theory [J. Svensson, JET Internal Report EFDA-JET-PR(11)24, 2011 and Li et al., Rev. Sci. Instrum. 84, 083506 (2013)]. By modeling the soft X-ray (SXR) emissivity field in a poloidal cross section as a Gaussian process, the Bayesian SXR tomography can be carried out in a robust and extremely fast way. Owing to the short execution time of the algorithm, GPT is an important candidate for providing real-time reconstructions with a view to impurity transport and fast magnetohydrodynamic control. In addition, the Bayesian formalism allows quantifying uncertainty on the inferred parameters. In this paper, the GPT technique is validated using a synthetic data set expected from the WEST tokamak, and the results are shown of its application to the reconstruction of SXR emissivity profiles measured on Tore Supra. The method is compared with the standard algorithm based on minimization of the Fisher information.

Bayesian image reconstruction for improving detection performance of muon tomography.

PubMed

Wang, Guobao; Schultz, Larry J; Qi, Jinyi

2009-05-01

Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.

Quarterly Research Performance Progress Report (2015 Q3). Ultrasonic Phased Arrays and Interactive Reflectivity Tomography for Nondestructive Inspection of Injection and Production Wells in Geothermal Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santos-Villalobos, Hector J; Polsky, Yarom; Kisner, Roger A

2015-09-01

For the past quarter, we have placed our effort in implementing the first version of the ModelBased Iterative Reconstruction (MBIR) algorithm, assembling and testing the electronics, designing transducers mounts, and defining our laboratory test samples. We have successfully developed the first implementation of MBIR for ultrasound imaging. The current algorithm was tested with synthetic data and we are currently making new modifications for the reconstruction of real ultrasound data. Beside assembling and testing the electronics, we developed a LabView graphic user interface (GUI) to fully control the ultrasonic phased array, adjust the time-delays of the transducers, and store the measuredmore » reflections. As part of preparing for a laboratory-scale demonstration, the design and fabrication of the laboratory samples has begun. Three cement blocks with embedded objects will be fabricated, characterized, and used to demonstrate the capabilities of the system. During the next quarter, we will continue to improve the current MBIR forward model and integrate the reconstruction code with the LabView GUI. In addition, we will define focal laws for the ultrasonic phased array and perform the laboratory demonstration. We expect to perform laboratory demonstration by the end of October 2015.« less

On the importance of FIB-SEM specific segmentation algorithms for porous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salzer, Martin, E-mail: martin.salzer@uni-ulm.de; Thiele, Simon, E-mail: simon.thiele@imtek.uni-freiburg.de; Zengerle, Roland, E-mail: zengerle@imtek.uni-freiburg.de

2014-09-15

A new algorithmic approach to segmentation of highly porous three dimensional image data gained by focused ion beam tomography is described which extends the key-principle of local threshold backpropagation described in Salzer et al. (2012). The technique of focused ion beam tomography has shown to be capable of imaging the microstructure of functional materials. In order to perform a quantitative analysis on the corresponding microstructure a segmentation task needs to be performed. However, algorithmic segmentation of images obtained with focused ion beam tomography is a challenging problem for highly porous materials if filling the pore phase, e.g. with epoxy resin,more » is difficult. The gray intensities of individual voxels are not sufficient to determine the phase represented by them and usual thresholding methods are not applicable. We thus propose a new approach to segmentation that pays respect to the specifics of the imaging process of focused ion beam tomography. As an application of our approach, the segmentation of three dimensional images for a cathode material used in polymer electrolyte membrane fuel cells is discussed. We show that our approach preserves significantly more of the original nanostructure than a thresholding approach. - Highlights: • We describe a new approach to the segmentation of FIB-SEM images of porous media. • The first and last occurrences of structures are detected by analysing the z-profiles. • The algorithm is validated by comparing it to a manual segmentation. • The new approach shows significantly less artifacts than a thresholding approach. • A structural analysis also shows improved results for the obtained microstructure.« less

Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction

NASA Technical Reports Server (NTRS)

Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

2000-01-01

This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

Seismic waveform tomography with shot-encoding using a restarted L-BFGS algorithm.

PubMed

Rao, Ying; Wang, Yanghua

2017-08-17

In seismic waveform tomography, or full-waveform inversion (FWI), one effective strategy used to reduce the computational cost is shot-encoding, which encodes all shots randomly and sums them into one super shot to significantly reduce the number of wavefield simulations in the inversion. However, this process will induce instability in the iterative inversion regardless of whether it uses a robust limited-memory BFGS (L-BFGS) algorithm. The restarted L-BFGS algorithm proposed here is both stable and efficient. This breakthrough ensures, for the first time, the applicability of advanced FWI methods to three-dimensional seismic field data. In a standard L-BFGS algorithm, if the shot-encoding remains unchanged, it will generate a crosstalk effect between different shots. This crosstalk effect can only be suppressed by employing sufficient randomness in the shot-encoding. Therefore, the implementation of the L-BFGS algorithm is restarted at every segment. Each segment consists of a number of iterations; the first few iterations use an invariant encoding, while the remainder use random re-coding. This restarted L-BFGS algorithm balances the computational efficiency of shot-encoding, the convergence stability of the L-BFGS algorithm, and the inversion quality characteristic of random encoding in FWI.

Tomography experiment of an integrated circuit specimen using 3 MeV electrons in the transmission electron microscope.

PubMed

Zhang, Hai-Bo; Zhang, Xiang-Liang; Wang, Yong; Takaoka, Akio

2007-01-01

The possibility of utilizing high-energy electron tomography to characterize the micron-scale three dimensional (3D) structures of integrated circuits has been demonstrated experimentally. First, electron transmission through a tilted SiO(2) film was measured with an ultrahigh-voltage electron microscope (ultra-HVEM) and analyzed from the point of view of elastic scattering of electrons, showing that linear attenuation of the logarithmic electron transmission still holds valid for effective specimen thicknesses up to 5 microm under 2 MV accelerating voltages. Electron tomography of a micron-order thick integrated circuit specimen including the Cu/via interconnect was then tried with 3 MeV electrons in the ultra-HVEM. Serial projection images of the specimen tilted at different angles over the range of +/-90 degrees were acquired, and 3D reconstruction was performed with the images by means of the IMOD software package. Consequently, the 3D structures of the Cu lines, via and void, were revealed by cross sections and surface rendering.

RADIAL COMPUTED TOMOGRAPHY OF AIR CONTAMINANTS USING OPTICAL REMOTE SENSING

EPA Science Inventory

The paper describes the application of an optical remote-sensing (ORS) system to map air contaminants and locate fugitive emissions. Many ORD systems may utilize radial non-overlapping beam geometry and a computed tomography (CT) algorithm to map the concentrations in a plane. In...

FIB-SEM cathodoluminescence tomography: practical and theoretical considerations.

PubMed

De Winter, D A M; Lebbink, M N; Wiggers De Vries, D F; Post, J A; Drury, M R

2011-09-01

Focused ion beam-scanning electron microscope (FIB-SEM) tomography is a powerful application in obtaining three-dimensional (3D) information. The FIB creates a cross section and subsequently removes thin slices. The SEM takes images using secondary or backscattered electrons, or maps every slice using X-rays and/or electron backscatter diffraction patterns. The objective of this study is to assess the possibilities of combining FIB-SEM tomography with cathodoluminescence (CL) imaging. The intensity of CL emission is related to variations in defect or impurity concentrations. A potential problem with FIB-SEM CL tomography is that ion milling may change the defect state of the material and the CL emission. In addition the conventional tilted sample geometry used in FIB-SEM tomography is not compatible with conventional CL detectors. Here we examine the influence of the FIB on CL emission in natural diamond and the feasibility of FIB-SEM CL tomography. A systematic investigation establishes that the ion beam influences CL emission of diamond, with a dependency on both the ion beam and electron beam acceleration voltage. CL emission in natural diamond is enhanced particularly at low ion beam and electron beam voltages. This enhancement of the CL emission can be partly explained by an increase in surface defects induced by ion milling. CL emission enhancement could be used to improve the CL image quality. To conduct FIB-SEM CL tomography, a recently developed novel specimen geometry is adopted to enable sequential ion milling and CL imaging on an untilted sample. We show that CL imaging can be manually combined with FIB-SEM tomography with a modified protocol for 3D microstructure reconstruction. In principle, automated FIB-SEM CL tomography should be feasible, provided that dedicated CL detectors are developed that allow subsequent milling and CL imaging without manual intervention, as the current CL detector needs to be manually retracted before a slice can be milled. Due to the required high electron beam acceleration voltage for CL emission, the resolution for FIB-SEM CL tomography is currently limited to several hundreds of nm in XY and up to 650 nm in Z for diamonds. Opaque materials are likely to have an improved Z resolution, as CL emission generated deeper in the material is not able to escape from it. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.

Evaluation of a Multicore-Optimized Implementation for Tomographic Reconstruction

PubMed Central

Agulleiro, Jose-Ignacio; Fernández, José Jesús

2012-01-01

Tomography allows elucidation of the three-dimensional structure of an object from a set of projection images. In life sciences, electron microscope tomography is providing invaluable information about the cell structure at a resolution of a few nanometres. Here, large images are required to combine wide fields of view with high resolution requirements. The computational complexity of the algorithms along with the large image size then turns tomographic reconstruction into a computationally demanding problem. Traditionally, high-performance computing techniques have been applied to cope with such demands on supercomputers, distributed systems and computer clusters. In the last few years, the trend has turned towards graphics processing units (GPUs). Here we present a detailed description and a thorough evaluation of an alternative approach that relies on exploitation of the power available in modern multicore computers. The combination of single-core code optimization, vector processing, multithreading and efficient disk I/O operations succeeds in providing fast tomographic reconstructions on standard computers. The approach turns out to be competitive with the fastest GPU-based solutions thus far. PMID:23139768

New hardware and workflows for semi-automated correlative cryo-fluorescence and cryo-electron microscopy/tomography.

PubMed

Schorb, Martin; Gaechter, Leander; Avinoam, Ori; Sieckmann, Frank; Clarke, Mairi; Bebeacua, Cecilia; Bykov, Yury S; Sonnen, Andreas F-P; Lihl, Reinhard; Briggs, John A G

2017-02-01

Correlative light and electron microscopy allows features of interest defined by fluorescence signals to be located in an electron micrograph of the same sample. Rare dynamic events or specific objects can be identified, targeted and imaged by electron microscopy or tomography. To combine it with structural studies using cryo-electron microscopy or tomography, fluorescence microscopy must be performed while maintaining the specimen vitrified at liquid-nitrogen temperatures and in a dry environment during imaging and transfer. Here we present instrumentation, software and an experimental workflow that improves the ease of use, throughput and performance of correlated cryo-fluorescence and cryo-electron microscopy. The new cryo-stage incorporates a specially modified high-numerical aperture objective lens and provides a stable and clean imaging environment. It is combined with a transfer shuttle for contamination-free loading of the specimen. Optimized microscope control software allows automated acquisition of the entire specimen area by cryo-fluorescence microscopy. The software also facilitates direct transfer of the fluorescence image and associated coordinates to the cryo-electron microscope for subsequent fluorescence-guided automated imaging. Here we describe these technological developments and present a detailed workflow, which we applied for automated cryo-electron microscopy and tomography of various specimens. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Improved tissue assignment using dual-energy computed tomography in low-dose rate prostate brachytherapy for Monte Carlo dose calculation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Côté, Nicolas; Bedwani, Stéphane; Carrier, Jean-François, E-mail: jean-francois.carrier.chum@ssss.gouv.qc.ca

Purpose: An improvement in tissue assignment for low-dose rate brachytherapy (LDRB) patients using more accurate Monte Carlo (MC) dose calculation was accomplished with a metallic artifact reduction (MAR) method specific to dual-energy computed tomography (DECT). Methods: The proposed MAR algorithm followed a four-step procedure. The first step involved applying a weighted blend of both DECT scans (I {sub H/L}) to generate a new image (I {sub Mix}). This action minimized Hounsfield unit (HU) variations surrounding the brachytherapy seeds. In the second step, the mean HU of the prostate in I {sub Mix} was calculated and shifted toward the mean HUmore » of the two original DECT images (I {sub H/L}). The third step involved smoothing the newly shifted I {sub Mix} and the two original I {sub H/L}, followed by a subtraction of both, generating an image that represented the metallic artifact (I {sub A,(H/L)}) of reduced noise levels. The final step consisted of subtracting the original I {sub H/L} from the newly generated I {sub A,(H/L)} and obtaining a final image corrected for metallic artifacts. Following the completion of the algorithm, a DECT stoichiometric method was used to extract the relative electronic density (ρ{sub e}) and effective atomic number (Z {sub eff}) at each voxel of the corrected scans. Tissue assignment could then be determined with these two newly acquired physical parameters. Each voxel was assigned the tissue bearing the closest resemblance in terms of ρ{sub e} and Z {sub eff}, comparing with values from the ICRU 42 database. A MC study was then performed to compare the dosimetric impacts of alternative MAR algorithms. Results: An improvement in tissue assignment was observed with the DECT MAR algorithm, compared to the single-energy computed tomography (SECT) approach. In a phantom study, tissue misassignment was found to reach 0.05% of voxels using the DECT approach, compared with 0.40% using the SECT method. Comparison of the DECT and SECT D {sub 90} dose parameter (volume receiving 90% of the dose) indicated that D {sub 90} could be underestimated by up to 2.3% using the SECT method. Conclusions: The DECT MAR approach is a simple alternative to reduce metallic artifacts found in LDRB patient scans. Images can be processed quickly and do not require the determination of x-ray spectra. Substantial information on density and atomic number can also be obtained. Furthermore, calcifications within the prostate are detected by the tissue assignment algorithm. This enables more accurate, patient-specific MC dose calculations.« less

Development and Translation of Hybrid Optoacoustic/Ultrasonic Tomography for Early Breast Cancer Detection

DTIC Science & Technology

2014-09-01

to develop an optimized system design and associated image reconstruction algorithms for a hybrid three-dimensional (3D) breast imaging system that...research is to develop an optimized system design and associated image reconstruction algorithms for a hybrid three-dimensional (3D) breast imaging ...i) developed time-of- flight extraction algorithms to perform USCT, (ii) developing image reconstruction algorithms for USCT, (iii) developed

Prior image constrained scatter correction in cone-beam computed tomography image-guided radiation therapy.

PubMed

Brunner, Stephen; Nett, Brian E; Tolakanahalli, Ranjini; Chen, Guang-Hong

2011-02-21

X-ray scatter is a significant problem in cone-beam computed tomography when thicker objects and larger cone angles are used, as scattered radiation can lead to reduced contrast and CT number inaccuracy. Advances have been made in x-ray computed tomography (CT) by incorporating a high quality prior image into the image reconstruction process. In this paper, we extend this idea to correct scatter-induced shading artifacts in cone-beam CT image-guided radiation therapy. Specifically, this paper presents a new scatter correction algorithm which uses a prior image with low scatter artifacts to reduce shading artifacts in cone-beam CT images acquired under conditions of high scatter. The proposed correction algorithm begins with an empirical hypothesis that the target image can be written as a weighted summation of a series of basis images that are generated by raising the raw cone-beam projection data to different powers, and then, reconstructing using the standard filtered backprojection algorithm. The weight for each basis image is calculated by minimizing the difference between the target image and the prior image. The performance of the scatter correction algorithm is qualitatively and quantitatively evaluated through phantom studies using a Varian 2100 EX System with an on-board imager. Results show that the proposed scatter correction algorithm using a prior image with low scatter artifacts can substantially mitigate scatter-induced shading artifacts in both full-fan and half-fan modes.

Study on beam geometry and image reconstruction algorithm in fast neutron computerized tomography at NECTAR facility

NASA Astrophysics Data System (ADS)

Guo, J.; Bücherl, T.; Zou, Y.; Guo, Z.

2011-09-01

Investigations on the fast neutron beam geometry for the NECTAR facility are presented. The results of MCNP simulations and experimental measurements of the beam distributions at NECTAR are compared. Boltzmann functions are used to describe the beam profile in the detection plane assuming the area source to be set up of large number of single neutron point sources. An iterative algebraic reconstruction algorithm is developed, realized and verified by both simulated and measured projection data. The feasibility for improved reconstruction in fast neutron computerized tomography at the NECTAR facility is demonstrated.

Hypersonic and Supersonic Flow Roadmaps Using Bibliometrics and Database Tomography.

ERIC Educational Resources Information Center

Kostoff, R. N.; Eberhart, Henry J.; Toothman, Darrell Ray

1999-01-01

Database Tomography (DT) is a textual database-analysis system consisting of algorithms for extracting multiword phrase frequencies and proximities from a large textual database, to augment interpretative capabilities of the expert human analyst. Describes use of the DT process, supplemented by literature bibliometric analyses, to derive technical…

Automatic segmentation of the optic nerve head for deformation measurements in video rate optical coherence tomography

NASA Astrophysics Data System (ADS)

Hidalgo-Aguirre, Maribel; Gitelman, Julian; Lesk, Mark Richard; Costantino, Santiago

2015-11-01

Optical coherence tomography (OCT) imaging has become a standard diagnostic tool in ophthalmology, providing essential information associated with various eye diseases. In order to investigate the dynamics of the ocular fundus, we present a simple and accurate automated algorithm to segment the inner limiting membrane in video-rate optic nerve head spectral domain (SD) OCT images. The method is based on morphological operations including a two-step contrast enhancement technique, proving to be very robust when dealing with low signal-to-noise ratio images and pathological eyes. An analysis algorithm was also developed to measure neuroretinal tissue deformation from the segmented retinal profiles. The performance of the algorithm is demonstrated, and deformation results are presented for healthy and glaucomatous eyes.

A fast reconstruction algorithm for fluorescence optical diffusion tomography based on preiteration.

PubMed

Song, Xiaolei; Xiong, Xiaoyun; Bai, Jing

2007-01-01

Fluorescence optical diffusion tomography in the near-infrared (NIR) bandwidth is considered to be one of the most promising ways for noninvasive molecular-based imaging. Many reconstructive approaches to it utilize iterative methods for data inversion. However, they are time-consuming and they are far from meeting the real-time imaging demands. In this work, a fast preiteration algorithm based on the generalized inverse matrix is proposed. This method needs only one step of matrix-vector multiplication online, by pushing the iteration process to be executed offline. In the preiteration process, the second-order iterative format is employed to exponentially accelerate the convergence. Simulations based on an analytical diffusion model show that the distribution of fluorescent yield can be well estimated by this algorithm and the reconstructed speed is remarkably increased.

Nonlinear inversion of borehole-radar tomography data to reconstruct velocity and attenuation distribution in earth materials

USGS Publications Warehouse

Zhou, C.; Liu, L.; Lane, J.W.

2001-01-01

A nonlinear tomographic inversion method that uses first-arrival travel-time and amplitude-spectra information from cross-hole radar measurements was developed to simultaneously reconstruct electromagnetic velocity and attenuation distribution in earth materials. Inversion methods were developed to analyze single cross-hole tomography surveys and differential tomography surveys. Assuming the earth behaves as a linear system, the inversion methods do not require estimation of source radiation pattern, receiver coupling, or geometrical spreading. The data analysis and tomographic inversion algorithm were applied to synthetic test data and to cross-hole radar field data provided by the US Geological Survey (USGS). The cross-hole radar field data were acquired at the USGS fractured-rock field research site at Mirror Lake near Thornton, New Hampshire, before and after injection of a saline tracer, to monitor the transport of electrically conductive fluids in the image plane. Results from the synthetic data test demonstrate the algorithm computational efficiency and indicate that the method robustly can reconstruct electromagnetic (EM) wave velocity and attenuation distribution in earth materials. The field test results outline zones of velocity and attenuation anomalies consistent with the finding of previous investigators; however, the tomograms appear to be quite smooth. Further work is needed to effectively find the optimal smoothness criterion in applying the Tikhonov regularization in the nonlinear inversion algorithms for cross-hole radar tomography. ?? 2001 Elsevier Science B.V. All rights reserved.

Three-dimensional structural dynamics and fluctuations of DNA-nanogold conjugates by individual-particle electron tomography

DOE PAGES

Zhang, Lei; Lei, Dongsheng; Smith, Jessica M.; ...

2016-03-30

DNA base pairing has been used for many years to direct the arrangement of inorganic nanocrystals into small groupings and arrays with tailored optical and electrical properties. The control of DNA-mediated assembly depends crucially on a better understanding of three-dimensional structure of DNA-nanocrystal-hybridized building blocks. Existing techniques do not allow for structural determination of these flexible and heterogeneous samples. Here we report cryo-electron microscopy and negative-staining electron tomography approaches to image, and three-dimensionally reconstruct a single DNA-nanogold conjugate, an 84-bp double-stranded DNA with two 5-nm nanogold particles for potential substrates in plasmon-coupling experiments. By individual-particle electron tomography reconstruction, we obtainmore » 14 density maps at ~ 2-nm resolution . Using these maps as constraints, we derive 14 conformations of dsDNA by molecular dynamics simulations. The conformational variation is consistent with that from liquid solution, suggesting that individual-particle electron tomography could be an expected approach to study DNA-assembling and flexible protein structure and dynamics.« less

Accelerated gradient-based free form deformable registration for online adaptive radiotherapy

NASA Astrophysics Data System (ADS)

Yu, Gang; Liang, Yueqiang; Yang, Guanyu; Shu, Huazhong; Li, Baosheng; Yin, Yong; Li, Dengwang

2015-04-01

The registration of planning fan-beam computed tomography (FBCT) and daily cone-beam CT (CBCT) is a crucial step in adaptive radiation therapy. The current intensity-based registration algorithms, such as Demons, may fail when they are used to register FBCT and CBCT, because the CT numbers in CBCT cannot exactly correspond to the electron densities. In this paper, we investigated the effects of CBCT intensity inaccuracy on the registration accuracy and developed an accurate gradient-based free form deformation algorithm (GFFD). GFFD distinguishes itself from other free form deformable registration algorithms by (a) measuring the similarity using the 3D gradient vector fields to avoid the effect of inconsistent intensities between the two modalities; (b) accommodating image sampling anisotropy using the local polynomial approximation-intersection of confidence intervals (LPA-ICI) algorithm to ensure a smooth and continuous displacement field; and (c) introducing a ‘bi-directional’ force along with an adaptive force strength adjustment to accelerate the convergence process. It is expected that such a strategy can decrease the effect of the inconsistent intensities between the two modalities, thus improving the registration accuracy and robustness. Moreover, for clinical application, the algorithm was implemented by graphics processing units (GPU) through OpenCL framework. The registration time of the GFFD algorithm for each set of CT data ranges from 8 to 13 s. The applications of on-line adaptive image-guided radiation therapy, including auto-propagation of contours, aperture-optimization and dose volume histogram (DVH) in the course of radiation therapy were also studied by in-house-developed software.

New trend in electron holography

NASA Astrophysics Data System (ADS)

Tanigaki, Toshiaki; Harada, Ken; Murakami, Yasukazu; Niitsu, Kodai; Akashi, Tetsuya; Takahashi, Yoshio; Sugawara, Akira; Shindo, Daisuke

2016-06-01

Electron holography using a coherent electron wave is a promising technique for high-resolution visualization of electromagnetic fields in and around objects. The capability of electron holography has been enhanced by the development of new technologies and has thus become an even more powerful tool for exploring scientific frontiers. This review introduces these technologies including split-illumination electron holography and vector-field electron tomography. Split-illumination electron holography, which uses separated coherent waves, overcomes the limits imposed by the lateral coherence requirement for electron waves in electron holography. Areas that are difficult to observe using conventional electron holography are now observable. Exemplified applications include observing a singular magnetic domain wall in electrical steel sheets, local magnetizations at anti-phase boundaries, and electrostatic potentials in metal-oxide-semiconductor field-effect transistors. Vector-field electron tomography can be used to visualize magnetic vectors in three dimensions. Two components of the vectors are reconstructed using dual-axis tomography, and the remaining one is calculated using div B   =  0. A high-voltage electron microscope can be used to achieve precise magnetic reconstruction. For example, magnetic vortices have been visualized using a 1 MV holography electron microscope.

A 3D reconstruction algorithm for magneto-acoustic tomography with magnetic induction based on ultrasound transducer characteristics.

PubMed

Ma, Ren; Zhou, Xiaoqing; Zhang, Shunqi; Yin, Tao; Liu, Zhipeng

2016-12-21

In this study we present a three-dimensional (3D) reconstruction algorithm for magneto-acoustic tomography with magnetic induction (MAT-MI) based on the characteristics of the ultrasound transducer. The algorithm is investigated to solve the blur problem of the MAT-MI acoustic source image, which is caused by the ultrasound transducer and the scanning geometry. First, we established a transducer model matrix using measured data from the real transducer. With reference to the S-L model used in the computed tomography algorithm, a 3D phantom model of electrical conductivity is set up. Both sphere scanning and cylinder scanning geometries are adopted in the computer simulation. Then, using finite element analysis, the distribution of the eddy current and the acoustic source as well as the acoustic pressure can be obtained with the transducer model matrix. Next, using singular value decomposition, the inverse transducer model matrix together with the reconstruction algorithm are worked out. The acoustic source and the conductivity images are reconstructed using the proposed algorithm. Comparisons between an ideal point transducer and the realistic transducer are made to evaluate the algorithms. Finally, an experiment is performed using a graphite phantom. We found that images of the acoustic source reconstructed using the proposed algorithm are a better match than those using the previous one, the correlation coefficient of sphere scanning geometry is 98.49% and that of cylinder scanning geometry is 94.96%. Comparison between the ideal point transducer and the realistic transducer shows that the correlation coefficients are 90.2% in sphere scanning geometry and 86.35% in cylinder scanning geometry. The reconstruction of the graphite phantom experiment also shows a higher resolution using the proposed algorithm. We conclude that the proposed reconstruction algorithm, which considers the characteristics of the transducer, can obviously improve the resolution of the reconstructed image. This study can be applied to analyse the effect of the position of the transducer and the scanning geometry on imaging. It may provide a more precise method to reconstruct the conductivity distribution in MAT-MI.

Electron tomography and computer visualisation of a three-dimensional 'photonic' crystal in a butterfly wing-scale.

PubMed

Argyros, A; Manos, S; Large, M C J; McKenzie, D R; Cox, G C; Dwarte, D M

2002-01-01

A combination of transmission electron tomography and computer modelling has been used to determine the three-dimensional structure of the photonic crystals found in the wing-scales of the Kaiser-I-Hind butterfly (Teinopalpus imperialis). These scales presented challenges for electron microscopy because the periodicity of the structure was comparable to the thickness of a section and because of the complex connectivity of the object. The structure obtained has been confirmed by taking slices of the three-dimensional computer model constructed from the tomography and comparing these with transmission electron microscope (TEM) images of microtomed sections of the actual scale. The crystal was found to have chiral tetrahedral repeating units packed in a triclinic lattice.

Three-dimensional structural analysis of eukaryotic flagella/cilia by electron cryo-tomography

PubMed Central

Bui, Khanh Huy; Pigino, Gaia; Ishikawa, Takashi

2011-01-01

Electron cryo-tomography is a potential approach to analyzing the three-dimensional conformation of frozen hydrated biological macromolecules using electron microscopy. Since projections of each individual object illuminated from different orientations are merged, electron tomography is capable of structural analysis of such heterogeneous environments as in vivo or with polymorphism, although radiation damage and the missing wedge are severe problems. Here, recent results on the structure of eukaryotic flagella, which is an ATP-driven bending organelle, from green algae Chlamydomonas are presented. Tomographic analysis reveals asymmetric molecular arrangements, especially that of the dynein motor proteins, in flagella, giving insight into the mechanism of planar asymmetric bending motion. Methodological challenges to obtaining higher-resolution structures from this technique are also discussed. PMID:21169680

Application of Patterson-function direct methods to materials characterization.

PubMed

Rius, Jordi

2014-09-01

The aim of this article is a general description of the so-called Patterson-function direct methods (PFDM), from their origin to their present state. It covers a 20-year period of methodological contributions to crystal structure solution, most of them published in Acta Crystallographica Section A. The common feature of these variants of direct methods is the introduction of the experimental intensities in the form of the Fourier coefficients of origin-free Patterson-type functions, which allows the active use of both strong and weak reflections. The different optimization algorithms are discussed and their performances compared. This review focuses not only on those PFDM applications related to powder diffraction data but also on some recent results obtained with electron diffraction tomography data.

Multi-GPU parallel algorithm design and analysis for improved inversion of probability tomography with gravity gradiometry data

NASA Astrophysics Data System (ADS)

Hou, Zhenlong; Huang, Danian

2017-09-01

In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.

Experimental Evaluation of a Deformable Registration Algorithm for Motion Correction in PET-CT Guided Biopsy.

PubMed

Khare, Rahul; Sala, Guillaume; Kinahan, Paul; Esposito, Giuseppe; Banovac, Filip; Cleary, Kevin; Enquobahrie, Andinet

2013-01-01

Positron emission tomography computed tomography (PET-CT) images are increasingly being used for guidance during percutaneous biopsy. However, due to the physics of image acquisition, PET-CT images are susceptible to problems due to respiratory and cardiac motion, leading to inaccurate tumor localization, shape distortion, and attenuation correction. To address these problems, we present a method for motion correction that relies on respiratory gated CT images aligned using a deformable registration algorithm. In this work, we use two deformable registration algorithms and two optimization approaches for registering the CT images obtained over the respiratory cycle. The two algorithms are the BSpline and the symmetric forces Demons registration. In the first optmization approach, CT images at each time point are registered to a single reference time point. In the second approach, deformation maps are obtained to align each CT time point with its adjacent time point. These deformations are then composed to find the deformation with respect to a reference time point. We evaluate these two algorithms and optimization approaches using respiratory gated CT images obtained from 7 patients. Our results show that overall the BSpline registration algorithm with the reference optimization approach gives the best results.

Methods and algorithms for optical coherence tomography-based angiography: a review and comparison

NASA Astrophysics Data System (ADS)

Zhang, Anqi; Zhang, Qinqin; Chen, Chieh-Li; Wang, Ruikang K.

2015-10-01

Optical coherence tomography (OCT)-based angiography is increasingly becoming a clinically useful and important imaging technique due to its ability to provide volumetric microvascular networks innervating tissue beds in vivo without a need for exogenous contrast agent. Numerous OCT angiography algorithms have recently been proposed for the purpose of contrasting microvascular networks. A general literature review is provided on the recent progress of OCT angiography methods and algorithms. The basic physics and mathematics behind each method together with its contrast mechanism are described. Potential directions for future technical development of OCT based angiography is then briefly discussed. Finally, by the use of clinical data captured from normal and pathological subjects, the imaging performance of vascular networks delivered by the most recently reported algorithms is evaluated and compared, including optical microangiography, speckle variance, phase variance, split-spectrum amplitude decorrelation angiography, and correlation mapping. It is found that the method that utilizes complex OCT signal to contrast retinal blood flow delivers the best performance among all the algorithms in terms of image contrast and vessel connectivity. The purpose of this review is to help readers understand and select appropriate OCT angiography algorithm for use in specific applications.

TOWARD QUANTITATIVE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY: Visualizing Blood Flow Speeds in Ocular Pathology Using Variable Interscan Time Analysis.

PubMed

Ploner, Stefan B; Moult, Eric M; Choi, WooJhon; Waheed, Nadia K; Lee, ByungKun; Novais, Eduardo A; Cole, Emily D; Potsaid, Benjamin; Husvogt, Lennart; Schottenhamml, Julia; Maier, Andreas; Rosenfeld, Philip J; Duker, Jay S; Hornegger, Joachim; Fujimoto, James G

2016-12-01

Currently available optical coherence tomography angiography systems provide information about blood flux but only limited information about blood flow speed. The authors develop a method for mapping the previously proposed variable interscan time analysis (VISTA) algorithm into a color display that encodes relative blood flow speed. Optical coherence tomography angiography was performed with a 1,050 nm, 400 kHz A-scan rate, swept source optical coherence tomography system using a 5 repeated B-scan protocol. Variable interscan time analysis was used to compute the optical coherence tomography angiography signal from B-scan pairs having 1.5 millisecond and 3.0 milliseconds interscan times. The resulting VISTA data were then mapped to a color space for display. The authors evaluated the VISTA visualization algorithm in normal eyes (n = 2), nonproliferative diabetic retinopathy eyes (n = 6), proliferative diabetic retinopathy eyes (n = 3), geographic atrophy eyes (n = 4), and exudative age-related macular degeneration eyes (n = 2). All eyes showed blood flow speed variations, and all eyes with pathology showed abnormal blood flow speeds compared with controls. The authors developed a novel method for mapping VISTA into a color display, allowing visualization of relative blood flow speeds. The method was found useful, in a small case series, for visualizing blood flow speeds in a variety of ocular diseases and serves as a step toward quantitative optical coherence tomography angiography.

Evaluation of a prototype correction algorithm to reduce metal artefacts in flat detector computed tomography of scaphoid fixation screws.

PubMed

Filli, Lukas; Marcon, Magda; Scholz, Bernhard; Calcagni, Maurizio; Finkenstädt, Tim; Andreisek, Gustav; Guggenberger, Roman

2014-12-01

The aim of this study was to evaluate a prototype correction algorithm to reduce metal artefacts in flat detector computed tomography (FDCT) of scaphoid fixation screws. FDCT has gained interest in imaging small anatomic structures of the appendicular skeleton. Angiographic C-arm systems with flat detectors allow fluoroscopy and FDCT imaging in a one-stop procedure emphasizing their role as an ideal intraoperative imaging tool. However, FDCT imaging can be significantly impaired by artefacts induced by fixation screws. Following ethical board approval, commercially available scaphoid fixation screws were inserted into six cadaveric specimens in order to fix artificially induced scaphoid fractures. FDCT images corrected with the algorithm were compared to uncorrected images both quantitatively and qualitatively by two independent radiologists in terms of artefacts, screw contour, fracture line visibility, bone visibility, and soft tissue definition. Normal distribution of variables was evaluated using the Kolmogorov-Smirnov test. In case of normal distribution, quantitative variables were compared using paired Student's t tests. The Wilcoxon signed-rank test was used for quantitative variables without normal distribution and all qualitative variables. A p value of < 0.05 was considered to indicate statistically significant differences. Metal artefacts were significantly reduced by the correction algorithm (p < 0.001), and the fracture line was more clearly defined (p < 0.01). The inter-observer reliability was "almost perfect" (intra-class correlation coefficient 0.85, p < 0.001). The prototype correction algorithm in FDCT for metal artefacts induced by scaphoid fixation screws may facilitate intra- and postoperative follow-up imaging. Flat detector computed tomography (FDCT) is a helpful imaging tool for scaphoid fixation. The correction algorithm significantly reduces artefacts in FDCT induced by scaphoid fixation screws. This may facilitate intra- and postoperative follow-up imaging.

Three-dimensional imaging of adherent cells using FIB/SEM and STEM.

PubMed

Villinger, Clarissa; Schauflinger, Martin; Gregorius, Heiko; Kranz, Christine; Höhn, Katharina; Nafeey, Soufi; Walther, Paul

2014-01-01

In this chapter we describe three different approaches for three-dimensional imaging of electron microscopic samples: serial sectioning transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM) tomography, and focused ion beam/scanning electron microscopy (FIB/SEM) tomography. With these methods, relatively large volumes of resin-embedded biological structures can be analyzed at resolutions of a few nm within a reasonable expenditure of time. The traditional method is serial sectioning and imaging the same area in all sections. Another method is TEM tomography that involves tilting a section in the electron beam and then reconstruction of the volume by back projection of the images. When the scanning transmission (STEM) mode is used, thicker sections (up to 1 μm) can be analyzed. The third approach presented here is focused ion beam/scanning electron microscopy (FIB/SEM) tomography, in which a sample is repeatedly milled with a focused ion beam (FIB) and each newly produced block face is imaged with the scanning electron microscope (SEM). This process can be repeated ad libitum in arbitrary small increments allowing 3D analysis of relatively large volumes such as eukaryotic cells. We show that resolution of this approach is considerably improved when the secondary electron signal is used. However, the most important prerequisite for three-dimensional imaging is good specimen preparation. For all three imaging methods, cryo-fixed (high-pressure frozen) and freeze-substituted samples have been used.

Uses of megavoltage digital tomosynthesis in radiotherapy

NASA Astrophysics Data System (ADS)

Sarkar, Vikren

With the advent of intensity modulated radiotherapy, radiation treatment plans are becoming more conformal to the tumor with the decreasing margins. It is therefore of prime importance that the patient be positioned correctly prior to treatment. Therefore, image guided treatment is necessary for intensity modulated radiotherapy plans to be implemented successfully. Current advanced imaging devices require costly hardware and software upgrade, and radiation imaging solutions, such as cone beam computed tomography, may introduce extra radiation dose to the patient in order to acquire better quality images. Thus, there is a need to extend current existing imaging device ability and functions while reducing cost and radiation dose. Existing electronic portal imaging devices can be used to generate computed tomography-like tomograms through projection images acquired over a small angle using the technique of cone-beam digital tomosynthesis. Since it uses a fraction of the images required for computed tomography reconstruction, use of this technique correspondingly delivers only a fraction of the imaging dose to the patient. Furthermore, cone-beam digital tomosynthesis can be offered as a software-only solution as long as a portal imaging device is available. In this study, the feasibility of performing digital tomosynthesis using individually-acquired megavoltage images from a charge coupled device-based electronic portal imaging device was investigated. Three digital tomosynthesis reconstruction algorithms, the shift-and-add, filtered back-projection, and simultaneous algebraic reconstruction technique, were compared considering the final image quality and radiation dose during imaging. A software platform, DART, was created using a combination of the Matlab and C++ languages. The platform allows for the registration of a reference Cone Beam Digital Tomosynthesis (CBDT) image against a daily acquired set to determine how to shift the patient prior to treatment. Finally, the software was extended to investigate if the digital tomosynthesis dataset could be used in an adaptive radiotherapy regimen through the use of the Pinnacle treatment planning software to recalculate dose delivered. The feasibility study showed that the megavoltage CBDT visually agreed with corresponding megavoltage computed tomography images. The comparative study showed that the best compromise between imaging quality and imaging dose is obtained when 11 projection images, acquired over an imaging angle of 40°, are used with the filtered back-projection algorithm. DART was successfully used to register reference and daily image sets to within 1 mm in-plane and 2.5 mm out of plane. The DART platform was also effectively used to generate updated files that the Pinnacle treatment planning system used to calculate updated dose in a rigidly shifted patient. These doses were then used to calculate a cumulative dose distribution that could be used by a physician as reference to decide when the treatment plan should be updated. In conclusion, this study showed that a software solution is possible to extend existing electronic portal imaging devices to function as cone-beam digital tomosynthesis devices and achieve daily requirement for image guided intensity modulated radiotherapy treatments. The DART platform also has the potential to be used as a part of adaptive radiotherapy solution.

DALMATIAN: An Algorithm for Automatic Cell Detection and Counting in 3D.

PubMed

Shuvaev, Sergey A; Lazutkin, Alexander A; Kedrov, Alexander V; Anokhin, Konstantin V; Enikolopov, Grigori N; Koulakov, Alexei A

2017-01-01

Current 3D imaging methods, including optical projection tomography, light-sheet microscopy, block-face imaging, and serial two photon tomography enable visualization of large samples of biological tissue. Large volumes of data obtained at high resolution require development of automatic image processing techniques, such as algorithms for automatic cell detection or, more generally, point-like object detection. Current approaches to automated cell detection suffer from difficulties originating from detection of particular cell types, cell populations of different brightness, non-uniformly stained, and overlapping cells. In this study, we present a set of algorithms for robust automatic cell detection in 3D. Our algorithms are suitable for, but not limited to, whole brain regions and individual brain sections. We used watershed procedure to split regional maxima representing overlapping cells. We developed a bootstrap Gaussian fit procedure to evaluate the statistical significance of detected cells. We compared cell detection quality of our algorithm and other software using 42 samples, representing 6 staining and imaging techniques. The results provided by our algorithm matched manual expert quantification with signal-to-noise dependent confidence, including samples with cells of different brightness, non-uniformly stained, and overlapping cells for whole brain regions and individual tissue sections. Our algorithm provided the best cell detection quality among tested free and commercial software.

Contours identification of elements in a cone beam computed tomography for investigating maxillary cysts

NASA Astrophysics Data System (ADS)

Chioran, Doina; Nicoarǎ, Adrian; Roşu, Şerban; Cǎrligeriu, Virgil; Ianeş, Emilia

2013-10-01

Digital processing of two-dimensional cone beam computer tomography slicesstarts by identification of the contour of elements within. This paper deals with the collective work of specialists in medicine and applied mathematics in computer science on elaborating and implementation of algorithms in dental 2D imagery.

Fast automatic segmentation of anatomical structures in x-ray computed tomography images to improve fluorescence molecular tomography reconstruction.

PubMed

Freyer, Marcus; Ale, Angelique; Schulz, Ralf B; Zientkowska, Marta; Ntziachristos, Vasilis; Englmeier, Karl-Hans

2010-01-01

The recent development of hybrid imaging scanners that integrate fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) allows the utilization of x-ray information as image priors for improving optical tomography reconstruction. To fully capitalize on this capacity, we consider a framework for the automatic and fast detection of different anatomic structures in murine XCT images. To accurately differentiate between different structures such as bone, lung, and heart, a combination of image processing steps including thresholding, seed growing, and signal detection are found to offer optimal segmentation performance. The algorithm and its utilization in an inverse FMT scheme that uses priors is demonstrated on mouse images.

Assessment of Systematic Measurement Errors for Acoustic Travel-Time Tomography of the Atmosphere

DTIC Science & Technology

2013-01-01

measurements include assess- ment of the time delays in electronic circuits and mechanical hardware (e.g., drivers and microphones) of a tomography array ...hardware and electronic circuits of the tomography array and errors in synchronization of the transmitted and recorded signals. For example, if...coordinates can be as large as 30 cm. These errors are equivalent to the systematic errors in the travel times of 0.9 ms. Third, loudspeakers which are used

Nonuniform update for sparse target recovery in fluorescence molecular tomography accelerated by ordered subsets.

PubMed

Zhu, Dianwen; Li, Changqing

2014-12-01

Fluorescence molecular tomography (FMT) is a promising imaging modality and has been actively studied in the past two decades since it can locate the specific tumor position three-dimensionally in small animals. However, it remains a challenging task to obtain fast, robust and accurate reconstruction of fluorescent probe distribution in small animals due to the large computational burden, the noisy measurement and the ill-posed nature of the inverse problem. In this paper we propose a nonuniform preconditioning method in combination with L (1) regularization and ordered subsets technique (NUMOS) to take care of the different updating needs at different pixels, to enhance sparsity and suppress noise, and to further boost convergence of approximate solutions for fluorescence molecular tomography. Using both simulated data and phantom experiment, we found that the proposed nonuniform updating method outperforms its popular uniform counterpart by obtaining a more localized, less noisy, more accurate image. The computational cost was greatly reduced as well. The ordered subset (OS) technique provided additional 5 times and 3 times speed enhancements for simulation and phantom experiments, respectively, without degrading image qualities. When compared with the popular L (1) algorithms such as iterative soft-thresholding algorithm (ISTA) and Fast iterative soft-thresholding algorithm (FISTA) algorithms, NUMOS also outperforms them by obtaining a better image in much shorter period of time.

J-substitution algorithm in magnetic resonance electrical impedance tomography (MREIT): phantom experiments for static resistivity images.

PubMed

Khang, Hyun Soo; Lee, Byung Il; Oh, Suk Hoon; Woo, Eung Je; Lee, Soo Yeol; Cho, Min Hyoung; Kwon, Ohin; Yoon, Jeong Rock; Seo, Jin Keun

2002-06-01

Recently, a new static resistivity image reconstruction algorithm is proposed utilizing internal current density data obtained by magnetic resonance current density imaging technique. This new imaging method is called magnetic resonance electrical impedance tomography (MREIT). The derivation and performance of J-substitution algorithm in MREIT have been reported as a new accurate and high-resolution static impedance imaging technique via computer simulation methods. In this paper, we present experimental procedures, denoising techniques, and image reconstructions using a 0.3-tesla (T) experimental MREIT system and saline phantoms. MREIT using J-substitution algorithm effectively utilizes the internal current density information resolving the problem inherent in a conventional EIT, that is, the low sensitivity of boundary measurements to any changes of internal tissue resistivity values. Resistivity images of saline phantoms show an accuracy of 6.8%-47.2% and spatial resolution of 64 x 64. Both of them can be significantly improved by using an MRI system with a better signal-to-noise ratio.

A combined reconstruction-classification method for diffuse optical tomography.

PubMed

Hiltunen, P; Prince, S J D; Arridge, S

2009-11-07

We present a combined classification and reconstruction algorithm for diffuse optical tomography (DOT). DOT is a nonlinear ill-posed inverse problem. Therefore, some regularization is needed. We present a mixture of Gaussians prior, which regularizes the DOT reconstruction step. During each iteration, the parameters of a mixture model are estimated. These associate each reconstructed pixel with one of several classes based on the current estimate of the optical parameters. This classification is exploited to form a new prior distribution to regularize the reconstruction step and update the optical parameters. The algorithm can be described as an iteration between an optimization scheme with zeroth-order variable mean and variance Tikhonov regularization and an expectation-maximization scheme for estimation of the model parameters. We describe the algorithm in a general Bayesian framework. Results from simulated test cases and phantom measurements show that the algorithm enhances the contrast of the reconstructed images with good spatial accuracy. The probabilistic classifications of each image contain only a few misclassified pixels.

Separation of left and right lungs using 3-dimensional information of sequential computed tomography images and a guided dynamic programming algorithm.

PubMed

Park, Sang Cheol; Leader, Joseph Ken; Tan, Jun; Lee, Guee Sang; Kim, Soo Hyung; Na, In Seop; Zheng, Bin

2011-01-01

This article presents a new computerized scheme that aims to accurately and robustly separate left and right lungs on computed tomography (CT) examinations. We developed and tested a method to separate the left and right lungs using sequential CT information and a guided dynamic programming algorithm using adaptively and automatically selected start point and end point with especially severe and multiple connections. The scheme successfully identified and separated all 827 connections on the total 4034 CT images in an independent testing data set of CT examinations. The proposed scheme separated multiple connections regardless of their locations, and the guided dynamic programming algorithm reduced the computation time to approximately 4.6% in comparison with the traditional dynamic programming and avoided the permeation of the separation boundary into normal lung tissue. The proposed method is able to robustly and accurately disconnect all connections between left and right lungs, and the guided dynamic programming algorithm is able to remove redundant processing.

A convolutional neural network approach to calibrating the rotation axis for X-ray computed tomography.

PubMed

Yang, Xiaogang; De Carlo, Francesco; Phatak, Charudatta; Gürsoy, Dogˇa

2017-03-01

This paper presents an algorithm to calibrate the center-of-rotation for X-ray tomography by using a machine learning approach, the Convolutional Neural Network (CNN). The algorithm shows excellent accuracy from the evaluation of synthetic data with various noise ratios. It is further validated with experimental data of four different shale samples measured at the Advanced Photon Source and at the Swiss Light Source. The results are as good as those determined by visual inspection and show better robustness than conventional methods. CNN has also great potential for reducing or removing other artifacts caused by instrument instability, detector non-linearity, etc. An open-source toolbox, which integrates the CNN methods described in this paper, is freely available through GitHub at tomography/xlearn and can be easily integrated into existing computational pipelines available at various synchrotron facilities. Source code, documentation and information on how to contribute are also provided.

Framework for cognitive analysis of dynamic perfusion computed tomography with visualization of large volumetric data

NASA Astrophysics Data System (ADS)

Hachaj, Tomasz; Ogiela, Marek R.

2012-10-01

The proposed framework for cognitive analysis of perfusion computed tomography images is a fusion of image processing, pattern recognition, and image analysis procedures. The output data of the algorithm consists of: regions of perfusion abnormalities, anatomy atlas description of brain tissues, measures of perfusion parameters, and prognosis for infracted tissues. That information is superimposed onto volumetric computed tomography data and displayed to radiologists. Our rendering algorithm enables rendering large volumes on off-the-shelf hardware. This portability of rendering solution is very important because our framework can be run without using expensive dedicated hardware. The other important factors are theoretically unlimited size of rendered volume and possibility of trading of image quality for rendering speed. Such rendered, high quality visualizations may be further used for intelligent brain perfusion abnormality identification, and computer aided-diagnosis of selected types of pathologies.

A penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography.

PubMed

Shang, Shang; Bai, Jing; Song, Xiaolei; Wang, Hongkai; Lau, Jaclyn

2007-01-01

Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.

Image quality improvement in optical coherence tomography using Lucy-Richardson deconvolution algorithm.

PubMed

Hojjatoleslami, S A; Avanaki, M R N; Podoleanu, A Gh

2013-08-10

Optical coherence tomography (OCT) has the potential for skin tissue characterization due to its high axial and transverse resolution and its acceptable depth penetration. In practice, OCT cannot reach the theoretical resolutions due to imperfections of some of the components used. One way to improve the quality of the images is to estimate the point spread function (PSF) of the OCT system and deconvolve it from the output images. In this paper, we investigate the use of solid phantoms to estimate the PSF of the imaging system. We then utilize iterative Lucy-Richardson deconvolution algorithm to improve the quality of the images. The performance of the proposed algorithm is demonstrated on OCT images acquired from a variety of samples, such as epoxy-resin phantoms, fingertip skin and basaloid larynx and eyelid tissues.

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

3D reconstruction of the magnetic vector potential using model based iterative reconstruction.

PubMed

Prabhat, K C; Aditya Mohan, K; Phatak, Charudatta; Bouman, Charles; De Graef, Marc

2017-11-01

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. A comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach. Copyright © 2017 Elsevier B.V. All rights reserved.

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

DOE PAGES

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta; ...

2017-07-03

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

Accurately Diagnosing Uric Acid Stones from Conventional Computerized Tomography Imaging: Development and Preliminary Assessment of a Pixel Mapping Software.

PubMed

Ganesan, Vishnu; De, Shubha; Shkumat, Nicholas; Marchini, Giovanni; Monga, Manoj

2018-02-01

Preoperative determination of uric acid stones from computerized tomography imaging would be of tremendous clinical use. We sought to design a software algorithm that could apply data from noncontrast computerized tomography to predict the presence of uric acid stones. Patients with pure uric acid and calcium oxalate stones were identified from our stone registry. Only stones greater than 4 mm which were clearly traceable from initial computerized tomography to final composition were included in analysis. A semiautomated computer algorithm was used to process image data. Average and maximum HU, eccentricity (deviation from a circle) and kurtosis (peakedness vs flatness) were automatically generated. These parameters were examined in several mathematical models to predict the presence of uric acid stones. A total of 100 patients, of whom 52 had calcium oxalate and 48 had uric acid stones, were included in the final analysis. Uric acid stones were significantly larger (12.2 vs 9.0 mm, p = 0.03) but calcium oxalate stones had higher mean attenuation (457 vs 315 HU, p = 0.001) and maximum attenuation (918 vs 553 HU, p <0.001). Kurtosis was significantly higher in each axis for calcium oxalate stones (each p <0.001). A composite algorithm using attenuation distribution pattern, average attenuation and stone size had overall 89% sensitivity, 91% specificity, 91% positive predictive value and 89% negative predictive value to predict uric acid stones. A combination of stone size, attenuation intensity and attenuation pattern from conventional computerized tomography can distinguish uric acid stones from calcium oxalate stones with high sensitivity and specificity. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Dose reduction in whole-body computed tomography of multiple injuries (DoReMI): protocol for a prospective cohort study

PubMed Central

2014-01-01

Background Single-pass, contrast-enhanced whole body multidetector computed tomography (MDCT) emerged as the diagnostic standard for evaluating patients with major trauma. Modern iterative image algorithms showed high image quality at a much lower radiation dose in the non-trauma setting. This study aims at investigating whether the radiation dose can safely be reduced in trauma patients without compromising the diagnostic accuracy and image quality. Methods/Design Prospective observational study with two consecutive cohorts of patients. Setting: A high-volume, academic, supra-regional trauma centre in Germany. Study population: Consecutive male and female patients who 1. had been exposed to a high-velocity trauma mechanism, 2. present with clinical evidence or high suspicion of multiple trauma (predicted Injury Severity Score [ISS] ≥16) and 3. are scheduled for primary MDCT based on the decision of the trauma leader on call. Imaging protocols: In a before/after design, a consecutive series of 500 patients will undergo single-pass, whole-body 128-row multi-detector computed tomography (MDCT) with a standard, as low as possible radiation dose. This will be followed by a consecutive series of 500 patients undergoing an approved ultra-low dose MDCT protocol using an image processing algorithm. Data: Routine administrative data and electronic patient records, as well as digital images stored in a picture archiving and communications system will serve as the primary data source. The protocol was approved by the institutional review board. Main outcomes: (1) incidence of delayed diagnoses, (2) diagnostic accuracy, as correlated to the reference standard of a synopsis of all subsequent clinical, imaging, surgical and autopsy findings, (3) patients’ safety, (4) radiation exposure (e.g. effective dose), (5) subjective image quality (assessed independently radiologists and trauma surgeons on a 100-mm visual analogue scale), (6) objective image quality (e.g., contrast-to-noise ratio). Analysis: Multivariate regression will be employed to adjust and correct the findings for time and cohort effects. An exploratory interim analysis halfway after introduction of low-dose MDCT will be conducted to assess whether this protocol is clearly inferior or superior to the current standard. Discussion Although non-experimental, this study will generate first large-scale data on the utility of imaging-enhancing algorithms in whole-body MDCT for major blunt trauma. Trial registration Current Controlled Trials ISRCTN74557102. PMID:24589310

Dynamic discrete tomography

NASA Astrophysics Data System (ADS)

Alpers, Andreas; Gritzmann, Peter

2018-03-01

We consider the problem of reconstructing the paths of a set of points over time, where, at each of a finite set of moments in time the current positions of points in space are only accessible through some small number of their x-rays. This particular particle tracking problem, with applications, e.g. in plasma physics, is the basic problem in dynamic discrete tomography. We introduce and analyze various different algorithmic models. In particular, we determine the computational complexity of the problem (and various of its relatives) and derive algorithms that can be used in practice. As a byproduct we provide new results on constrained variants of min-cost flow and matching problems.

Fast sparse recovery and coherence factor weighting in optoacoustic tomography

NASA Astrophysics Data System (ADS)

He, Hailong; Prakash, Jaya; Buehler, Andreas; Ntziachristos, Vasilis

2017-03-01

Sparse recovery algorithms have shown great potential to reconstruct images with limited view datasets in optoacoustic tomography, with a disadvantage of being computational expensive. In this paper, we improve the fast convergent Split Augmented Lagrangian Shrinkage Algorithm (SALSA) method based on least square QR (LSQR) formulation for performing accelerated reconstructions. Further, coherence factor is calculated to weight the final reconstruction result, which can further reduce artifacts arising in limited-view scenarios and acoustically heterogeneous mediums. Several phantom and biological experiments indicate that the accelerated SALSA method with coherence factor (ASALSA-CF) can provide improved reconstructions and much faster convergence compared to existing sparse recovery methods.

Depth-resolved birefringence and differential optical axis orientation measurements with fiber-based polarization-sensitive optical coherence tomography.

PubMed

Guo, Shuguang; Zhang, Jun; Wang, Lei; Nelson, J Stuart; Chen, Zhongping

2004-09-01

Conventional polarization-sensitive optical coherence tomography (PS-OCT) can provide depth-resolved Stokes parameter measurements of light reflected from turbid media. A new algorithm that takes into account changes in the optical axis is introduced to provide depth-resolved birefringence and differential optical axis orientation images by use of fiber-based PS-OCT. Quaternion, a convenient mathematical tool, is used to represent an optical element and simplify the algorithm. Experimental results with beef tendon and rabbit tendon and muscle show that this technique has promising potential for imaging the birefringent structure of multiple-layer samples with varying optical axes.

Poster — Thur Eve — 09: Evaluation of electrical impedance and computed tomography fusion algorithms using an anthropomorphic phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chugh, Brige Paul; Krishnan, Kalpagam; Liu, Jeff

2014-08-15

Integration of biological conductivity information provided by Electrical Impedance Tomography (EIT) with anatomical information provided by Computed Tomography (CT) imaging could improve the ability to characterize tissues in clinical applications. In this paper, we report results of our study which compared the fusion of EIT with CT using three different image fusion algorithms, namely: weighted averaging, wavelet fusion, and ROI indexing. The ROI indexing method of fusion involves segmenting the regions of interest from the CT image and replacing the pixels with the pixels of the EIT image. The three algorithms were applied to a CT and EIT image ofmore » an anthropomorphic phantom, constructed out of five acrylic contrast targets with varying diameter embedded in a base of gelatin bolus. The imaging performance was assessed using Detectability and Structural Similarity Index Measure (SSIM). Wavelet fusion and ROI-indexing resulted in lower Detectability (by 35% and 47%, respectively) yet higher SSIM (by 66% and 73%, respectively) than weighted averaging. Our results suggest that wavelet fusion and ROI-indexing yielded more consistent and optimal fusion performance than weighted averaging.« less

Jini service to reconstruct tomographic data

NASA Astrophysics Data System (ADS)

Knoll, Peter; Mirzaei, S.; Koriska, K.; Koehn, H.

2002-06-01

A number of imaging systems rely on the reconstruction of a 3- dimensional model from its projections through the process of computed tomography (CT). In medical imaging, for example magnetic resonance imaging (MRI), positron emission tomography (PET), and Single Computer Tomography (SPECT) acquire two-dimensional projections of a three dimensional projections of a three dimensional object. In order to calculate the 3-dimensional representation of the object, i.e. its voxel distribution, several reconstruction algorithms have been developed. Currently, mainly two reconstruct use: the filtered back projection(FBP) and iterative methods. Although the quality of iterative reconstructed SPECT slices is better than that of FBP slices, such iterative algorithms are rarely used for clinical routine studies because of their low availability and increased reconstruction time. We used Jini and a self-developed iterative reconstructions algorithm to design and implement a Jini reconstruction service. With this service, the physician selects the patient study from a database and a Jini client automatically discovers the registered Jini reconstruction services in the department's Intranet. After downloading the proxy object the this Jini service, the SPECT acquisition data are reconstructed. The resulting transaxial slices are visualized using a Jini slice viewer, which can be used for various imaging modalities.

The challenge of determining handedness in electron tomography and the use of DNA origami gold nanoparticle helices as molecular standards

PubMed Central

Briegel, Ariane; Pilhofer, Martin; Mastronarde, David N.; Jensen, Grant J.

2013-01-01

The apparent handedness of an EM-tomography reconstruction depends on a number of conventions and can be confused in many ways. As the number of different hardware and software combinations being used for electron tomography continue to climb, and the reconstructions being produced reach higher and higher resolutions, the need to verify the hand of the results has increased. Here we enumerate various steps in a typical tomography experiment that affect handedness and show that DNA origami gold nanoparticle helices can be used as convenient and fail-safe handedness standards. PMID:23639902

Quantitative 3D high resolution transmission ultrasound tomography: creating clinically relevant images (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wiskin, James; Klock, John; Iuanow, Elaine; Borup, Dave T.; Terry, Robin; Malik, Bilal H.; Lenox, Mark

2017-03-01

There has been a great deal of research into ultrasound tomography for breast imaging over the past 35 years. Few successful attempts have been made to reconstruct high-resolution images using transmission ultrasound. To this end, advances have been made in 2D and 3D algorithms that utilize either time of arrival or full wave data to reconstruct images with high spatial and contrast resolution suitable for clinical interpretation. The highest resolution and quantitative accuracy result from inverse scattering applied to full wave data in 3D. However, this has been prohibitively computationally expensive, meaning that full inverse scattering ultrasound tomography has not been considered clinically viable. Here we show the results of applying a nonlinear inverse scattering algorithm to 3D data in a clinically useful time frame. This method yields Quantitative Transmission (QT) ultrasound images with high spatial and contrast resolution. We reconstruct sound speeds for various 2D and 3D phantoms and verify these values with independent measurements. The data are fully 3D as is the reconstruction algorithm, with no 2D approximations. We show that 2D reconstruction algorithms can introduce artifacts into the QT breast image which are avoided by using a full 3D algorithm and data. We show high resolution gross and microscopic anatomic correlations comparing cadaveric breast QT images with MRI to establish imaging capability and accuracy. Finally, we show reconstructions of data from volunteers, as well as an objective visual grading analysis to confirm clinical imaging capability and accuracy.

Reconstructing the microstructure of polyimide-silicalite mixed-matrix membranes and their particle connectivity using FIB-SEM tomography.

PubMed

Diblíková, P; Veselý, M; Sysel, P; Čapek, P

2018-03-01

Properties of a composite material made of a continuous matrix and particles often depend on microscopic details, such as contacts between particles. Focusing on processing raw focused-ion beam scanning electron microscope (FIB-SEM) tomography data, we reconstructed three mixed-matrix membrane samples made of 6FDA-ODA polyimide and silicalite-1 particles. In the first step of image processing, backscattered electron (BSE) and secondary electron (SE) signals were mixed in a ratio that was expected to obtain a segmented 3D image with a realistic volume fraction of silicalite-1. Second, after spatial alignment of the stacked FIB-SEM data, the 3D image was smoothed using adaptive median and anisotropic nonlinear diffusion filters. Third, the image was segmented using the power watershed method coupled with a seeding algorithm based on geodesic reconstruction from the markers. If the resulting volume fraction did not match the target value quantified by chemical analysis of the sample, the BSE and SE signals were mixed in another ratio and the procedure was repeated until the target volume fraction was achieved. Otherwise, the segmented 3D image (replica) was accepted and its microstructure was thoroughly characterized with special attention paid to connectivity of the silicalite phase. In terms of the phase connectivity, Monte Carlo simulations based on the pure-phase permeability values enabled us to calculate the effective permeability tensor, the main diagonal elements of which were compared with the experimental permeability. In line with the hypothesis proposed in our recent paper (Čapek, P. et al. (2014) Comput. Mater. Sci. 89, 142-156), the results confirmed that the existence of particle clusters was a key microstructural feature determining effective permeability. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Alternative method of quantum state tomography toward a typical target via a weak-value measurement

NASA Astrophysics Data System (ADS)

Chen, Xi; Dai, Hong-Yi; Yang, Le; Zhang, Ming

2018-03-01

There is usually a limitation of weak interaction on the application of weak-value measurement. This limitation dominates the performance of the quantum state tomography toward a typical target in the finite and high-dimensional complex-valued superposition of its basis states, especially when the compressive sensing technique is also employed. Here we propose an alternative method of quantum state tomography, presented as a general model, toward such typical target via weak-value measurement to overcome such limitation. In this model the pointer for the weak-value measurement is a qubit, and the target-pointer coupling interaction is no longer needed within the weak interaction limitation, meanwhile this interaction under the compressive sensing can be described with the Taylor series of the unitary evolution operator. The postselection state at the target is the equal superposition of all basis states, and the pointer readouts are gathered under multiple Pauli operator measurements. The reconstructed quantum state is generated from an optimization algorithm of total variation augmented Lagrangian alternating direction algorithm. Furthermore, we demonstrate an example of this general model for the quantum state tomography toward the planar laser-energy distribution and discuss the relations among some parameters at both our general model and the original first-order approximate model for this tomography.

Multigrid-based reconstruction algorithm for quantitative photoacoustic tomography

PubMed Central

Li, Shengfu; Montcel, Bruno; Yuan, Zhen; Liu, Wanyu; Vray, Didier

2015-01-01

This paper proposes a multigrid inversion framework for quantitative photoacoustic tomography reconstruction. The forward model of optical fluence distribution and the inverse problem are solved at multiple resolutions. A fixed-point iteration scheme is formulated for each resolution and used as a cost function. The simulated and experimental results for quantitative photoacoustic tomography reconstruction show that the proposed multigrid inversion can dramatically reduce the required number of iterations for the optimization process without loss of reliability in the results. PMID:26203371

Advanced Optical Diagnostics for Ice Crystal Cloud Measurements in the NASA Glenn Propulsion Systems Laboratory

NASA Technical Reports Server (NTRS)

Bencic, Timothy J.; Fagan, Amy; Van Zante, Judith F.; Kirkegaard, Jonathan P.; Rohler, David P.; Maniyedath, Arjun; Izen, Steven H.

2013-01-01

A light extinction tomography technique has been developed to monitor ice water clouds upstream of a direct connected engine in the Propulsion Systems Laboratory (PSL) at NASA Glenn Research Center (GRC). The system consists of 60 laser diodes with sheet generating optics and 120 detectors mounted around a 36-inch diameter ring. The sources are pulsed sequentially while the detectors acquire line-of-sight extinction data for each laser pulse. Using computed tomography algorithms, the extinction data are analyzed to produce a plot of the relative water content in the measurement plane. To target the low-spatial-frequency nature of ice water clouds, unique tomography algorithms were developed using filtered back-projection methods and direct inversion methods that use Gaussian basis functions. With the availability of a priori knowledge of the mean droplet size and the total water content at some point in the measurement plane, the tomography system can provide near real-time in-situ quantitative full-field total water content data at a measurement plane approximately 5 feet upstream of the engine inlet. Results from ice crystal clouds in the PSL are presented. In addition to the optical tomography technique, laser sheet imaging has also been applied in the PSL to provide planar ice cloud uniformity and relative water content data during facility calibration before the tomography system was available and also as validation data for the tomography system. A comparison between the laser sheet system and light extinction tomography resulting data are also presented. Very good agreement of imaged intensity and water content is demonstrated for both techniques. Also, comparative studies between the two techniques show excellent agreement in calculation of bulk total water content averaged over the center of the pipe.

Electronic resistance tomography imaging of spatial moisture distribution, moisture distribution and movement in pavements

DOT National Transportation Integrated Search

1997-07-01

Electronic resistance tomography (ERT) was used to follow the infiltration of water into a pavement section at the UC Berkeley Richmond Field Station. A volume of pavement 1 m square and 1.29 m in depth was sampled by an ERT array consisting of elect...

Bayesian seismic tomography by parallel interacting Markov chains

NASA Astrophysics Data System (ADS)

Gesret, Alexandrine; Bottero, Alexis; Romary, Thomas; Noble, Mark; Desassis, Nicolas

2014-05-01

The velocity field estimated by first arrival traveltime tomography is commonly used as a starting point for further seismological, mineralogical, tectonic or similar analysis. In order to interpret quantitatively the results, the tomography uncertainty values as well as their spatial distribution are required. The estimated velocity model is obtained through inverse modeling by minimizing an objective function that compares observed and computed traveltimes. This step is often performed by gradient-based optimization algorithms. The major drawback of such local optimization schemes, beyond the possibility of being trapped in a local minimum, is that they do not account for the multiple possible solutions of the inverse problem. They are therefore unable to assess the uncertainties linked to the solution. Within a Bayesian (probabilistic) framework, solving the tomography inverse problem aims at estimating the posterior probability density function of velocity model using a global sampling algorithm. Markov chains Monte-Carlo (MCMC) methods are known to produce samples of virtually any distribution. In such a Bayesian inversion, the total number of simulations we can afford is highly related to the computational cost of the forward model. Although fast algorithms have been recently developed for computing first arrival traveltimes of seismic waves, the complete browsing of the posterior distribution of velocity model is hardly performed, especially when it is high dimensional and/or multimodal. In the latter case, the chain may even stay stuck in one of the modes. In order to improve the mixing properties of classical single MCMC, we propose to make interact several Markov chains at different temperatures. This method can make efficient use of large CPU clusters, without increasing the global computational cost with respect to classical MCMC and is therefore particularly suited for Bayesian inversion. The exchanges between the chains allow a precise sampling of the high probability zones of the model space while avoiding the chains to end stuck in a probability maximum. This approach supplies thus a robust way to analyze the tomography imaging uncertainties. The interacting MCMC approach is illustrated on two synthetic examples of tomography of calibration shots such as encountered in induced microseismic studies. On the second application, a wavelet based model parameterization is presented that allows to significantly reduce the dimension of the problem, making thus the algorithm efficient even for a complex velocity model.

Measuring the Autocorrelation Function of Nanoscale Three-Dimensional Density Distribution in Individual Cells Using Scanning Transmission Electron Microscopy, Atomic Force Microscopy, and a New Deconvolution Algorithm.

PubMed

Li, Yue; Zhang, Di; Capoglu, Ilker; Hujsak, Karl A; Damania, Dhwanil; Cherkezyan, Lusik; Roth, Eric; Bleher, Reiner; Wu, Jinsong S; Subramanian, Hariharan; Dravid, Vinayak P; Backman, Vadim

2017-06-01

Essentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass-density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass-density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass-density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass-density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass-density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes.

Measuring the Autocorrelation Function of Nanoscale Three-Dimensional Density Distribution in Individual Cells Using Scanning Transmission Electron Microscopy, Atomic Force Microscopy, and a New Deconvolution Algorithm

PubMed Central

Li, Yue; Zhang, Di; Capoglu, Ilker; Hujsak, Karl A.; Damania, Dhwanil; Cherkezyan, Lusik; Roth, Eric; Bleher, Reiner; Wu, Jinsong S.; Subramanian, Hariharan; Dravid, Vinayak P.; Backman, Vadim

2018-01-01

Essentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass–density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass–density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass–density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass–density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass–density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes. PMID:28416035

Advanced prior modeling for 3D bright field electron tomography

NASA Astrophysics Data System (ADS)

Sreehari, Suhas; Venkatakrishnan, S. V.; Drummy, Lawrence F.; Simmons, Jeffrey P.; Bouman, Charles A.

2015-03-01

Many important imaging problems in material science involve reconstruction of images containing repetitive non-local structures. Model-based iterative reconstruction (MBIR) could in principle exploit such redundancies through the selection of a log prior probability term. However, in practice, determining such a log prior term that accounts for the similarity between distant structures in the image is quite challenging. Much progress has been made in the development of denoising algorithms like non-local means and BM3D, and these are known to successfully capture non-local redundancies in images. But the fact that these denoising operations are not explicitly formulated as cost functions makes it unclear as to how to incorporate them in the MBIR framework. In this paper, we formulate a solution to bright field electron tomography by augmenting the existing bright field MBIR method to incorporate any non-local denoising operator as a prior model. We accomplish this using a framework we call plug-and-play priors that decouples the log likelihood and the log prior probability terms in the MBIR cost function. We specifically use 3D non-local means (NLM) as the prior model in the plug-and-play framework, and showcase high quality tomographic reconstructions of a simulated aluminum spheres dataset, and two real datasets of aluminum spheres and ferritin structures. We observe that streak and smear artifacts are visibly suppressed, and that edges are preserved. Also, we report lower RMSE values compared to the conventional MBIR reconstruction using qGGMRF as the prior model.

Ultrastructure Features and Three-Dimensional Transmission Electron Tomography of Dhub Lizard (Uromastyx Aegyptia) Cornea and Its Adaptation to a Desert Environment.

PubMed

Akhtar, Saeed; Alkhalaf, Mousa; Khan, Adnan A; Almubrad, Turki M

2016-08-01

We report ultrastructural features and transmission electron tomography of the dhub lizard (Uromastyx aegyptia) cornea and its adaptation to hot and dry environments. Six corneas of dhub lizards were fixed in 2.5% glutaraldehyde and processed for electron microscopy and tomography. The ultrathin sections were observed with a JEOL 1400 transmission electron microscope. The cornea of the dhub lizard is very thin (~28-30 µm). The epithelium constitutes ~14% of the cornea, whereas the stroma constitutes 80% of the cornea. The middle stromal lamellae are significantly thicker than anterior and posterior stromal lamellae. Collagen fibril (CF) diameters in the anterior stroma are variable in size (25-75 nm). Proteoglycans (PGs) are very large in the middle and posterior stroma, whereas they are small in the anterior stroma. Three-dimensional electron tomography was carried out to understand the structure and arrangement of the PG and CFs. The presence of large PGs in the posterior and middle stroma might help the animal retain a large amount of water to protect it from dryness. The dhub corneal structure is equipped to adapt to the dry and hot desert environment.

Direct coupling of tomography and ptychography

DOE PAGES

Gürsoy, Doğa

2017-08-09

We present a generalization of the ptychographic phase problem for recovering refractive properties of a three-dimensional object in a tomography setting. Our approach, which ignores the lateral overlapping probe requirements in existing ptychography algorithms, can enable the reconstruction of objects using highly flexible acquisition patterns and pave the way for sparse and rapid data collection with lower radiation exposure.

Statistical image reconstruction from correlated data with applications to PET

PubMed Central

Alessio, Adam; Sauer, Ken; Kinahan, Paul

2008-01-01

Most statistical reconstruction methods for emission tomography are designed for data modeled as conditionally independent Poisson variates. In reality, due to scanner detectors, electronics and data processing, correlations are introduced into the data resulting in dependent variates. In general, these correlations are ignored because they are difficult to measure and lead to computationally challenging statistical reconstruction algorithms. This work addresses the second concern, seeking to simplify the reconstruction of correlated data and provide a more precise image estimate than the conventional independent methods. In general, correlated variates have a large non-diagonal covariance matrix that is computationally challenging to use as a weighting term in a reconstruction algorithm. This work proposes two methods to simplify the use of a non-diagonal covariance matrix as the weighting term by (a) limiting the number of dimensions in which the correlations are modeled and (b) adopting flexible, yet computationally tractable, models for correlation structure. We apply and test these methods with simple simulated PET data and data processed with the Fourier rebinning algorithm which include the one-dimensional correlations in the axial direction and the two-dimensional correlations in the transaxial directions. The methods are incorporated into a penalized weighted least-squares 2D reconstruction and compared with a conventional maximum a posteriori approach. PMID:17921576

High resolution IVEM tomography of biological specimens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sedat, J.W.; Agard, D.A.

Electron tomography is a powerful tool for elucidating the three-dimensional architecture of large biological complexes and subcellular organelles. The introduction of intermediate voltage electron microscopes further extended the technique by providing the means to examine very large and non-symmetrical subcellular organelles, at resolutions beyond what would be possible using light microscopy. Recent studies using electron tomography on a variety of cellular organelles and assemblies such as centrosomes, kinetochores, and chromatin have clearly demonstrated the power of this technique for obtaining 3D structural information on non-symmetric cell components. When combined with biochemical and molecular observations, these 3D reconstructions have provided significantmore » new insights into biological function.« less

Cone-Beam Computed Tomography for Image-Guided Radiation Therapy of Prostate Cancer

DTIC Science & Technology

2008-01-01

forexa t volumetri image re onstru tion. As a onsequense, images re onstru ted by approx-imate algorithms, mostly based on the Feldkamp algorithm...patient dose from CBCT. Reverse heli al CBCT has been developed for exa tre onstru tion of volumetri images, region-of-interest (ROI) re onstru tion...algorithm with a priori informa-tion in few-view CBCT for IGRT. We expe t the proposed algorithm an redu e the numberof proje tions needed for volumetri

Frequency-domain ultrasound waveform tomography breast attenuation imaging

NASA Astrophysics Data System (ADS)

Sandhu, Gursharan Yash Singh; Li, Cuiping; Roy, Olivier; West, Erik; Montgomery, Katelyn; Boone, Michael; Duric, Neb

2016-04-01

Ultrasound waveform tomography techniques have shown promising results for the visualization and characterization of breast disease. By using frequency-domain waveform tomography techniques and a gradient descent algorithm, we have previously reconstructed the sound speed distributions of breasts of varying densities with different types of breast disease including benign and malignant lesions. By allowing the sound speed to have an imaginary component, we can model the intrinsic attenuation of a medium. We can similarly recover the imaginary component of the velocity and thus the attenuation. In this paper, we will briefly review ultrasound waveform tomography techniques, discuss attenuation and its relations to the imaginary component of the sound speed, and provide both numerical and ex vivo examples of waveform tomography attenuation reconstructions.

Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm

NASA Astrophysics Data System (ADS)

Wang, Yuzhu; Rahman, Sheik S.; Arns, Christoph H.

2018-03-01

X-ray computed tomography (μ-CT) is considered to be the most effective way to obtain the inner structure of rock sample without destructions. However, its limited resolution hampers its ability to probe sub-micro structures which is critical for flow transportation of rock sample. In this study, we propose an innovative methodology to improve the resolution of μ-CT image using neighbour embedding algorithm where low frequency information is provided by μ-CT image itself while high frequency information is supplemented by high resolution scanning electron microscopy (SEM) image. In order to obtain prior for reconstruction, a large number of image patch pairs contain high- and low- image patches are extracted from the Gaussian image pyramid generated by SEM image. These image patch pairs contain abundant information about tomographic evolution of local porous structures under different resolution spaces. Relying on the assumption of self-similarity of porous structure, this prior information can be used to supervise the reconstruction of high resolution μ-CT image effectively. The experimental results show that the proposed method is able to achieve the state-of-the-art performance.

STEM Tomography Imaging of Hypertrophied Golgi Stacks in Mucilage-Secreting Cells.

PubMed

Kang, Byung-Ho

2016-01-01

Because of the weak penetrating power of electrons, the signal-to-noise ratio of a transmission electron micrograph (TEM) worsens as section thickness increases. This problem is alleviated by the use of the scanning transmission electron microscopy (STEM). Tomography analyses using STEM of thick sections from yeast and mammalian cells are of higher quality than are bright-field (BF) images. In this study, we compared regular BF tomograms and STEM tomograms from 500-nm thick sections from hypertrophied Golgi stacks of alfalfa root cap cells. Due to their thickness and intense heavy metal staining, BF tomograms of the thick sections suffer from poor contrast and high noise levels. We were able to mitigate these drawbacks by using STEM tomography. When we performed STEM tomography of densely stained chloroplasts of Arabidopsis cotyledon, we observed similar improvements relative to BF tomograms. A longer time is required to collect a STEM tilt series than similar BF TEM images, and dynamic autofocusing required for STEM imaging often fails at high tilt angles. Despite these limitations, STEM tomography is a powerful method for analyzing structures of large or dense organelles of plant cells.

Automated fiber tracking and tissue characterization of the anterior cruciate ligament with optical coherence tomography

NASA Astrophysics Data System (ADS)

Balasubramanian, Priya S.; Guo, Jiaqi; Yao, Xinwen; Qu, Dovina; Lu, Helen H.; Hendon, Christine P.

2017-02-01

The directionality of collagen fibers across the anterior cruciate ligament (ACL) as well as the insertion of this key ligament into bone are important for understanding the mechanical integrity and functionality of this complex tissue. Quantitative analysis of three-dimensional fiber directionality is of particular interest due to the physiological, mechanical, and biological heterogeneity inherent across the ACL-to-bone junction, the behavior of the ligament under mechanical stress, and the usefulness of this information in designing tissue engineered grafts. We have developed an algorithm to characterize Optical Coherence Tomography (OCT) image volumes of the ACL. We present an automated algorithm for measuring ligamentous fiber angles, and extracting attenuation and backscattering coefficients of ligament, interface, and bone regions within mature and immature bovine ACL insertion samples. Future directions include translating this algorithm for real time processing to allow three-dimensional volumetric analysis within dynamically moving samples.

A frequency dependent preconditioned wavelet method for atmospheric tomography

NASA Astrophysics Data System (ADS)

Yudytskiy, Mykhaylo; Helin, Tapio; Ramlau, Ronny

2013-12-01

Atmospheric tomography, i.e. the reconstruction of the turbulence in the atmosphere, is a main task for the adaptive optics systems of the next generation telescopes. For extremely large telescopes, such as the European Extremely Large Telescope, this problem becomes overly complex and an efficient algorithm is needed to reduce numerical costs. Recently, a conjugate gradient method based on wavelet parametrization of turbulence layers was introduced [5]. An iterative algorithm can only be numerically efficient when the number of iterations required for a sufficient reconstruction is low. A way to achieve this is to design an efficient preconditioner. In this paper we propose a new frequency-dependent preconditioner for the wavelet method. In the context of a multi conjugate adaptive optics (MCAO) system simulated on the official end-to-end simulation tool OCTOPUS of the European Southern Observatory we demonstrate robustness and speed of the preconditioned algorithm. We show that three iterations are sufficient for a good reconstruction.

Inverse transport calculations in optical imaging with subspace optimization algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tian, E-mail: tding@math.utexas.edu; Ren, Kui, E-mail: ren@math.utexas.edu

2014-09-15

Inverse boundary value problems for the radiative transport equation play an important role in optics-based medical imaging techniques such as diffuse optical tomography (DOT) and fluorescence optical tomography (FOT). Despite the rapid progress in the mathematical theory and numerical computation of these inverse problems in recent years, developing robust and efficient reconstruction algorithms remains a challenging task and an active research topic. We propose here a robust reconstruction method that is based on subspace minimization techniques. The method splits the unknown transport solution (or a functional of it) into low-frequency and high-frequency components, and uses singular value decomposition to analyticallymore » recover part of low-frequency information. Minimization is then applied to recover part of the high-frequency components of the unknowns. We present some numerical simulations with synthetic data to demonstrate the performance of the proposed algorithm.« less

A Reconstruction Algorithm of Magnetoacoustic Tomography with Magnetic Induction for Acoustically Inhomogeneous Tissue

PubMed Central

Zhou, Lian; Zhu, Shanan

2014-01-01

Magnetoacoustic tomography with Magnetic Induction (MAT-MI) is a noninvasive electrical conductivity imaging approach that measures ultrasound wave induced by magnetic stimulation, for reconstructing the distribution of electrical impedance in biological tissue. Existing reconstruction algorithms for MAT-MI are based on the assumption that the acoustic properties in the tissue are homogeneous. However, the tissue in most parts of human body, has heterogeneous acoustic properties, which leads to potential distortion and blurring of small buried objects in the impedance images. In the present study, we proposed a new algorithm for MAT-MI to image the impedance distribution in tissues with inhomogeneous acoustic speed distributions. With a computer head model constructed from MR images of a human subject, a series of numerical simulation experiments were conducted. The present results indicate that the inhomogeneous acoustic properties of tissues in terms of speed variation can be incorporated in MAT-MI imaging. PMID:24845284

DART: a practical reconstruction algorithm for discrete tomography.

PubMed

Batenburg, Kees Joost; Sijbers, Jan

2011-09-01

In this paper, we present an iterative reconstruction algorithm for discrete tomography, called discrete algebraic reconstruction technique (DART). DART can be applied if the scanned object is known to consist of only a few different compositions, each corresponding to a constant gray value in the reconstruction. Prior knowledge of the gray values for each of the compositions is exploited to steer the current reconstruction towards a reconstruction that contains only these gray values. Based on experiments with both simulated CT data and experimental μCT data, it is shown that DART is capable of computing more accurate reconstructions from a small number of projection images, or from a small angular range, than alternative methods. It is also shown that DART can deal effectively with noisy projection data and that the algorithm is robust with respect to errors in the estimation of the gray values.

A partially reflecting random walk on spheres algorithm for electrical impedance tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maire, Sylvain, E-mail: maire@univ-tln.fr; Simon, Martin, E-mail: simon@math.uni-mainz.de

2015-12-15

In this work, we develop a probabilistic estimator for the voltage-to-current map arising in electrical impedance tomography. This novel so-called partially reflecting random walk on spheres estimator enables Monte Carlo methods to compute the voltage-to-current map in an embarrassingly parallel manner, which is an important issue with regard to the corresponding inverse problem. Our method uses the well-known random walk on spheres algorithm inside subdomains where the diffusion coefficient is constant and employs replacement techniques motivated by finite difference discretization to deal with both mixed boundary conditions and interface transmission conditions. We analyze the global bias and the variance ofmore » the new estimator both theoretically and experimentally. Subsequently, the variance of the new estimator is considerably reduced via a novel control variate conditional sampling technique which yields a highly efficient hybrid forward solver coupling probabilistic and deterministic algorithms.« less

Advanced Fast 3-D Electromagnetic Solver for Microwave Tomography Imaging.

PubMed

Simonov, Nikolai; Kim, Bo-Ra; Lee, Kwang-Jae; Jeon, Soon-Ik; Son, Seong-Ho

2017-10-01

This paper describes a fast-forward electromagnetic solver (FFS) for the image reconstruction algorithm of our microwave tomography system. Our apparatus is a preclinical prototype of a biomedical imaging system, designed for the purpose of early breast cancer detection. It operates in the 3-6-GHz frequency band using a circular array of probe antennas immersed in a matching liquid; it produces image reconstructions of the permittivity and conductivity profiles of the breast under examination. Our reconstruction algorithm solves the electromagnetic (EM) inverse problem and takes into account the real EM properties of the probe antenna array as well as the influence of the patient's body and that of the upper metal screen sheet. This FFS algorithm is much faster than conventional EM simulation solvers. In comparison, in the same PC, the CST solver takes ~45 min, while the FFS takes ~1 s of effective simulation time for the same EM model of a numerical breast phantom.

Fast Acquisition and Reconstruction of Optical Coherence Tomography Images via Sparse Representation

PubMed Central

Li, Shutao; McNabb, Ryan P.; Nie, Qing; Kuo, Anthony N.; Toth, Cynthia A.; Izatt, Joseph A.; Farsiu, Sina

2014-01-01

In this paper, we present a novel technique, based on compressive sensing principles, for reconstruction and enhancement of multi-dimensional image data. Our method is a major improvement and generalization of the multi-scale sparsity based tomographic denoising (MSBTD) algorithm we recently introduced for reducing speckle noise. Our new technique exhibits several advantages over MSBTD, including its capability to simultaneously reduce noise and interpolate missing data. Unlike MSBTD, our new method does not require an a priori high-quality image from the target imaging subject and thus offers the potential to shorten clinical imaging sessions. This novel image restoration method, which we termed sparsity based simultaneous denoising and interpolation (SBSDI), utilizes sparse representation dictionaries constructed from previously collected datasets. We tested the SBSDI algorithm on retinal spectral domain optical coherence tomography images captured in the clinic. Experiments showed that the SBSDI algorithm qualitatively and quantitatively outperforms other state-of-the-art methods. PMID:23846467

Ultra-high resolution computed tomography imaging

DOEpatents

Paulus, Michael J.; Sari-Sarraf, Hamed; Tobin, Jr., Kenneth William; Gleason, Shaun S.; Thomas, Jr., Clarence E.

2002-01-01

A method for ultra-high resolution computed tomography imaging, comprising the steps of: focusing a high energy particle beam, for example x-rays or gamma-rays, onto a target object; acquiring a 2-dimensional projection data set representative of the target object; generating a corrected projection data set by applying a deconvolution algorithm, having an experimentally determined a transfer function, to the 2-dimensional data set; storing the corrected projection data set; incrementally rotating the target object through an angle of approximately 180.degree., and after each the incremental rotation, repeating the radiating, acquiring, generating and storing steps; and, after the rotating step, applying a cone-beam algorithm, for example a modified tomographic reconstruction algorithm, to the corrected projection data sets to generate a 3-dimensional image. The size of the spot focus of the beam is reduced to not greater than approximately 1 micron, and even to not greater than approximately 0.5 microns.

Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis

NASA Astrophysics Data System (ADS)

Pu, Huangsheng; Zhang, Guanglei; He, Wei; Liu, Fei; Guang, Huizhi; Zhang, Yue; Bai, Jing; Luo, Jianwen

2014-09-01

It is a challenging problem to resolve and identify drug (or non-specific fluorophore) distribution throughout the whole body of small animals in vivo. In this article, an algorithm of unmixing multispectral fluorescence tomography (MFT) images based on independent component analysis (ICA) is proposed to solve this problem. ICA is used to unmix the data matrix assembled by the reconstruction results from MFT. Then the independent components (ICs) that represent spatial structures and the corresponding spectrum courses (SCs) which are associated with spectral variations can be obtained. By combining the ICs with SCs, the recovered MFT images can be generated and fluorophore concentration can be calculated. Simulation studies, phantom experiments and animal experiments with different concentration contrasts and spectrum combinations are performed to test the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can not only provide the spatial information of fluorophores, but also recover the actual reconstruction of MFT images.

Optimization-based image reconstruction from sparse-view data in offset-detector CBCT

NASA Astrophysics Data System (ADS)

Bian, Junguo; Wang, Jiong; Han, Xiao; Sidky, Emil Y.; Shao, Lingxiong; Pan, Xiaochuan

2013-01-01

The field of view (FOV) of a cone-beam computed tomography (CBCT) unit in a single-photon emission computed tomography (SPECT)/CBCT system can be increased by offsetting the CBCT detector. Analytic-based algorithms have been developed for image reconstruction from data collected at a large number of densely sampled views in offset-detector CBCT. However, the radiation dose involved in a large number of projections can be of a health concern to the imaged subject. CBCT-imaging dose can be reduced by lowering the number of projections. As analytic-based algorithms are unlikely to reconstruct accurate images from sparse-view data, we investigate and characterize in the work optimization-based algorithms, including an adaptive steepest descent-weighted projection onto convex sets (ASD-WPOCS) algorithms, for image reconstruction from sparse-view data collected in offset-detector CBCT. Using simulated data and real data collected from a physical pelvis phantom and patient, we verify and characterize properties of the algorithms under study. Results of our study suggest that optimization-based algorithms such as ASD-WPOCS may be developed for yielding images of potential utility from a number of projections substantially smaller than those used currently in clinical SPECT/CBCT imaging, thus leading to a dose reduction in CBCT imaging.

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study

PubMed Central

Rudyanto, Rina D.; Kerkstra, Sjoerd; van Rikxoort, Eva M.; Fetita, Catalin; Brillet, Pierre-Yves; Lefevre, Christophe; Xue, Wenzhe; Zhu, Xiangjun; Liang, Jianming; Öksüz, İlkay; Ünay, Devrim; Kadipaşaogandcaron;lu, Kamuran; Estépar, Raúl San José; Ross, James C.; Washko, George R.; Prieto, Juan-Carlos; Hoyos, Marcela Hernández; Orkisz, Maciej; Meine, Hans; Hüllebrand, Markus; Stöcker, Christina; Mir, Fernando Lopez; Naranjo, Valery; Villanueva, Eliseo; Staring, Marius; Xiao, Changyan; Stoel, Berend C.; Fabijanska, Anna; Smistad, Erik; Elster, Anne C.; Lindseth, Frank; Foruzan, Amir Hossein; Kiros, Ryan; Popuri, Karteek; Cobzas, Dana; Jimenez-Carretero, Daniel; Santos, Andres; Ledesma-Carbayo, Maria J.; Helmberger, Michael; Urschler, Martin; Pienn, Michael; Bosboom, Dennis G.H.; Campo, Arantza; Prokop, Mathias; de Jong, Pim A.; Ortiz-de-Solorzano, Carlos; Muñoz-Barrutia, Arrate; van Ginneken, Bram

2016-01-01

The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases. PMID:25113321

High-pressure freezing for scanning transmission electron tomography analysis of cellular organelles.

PubMed

Walther, Paul; Schmid, Eberhard; Höhn, Katharina

2013-01-01

Using an electron microscope's scanning transmission mode (STEM) for collection of tomographic datasets is advantageous compared to bright field transmission electron microscopic (TEM). For image formation, inelastic scattering does not cause chromatic aberration, since in STEM mode no image forming lenses are used after the beam has passed the sample, in contrast to regular TEM. Therefore, thicker samples can be imaged. It has been experimentally demonstrated that STEM is superior to TEM and energy filtered TEM for tomography of samples as thick as 1 μm. Even when using the best electron microscope, adequate sample preparation is the key for interpretable results. We adapted protocols for high-pressure freezing of cultivated cells from a physiological state. In this chapter, we describe optimized high-pressure freezing and freeze substitution protocols for STEM tomography in order to obtain high membrane contrast.

Advancements to the planogram frequency–distance rebinning algorithm

PubMed Central

Champley, Kyle M; Raylman, Raymond R; Kinahan, Paul E

2010-01-01

In this paper we consider the task of image reconstruction in positron emission tomography (PET) with the planogram frequency–distance rebinning (PFDR) algorithm. The PFDR algorithm is a rebinning algorithm for PET systems with panel detectors. The algorithm is derived in the planogram coordinate system which is a native data format for PET systems with panel detectors. A rebinning algorithm averages over the redundant four-dimensional set of PET data to produce a three-dimensional set of data. Images can be reconstructed from this rebinned three-dimensional set of data. This process enables one to reconstruct PET images more quickly than reconstructing directly from the four-dimensional PET data. The PFDR algorithm is an approximate rebinning algorithm. We show that implementing the PFDR algorithm followed by the (ramp) filtered backprojection (FBP) algorithm in linogram coordinates from multiple views reconstructs a filtered version of our image. We develop an explicit formula for this filter which can be used to achieve exact reconstruction by means of a modified FBP algorithm applied to the stack of rebinned linograms and can also be used to quantify the errors introduced by the PFDR algorithm. This filter is similar to the filter in the planogram filtered backprojection algorithm derived by Brasse et al. The planogram filtered backprojection and exact reconstruction with the PFDR algorithm require complete projections which can be completed with a reprojection algorithm. The PFDR algorithm is similar to the rebinning algorithm developed by Kao et al. By expressing the PFDR algorithm in detector coordinates, we provide a comparative analysis between the two algorithms. Numerical experiments using both simulated data and measured data from a positron emission mammography/tomography (PEM/PET) system are performed. Images are reconstructed by PFDR+FBP (PFDR followed by 2D FBP reconstruction), PFDRX (PFDR followed by the modified FBP algorithm for exact reconstruction) and planogram filtered backprojection image reconstruction algorithms. We show that the PFDRX algorithm produces images that are nearly as accurate as images reconstructed with the planogram filtered backprojection algorithm and more accurate than images reconstructed with the PFDR+FBP algorithm. Both the PFDR+FBP and PFDRX algorithms provide a dramatic improvement in computation time over the planogram filtered backprojection algorithm. PMID:20436790

Short-term reproducibility of computed tomography-based lung density measurements in alpha-1 antitrypsin deficiency and smokers with emphysema.

PubMed

Shaker, S B; Dirksen, A; Laursen, L C; Maltbaek, N; Christensen, L; Sander, U; Seersholm, N; Skovgaard, L T; Nielsen, L; Kok-Jensen, A

2004-07-01

To study the short-term reproducibility of lung density measurements by multi-slice computed tomography (CT) using three different radiation doses and three reconstruction algorithms. Twenty-five patients with smoker's emphysema and 25 patients with alpha1-antitrypsin deficiency underwent 3 scans at 2-week intervals. Low-dose protocol was applied, and images were reconstructed with bone, detail, and soft algorithms. Total lung volume (TLV), 15th percentile density (PD-15), and relative area at -910 Hounsfield units (RA-910) were obtained from the images using Pulmo-CMS software. Reproducibility of PD-15 and RA-910 and the influence of radiation dose, reconstruction algorithm, and type of emphysema were then analysed. The overall coefficient of variation of volume adjusted PD-15 for all combinations of radiation dose and reconstruction algorithm was 3.7%. The overall standard deviation of volume-adjusted RA-910 was 1.7% (corresponding to a coefficient of variation of 6.8%). Radiation dose, reconstruction algorithm, and type of emphysema had no significant influence on the reproducibility of PD-15 and RA-910. However, bone algorithm and very low radiation dose result in overestimation of the extent of emphysema. Lung density measurement by CT is a sensitive marker for quantitating both subtypes of emphysema. A CT-protocol with radiation dose down to 16 mAs and soft or detail reconstruction algorithm is recommended.

SPECTRE (www.noveltis.fr/spectre): a web Service for Ionospheric Products

NASA Astrophysics Data System (ADS)

Jeansou, E.; Crespon, F.; Garcia, R.; Helbert, J.; Moreaux, G.; Lognonne, P.

2005-12-01

The dense GPS networks developed for geodesic applications appear to be very efficient ionospheric sensors because of interaction between plasma and electromagnetic waves. Indeed, the dual frequency receivers provide data from which the Slant Total Electron Content (STEC) can be easily extracted to compute Vertical Total Electron Content (VTEC) maps. The SPECTRE project, Service and Products for ionospheric Electron Content and Tropospheric Refractivity over Europe, is currently a pre-operational service providing VTEC maps with high time and space resolution after 3 days time delay (http://www.noveltis.fr/spectre and http://ganymede.ipgp.jussieu.fr/spectre). This project is a part of SWENET, SpaceWeather European Network, initiated by the European Space Agency. The SPECTRE data products are useful for many applications. We will present these applications in term of interest for the scientific community with a special focus on spaceweather and transient ionospheric perturbations related to Earthquakes. Moreover, the pre-operational extensions of SPECTRE to the californian (SCIGN/BARD) and japanese (GEONET) dense GPS networks will be presented. Then the method of 3D tomography of the electron density from GPS data will be presented and its resolution discussed. The expected improvements of the 3D tomographic images by new tomographic reconstruction algorithms and by the advent of the Galileo system will conclude the presentation.

Comparison of low‐dose, half‐rotation, cone‐beam CT with electronic portal imaging device for registration of fiducial markers during prostate radiotherapy

PubMed Central

Wee, Leonard; Hackett, Sara Lyons; Jones, Andrew; Lim, Tee Sin; Harper, Christopher Stirling

2013-01-01

This study evaluated the agreement of fiducial marker localization between two modalities — an electronic portal imaging device (EPID) and cone‐beam computed tomography (CBCT) — using a low‐dose, half‐rotation scanning protocol. Twenty‐five prostate cancer patients with implanted fiducial markers were enrolled. Before each daily treatment, EPID and half‐rotation CBCT images were acquired. Translational shifts were computed for each modality and two marker‐matching algorithms, seed‐chamfer and grey‐value, were performed for each set of CBCT images. The localization offsets, and systematic and random errors from both modalities were computed. Localization performances for both modalities were compared using Bland‐Altman limits of agreement (LoA) analysis, Deming regression analysis, and Cohen's kappa inter‐rater analysis. The differences in the systematic and random errors between the modalities were within 0.2 mm in all directions. The LoA analysis revealed a 95% agreement limit of the modalities of 2 to 3.5 mm in any given translational direction. Deming regression analysis demonstrated that constant biases existed in the shifts computed by the modalities in the superior–inferior (SI) direction, but no significant proportional biases were identified in any direction. Cohen's kappa analysis showed good agreement between the modalities in prescribing translational corrections of the couch at 3 and 5 mm action levels. Images obtained from EPID and half‐rotation CBCT showed acceptable agreement for registration of fiducial markers. The seed‐chamfer algorithm for tracking of fiducial markers in CBCT datasets yielded better agreement than the grey‐value matching algorithm with EPID‐based registration. PACS numbers: 87.55.km, 87.55.Qr PMID:23835391

Multi-scale structural analysis of gas diffusion layers

NASA Astrophysics Data System (ADS)

Göbel, Martin; Godehardt, Michael; Schladitz, Katja

2017-07-01

The macroscopic properties of materials are strongly determined by their micro structure. Here, transport properties of gas diffusion layers (GDL) for fuel cells are considered. In order to simulate flow and thermal properties, detailed micro structural information is essential. 3D images obtained by high-resolution computed tomography using synchrotron radiation and scanning electron microscopy (SEM) combined with focused ion beam (FIB) serial slicing were used. A recent method for reconstruction of porous structures from FIB-SEM images and sophisticated morphological image transformations were applied to segment the solid structural components. The essential algorithmic steps for segmenting the different components in the tomographic data-sets are described and discussed. In this paper, two types of GDL, based on a non-woven substrate layer and a paper substrate layer were considered, respectively. More than three components are separated within the synchrotron radiation computed tomography data. That is, fiber system, polytetrafluoroethylene (PTFE) binder/impregnation, micro porous layer (MPL), inclusions within the latter, and pore space are segmented. The usage of the thus derived 3D structure data in different simulation applications can be demonstrated. Simulations of macroscopic properties such as thermal conductivity, depending on the flooding state of the GDL are possible.

Local reconstruction in computed tomography of diffraction enhanced imaging

NASA Astrophysics Data System (ADS)

Huang, Zhi-Feng; Zhang, Li; Kang, Ke-Jun; Chen, Zhi-Qiang; Zhu, Pei-Ping; Yuan, Qing-Xi; Huang, Wan-Xia

2007-07-01

Computed tomography of diffraction enhanced imaging (DEI-CT) based on synchrotron radiation source has extremely high sensitivity of weakly absorbing low-Z samples in medical and biological fields. The authors propose a modified backprojection filtration(BPF)-type algorithm based on PI-line segments to reconstruct region of interest from truncated refraction-angle projection data in DEI-CT. The distribution of refractive index decrement in the sample can be directly estimated from its reconstruction images, which has been proved by experiments at the Beijing Synchrotron Radiation Facility. The algorithm paves the way for local reconstruction of large-size samples by the use of DEI-CT with small field of view based on synchrotron radiation source.

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

PubMed

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.

New diagnostic pathways urgently needed. Protocol of PET Guidance I pilot study: positron emission tomography in suspected cardiac implantable electronic device-related infection.

PubMed

Marciniak-Emmons, Marta Barbara; Sterliński, Maciej; Syska, Paweł; Maciąg, Aleksander; Farkowski, Michał Mirosław; Firek, Bohdan; Dziuk, Mirosław; Zając, Dariusz; Pytkowski, Mariusz; Szwed, Hanna

2016-01-01

Cardiovascular implantable electronic device (CIED) infection is a complication of increasing incidence. We present a protocol of an observational case control clinical trial "Positron Emission Tomography Combined With Computed Tomography (PET CT) in Suspected Cardiac Implantable Electronic Device Infection, a Pilot Study - PET Guidance I" (NCT02196753). The aim of this observational clinical trial is to assess and standardise diagnostic algorithms for CIED infections (lead-dependent infective endocarditis, generator pocket infection, fever of unknown origin) with PET CT in Poland. Study group will consist of 20 patients with initial diagnosis of CIED-related infection paired with a control group of 20 patients with implanted CIEDs, who underwent PET CT due to other non-infectious indications and have no data for infectious process in follow-up. All patients included in the study will undergo standard diagnostic pro-cess. Conventional/standard diagnostic and therapeutic process will consist of: medical interview, physical examination, laboratory tests, blood cultures; imaging studies: echocardiography: transthoracic (TTE), and, if there are no contraindications transoesophageal, computed tomography scan for pulmonary embolism if indicated; if there are abnormalities in other systems, decisions concerning further diagnostics will be made at the physician's discretion. As well as standard diagnostic procedures, patients will undergo whole body PET CT scan to localise infection or inflammation. Diagnosis and therapeutic decision will be obtained from the Study Committee. Follow-up will be held within six months with control visits at three and six months. During each follow-up visit, all patients will undergo laboratory tests, two blood cultures collected 1 h apart, and TTE. In case of actual clinical suspicion of infective endocarditis or local generator pocket infection, patients will be referred for further diagnostics. Endpoints for the results assessment - primary endpoints are to standardise PET CT in the diagnostic process: sensitivity, specificity, positive predictive value, and negative predictive value of the diagnosis made by PET CT; secondary endpoints are: assessment of usefulness of PET CT for detection of remote infective complications (metastatic abscesses, infected pulmonary emboli), incidence of particular localisations of infection, influence of PET CT on therapeutic decision: confirmation or change of decision based on PET CT, safety and complications of diagnostic process of CIED-related infections with PET CT. Evaluation of PET CT use for device-related infections in a case control study may be conclusive and improve diagnostic pathway.

Single-Photon Computed Tomography With Large Position-Sensitive Phototubes*

NASA Astrophysics Data System (ADS)

Feldmann, John; Ranck, Amoreena; Saunders, Robert S.; Welsh, Robert E.; Bradley, Eric L.; Saha, Margaret S.; Kross, Brian; Majewski, Stan; Popov, Vladimir; Weisenberger, Andrew G.; Wojcik, Randolph

2000-10-01

Position-sensitive photomultiplier tubes (PSPMTs) coupled to pixelated CsI(Tl) scintillators have been used with parallel-hole collimators to view the metabolism in small animals of radiopharmaceuticals tagged with ^125I. We report here our preliminary results analyzed using a tomography program^1 written in IDL programming language. The PSPMTs are mounted on a rotating gantry so as to view the subject animal from any azimuth. Preliminary results to test the tomography algorithm have been obtained by placing a variety of plastic mouse-brain phantoms (loaded with Na^125I) in front of one of the detectors and rotating the phantom in steps through 360 degrees. Results of this simulation taken with a variety of collimator hole sizes will be compared and discussed. Extentions of this technique to the use of very small PSPMTs (Hamamatsu M-64) which are capable of a very close approach to those parts of the animal of greatest interest will be described. *Supported in part by The Department of Energy, The National Science Foundation, The American Diabetes Association, The Howard Hughes Foundation and The Jeffress Trust. 1. Tomography algorithm kindly provided by Dr. S. Meikle of The Royal Prince Albert Hospital, Sydney, Australia

PI-line-based image reconstruction in helical cone-beam computed tomography with a variable pitch.

PubMed

Zou, Yu; Pan, Xiaochuan; Xia, Dan; Wang, Ge

2005-08-01

Current applications of helical cone-beam computed tomography (CT) involve primarily a constant pitch where the translating speed of the table and the rotation speed of the source-detector remain constant. However, situations do exist where it may be more desirable to use a helical scan with a variable translating speed of the table, leading a variable pitch. One of such applications could arise in helical cone-beam CT fluoroscopy for the determination of vascular structures through real-time imaging of contrast bolus arrival. Most of the existing reconstruction algorithms have been developed only for helical cone-beam CT with constant pitch, including the backprojection-filtration (BPF) and filtered-backprojection (FBP) algorithms that we proposed previously. It is possible to generalize some of these algorithms to reconstruct images exactly for helical cone-beam CT with a variable pitch. In this work, we generalize our BPF and FBP algorithms to reconstruct images directly from data acquired in helical cone-beam CT with a variable pitch. We have also performed a preliminary numerical study to demonstrate and verify the generalization of the two algorithms. The results of the study confirm that our generalized BPF and FBP algorithms can yield exact reconstruction in helical cone-beam CT with a variable pitch. It should be pointed out that our generalized BPF algorithm is the only algorithm that is capable of reconstructing exactly region-of-interest image from data containing transverse truncations.

Bayesian ionospheric multi-instrument 3D tomography

NASA Astrophysics Data System (ADS)

Norberg, Johannes; Vierinen, Juha; Roininen, Lassi

2017-04-01

The tomographic reconstruction of ionospheric electron densities is an inverse problem that cannot be solved without relatively strong regularising additional information. % Especially the vertical electron density profile is determined predominantly by the regularisation. % %Often utilised regularisations in ionospheric tomography include smoothness constraints and iterative methods with initial ionospheric models. % Despite its crucial role, the regularisation is often hidden in the algorithm as a numerical procedure without physical understanding. % % The Bayesian methodology provides an interpretative approach for the problem, as the regularisation can be given in a physically meaningful and quantifiable prior probability distribution. % The prior distribution can be based on ionospheric physics, other available ionospheric measurements and their statistics. % Updating the prior with measurements results as the posterior distribution that carries all the available information combined. % From the posterior distribution, the most probable state of the ionosphere can then be solved with the corresponding probability intervals. % Altogether, the Bayesian methodology provides understanding on how strong the given regularisation is, what is the information gained with the measurements and how reliable the final result is. % In addition, the combination of different measurements and temporal development can be taken into account in a very intuitive way. However, a direct implementation of the Bayesian approach requires inversion of large covariance matrices resulting in computational infeasibility. % In the presented method, Gaussian Markov random fields are used to form a sparse matrix approximations for the covariances. % The approach makes the problem computationally feasible while retaining the probabilistic and physical interpretation. Here, the Bayesian method with Gaussian Markov random fields is applied for ionospheric 3D tomography over Northern Europe. % Multi-instrument measurements are utilised from TomoScand receiver network for Low Earth orbit beacon satellite signals, GNSS receiver networks, as well as from EISCAT ionosondes and incoherent scatter radars. % %The performance is demonstrated in three-dimensional spatial domain with temporal development also taken into account.

A fast marching algorithm for the factored eikonal equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Treister, Eran, E-mail: erantreister@gmail.com; Haber, Eldad, E-mail: haber@math.ubc.ca; Department of Mathematics, The University of British Columbia, Vancouver, BC

The eikonal equation is instrumental in many applications in several fields ranging from computer vision to geoscience. This equation can be efficiently solved using the iterative Fast Sweeping (FS) methods and the direct Fast Marching (FM) methods. However, when used for a point source, the original eikonal equation is known to yield inaccurate numerical solutions, because of a singularity at the source. In this case, the factored eikonal equation is often preferred, and is known to yield a more accurate numerical solution. One application that requires the solution of the eikonal equation for point sources is travel time tomography. Thismore » inverse problem may be formulated using the eikonal equation as a forward problem. While this problem has been solved using FS in the past, the more recent choice for applying it involves FM methods because of the efficiency in which sensitivities can be obtained using them. However, while several FS methods are available for solving the factored equation, the FM method is available only for the original eikonal equation. In this paper we develop a Fast Marching algorithm for the factored eikonal equation, using both first and second order finite-difference schemes. Our algorithm follows the same lines as the original FM algorithm and requires the same computational effort. In addition, we show how to obtain sensitivities using this FM method and apply travel time tomography, formulated as an inverse factored eikonal equation. Numerical results in two and three dimensions show that our algorithm solves the factored eikonal equation efficiently, and demonstrate the achieved accuracy for computing the travel time. We also demonstrate a recovery of a 2D and 3D heterogeneous medium by travel time tomography using the eikonal equation for forward modeling and inversion by Gauss–Newton.« less

CT image electron density quantification in regions with metal implants: implications for radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Jechel, Christopher Alexander

In radiotherapy planning, computed tomography (CT) images are used to quantify the electron density of tissues and provide spatial anatomical information. Treatment planning systems use these data to calculate the expected spatial distribution of absorbed dose in a patient. CT imaging is complicated by the presence of metal implants which cause increased image noise, produce artifacts throughout the image and can exceed the available range of CT number values within the implant, perturbing electron density estimates in the image. Furthermore, current dose calculation algorithms do not accurately model radiation transport at metal-tissue interfaces. Combined, these issues adversely affect the accuracy of dose calculations in the vicinity of metal implants. As the number of patients with orthopedic and dental implants grows, so does the need to deliver safe and effective radiotherapy treatments in the presence of implants. The Medical Physics group at the Cancer Centre of Southeastern Ontario and Queen's University has developed a Cobalt-60 CT system that is relatively insensitive to metal artifacts due to the high energy, nearly monoenergetic Cobalt-60 photon beam. Kilovoltage CT (kVCT) images, including images corrected using a commercial metal artifact reduction tool, were compared to Cobalt-60 CT images throughout the treatment planning process, from initial imaging through to dose calculation. An effective metal artifact reduction algorithm was also implemented for the Cobalt-60 CT system. Electron density maps derived from the same kVCT and Cobalt-60 CT images indicated the impact of image artifacts on estimates of photon attenuation for treatment planning applications. Measurements showed that truncation of CT number data in kVCT images produced significant mischaracterization of the electron density of metals. Dose measurements downstream of metal inserts in a water phantom were compared to dose data calculated using CT images from kVCT and Cobalt-60 systems with and without artifact correction. The superior accuracy of electron density data derived from Cobalt-60 images compared to kVCT images produced calculated dose with far better agreement with measured results. These results indicated that dose calculation errors from metal image artifacts are primarily due to misrepresentation of electron density within metals rather than artifacts surrounding the implants.

Terahertz wide aperture reflection tomography.

PubMed

Pearce, Jeremy; Choi, Hyeokho; Mittleman, Daniel M; White, Jeff; Zimdars, David

2005-07-01

We describe a powerful imaging modality for terahertz (THz) radiation, THz wide aperture reflection tomography (WART). Edge maps of an object's cross section are reconstructed from a series of time-domain reflection measurements at different viewing angles. Each measurement corresponds to a parallel line projection of the object's cross section. The filtered backprojection algorithm is applied to recover the image from the projection data. To our knowledge, this is the first demonstration of a reflection computed tomography technique using electromagnetic waves. We demonstrate the capabilities of THz WART by imaging the cross sections of two test objects.

Event-by-event PET image reconstruction using list-mode origin ensembles algorithm

NASA Astrophysics Data System (ADS)

Andreyev, Andriy

2016-03-01

There is a great demand for real time or event-by-event (EBE) image reconstruction in emission tomography. Ideally, as soon as event has been detected by the acquisition electronics, it needs to be used in the image reconstruction software. This would greatly speed up the image reconstruction since most of the data will be processed and reconstructed while the patient is still undergoing the scan. Unfortunately, the current industry standard is that the reconstruction of the image would not start until all the data for the current image frame would be acquired. Implementing an EBE reconstruction for MLEM family of algorithms is possible, but not straightforward as multiple (computationally expensive) updates to the image estimate are required. In this work an alternative Origin Ensembles (OE) image reconstruction algorithm for PET imaging is converted to EBE mode and is investigated whether it is viable alternative for real-time image reconstruction. In OE algorithm all acquired events are seen as points that are located somewhere along the corresponding line-of-responses (LORs), together forming a point cloud. Iteratively, with a multitude of quasi-random shifts following the likelihood function the point cloud converges to a reflection of an actual radiotracer distribution with the degree of accuracy that is similar to MLEM. New data can be naturally added into the point cloud. Preliminary results with simulated data show little difference between regular reconstruction and EBE mode, proving the feasibility of the proposed approach.

3D structure of eukaryotic flagella/cilia by cryo-electron tomography.

PubMed

Ishikawa, Takashi

2013-01-01

Flagella/cilia are motile organelles with more than 400 proteins. To understand the mechanism of such complex systems, we need methods to describe molecular arrange-ments and conformations three-dimensionally in vivo. Cryo-electron tomography enabled us such a 3D structural analysis. Our group has been working on 3D structure of flagella/cilia using this method and revealed highly ordered and beautifully organized molecular arrangement. 3D structure gave us insights into the mechanism to gener-ate bending motion with well defined waveforms. In this review, I summarize our recent structural studies on fla-gella/cilia by cryo-electron tomography, mainly focusing on dynein microtubule-based ATPase motor proteins and the radial spoke, a regulatory protein complex.

3D structure of eukaryotic flagella/cilia by cryo-electron tomography

PubMed Central

Ishikawa, Takashi

2013-01-01

Flagella/cilia are motile organelles with more than 400 proteins. To understand the mechanism of such complex systems, we need methods to describe molecular arrange-ments and conformations three-dimensionally in vivo. Cryo-electron tomography enabled us such a 3D structural analysis. Our group has been working on 3D structure of flagella/cilia using this method and revealed highly ordered and beautifully organized molecular arrangement. 3D structure gave us insights into the mechanism to gener-ate bending motion with well defined waveforms. In this review, I summarize our recent structural studies on fla-gella/cilia by cryo-electron tomography, mainly focusing on dynein microtubule-based ATPase motor proteins and the radial spoke, a regulatory protein complex. PMID:27493552

A reconstruction method for cone-beam differential x-ray phase-contrast computed tomography.

PubMed

Fu, Jian; Velroyen, Astrid; Tan, Renbo; Zhang, Junwei; Chen, Liyuan; Tapfer, Arne; Bech, Martin; Pfeiffer, Franz

2012-09-10

Most existing differential phase-contrast computed tomography (DPC-CT) approaches are based on three kinds of scanning geometries, described by parallel-beam, fan-beam and cone-beam. Due to the potential of compact imaging systems with magnified spatial resolution, cone-beam DPC-CT has attracted significant interest. In this paper, we report a reconstruction method based on a back-projection filtration (BPF) algorithm for cone-beam DPC-CT. Due to the differential nature of phase contrast projections, the algorithm restrains from differentiation of the projection data prior to back-projection, unlike BPF algorithms commonly used for absorption-based CT data. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured with a three-grating interferometer and a micro-focus x-ray tube source. Moreover, the numerical simulation and experimental results demonstrate that the proposed method can deal with several classes of truncated cone-beam datasets. We believe that this feature is of particular interest for future medical cone-beam phase-contrast CT imaging applications.

Fast detection of vascular plaque in optical coherence tomography images using a reduced feature set

NASA Astrophysics Data System (ADS)

Prakash, Ammu; Ocana Macias, Mariano; Hewko, Mark; Sowa, Michael; Sherif, Sherif

2018-03-01

Optical coherence tomography (OCT) images are capable of detecting vascular plaque by using the full set of 26 Haralick textural features and a standard K-means clustering algorithm. However, the use of the full set of 26 textural features is computationally expensive and may not be feasible for real time implementation. In this work, we identified a reduced set of 3 textural feature which characterizes vascular plaque and used a generalized Fuzzy C-means clustering algorithm. Our work involves three steps: 1) the reduction of a full set 26 textural feature to a reduced set of 3 textural features by using genetic algorithm (GA) optimization method 2) the implementation of an unsupervised generalized clustering algorithm (Fuzzy C-means) on the reduced feature space, and 3) the validation of our results using histology and actual photographic images of vascular plaque. Our results show an excellent match with histology and actual photographic images of vascular tissue. Therefore, our results could provide an efficient pre-clinical tool for the detection of vascular plaque in real time OCT imaging.

Electron tomography of whole cultured cells using novel transmission electron imaging technique.

PubMed

Okumura, Taiga; Shoji, Minami; Hisada, Akiko; Ominami, Yusuke; Ito, Sukehiro; Ushiki, Tatsuo; Nakajima, Masato; Ohshima, Takashi

2018-01-01

Since a three-dimensional (3D) cellular ultrastructure is significant for biological functions, it has been investigated using various electron microscopic techniques. Although transmission electron microscopy (TEM)-based techniques are traditionally used, cells must be embedded in resin and sliced into ultrathin sections in sample preparation processes. Block-face observation using a scanning electron microscope (SEM) has also been recently applied to 3D observation of cellular components, but this is a destructive inspection and does not allow re-examination. Therefore, we developed electron tomography using a transmission electron imaging technique called Plate-TEM. With Plate-TEM, the cells cultured directly on a scintillator plate are inserted into a conventional SEM equipped with a Plate-TEM observation system, and their internal structures are observed by detecting scintillation light produced by electrons passing through the cells. This technology has the following four advantages. First, the cells cultured on the plate can be observed at electron-microscopic resolution since they remain on the plate. Second, both surface and internal information can be obtained simultaneously by using electron- and photo-detectors, respectively, because a Plate-TEM detector is installed in an SEM. Third, the cells on the scintillator plate can also be inspected using light microscopy because the plate has transparent features. Finally, correlative observation with other techniques, such as conventional TEM, is possible after Plate-TEM observation because Plate-TEM is a non-destructive analysis technique. We also designed a sample stage to tilt the samples for tomography with Plate-TEM, by which 3D organization of cellular structures can be visualized as a whole cell. In the present study, Mm2T cells were investigated using our tomography system, resulting in 3D visualization of cell organelles such as mitochondria, lipid droplets, and microvilli. Correlative observations with various imaging techniques were also conducted by successive observations with light microscopy, SEM, Plate-TEM, and conventional TEM. Consequently, the Plate-TEM tomography technique encourages understanding of cellular structures at high resolution, which can contribute to cellular biological research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transverse Phase Space Reconstruction and Emittance Measurement of Intense Electron Beams using a Tomography Technique

NASA Astrophysics Data System (ADS)

Stratakis, D.; Kishek, R. A.; Li, H.; Bernal, S.; Walter, M.; Tobin, J.; Quinn, B.; Reiser, M.; O'Shea, P. G.

2006-11-01

Tomography is the technique of reconstructing an image from its projections. It is widely used in the medical community to observe the interior of the human body by processing multiple x-ray images taken at different angles, A few pioneering researchers have adapted tomography to reconstruct detailed phase space maps of charged particle beams. Some questions arise regarding the limitations of tomography technique for space charge dominated beams. For instance is the linear space charge force a valid approximation? Does tomography equally reproduce phase space for complex, experimentally observed, initial particle distributions? Does tomography make any assumptions about the initial distribution? This study explores the use of accurate modeling with the particle-in-cell code WARP to address these questions, using a wide range of different initial distributions in the code. The study also includes a number of experimental results on tomographic phase space mapping performed on the University of Maryland Electron Ring (UMER).

Using the Hilbert uniqueness method in a reconstruction algorithm for electrical impedance tomography.

PubMed

Dai, W W; Marsili, P M; Martinez, E; Morucci, J P

1994-05-01

This paper presents a new version of the layer stripping algorithm in the sense that it works essentially by repeatedly stripping away the outermost layer of the medium after having determined the conductivity value in this layer. In order to stabilize the ill posed boundary value problem related to each layer, we base our algorithm on the Hilbert uniqueness method (HUM) and implement it with the boundary element method (BEM).

Detection of mouse liver cancer via a parallel iterative shrinkage method in hybrid optical/microcomputed tomography imaging

NASA Astrophysics Data System (ADS)

Wu, Ping; Liu, Kai; Zhang, Qian; Xue, Zhenwen; Li, Yongbao; Ning, Nannan; Yang, Xin; Li, Xingde; Tian, Jie

2012-12-01

Liver cancer is one of the most common malignant tumors worldwide. In order to enable the noninvasive detection of small liver tumors in mice, we present a parallel iterative shrinkage (PIS) algorithm for dual-modality tomography. It takes advantage of microcomputed tomography and multiview bioluminescence imaging, providing anatomical structure and bioluminescence intensity information to reconstruct the size and location of tumors. By incorporating prior knowledge of signal sparsity, we associate some mathematical strategies including specific smooth convex approximation, an iterative shrinkage operator, and affine subspace with the PIS method, which guarantees the accuracy, efficiency, and reliability for three-dimensional reconstruction. Then an in vivo experiment on the bead-implanted mouse has been performed to validate the feasibility of this method. The findings indicate that a tiny lesion less than 3 mm in diameter can be localized with a position bias no more than 1 mm the computational efficiency is one to three orders of magnitude faster than the existing algorithms; this approach is robust to the different regularization parameters and the lp norms. Finally, we have applied this algorithm to another in vivo experiment on an HCCLM3 orthotopic xenograft mouse model, which suggests the PIS method holds the promise for practical applications of whole-body cancer detection.

An extended diffraction tomography method for quantifying structural damage using numerical Green's functions.

PubMed

Chan, Eugene; Rose, L R Francis; Wang, Chun H

2015-05-01

Existing damage imaging algorithms for detecting and quantifying structural defects, particularly those based on diffraction tomography, assume far-field conditions for the scattered field data. This paper presents a major extension of diffraction tomography that can overcome this limitation and utilises a near-field multi-static data matrix as the input data. This new algorithm, which employs numerical solutions of the dynamic Green's functions, makes it possible to quantitatively image laminar damage even in complex structures for which the dynamic Green's functions are not available analytically. To validate this new method, the numerical Green's functions and the multi-static data matrix for laminar damage in flat and stiffened isotropic plates are first determined using finite element models. Next, these results are time-gated to remove boundary reflections, followed by discrete Fourier transform to obtain the amplitude and phase information for both the baseline (damage-free) and the scattered wave fields. Using these computationally generated results and experimental verification, it is shown that the new imaging algorithm is capable of accurately determining the damage geometry, size and severity for a variety of damage sizes and shapes, including multi-site damage. Some aspects of minimal sensors requirement pertinent to image quality and practical implementation are also briefly discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

An algorithm for automated ROI definition in water or epoxy-filled NEMA NU-2 image quality phantoms.

PubMed

Pierce, Larry A; Byrd, Darrin W; Elston, Brian F; Karp, Joel S; Sunderland, John J; Kinahan, Paul E

2016-01-08

Drawing regions of interest (ROIs) in positron emission tomography/computed tomography (PET/CT) scans of the National Electrical Manufacturers Association (NEMA) NU-2 Image Quality (IQ) phantom is a time-consuming process that allows for interuser variability in the measurements. In order to reduce operator effort and allow batch processing of IQ phantom images, we propose a fast, robust, automated algorithm for performing IQ phantom sphere localization and analysis. The algorithm is easily altered to accommodate different configurations of the IQ phantom. The proposed algorithm uses information from both the PET and CT image volumes in order to overcome the challenges of detecting the smallest spheres in the PET volume. This algorithm has been released as an open-source plug-in to the Osirix medical image viewing software package. We test the algorithm under various noise conditions, positions within the scanner, air bubbles in the phantom spheres, and scanner misalignment conditions. The proposed algorithm shows run-times between 3 and 4 min and has proven to be robust under all tested conditions, with expected sphere localization deviations of less than 0.2 mm and variations of PET ROI mean and maximum values on the order of 0.5% and 2%, respectively, over multiple PET acquisitions. We conclude that the proposed algorithm is stable when challenged with a variety of physical and imaging anomalies, and that the algorithm can be a valuable tool for those who use the NEMA NU-2 IQ phantom for PET/CT scanner acceptance testing and QA/QC.

A convolutional neural network approach to calibrating the rotation axis for X-ray computed tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaogang; De Carlo, Francesco; Phatak, Charudatta

This paper presents an algorithm to calibrate the center-of-rotation for X-ray tomography by using a machine learning approach, the Convolutional Neural Network (CNN). The algorithm shows excellent accuracy from the evaluation of synthetic data with various noise ratios. It is further validated with experimental data of four different shale samples measured at the Advanced Photon Source and at the Swiss Light Source. The results are as good as those determined by visual inspection and show better robustness than conventional methods. CNN has also great potential forreducing or removingother artifacts caused by instrument instability, detector non-linearity,etc. An open-source toolbox, which integratesmore » the CNN methods described in this paper, is freely available through GitHub at tomography/xlearn and can be easily integrated into existing computational pipelines available at various synchrotron facilities. Source code, documentation and information on how to contribute are also provided.« less

A novel permeabilization protocol to obtain intracellular 3D immunolabeling for electron tomography.

PubMed

Jiménez, Nuria; Post, Jan A

2014-01-01

Electron tomography (ET) is a very important high-resolution tool for 3D imaging in cell biology. By combining the technique with immunolabeling, ET can provide essential insights into both cellular architecture and dynamics. We recently developed a protocol to achieve 3D immunolabeling of intracellular antigens without the need for uncontrolled permeabilization steps that cause random, extensive cell membrane disruption. Here we describe this novel method based on well-controlled permeabilization by targeted laser cell perforation. Mechanical permeabilization of the plasma membrane can be applied at specific sites without affecting other parts of the plasma membrane and intracellular membranes. Despite the relatively small opening created in the plasma membrane, the method allows specific 3D immunolocalization of cytoplasmic antigens in cultured cells by a pre-embedment protocol. The approach is unique and leads to a superior ultrastructural preservation for transmission electron microscopy and electron tomography.

A unified framework for penalized statistical muon tomography reconstruction with edge preservation priors of lp norm type

NASA Astrophysics Data System (ADS)

Yu, Baihui; Zhao, Ziran; Wang, Xuewu; Wu, Dufan; Zeng, Zhi; Zeng, Ming; Wang, Yi; Cheng, Jianping

2016-01-01

The Tsinghua University MUon Tomography facilitY (TUMUTY) has been built up and it is utilized to reconstruct the special objects with complex structure. Since fine image is required, the conventional Maximum likelihood Scattering and Displacement (MLSD) algorithm is employed. However, due to the statistical characteristics of muon tomography and the data incompleteness, the reconstruction is always instable and accompanied with severe noise. In this paper, we proposed a Maximum a Posterior (MAP) algorithm for muon tomography regularization, where an edge-preserving prior on the scattering density image is introduced to the object function. The prior takes the lp norm (p>0) of the image gradient magnitude, where p=1 and p=2 are the well-known total-variation (TV) and Gaussian prior respectively. The optimization transfer principle is utilized to minimize the object function in a unified framework. At each iteration the problem is transferred to solving a cubic equation through paraboloidal surrogating. To validate the method, the French Test Object (FTO) is imaged by both numerical simulation and TUMUTY. The proposed algorithm is used for the reconstruction where different norms are detailedly studied, including l2, l1, l0.5, and an l2-0.5 mixture norm. Compared with MLSD method, MAP achieves better image quality in both structure preservation and noise reduction. Furthermore, compared with the previous work where one dimensional image was acquired, we achieve the relatively clear three dimensional images of FTO, where the inner air hole and the tungsten shell is visible.

Material characterization using ultrasound tomography

NASA Astrophysics Data System (ADS)

Falardeau, Timothe; Belanger, Pierre

2018-04-01

Characterization of material properties can be performed using a wide array of methods e.g. X-ray diffraction or tensile testing. Each method leads to a limited set of material properties. This paper is interested in using ultrasound tomography to map speed of sound inside a material sample. The velocity inside the sample is directly related to its elastic properties. Recent develop-ments in ultrasound diffraction tomography have enabled velocity mapping of high velocity contrast objects using a combination of bent-ray time-of-flight tomography and diffraction tomography. In this study, ultrasound diffraction tomography was investigated using simulations in human bone phantoms. A finite element model was developed to assess the influence of the frequency, the number of transduction positions and the distance from the sample as well as to adapt the imaging algorithm. The average velocity in both regions of the bone phantoms were within 5% of the true value.

A reconstruction algorithm for helical CT imaging on PI-planes.

PubMed

Liang, Hongzhu; Zhang, Cishen; Yan, Ming

2006-01-01

In this paper, a Feldkamp type approximate reconstruction algorithm is presented for helical cone-beam Computed Tomography. To effectively suppress artifacts due to large cone angle scanning, it is proposed to reconstruct the object point-wisely on unique customized tilted PI-planes which are close to the data collecting helices of the corresponding points. Such a reconstruction scheme can considerably suppress the artifacts in the cone-angle scanning. Computer simulations show that the proposed algorithm can provide improved imaging performance compared with the existing approximate cone-beam reconstruction algorithms.

Sinogram-based adaptive iterative reconstruction for sparse view x-ray computed tomography

NASA Astrophysics Data System (ADS)

Trinca, D.; Zhong, Y.; Wang, Y.-Z.; Mamyrbayev, T.; Libin, E.

2016-10-01

With the availability of more powerful computing processors, iterative reconstruction algorithms have recently been successfully implemented as an approach to achieving significant dose reduction in X-ray CT. In this paper, we propose an adaptive iterative reconstruction algorithm for X-ray CT, that is shown to provide results comparable to those obtained by proprietary algorithms, both in terms of reconstruction accuracy and execution time. The proposed algorithm is thus provided for free to the scientific community, for regular use, and for possible further optimization.

Assessment of calcium scoring performance in cardiac computed tomography.

PubMed

Ulzheimer, Stefan; Kalender, Willi A

2003-03-01

Electron beam tomography (EBT) has been used for cardiac diagnosis and the quantitative assessment of coronary calcium since the late 1980s. The introduction of mechanical multi-slice spiral CT (MSCT) scanners with shorter rotation times opened new possibilities of cardiac imaging with conventional CT scanners. The purpose of this work was to qualitatively and quantitatively evaluate the performance for EBT and MSCT for the task of coronary artery calcium imaging as a function of acquisition protocol, heart rate, spiral reconstruction algorithm (where applicable) and calcium scoring method. A cardiac CT semi-anthropomorphic phantom was designed and manufactured for the investigation of all relevant image quality parameters in cardiac CT. This phantom includes various test objects, some of which can be moved within the anthropomorphic phantom in a manner that mimics realistic heart motion. These tools were used to qualitatively and quantitatively demonstrate the accuracy of coronary calcium imaging using typical protocols for an electron beam (Evolution C-150XP, Imatron, South San Francisco, Calif.) and a 0.5-s four-slice spiral CT scanner (Sensation 4, Siemens, Erlangen, Germany). A special focus was put on the method of quantifying coronary calcium, and three scoring systems were evaluated (Agatston, volume, and mass scoring). Good reproducibility in coronary calcium scoring is always the result of a combination of high temporal and spatial resolution; consequently, thin-slice protocols in combination with retrospective gating on MSCT scanners yielded the best results. The Agatston score was found to be the least reproducible scoring method. The hydroxyapatite mass, being better reproducible and comparable on different scanners and being a physical quantitative measure, appears to be the method of choice for future clinical studies. The hydroxyapatite mass is highly correlated to the Agatston score. The introduced phantoms can be used to quantitatively assess the performance characteristics of, for example, different scanners, reconstruction algorithms, and quantification methods in cardiac CT. This is especially important for quantitative tasks, such as the determination of the amount of calcium in the coronary arteries, to achieve high and constant quality in this field.

Gaussian diffusion sinogram inpainting for X-ray CT metal artifact reduction.

PubMed

Peng, Chengtao; Qiu, Bensheng; Li, Ming; Guan, Yihui; Zhang, Cheng; Wu, Zhongyi; Zheng, Jian

2017-01-05

Metal objects implanted in the bodies of patients usually generate severe streaking artifacts in reconstructed images of X-ray computed tomography, which degrade the image quality and affect the diagnosis of disease. Therefore, it is essential to reduce these artifacts to meet the clinical demands. In this work, we propose a Gaussian diffusion sinogram inpainting metal artifact reduction algorithm based on prior images to reduce these artifacts for fan-beam computed tomography reconstruction. In this algorithm, prior information that originated from a tissue-classified prior image is used for the inpainting of metal-corrupted projections, and it is incorporated into a Gaussian diffusion function. The prior knowledge is particularly designed to locate the diffusion position and improve the sparsity of the subtraction sinogram, which is obtained by subtracting the prior sinogram of the metal regions from the original sinogram. The sinogram inpainting algorithm is implemented through an approach of diffusing prior energy and is then solved by gradient descent. The performance of the proposed metal artifact reduction algorithm is compared with two conventional metal artifact reduction algorithms, namely the interpolation metal artifact reduction algorithm and normalized metal artifact reduction algorithm. The experimental datasets used included both simulated and clinical datasets. By evaluating the results subjectively, the proposed metal artifact reduction algorithm causes fewer secondary artifacts than the two conventional metal artifact reduction algorithms, which lead to severe secondary artifacts resulting from impertinent interpolation and normalization. Additionally, the objective evaluation shows the proposed approach has the smallest normalized mean absolute deviation and the highest signal-to-noise ratio, indicating that the proposed method has produced the image with the best quality. No matter for the simulated datasets or the clinical datasets, the proposed algorithm has reduced the metal artifacts apparently.

Prompt gamma-ray imaging for small animals

NASA Astrophysics Data System (ADS)

Xu, Libai

Small animal imaging is recognized as a powerful discovery tool for small animal modeling of human diseases, which is providing an important clue to complete understanding of disease mechanisms and is helping researchers develop and test new treatments. The current small animal imaging techniques include positron emission tomography (PET), single photon emission tomography (SPECT), computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). A new imaging modality called prompt gamma-ray imaging (PGI) has been identified and investigated primarily by Monte Carlo simulation. Currently it is suggested for use on small animals. This new technique could greatly enhance and extend the present capabilities of PET and SPECT imaging from ingested radioisotopes to the imaging of selected non-radioactive elements, such as Gd, Cd, Hg, and B, and has the great potential to be used in Neutron Cancer Therapy to monitor neutron distribution and neutron-capture agent distribution. This approach consists of irradiating small animals in the thermal neutron beam of a nuclear reactor to produce prompt gamma rays from the elements in the sample by the radiative capture (n, gamma) reaction. These prompt gamma rays are emitted in energies that are characteristic of each element and they are also produced in characteristic coincident chains. After measuring these prompt gamma rays by surrounding spectrometry array, the distribution of each element of interest in the sample is reconstructed from the mapping of each detected signature gamma ray by either electronic collimations or mechanical collimations. In addition, the transmitted neutrons from the beam can be simultaneously used for very sensitive anatomical imaging, which provides the registration for the elemental distributions obtained from PGI. The primary approach is to use Monte Carlo simulation methods either with the specific purpose code CEARCPG, developed at NC State University or with the general purpose codes GEANT4 or MCNP5, to predict results and investigate the feasibility of this new imaging idea. Benchmark experiments have been conducted to test the capability of the code to simulate prompt gamma rays, which are produced by following the nuclear structures of each irradiated isotope, and coincidence counting techniques, which are considered the most important improvement in neutron-related gamma-ray detection applications to reduce gamma background and improve system signal-to-noise ratios. With coincidence prompt gamma rays available, two major imaging techniques, electronic collimations and mechanic collimations, are implemented in the simulation to illustrate the feasibility of imaging elemental distribution by this new technique. The expectation maximization algorithm is employed in electronic collimation to reconstruct images. The common SPECT imaging algorithms are used in mechanical collimation to get an image. Several critical topics concerning practical applications have already been discussed, such as the radiation dose to the mouse and the detection efficiency of high-energy gamma rays. The funding of this work is provided by the Center for Engineering Application of Radioisotopes (CEAR) at North Carolina State University (NCSU) and Nuclear Engineering Education Research.

An Application of Computerized Axial Tomography (CAT) Technology to Mass Raid Tracking

DTIC Science & Technology

1989-08-01

ESD-TR-89-305 MTR-10542 An Application of Computerized Axial Tomography ( CAT ) Technology to Mass Raid Tracking By John K. Barr August 1989...NO 11. TITLE (Include Security Classification) An Application of Computerized Axial Tomography ( CAT ) Technology to Mass Raid Tracking 12...by block number) Computerized Axial Tomography ( CAT ) Scanner Electronic Support Measures (ESM) Fusion (continued) 19. ABSTRACT (Continue on

Comparison of Compressed Sensing Algorithms for Inversion of 3-D Electrical Resistivity Tomography.

NASA Astrophysics Data System (ADS)

Peddinti, S. R.; Ranjan, S.; Kbvn, D. P.

2016-12-01

Image reconstruction algorithms derived from electrical resistivity tomography (ERT) are highly non-linear, sparse, and ill-posed. The inverse problem is much severe, when dealing with 3-D datasets that result in large sized matrices. Conventional gradient based techniques using L2 norm minimization with some sort of regularization can impose smoothness constraint on the solution. Compressed sensing (CS) is relatively new technique that takes the advantage of inherent sparsity in parameter space in one or the other form. If favorable conditions are met, CS was proven to be an efficient image reconstruction technique that uses limited observations without losing edge sharpness. This paper deals with the development of an open source 3-D resistivity inversion tool using CS framework. The forward model was adopted from RESINVM3D (Pidlisecky et al., 2007) with CS as the inverse code. Discrete cosine transformation (DCT) function was used to induce model sparsity in orthogonal form. Two CS based algorithms viz., interior point method and two-step IST were evaluated on a synthetic layered model with surface electrode observations. The algorithms were tested (in terms of quality and convergence) under varying degrees of parameter heterogeneity, model refinement, and reduced observation data space. In comparison to conventional gradient algorithms, CS was proven to effectively reconstruct the sub-surface image with less computational cost. This was observed by a general increase in NRMSE from 0.5 in 10 iterations using gradient algorithm to 0.8 in 5 iterations using CS algorithms.

Parallel programming of gradient-based iterative image reconstruction schemes for optical tomography.

PubMed

Hielscher, Andreas H; Bartel, Sebastian

2004-02-01

Optical tomography (OT) is a fast developing novel imaging modality that uses near-infrared (NIR) light to obtain cross-sectional views of optical properties inside the human body. A major challenge remains the time-consuming, computational-intensive image reconstruction problem that converts NIR transmission measurements into cross-sectional images. To increase the speed of iterative image reconstruction schemes that are commonly applied for OT, we have developed and implemented several parallel algorithms on a cluster of workstations. Static process distribution as well as dynamic load balancing schemes suitable for heterogeneous clusters and varying machine performances are introduced and tested. The resulting algorithms are shown to accelerate the reconstruction process to various degrees, substantially reducing the computation times for clinically relevant problems.

Extracting three-dimensional orientation and tractography of myofibers using optical coherence tomography

PubMed Central

Gan, Yu; Fleming, Christine P.

2013-01-01

Abnormal changes in orientation of myofibers are associated with various cardiac diseases such as arrhythmia, irregular contraction, and cardiomyopathy. To extract fiber information, we present a method of quantifying fiber orientation and reconstructing three-dimensional tractography of myofibers using optical coherence tomography (OCT). A gradient based algorithm was developed to quantify fiber orientation in three dimensions and particle filtering technique was employed to track myofibers. Prior to image processing, three-dimensional image data set were acquired from all cardiac chambers and ventricular septum of swine hearts using OCT system without optical clearing. The algorithm was validated through rotation test and comparison with manual measurements. The experimental results demonstrate that we are able to visualize three-dimensional fiber tractography in myocardium tissues. PMID:24156071

Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography.

PubMed

Zaki, Farzana; Wang, Yahui; Su, Hao; Yuan, Xin; Liu, Xuan

2017-05-01

Optical coherence tomography (OCT) is based on coherence detection of interferometric signals and hence inevitably suffers from speckle noise. To remove speckle noise in OCT images, wavelet domain thresholding has demonstrated significant advantages in suppressing noise magnitude while preserving image sharpness. However, speckle noise in OCT images has different characteristics in different spatial scales, which has not been considered in previous applications of wavelet domain thresholding. In this study, we demonstrate a noise adaptive wavelet thresholding (NAWT) algorithm that exploits the difference of noise characteristics in different wavelet sub-bands. The algorithm is simple, fast, effective and is closely related to the physical origin of speckle noise in OCT image. Our results demonstrate that NAWT outperforms conventional wavelet thresholding.

Deep learning approach for the detection and quantification of intraretinal cystoid fluid in multivendor optical coherence tomography.

PubMed

Venhuizen, Freerk G; van Ginneken, Bram; Liefers, Bart; van Asten, Freekje; Schreur, Vivian; Fauser, Sascha; Hoyng, Carel; Theelen, Thomas; Sánchez, Clara I

2018-04-01

We developed a deep learning algorithm for the automatic segmentation and quantification of intraretinal cystoid fluid (IRC) in spectral domain optical coherence tomography (SD-OCT) volumes independent of the device used for acquisition. A cascade of neural networks was introduced to include prior information on the retinal anatomy, boosting performance significantly. The proposed algorithm approached human performance reaching an overall Dice coefficient of 0.754 ± 0.136 and an intraclass correlation coefficient of 0.936, for the task of IRC segmentation and quantification, respectively. The proposed method allows for fast quantitative IRC volume measurements that can be used to improve patient care, reduce costs, and allow fast and reliable analysis in large population studies.

Deep learning approach for the detection and quantification of intraretinal cystoid fluid in multivendor optical coherence tomography

PubMed Central

Venhuizen, Freerk G.; van Ginneken, Bram; Liefers, Bart; van Asten, Freekje; Schreur, Vivian; Fauser, Sascha; Hoyng, Carel; Theelen, Thomas; Sánchez, Clara I.

2018-01-01

We developed a deep learning algorithm for the automatic segmentation and quantification of intraretinal cystoid fluid (IRC) in spectral domain optical coherence tomography (SD-OCT) volumes independent of the device used for acquisition. A cascade of neural networks was introduced to include prior information on the retinal anatomy, boosting performance significantly. The proposed algorithm approached human performance reaching an overall Dice coefficient of 0.754 ± 0.136 and an intraclass correlation coefficient of 0.936, for the task of IRC segmentation and quantification, respectively. The proposed method allows for fast quantitative IRC volume measurements that can be used to improve patient care, reduce costs, and allow fast and reliable analysis in large population studies. PMID:29675301

Modeling and image reconstruction in spectrally resolved bioluminescence tomography

NASA Astrophysics Data System (ADS)

Dehghani, Hamid; Pogue, Brian W.; Davis, Scott C.; Patterson, Michael S.

2007-02-01

Recent interest in modeling and reconstruction algorithms for Bioluminescence Tomography (BLT) has increased and led to the general consensus that non-spectrally resolved intensity-based BLT results in a non-unique problem. However, the light emitted from, for example firefly Luciferase, is widely distributed over the band of wavelengths from 500 nm to 650 nm and above, with the dominant fraction emitted from tissue being above 550 nm. This paper demonstrates the development of an algorithm used for multi-wavelength 3D spectrally resolved BLT image reconstruction in a mouse model. It is shown that using a single view data, bioluminescence sources of up to 15 mm deep can be successfully recovered given correct information about the underlying tissue absorption and scatter.

Projection matrix acquisition for cone-beam computed tomography iterative reconstruction

NASA Astrophysics Data System (ADS)

Yang, Fuqiang; Zhang, Dinghua; Huang, Kuidong; Shi, Wenlong; Zhang, Caixin; Gao, Zongzhao

2017-02-01

Projection matrix is an essential and time-consuming part in computed tomography (CT) iterative reconstruction. In this article a novel calculation algorithm of three-dimensional (3D) projection matrix is proposed to quickly acquire the matrix for cone-beam CT (CBCT). The CT data needed to be reconstructed is considered as consisting of the three orthogonal sets of equally spaced and parallel planes, rather than the individual voxels. After getting the intersections the rays with the surfaces of the voxels, the coordinate points and vertex is compared to obtain the index value that the ray traversed. Without considering ray-slope to voxel, it just need comparing the position of two points. Finally, the computer simulation is used to verify the effectiveness of the algorithm.

Machine learning based detection of age-related macular degeneration (AMD) and diabetic macular edema (DME) from optical coherence tomography (OCT) images

PubMed Central

Wang, Yu; Zhang, Yaonan; Yao, Zhaomin; Zhao, Ruixue; Zhou, Fengfeng

2016-01-01

Non-lethal macular diseases greatly impact patients’ life quality, and will cause vision loss at the late stages. Visual inspection of the optical coherence tomography (OCT) images by the experienced clinicians is the main diagnosis technique. We proposed a computer-aided diagnosis (CAD) model to discriminate age-related macular degeneration (AMD), diabetic macular edema (DME) and healthy macula. The linear configuration pattern (LCP) based features of the OCT images were screened by the Correlation-based Feature Subset (CFS) selection algorithm. And the best model based on the sequential minimal optimization (SMO) algorithm achieved 99.3% in the overall accuracy for the three classes of samples. PMID:28018716

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

PubMed Central

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. PMID:24058889

Three-dimensional monochromatic x-ray computed tomography using synchrotron radiation

NASA Astrophysics Data System (ADS)

Saito, Tsuneo; Kudo, Hiroyuki; Takeda, Tohoru; Itai, Yuji; Tokumori, Kenji; Toyofuku, Fukai; Hyodo, Kazuyuki; Ando, Masami; Nishimura, Katsuyuki; Uyama, Chikao

1998-08-01

We describe a technique of 3D computed tomography (3D CT) using monochromatic x rays generated by synchrotron radiation, which performs a direct reconstruction of a 3D volume image of an object from its cone-beam projections. For the development, we propose a practical scanning orbit of the x-ray source to obtain complete 3D information on an object, and its corresponding 3D image reconstruction algorithm. The validity and usefulness of the proposed scanning orbit and reconstruction algorithm were confirmed by computer simulation studies. Based on these investigations, we have developed a prototype 3D monochromatic x-ray CT using synchrotron radiation, which provides exact 3D reconstruction and material-selective imaging by using the K-edge energy subtraction technique.

Energy-angle correlation correction algorithm for monochromatic computed tomography based on Thomson scattering X-ray source

NASA Astrophysics Data System (ADS)

Chi, Zhijun; Du, Yingchao; Huang, Wenhui; Tang, Chuanxiang

2017-12-01

The necessity for compact and relatively low cost x-ray sources with monochromaticity, continuous tunability of x-ray energy, high spatial coherence, straightforward polarization control, and high brightness has led to the rapid development of Thomson scattering x-ray sources. To meet the requirement of in-situ monochromatic computed tomography (CT) for large-scale and/or high-attenuation materials based on this type of x-ray source, there is an increasing demand for effective algorithms to correct the energy-angle correlation. In this paper, we take advantage of the parametrization of the x-ray attenuation coefficient to resolve this problem. The linear attenuation coefficient of a material can be decomposed into a linear combination of the energy-dependent photoelectric and Compton cross-sections in the keV energy regime without K-edge discontinuities, and the line integrals of the decomposition coefficients of the above two parts can be determined by performing two spectrally different measurements. After that, the line integral of the linear attenuation coefficient of an imaging object at a certain interested energy can be derived through the above parametrization formula, and monochromatic CT can be reconstructed at this energy using traditional reconstruction methods, e.g., filtered back projection or algebraic reconstruction technique. Not only can monochromatic CT be realized, but also the distributions of the effective atomic number and electron density of the imaging object can be retrieved at the expense of dual-energy CT scan. Simulation results validate our proposal and will be shown in this paper. Our results will further expand the scope of application for Thomson scattering x-ray sources.

Dosimetric comparison of lung stereotactic body radiotherapy treatment plans using averaged computed tomography and end-exhalation computed tomography images: Evaluation of the effect of different dose-calculation algorithms and prescription methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitsuyoshi, Takamasa; Nakamura, Mitsuhiro, E-mail: m_nkmr@kuhp.kyoto-u.ac.jp; Matsuo, Yukinori

The purpose of this article is to quantitatively evaluate differences in dose distributions calculated using various computed tomography (CT) datasets, dose-calculation algorithms, and prescription methods in stereotactic body radiotherapy (SBRT) for patients with early-stage lung cancer. Data on 29 patients with early-stage lung cancer treated with SBRT were retrospectively analyzed. Averaged CT (Ave-CT) and expiratory CT (Ex-CT) images were reconstructed for each patient using 4-dimensional CT data. Dose distributions were initially calculated using the Ave-CT images and recalculated (in the same monitor units [MUs]) by employing Ex-CT images with the same beam arrangements. The dose-volume parameters, including D{sub 95}, D{submore » 90}, D{sub 50}, and D{sub 2} of the planning target volume (PTV), were compared between the 2 image sets. To explore the influence of dose-calculation algorithms and prescription methods on the differences in dose distributions evident between Ave-CT and Ex-CT images, we calculated dose distributions using the following 3 different algorithms: x-ray Voxel Monte Carlo (XVMC), Acuros XB (AXB), and the anisotropic analytical algorithm (AAA). We also used 2 different dose-prescription methods; the isocenter prescription and the PTV periphery prescription methods. All differences in PTV dose-volume parameters calculated using Ave-CT and Ex-CT data were within 3 percentage points (%pts) employing the isocenter prescription method, and within 1.5%pts using the PTV periphery prescription method, irrespective of which of the 3 algorithms (XVMC, AXB, and AAA) was employed. The frequencies of dose-volume parameters differing by >1%pt when the XVMC and AXB were used were greater than those associated with the use of the AAA, regardless of the dose-prescription method employed. All differences in PTV dose-volume parameters calculated using Ave-CT and Ex-CT data on patients who underwent lung SBRT were within 3%pts, regardless of the dose-calculation algorithm or the dose-prescription method employed.« less

Tomography of the fast electron bremsstrahlung emission during lower hybrid current drive on TORE SUPRA

NASA Astrophysics Data System (ADS)

Peysson, Yves; Imbeaux, Frédéric

1999-10-01

A new tomography dedicated to detailed studies of the fast electron bremsstrahlung emission in the hard x-ray (HXR) energy range between 20 and 200 keV during lower hybrid (LH) current drive experiments on the TORE SUPRA tokamak [Equipe TORE SUPRA, in Proceedings of the 15th Conference on Plasma Physics and Controlled Nuclear Fusion Research, Seville (International Atomic Energy Agency, Vienna, 1995), Vol. 1, AIEA-CN-60 / A1-5, p. 105] is presented. Radiation detection is performed by cadmium telluride semiconductors, which have most of the desirable features for a powerful diagnosing of magnetically confined hot plasmas—compact size, high x-ray stopping efficiency, fast timing characteristics, good energy resolution, no sensitivity to magnetic field, reasonable susceptibility to performance degradation from neutron/γ-induced damages. This instrument is made of two independent cameras viewing a poloidal cross-section of the plasma, with respectively 21 and 38 detectors. A coarse spectrometry—8 energy channels—is carried out for each chord, with an energy resolution of 20 keV. The spatial resolution in the core of the plasma is 4-5 cm, while the time sampling may be lowered down to of 2-4 ms. Powerful inversion techniques based on maximum entropy or regularization algorithms take full advantage of the large number of line-integrated measurements for very robust estimates of the local HXR profiles as a function of time and photon energy. A detailed account of main characteristics and performances of the diagnostic is reported, as well as preliminary results on LH current drive experiments.

Use of the Hotelling observer to optimize image reconstruction in digital breast tomosynthesis

PubMed Central

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

2015-01-01

Abstract. We propose an implementation of the Hotelling observer that can be applied to the optimization of linear image reconstruction algorithms in digital breast tomosynthesis. The method is based on considering information within a specific region of interest, and it is applied to the optimization of algorithms for detectability of microcalcifications. Several linear algorithms are considered: simple back-projection, filtered back-projection, back-projection filtration, and Λ-tomography. The optimized algorithms are then evaluated through the reconstruction of phantom data. The method appears robust across algorithms and parameters and leads to the generation of algorithm implementations which subjectively appear optimized for the task of interest. PMID:26702408

Breast ultrasound tomography with two parallel transducer arrays

NASA Astrophysics Data System (ADS)

Huang, Lianjie; Shin, Junseob; Chen, Ting; Lin, Youzuo; Gao, Kai; Intrator, Miranda; Hanson, Kenneth

2016-03-01

Breast ultrasound tomography is an emerging imaging modality to reconstruct the sound speed, density, and ultrasound attenuation of the breast in addition to ultrasound reflection/beamforming images for breast cancer detection and characterization. We recently designed and manufactured a new synthetic-aperture breast ultrasound tomography prototype with two parallel transducer arrays consisting of a total of 768 transducer elements. The transducer arrays are translated vertically to scan the breast in a warm water tank from the chest wall/axillary region to the nipple region to acquire ultrasound transmission and reflection data for whole-breast ultrasound tomography imaging. The distance of these two ultrasound transducer arrays is adjustable for scanning breasts with different sizes. We use our breast ultrasound tomography prototype to acquire phantom and in vivo patient ultrasound data to study its feasibility for breast imaging. We apply our recently developed ultrasound imaging and tomography algorithms to ultrasound data acquired using our breast ultrasound tomography system. Our in vivo patient imaging results demonstrate that our breast ultrasound tomography can detect breast lesions shown on clinical ultrasound and mammographic images.

A fast rebinning algorithm for 3D positron emission tomography using John's equation

NASA Astrophysics Data System (ADS)

Defrise, Michel; Liu, Xuan

1999-08-01

Volume imaging in positron emission tomography (PET) requires the inversion of the three-dimensional (3D) x-ray transform. The usual solution to this problem is based on 3D filtered-backprojection (FBP), but is slow. Alternative methods have been proposed which factor the 3D data into independent 2D data sets corresponding to the 2D Radon transforms of a stack of parallel slices. Each slice is then reconstructed using 2D FBP. These so-called rebinning methods are numerically efficient but are approximate. In this paper a new exact rebinning method is derived by exploiting the fact that the 3D x-ray transform of a function is the solution to the second-order partial differential equation first studied by John. The method is proposed for two sampling schemes, one corresponding to a pair of infinite plane detectors and another one corresponding to a cylindrical multi-ring PET scanner. The new FORE-J algorithm has been implemented for this latter geometry and was compared with the approximate Fourier rebinning algorithm FORE and with another exact rebinning algorithm, FOREX. Results with simulated data demonstrate a significant improvement in accuracy compared to FORE, while the reconstruction time is doubled. Compared to FOREX, the FORE-J algorithm is slightly less accurate but more than three times faster.

LETTER TO THE EDITOR: Free-response operator characteristic models for visual search

NASA Astrophysics Data System (ADS)

Hutchinson, T. P.

2007-05-01

Computed tomography of diffraction enhanced imaging (DEI-CT) is a novel x-ray phase-contrast computed tomography which is applied to inspect weakly absorbing low-Z samples. Refraction-angle images which are extracted from a series of raw DEI images measured in different positions of the rocking curve of the analyser can be regarded as projections of DEI-CT. Based on them, the distribution of refractive index decrement in the sample can be reconstructed according to the principles of CT. How to combine extraction methods and reconstruction algorithms to obtain the most accurate reconstructed results is investigated in detail in this paper. Two kinds of comparison, the comparison of different extraction methods and the comparison between 'two-step' algorithms and the Hilbert filtered backprojection (HFBP) algorithm, draw the conclusion that the HFBP algorithm based on the maximum refraction-angle (MRA) method may be the best combination at present. Though all current extraction methods including the MRA method are approximate methods and cannot calculate very large refraction-angle values, the HFBP algorithm based on the MRA method is able to provide quite acceptable estimations of the distribution of refractive index decrement of the sample. The conclusion is proved by the experimental results at the Beijing Synchrotron Radiation Facility.

Optimizing convergence rates of alternating minimization reconstruction algorithms for real-time explosive detection applications

NASA Astrophysics Data System (ADS)

Bosch, Carl; Degirmenci, Soysal; Barlow, Jason; Mesika, Assaf; Politte, David G.; O'Sullivan, Joseph A.

2016-05-01

X-ray computed tomography reconstruction for medical, security and industrial applications has evolved through 40 years of experience with rotating gantry scanners using analytic reconstruction techniques such as filtered back projection (FBP). In parallel, research into statistical iterative reconstruction algorithms has evolved to apply to sparse view scanners in nuclear medicine, low data rate scanners in Positron Emission Tomography (PET) [5, 7, 10] and more recently to reduce exposure to ionizing radiation in conventional X-ray CT scanners. Multiple approaches to statistical iterative reconstruction have been developed based primarily on variations of expectation maximization (EM) algorithms. The primary benefit of EM algorithms is the guarantee of convergence that is maintained when iterative corrections are made within the limits of convergent algorithms. The primary disadvantage, however is that strict adherence to correction limits of convergent algorithms extends the number of iterations and ultimate timeline to complete a 3D volumetric reconstruction. Researchers have studied methods to accelerate convergence through more aggressive corrections [1], ordered subsets [1, 3, 4, 9] and spatially variant image updates. In this paper we describe the development of an AM reconstruction algorithm with accelerated convergence for use in a real-time explosive detection application for aviation security. By judiciously applying multiple acceleration techniques and advanced GPU processing architectures, we are able to perform 3D reconstruction of scanned passenger baggage at a rate of 75 slices per second. Analysis of the results on stream of commerce passenger bags demonstrates accelerated convergence by factors of 8 to 15, when comparing images from accelerated and strictly convergent algorithms.

Solid-state nanopores of controlled geometry fabricated in a transmission electron microscope

NASA Astrophysics Data System (ADS)

Qian, Hui; Egerton, Ray F.

2017-11-01

Energy-filtered transmission electron microscopy and electron tomography were applied to in situ studies of the formation, shape, and diameter of nanopores formed in a silicon nitride membrane in a transmission electron microscope. The nanopore geometry was observed in three dimensions by electron tomography. Drilling conditions, such as probe current, beam convergence angle, and probe position, affect the formation rate and the geometry of the pores. With a beam convergence semi-angle of α = 22 mrad, a conical shaped nanopore is formed but at α = 45 mrad, double-cone (hourglass-shaped) nanopores were produced. Nanopores with an effective diameter between 10 nm and 1.8 nm were fabricated by controlling the drilling time.

Entanglement in a solid-state spin ensemble.

PubMed

Simmons, Stephanie; Brown, Richard M; Riemann, Helge; Abrosimov, Nikolai V; Becker, Peter; Pohl, Hans-Joachim; Thewalt, Mike L W; Itoh, Kohei M; Morton, John J L

2011-02-03

Entanglement is the quintessential quantum phenomenon. It is a necessary ingredient in most emerging quantum technologies, including quantum repeaters, quantum information processing and the strongest forms of quantum cryptography. Spin ensembles, such as those used in liquid-state nuclear magnetic resonance, have been important for the development of quantum control methods. However, these demonstrations contain no entanglement and ultimately constitute classical simulations of quantum algorithms. Here we report the on-demand generation of entanglement between an ensemble of electron and nuclear spins in isotopically engineered, phosphorus-doped silicon. We combined high-field (3.4 T), low-temperature (2.9 K) electron spin resonance with hyperpolarization of the (31)P nuclear spin to obtain an initial state of sufficient purity to create a non-classical, inseparable state. The state was verified using density matrix tomography based on geometric phase gates, and had a fidelity of 98% relative to the ideal state at this field and temperature. The entanglement operation was performed simultaneously, with high fidelity, on 10(10) spin pairs; this fulfils one of the essential requirements for a silicon-based quantum information processor.

Combining endoscopic ultrasound with Time-Of-Flight PET: The EndoTOFPET-US Project

NASA Astrophysics Data System (ADS)

Frisch, Benjamin

2013-12-01

The EndoTOFPET-US collaboration develops a multimodal imaging technique for endoscopic exams of the pancreas or the prostate. It combines the benefits of high resolution metabolic imaging with Time-Of-Flight Positron Emission Tomography (TOF PET) and anatomical imaging with ultrasound (US). EndoTOFPET-US consists of a PET head extension for a commercial US endoscope and a PET plate outside the body in coincidence with the head. The high level of miniaturization and integration creates challenges in fields such as scintillating crystals, ultra-fast photo-detection, highly integrated electronics, system integration and image reconstruction. Amongst the developments, fast scintillators as well as fast and compact digital SiPMs with single SPAD readout are used to obtain the best coincidence time resolution (CTR). Highly integrated ASICs and DAQ electronics contribute to the timing performances of EndoTOFPET. In view of the targeted resolution of around 1 mm in the reconstructed image, we present a prototype detector system with a CTR better than 240 ps FWHM. We discuss the challenges in simulating such a system and introduce reconstruction algorithms based on graphics processing units (GPU).

Updating a preoperative surface model with information from real-time tracked 2D ultrasound using a Poisson surface reconstruction algorithm

NASA Astrophysics Data System (ADS)

Sun, Deyu; Rettmann, Maryam E.; Holmes, David R.; Linte, Cristian A.; Packer, Douglas; Robb, Richard A.

2014-03-01

In this work, we propose a method for intraoperative reconstruction of a left atrial surface model for the application of cardiac ablation therapy. In this approach, the intraoperative point cloud is acquired by a tracked, 2D freehand intra-cardiac echocardiography device, which is registered and merged with a preoperative, high resolution left atrial surface model built from computed tomography data. For the surface reconstruction, we introduce a novel method to estimate the normal vector of the point cloud from the preoperative left atrial model, which is required for the Poisson Equation Reconstruction algorithm. In the current work, the algorithm is evaluated using a preoperative surface model from patient computed tomography data and simulated intraoperative ultrasound data. Factors such as intraoperative deformation of the left atrium, proportion of the left atrial surface sampled by the ultrasound, sampling resolution, sampling noise, and registration error were considered through a series of simulation experiments.

Comparison of distribution of lung aeration measured with EIT and CT in spontaneously breathing, awake patients1.

PubMed

Radke, Oliver C; Schneider, Thomas; Braune, Anja; Pirracchio, Romain; Fischer, Felix; Koch, Thea

2016-09-28

Both Electrical Impedance Tomography (EIT) and Computed Tomography (CT) allow the estimation of the lung area. We compared two algorithms for the detection of the lung area per quadrant from the EIT images with the lung areas derived from the CT images. 39 outpatients who were scheduled for an elective CT scan of the thorax were included in the study. For each patient we recorded EIT images immediately before the CT scan. The lung area per quadrant was estimated from both CT and EIT data using two different algorithms for the EIT data. Data showed considerable variation during spontaneous breathing of the patients. Overall correlation between EIT and CT was poor (0.58-0.77), the correlation between the two EIT algorithms was better (0.90-0.92). Bland-Altmann analysis revealed absence of bias, but wide limits of agreement. Lung area estimation from CT and EIT differs significantly, most probably because of the fundamental difference in image generation.

Theoretical and experimental study on near infrared time-resolved optical diffuse tomography

NASA Astrophysics Data System (ADS)

Zhao, Huijuan; Gao, Feng; Tanikawa, Yukari; Yamada, Yukio

2006-08-01

Parts of the works of our group in the past five years on near infrared time-resolved (TR) optical tomography are summarized in this paper. The image reconstruction algorithm is based on Newton Raphson scheme with a datatype R generated from modified Generalized Pulse Spectrum Technique. Firstly, the algorithm is evaluated with simulated data from a 2-D model and the datatype R is compared with other popularly used datatypes. In this second part of the paper, the in vitro and in vivo NIR DOT imaging on a chicken leg and a human forearm, respectively are presented for evaluating both the image reconstruction algorithm and the TR measurement system. The third part of this paper is about the differential pathlength factor of human head while monitoring head activity with NIRS and applying the modified Lambert-Beer law. Benefiting from the TR system, the measured DPF maps of the three import areas of human head are presented in this paper.

Heart CT scan

MedlinePlus

... Computed tomography scan - heart; Calcium scoring; Multi-detector CT scan - heart; Electron beam computed tomography - heart; Agatston ... table that slides into the center of the CT scanner. You will lie on your back with ...

Seismic structure of the upper crust in the Albertine Rift from travel-time and ambient-noise tomography - a comparison

NASA Astrophysics Data System (ADS)

Jakovlev, Andrey; Kaviani, Ayoub; Ruempker, Georg

2017-04-01

Here we present results of the investigation of the upper crust in the Albertine rift around the Rwenzori Mountains. We use a data set collected from a temporary network of 33 broadband stations operated by the RiftLink research group between September 2009 and August 2011. During this period, 82639 P-wave and 73408 S-wave travel times from 12419 local and regional earthquakes were registered. This presents a very rare opportunity to apply both local travel-time and ambient-noise tomography to analyze data from the same network. For the local travel-time tomographic inversion the LOTOS algorithm (Koulakov, 2009) was used. The algorithm performs iterative simultaneous inversions for 3D models of P- and S-velocity anomalies in combination with earthquake locations and origin times. 28955 P- and S-wave picks from 2769 local earthquakes were used. To estimate the resolution and stability of the results a number of the synthetic and real data tests were performed. To perform the ambient noise tomography we use the following procedure. First, we follow the standard procedure described by Bensen et al. (2007) as modified by Boué et al. (2014) to compute the vertical component cross-correlation functions between all pairs of stations. We also adapted the algorithm introduced by Boué et al. (2014) and use the WHISPER software package (Briand et al., 2013) to preprocess individual daily vertical-component waveforms. On the next step, for each period, we use the method of Barmin et al. (2001) to invert the dispersion measurements along each path for group velocity tomographic maps. Finally, we adapt a modified version of the algorithm suggested by Macquet et al. (2014) to invert the group velocity maps for shear velocity structure. We apply several tests, which show that the best resolution is obtained at a period of 8 seconds, which correspond to a depth of approximately 6 km. Models of the seismic structure obtained by the two methods agree well at shallow depth of about 5 km Low velocities surround the mountain range from western and southern sides and coincide with the location of the rift valley. The Rwenzori Mountains itself and the eastern rift shoulder are represented by increased velocities. At greater depths of 10 - 15 km some differences in the models care observed. Thus, beneath the Rwenzories the travel time tomography shows low S-velocities, whereas the ambient noise tomography exhibits high S-velocities. This can be possibly explained by the fact that the ambient noise tomography is characterized by higher vertical resolution. Also, the number of the rays used for tomographic inversion in the ambient noise tomography is significantly smaller. This study was partly supported by the grant of Russian Foundation of Science #14-17-00430. References: Barmin, M.P., Ritzwoller, M.H. & Levshin, A.L., 2001. A fast and reliable method for surface wave tomography, Pure appl. Geophys., 158, 1351-1375. Bensen G.D., Ritzwoller M.H., Barmin M.P., Levshin A.L., Lin F., Moschetti M.P., Shapiro N.M., Yang Y., 2001, A fast and reliable method for surface wave tomography. Geophys. J. Int. 169, 1239-1260, doi: 10.1111/j.1365-246X.2007.03374.x. Boué P., Poli P., Campillo M., Roux P., 2014, Reverberations, coda waves and ambient-noise: correlations at the global scale and retrieval of the deep phases. Earth planet. Sci. Lett., 391, 137-145. Briand X., Campillo M., Brenguier F., Boué P., Poli P., Roux P., Takeda T. AGU Fall Meeting. San Francisco, CA; 2013. Processing of terabytes of data for seismic noise analysis with the Python codes of the Whisper Suite. 9-13 December, in Proceedings of the , Abstract n°IN51B-1544. Koulakov, I. (2009), LOTOS code for local earthquake tomographic inversion. Benchmarks for testing tomographic algorithms, Bull. Seismol. Soc. Am., 99, 194-214, doi:10.1785/0120080013.

Optical coherence tomography: A guide to interpretation of common macular diseases

PubMed Central

Bhende, Muna; Shetty, Sharan; Parthasarathy, Mohana Kuppuswamy; Ramya, S

2018-01-01

Optical coherence tomography is a quick, non invasive and reproducible imaging tool for macular lesions and has become an essential part of retina practice. This review address the common protocols for imaging the macula, basics of image interpretation, features of common macular disorders with clues to differentiate mimickers and an introduction to choroidal imaging. It includes case examples and also a practical algorithm for interpretation. PMID:29283118

Electron tomography and 3D molecular simulations of platinum nanocrystals

NASA Astrophysics Data System (ADS)

Florea, Ileana; Demortière, Arnaud; Petit, Christophe; Bulou, Hervé; Hirlimann, Charles; Ersen, Ovidiu

2012-07-01

This work reports on the morphology of individual platinum nanocrystals with sizes of about 5 nm. By using the electron tomography technique that gives 3D spatial selectivity, access to quantitative information in the real space was obtained. The morphology of individual nanoparticles was characterized using HAADF-STEM tomography and it was shown to be close to a truncated octahedron. Using molecular dynamics simulations, this geometrical shape was found to be the one minimizing the nanocrystal energy. Starting from the tomographic reconstruction, 3D crystallographic representations of the studied Pt nanocrystals were obtained at the nanometer scale, allowing the quantification of the relative amount of the crystallographic facets present on the particle surface.This work reports on the morphology of individual platinum nanocrystals with sizes of about 5 nm. By using the electron tomography technique that gives 3D spatial selectivity, access to quantitative information in the real space was obtained. The morphology of individual nanoparticles was characterized using HAADF-STEM tomography and it was shown to be close to a truncated octahedron. Using molecular dynamics simulations, this geometrical shape was found to be the one minimizing the nanocrystal energy. Starting from the tomographic reconstruction, 3D crystallographic representations of the studied Pt nanocrystals were obtained at the nanometer scale, allowing the quantification of the relative amount of the crystallographic facets present on the particle surface. Electronic supplementary information (ESI) available. See DOI: 10.1039/c2nr30990d

Cone-Beam Computed Tomography for Image-Guided Radiation Therapy of Prostate Cancer

DTIC Science & Technology

2010-01-01

ltered ba kproje tion (FBP) al-gorithm that does not depend upon the hords hastherefore been developed for volumetri image re- onstru tion in a...reproje tion of the rst re onstru ted volumetri image. The NCAT 6 phantom images re onstru ted by the tandem algorithm are shown in Fig. 3. The paper...algorithm has been applied to a ir ular one-beam mi ro-CT for volumetri images of the ROIwith a higher spatial resolution and at a redu edexposure to

Comparison of 3D cellular imaging techniques based on scanned electron probes: Serial block face SEM vs. Axial bright-field STEM tomography.

PubMed

McBride, E L; Rao, A; Zhang, G; Hoyne, J D; Calco, G N; Kuo, B C; He, Q; Prince, A A; Pokrovskaya, I D; Storrie, B; Sousa, A A; Aronova, M A; Leapman, R D

2018-06-01

Microscopies based on focused electron probes allow the cell biologist to image the 3D ultrastructure of eukaryotic cells and tissues extending over large volumes, thus providing new insight into the relationship between cellular architecture and function of organelles. Here we compare two such techniques: electron tomography in conjunction with axial bright-field scanning transmission electron microscopy (BF-STEM), and serial block face scanning electron microscopy (SBF-SEM). The advantages and limitations of each technique are illustrated by their application to determining the 3D ultrastructure of human blood platelets, by considering specimen geometry, specimen preparation, beam damage and image processing methods. Many features of the complex membranes composing the platelet organelles can be determined from both approaches, although STEM tomography offers a higher ∼3 nm isotropic pixel size, compared with ∼5 nm for SBF-SEM in the plane of the block face and ∼30 nm in the perpendicular direction. In this regard, we demonstrate that STEM tomography is advantageous for visualizing the platelet canalicular system, which consists of an interconnected network of narrow (∼50-100 nm) membranous cisternae. In contrast, SBF-SEM enables visualization of complete platelets, each of which extends ∼2 µm in minimum dimension, whereas BF-STEM tomography can typically only visualize approximately half of the platelet volume due to a rapid non-linear loss of signal in specimens of thickness greater than ∼1.5 µm. We also show that the limitations of each approach can be ameliorated by combining 3D and 2D measurements using a stereological approach. Copyright © 2018. Published by Elsevier Inc.

Attenuation correction in emission tomography using the emission data—A review

PubMed Central

Li, Yusheng

2016-01-01

The problem of attenuation correction (AC) for quantitative positron emission tomography (PET) had been considered solved to a large extent after the commercial availability of devices combining PET with computed tomography (CT) in 2001; single photon emission computed tomography (SPECT) has seen a similar development. However, stimulated in particular by technical advances toward clinical systems combining PET and magnetic resonance imaging (MRI), research interest in alternative approaches for PET AC has grown substantially in the last years. In this comprehensive literature review, the authors first present theoretical results with relevance to simultaneous reconstruction of attenuation and activity. The authors then look back at the early history of this research area especially in PET; since this history is closely interwoven with that of similar approaches in SPECT, these will also be covered. We then review algorithmic advances in PET, including analytic and iterative algorithms. The analytic approaches are either based on the Helgason–Ludwig data consistency conditions of the Radon transform, or generalizations of John’s partial differential equation; with respect to iterative methods, we discuss maximum likelihood reconstruction of attenuation and activity (MLAA), the maximum likelihood attenuation correction factors (MLACF) algorithm, and their offspring. The description of methods is followed by a structured account of applications for simultaneous reconstruction techniques: this discussion covers organ-specific applications, applications specific to PET/MRI, applications using supplemental transmission information, and motion-aware applications. After briefly summarizing SPECT applications, we consider recent developments using emission data other than unscattered photons. In summary, developments using time-of-flight (TOF) PET emission data for AC have shown promising advances and open a wide range of applications. These techniques may both remedy deficiencies of purely MRI-based AC approaches in PET/MRI and improve standalone PET imaging. PMID:26843243

Attenuation correction in emission tomography using the emission data—A review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berker, Yannick, E-mail: berker@mail.med.upenn.edu; Li, Yusheng

2016-02-15

The problem of attenuation correction (AC) for quantitative positron emission tomography (PET) had been considered solved to a large extent after the commercial availability of devices combining PET with computed tomography (CT) in 2001; single photon emission computed tomography (SPECT) has seen a similar development. However, stimulated in particular by technical advances toward clinical systems combining PET and magnetic resonance imaging (MRI), research interest in alternative approaches for PET AC has grown substantially in the last years. In this comprehensive literature review, the authors first present theoretical results with relevance to simultaneous reconstruction of attenuation and activity. The authors thenmore » look back at the early history of this research area especially in PET; since this history is closely interwoven with that of similar approaches in SPECT, these will also be covered. We then review algorithmic advances in PET, including analytic and iterative algorithms. The analytic approaches are either based on the Helgason–Ludwig data consistency conditions of the Radon transform, or generalizations of John’s partial differential equation; with respect to iterative methods, we discuss maximum likelihood reconstruction of attenuation and activity (MLAA), the maximum likelihood attenuation correction factors (MLACF) algorithm, and their offspring. The description of methods is followed by a structured account of applications for simultaneous reconstruction techniques: this discussion covers organ-specific applications, applications specific to PET/MRI, applications using supplemental transmission information, and motion-aware applications. After briefly summarizing SPECT applications, we consider recent developments using emission data other than unscattered photons. In summary, developments using time-of-flight (TOF) PET emission data for AC have shown promising advances and open a wide range of applications. These techniques may both remedy deficiencies of purely MRI-based AC approaches in PET/MRI and improve standalone PET imaging.« less

Quantitative Cryo-Scanning Transmission Electron Microscopy of Biological Materials.

PubMed

Elbaum, Michael

2018-05-11

Electron tomography provides a detailed view into the 3D structure of biological cells and tissues. Physical fixation by vitrification of the aqueous medium provides the most faithful preservation of biological specimens in the native, fully hydrated state. Cryo-microscopy is challenging, however, because of the sensitivity to electron irradiation and due to the weak electron scattering of organic material. Tomography is even more challenging because of the dependence on multiple exposures of the same area. Tomographic imaging is typically performed in wide-field transmission electron microscopy (TEM) mode with phase contrast generated by defocus. Scanning transmission electron microscopy (STEM) is an alternative mode based on detection of scattering from a focused probe beam, without imaging optics following the specimen. While careful configuration of the illumination and detectors is required to generate useful contrast, STEM circumvents the major restrictions of phase contrast TEM to very thin specimens and provides a signal that is more simply interpreted in terms of local composition and density. STEM has gained popularity in recent years for materials science. The extension of STEM to cryomicroscopy and tomography of cells and macromolecules is summarized herein. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Muon tomography imaging improvement using optimized limited angle data

NASA Astrophysics Data System (ADS)

Bai, Chuanyong; Simon, Sean; Kindem, Joel; Luo, Weidong; Sossong, Michael J.; Steiger, Matthew

2014-05-01

Image resolution of muon tomography is limited by the range of zenith angles of cosmic ray muons and the flux rate at sea level. Low flux rate limits the use of advanced data rebinning and processing techniques to improve image quality. By optimizing the limited angle data, however, image resolution can be improved. To demonstrate the idea, physical data of tungsten blocks were acquired on a muon tomography system. The angular distribution and energy spectrum of muons measured on the system was also used to generate simulation data of tungsten blocks of different arrangement (geometry). The data were grouped into subsets using the zenith angle and volume images were reconstructed from the data subsets using two algorithms. One was a distributed PoCA (point of closest approach) algorithm and the other was an accelerated iterative maximal likelihood/expectation maximization (MLEM) algorithm. Image resolution was compared for different subsets. Results showed that image resolution was better in the vertical direction for subsets with greater zenith angles and better in the horizontal plane for subsets with smaller zenith angles. The overall image resolution appeared to be the compromise of that of different subsets. This work suggests that the acquired data can be grouped into different limited angle data subsets for optimized image resolution in desired directions. Use of multiple images with resolution optimized in different directions can improve overall imaging fidelity and the intended applications.

Improve threshold segmentation using features extraction to automatic lung delimitation.

PubMed

França, Cleunio; Vasconcelos, Germano; Diniz, Paula; Melo, Pedro; Diniz, Jéssica; Novaes, Magdala

2013-01-01

With the consolidation of PACS and RIS systems, the development of algorithms for tissue segmentation and diseases detection have intensely evolved in recent years. These algorithms have advanced to improve its accuracy and specificity, however, there is still some way until these algorithms achieved satisfactory error rates and reduced processing time to be used in daily diagnosis. The objective of this study is to propose a algorithm for lung segmentation in x-ray computed tomography images using features extraction, as Centroid and orientation measures, to improve the basic threshold segmentation. As result we found a accuracy of 85.5%.

Enhanced spatial resolution in fluorescence molecular tomography using restarted L1-regularized nonlinear conjugate gradient algorithm.

PubMed

Shi, Junwei; Liu, Fei; Zhang, Guanglei; Luo, Jianwen; Bai, Jing

2014-04-01

Owing to the high degree of scattering of light through tissues, the ill-posedness of fluorescence molecular tomography (FMT) inverse problem causes relatively low spatial resolution in the reconstruction results. Unlike L2 regularization, L1 regularization can preserve the details and reduce the noise effectively. Reconstruction is obtained through a restarted L1 regularization-based nonlinear conjugate gradient (re-L1-NCG) algorithm, which has been proven to be able to increase the computational speed with low memory consumption. The algorithm consists of inner and outer iterations. In the inner iteration, L1-NCG is used to obtain the L1-regularized results. In the outer iteration, the restarted strategy is used to increase the convergence speed of L1-NCG. To demonstrate the performance of re-L1-NCG in terms of spatial resolution, simulation and physical phantom studies with fluorescent targets located with different edge-to-edge distances were carried out. The reconstruction results show that the re-L1-NCG algorithm has the ability to resolve targets with an edge-to-edge distance of 0.1 cm at a depth of 1.5 cm, which is a significant improvement for FMT.

Uniqueness and reconstruction in magnetic resonance-electrical impedance tomography (MR-EIT).

PubMed

Ider, Y Ziya; Onart, Serkan; Lionheart, William R B

2003-05-01

Magnetic resonance-electrical impedance tomography (MR-EIT) was first proposed in 1992. Since then various reconstruction algorithms have been suggested and applied. These algorithms use peripheral voltage measurements and internal current density measurements in different combinations. In this study the problem of MR-EIT is treated as a hyperbolic system of first-order partial differential equations, and three numerical methods are proposed for its solution. This approach is not utilized in any of the algorithms proposed earlier. The numerical solution methods are integration along equipotential surfaces (method of characteristics), integration on a Cartesian grid, and inversion of a system matrix derived by a finite difference formulation. It is shown that if some uniqueness conditions are satisfied, then using at least two injected current patterns, resistivity can be reconstructed apart from a multiplicative constant. This constant can then be identified using a single voltage measurement. The methods proposed are direct, non-iterative, and valid and feasible for 3D reconstructions. They can also be used to easily obtain slice and field-of-view images from a 3D object. 2D simulations are made to illustrate the performance of the algorithms.

A Reconstruction Algorithm for Breast Cancer Imaging With Electrical Impedance Tomography in Mammography Geometry

PubMed Central

Kao, Tzu-Jen; Isaacson, David; Saulnier, Gary J.; Newell, Jonathan C.

2009-01-01

The conductivity and permittivity of breast tumors are known to differ significantly from those of normal breast tissues, and electrical impedance tomography (EIT) is being studied as a modality for breast cancer imaging to exploit these differences. At present, X-ray mammography is the primary standard imaging modality used for breast cancer screening in clinical practice, so it is desirable to study EIT in the geometry of mammography. This paper presents a forward model of a simplified mammography geometry and a reconstruction algorithm for breast tumor imaging using EIT techniques. The mammography geometry is modeled as a rectangular box with electrode arrays on the top and bottom planes. A forward model for the electrical impedance imaging problem is derived for a homogeneous conductivity distribution and is validated by experiment using a phantom tank. A reconstruction algorithm for breast tumor imaging based on a linearization approach and the proposed forward model is presented. It is found that the proposed reconstruction algorithm performs well in the phantom experiment, and that the locations of a 5-mm-cube metal target and a 6-mm-cube agar target could be recovered at a target depth of 15 mm using a 32 electrode system. PMID:17405377

Spectral Prior Image Constrained Compressed Sensing (Spectral PICCS) for Photon-Counting Computed Tomography

PubMed Central

Yu, Zhicong; Leng, Shuai; Li, Zhoubo; McCollough, Cynthia H.

2016-01-01

Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in-vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43~73%) without sacrificing CT number accuracy or spatial resolution. PMID:27551878

Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms

NASA Astrophysics Data System (ADS)

Mohan, K. Aditya

2017-10-01

4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.

Extracting cardiac shapes and motion of the chick embryo heart outflow tract from four-dimensional optical coherence tomography images

NASA Astrophysics Data System (ADS)

Yin, Xin; Liu, Aiping; Thornburg, Kent L.; Wang, Ruikang K.; Rugonyi, Sandra

2012-09-01

Recent advances in optical coherence tomography (OCT), and the development of image reconstruction algorithms, enabled four-dimensional (4-D) (three-dimensional imaging over time) imaging of the embryonic heart. To further analyze and quantify the dynamics of cardiac beating, segmentation procedures that can extract the shape of the heart and its motion are needed. Most previous studies analyzed cardiac image sequences using manually extracted shapes and measurements. However, this is time consuming and subject to inter-operator variability. Automated or semi-automated analyses of 4-D cardiac OCT images, although very desirable, are also extremely challenging. This work proposes a robust algorithm to semi automatically detect and track cardiac tissue layers from 4-D OCT images of early (tubular) embryonic hearts. Our algorithm uses a two-dimensional (2-D) deformable double-line model (DLM) to detect target cardiac tissues. The detection algorithm uses a maximum-likelihood estimator and was successfully applied to 4-D in vivo OCT images of the heart outflow tract of day three chicken embryos. The extracted shapes captured the dynamics of the chick embryonic heart outflow tract wall, enabling further analysis of cardiac motion.

Spectral prior image constrained compressed sensing (spectral PICCS) for photon-counting computed tomography

NASA Astrophysics Data System (ADS)

Yu, Zhicong; Leng, Shuai; Li, Zhoubo; McCollough, Cynthia H.

2016-09-01

Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43-73%) without sacrificing CT number accuracy or spatial resolution.

Reconstruction of sparse-view X-ray computed tomography using adaptive iterative algorithms.

PubMed

Liu, Li; Lin, Weikai; Jin, Mingwu

2015-01-01

In this paper, we propose two reconstruction algorithms for sparse-view X-ray computed tomography (CT). Treating the reconstruction problems as data fidelity constrained total variation (TV) minimization, both algorithms adapt the alternate two-stage strategy: projection onto convex sets (POCS) for data fidelity and non-negativity constraints and steepest descent for TV minimization. The novelty of this work is to determine iterative parameters automatically from data, thus avoiding tedious manual parameter tuning. In TV minimization, the step sizes of steepest descent are adaptively adjusted according to the difference from POCS update in either the projection domain or the image domain, while the step size of algebraic reconstruction technique (ART) in POCS is determined based on the data noise level. In addition, projection errors are used to compare with the error bound to decide whether to perform ART so as to reduce computational costs. The performance of the proposed methods is studied and evaluated using both simulated and physical phantom data. Our methods with automatic parameter tuning achieve similar, if not better, reconstruction performance compared to a representative two-stage algorithm. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Unified Mathematical Approach to Image Analysis.

DTIC Science & Technology

1987-08-31

describes four instances of the paradigm in detail. Directions for ongoing and future research are also indicated. Keywords: Image processing; Algorithms; Segmentation; Boundary detection; tomography; Global image analysis .

Atom probe tomography of lithium-doped network glasses.

PubMed

Greiwe, Gerd-Hendrik; Balogh, Zoltan; Schmitz, Guido

2014-06-01

Li-doped silicate and borate glasses are electronically insulating, but provide considerable ionic conductivity. Under measurement conditions of laser-assisted atom probe tomography, mobile Li ions are redistributed in response to high electric fields. In consequence, the direct interpretation of measured composition profiles is prevented. It is demonstrated that composition profiles are nevertheless well understood by a complex model taking into account the electronic structure of dielectric materials, ionic mobility and field screening. Quantitative data on band bending and field penetration during measurement are derived which are important in understanding laser-assisted atom probe tomography of dielectric materials. Copyright © 2014 Elsevier B.V. All rights reserved.

An efficient algorithm for double-difference tomography and location in heterogeneous media, with an application to the Kilauea volcano

USGS Publications Warehouse

Monteiller, V.; Got, J.-L.; Virieux, J.; Okubo, P.

2005-01-01

Improving our understanding of crustal processes requires a better knowledge of the geometry and the position of geological bodies. In this study we have designed a method based upon double-difference relocation and tomography to image, as accurately as possible, a heterogeneous medium containing seismogenic objects. Our approach consisted not only of incorporating double difference in tomography but also partly in revisiting tomographic schemes for choosing accurate and stable numerical strategies, adapted to the use of cross-spectral time delays. We used a finite difference solution to the eikonal equation for travel time computation and a Tarantola-Valette approach for both the classical and double-difference three-dimensional tomographic inversion to find accurate earthquake locations and seismic velocity estimates. We estimated efficiently the square root of the inverse model's covariance matrix in the case of a Gaussian correlation function. It allows the use of correlation length and a priori model variance criteria to determine the optimal solution. Double-difference relocation of similar earthquakes is performed in the optimal velocity model, making absolute and relative locations less biased by the velocity model. Double-difference tomography is achieved by using high-accuracy time delay measurements. These algorithms have been applied to earthquake data recorded in the vicinity of Kilauea and Mauna Loa volcanoes for imaging the volcanic structures. Stable and detailed velocity models are obtained: the regional tomography unambiguously highlights the structure of the island of Hawaii and the double-difference tomography shows a detailed image of the southern Kilauea caldera-upper east rift zone magmatic complex. Copyright 2005 by the American Geophysical Union.

EEL spectroscopic tomography: towards a new dimension in nanomaterials analysis.

PubMed

Yedra, Lluís; Eljarrat, Alberto; Arenal, Raúl; Pellicer, Eva; Cabo, Moisés; López-Ortega, Alberto; Estrader, Marta; Sort, Jordi; Baró, Maria Dolors; Estradé, Sònia; Peiró, Francesca

2012-11-01

Electron tomography is a widely spread technique for recovering the three dimensional (3D) shape of nanostructured materials. Using a spectroscopic signal to achieve a reconstruction adds a fourth chemical dimension to the 3D structure. Up to date, energy filtering of the images in the transmission electron microscope (EFTEM) is the usual spectroscopic method even if most of the information in the spectrum is lost. Unlike EFTEM tomography, the use of electron energy-loss spectroscopy (EELS) spectrum images (SI) for tomographic reconstruction retains all chemical information, and the possibilities of this new approach still remain to be fully exploited. In this article we prove the feasibility of EEL spectroscopic tomography at low voltages (80 kV) and short acquisition times from data acquired using an aberration corrected instrument and data treatment by Multivariate Analysis (MVA), applied to Fe(x)Co((3-x))O(4)@Co(3)O(4) mesoporous materials. This approach provides a new scope into materials; the recovery of full EELS signal in 3D. Copyright © 2012 Elsevier B.V. All rights reserved.

Markov random field based automatic image alignment for electron tomography.

PubMed

Amat, Fernando; Moussavi, Farshid; Comolli, Luis R; Elidan, Gal; Downing, Kenneth H; Horowitz, Mark

2008-03-01

We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.

Measuring radiation dose in computed tomography using elliptic phantom and free-in-air, and evaluating iterative metal artifact reduction algorithm

NASA Astrophysics Data System (ADS)

Morgan, Ashraf

The need for an accurate and reliable way for measuring patient dose in multi-row detector computed tomography (MDCT) has increased significantly. This research was focusing on the possibility of measuring CT dose in air to estimate Computed Tomography Dose Index (CTDI) for routine quality control purposes. New elliptic CTDI phantom that better represent human geometry was manufactured for investigating the effect of the subject shape on measured CTDI. Monte Carlo simulation was utilized in order to determine the dose distribution in comparison to the traditional cylindrical CTDI phantom. This research also investigated the effect of Siemens health care newly developed iMAR (iterative metal artifact reduction) algorithm, arthroplasty phantom was designed and manufactured that purpose. The design of new phantoms was part of the research as they mimic the human geometry more than the existing CTDI phantom. The standard CTDI phantom is a right cylinder that does not adequately represent the geometry of the majority of the patient population. Any dose reduction algorithm that is used during patient scan will not be utilized when scanning the CTDI phantom, so a better-designed phantom will allow the use of dose reduction algorithms when measuring dose, which leads to better dose estimation and/or better understanding of dose delivery. Doses from a standard CTDI phantom and the newly-designed phantoms were compared to doses measured in air. Iterative reconstruction is a promising technique in MDCT dose reduction and artifacts correction. Iterative reconstruction algorithms have been developed to address specific imaging tasks as is the case with Iterative Metal Artifact Reduction or iMAR which was developed by Siemens and is to be in use with the companys future computed tomography platform. The goal of iMAR is to reduce metal artifact when imaging patients with metal implants and recover CT number of tissues adjacent to the implant. This research evaluated iMAR capability of recovering CT numbers and reducing noise. Also, the use of iMAR should allow using lower tube voltage instead of 140 KVp which is used frequently to image patients with shoulder implants. The evaluations of image quality and dose reduction were carried out using an arthroplasty phantom.

Research on ionospheric tomography based on variable pixel height

NASA Astrophysics Data System (ADS)

Zheng, Dunyong; Li, Peiqing; He, Jie; Hu, Wusheng; Li, Chaokui

2016-05-01

A novel ionospheric tomography technique based on variable pixel height was developed for the tomographic reconstruction of the ionospheric electron density distribution. The method considers the height of each pixel as an unknown variable, which is retrieved during the inversion process together with the electron density values. In contrast to conventional computerized ionospheric tomography (CIT), which parameterizes the model with a fixed pixel height, the variable-pixel-height computerized ionospheric tomography (VHCIT) model applies a disturbance to the height of each pixel. In comparison with conventional CIT models, the VHCIT technique achieved superior results in a numerical simulation. A careful validation of the reliability and superiority of VHCIT was performed. According to the results of the statistical analysis of the average root mean square errors, the proposed model offers an improvement by 15% compared with conventional CIT models.

A New Method for Computed Tomography Angiography (CTA) Imaging via Wavelet Decomposition-Dependented Edge Matching Interpolation.

PubMed

Li, Zeyu; Chen, Yimin; Zhao, Yan; Zhu, Lifeng; Lv, Shengqing; Lu, Jiahui

2016-08-01

The interpolation technique of computed tomography angiography (CTA) image provides the ability for 3D reconstruction, as well as reduces the detect cost and the amount of radiation. However, most of the image interpolation algorithms cannot take the automation and accuracy into account. This study provides a new edge matching interpolation algorithm based on wavelet decomposition of CTA. It includes mark, scale and calculation (MSC). Combining the real clinical image data, this study mainly introduces how to search for proportional factor and use the root mean square operator to find a mean value. Furthermore, we re- synthesize the high frequency and low frequency parts of the processed image by wavelet inverse operation, and get the final interpolation image. MSC can make up for the shortage of the conventional Computed Tomography (CT) and Magnetic Resonance Imaging(MRI) examination. The radiation absorption and the time to check through the proposed synthesized image were significantly reduced. In clinical application, it can help doctor to find hidden lesions in time. Simultaneously, the patients get less economic burden as well as less radiation exposure absorbed.

Reconstruction algorithms based on l1-norm and l2-norm for two imaging models of fluorescence molecular tomography: a comparative study.

PubMed

Yi, Huangjian; Chen, Duofang; Li, Wei; Zhu, Shouping; Wang, Xiaorui; Liang, Jimin; Tian, Jie

2013-05-01

Fluorescence molecular tomography (FMT) is an important imaging technique of optical imaging. The major challenge of the reconstruction method for FMT is the ill-posed and underdetermined nature of the inverse problem. In past years, various regularization methods have been employed for fluorescence target reconstruction. A comparative study between the reconstruction algorithms based on l1-norm and l2-norm for two imaging models of FMT is presented. The first imaging model is adopted by most researchers, where the fluorescent target is of small size to mimic small tissue with fluorescent substance, as demonstrated by the early detection of a tumor. The second model is the reconstruction of distribution of the fluorescent substance in organs, which is essential to drug pharmacokinetics. Apart from numerical experiments, in vivo experiments were conducted on a dual-modality FMT/micro-computed tomography imaging system. The experimental results indicated that l1-norm regularization is more suitable for reconstructing the small fluorescent target, while l2-norm regularization performs better for the reconstruction of the distribution of fluorescent substance.

Validation of Ionosonde Electron Density Reconstruction Algorithms with IONOLAB-RAY in Central Europe

NASA Astrophysics Data System (ADS)

Gok, Gokhan; Mosna, Zbysek; Arikan, Feza; Arikan, Orhan; Erdem, Esra

2016-07-01

Ionospheric observation is essentially accomplished by specialized radar systems called ionosondes. The time delay between the transmitted and received signals versus frequency is measured by the ionosondes and the received signals are processed to generate ionogram plots, which show the time delay or reflection height of signals with respect to transmitted frequency. The critical frequencies of ionospheric layers and virtual heights, that provide useful information about ionospheric structurecan be extracted from ionograms . Ionograms also indicate the amount of variability or disturbances in the ionosphere. With special inversion algorithms and tomographical methods, electron density profiles can also be estimated from the ionograms. Although structural pictures of ionosphere in the vertical direction can be observed from ionosonde measurements, some errors may arise due to inaccuracies that arise from signal propagation, modeling, data processing and tomographic reconstruction algorithms. Recently IONOLAB group (www.ionolab.org) developed a new algorithm for effective and accurate extraction of ionospheric parameters and reconstruction of electron density profile from ionograms. The electron density reconstruction algorithm applies advanced optimization techniques to calculate parameters of any existing analytical function which defines electron density with respect to height using ionogram measurement data. The process of reconstructing electron density with respect to height is known as the ionogram scaling or true height analysis. IONOLAB-RAY algorithm is a tool to investigate the propagation path and parameters of HF wave in the ionosphere. The algorithm models the wave propagation using ray representation under geometrical optics approximation. In the algorithm , the structural ionospheric characteristics arerepresented as realistically as possible including anisotropicity, inhomogenity and time dependence in 3-D voxel structure. The algorithm is also used for various purposes including calculation of actual height and generation of ionograms. In this study, the performance of electron density reconstruction algorithm of IONOLAB group and standard electron density profile algorithms of ionosondes are compared with IONOLAB-RAY wave propagation simulation in near vertical incidence. The electron density reconstruction and parameter extraction algorithms of ionosondes are validated with the IONOLAB-RAY results both for quiet anddisturbed ionospheric states in Central Europe using ionosonde stations such as Pruhonice and Juliusruh . It is observed that IONOLAB ionosonde parameter extraction and electron density reconstruction algorithm performs significantly better compared to standard algorithms especially for disturbed ionospheric conditions. IONOLAB-RAY provides an efficient and reliable tool to investigate and validate ionosonde electron density reconstruction algorithms, especially in determination of reflection height (true height) of signals and critical parameters of ionosphere. This study is supported by TUBITAK 114E541, 115E915 and Joint TUBITAK 114E092 and AS CR 14/001 projects.

Breast boundary detection with active contours

NASA Astrophysics Data System (ADS)

Balic, I.; Goyal, P.; Roy, O.; Duric, N.

2014-03-01

Ultrasound tomography is a modality that can be used to image various characteristics of the breast, such as sound speed, attenuation, and reflectivity. In the considered setup, the breast is immersed in water and scanned along the coronal axis from the chest wall to the nipple region. To improve image visualization, it is desirable to remove the water background. To this end, the 3D boundary of the breast must be accurately estimated. We present an iterative algorithm based on active contours that automatically detects the boundary of a breast using a 3D stack of attenuation images obtained from an ultrasound tomography scanner. We build upon an existing method to design an algorithm that is fast, fully automated, and reliable. We demonstrate the effectiveness of the proposed technique using clinical data sets.

Speckle attenuation by adaptive singular value shrinking with generalized likelihood matching in optical coherence tomography

NASA Astrophysics Data System (ADS)

Chen, Huaiguang; Fu, Shujun; Wang, Hong; Lv, Hongli; Zhang, Caiming

2018-03-01

As a high-resolution imaging mode of biological tissues and materials, optical coherence tomography (OCT) is widely used in medical diagnosis and analysis. However, OCT images are often degraded by annoying speckle noise inherent in its imaging process. Employing the bilateral sparse representation an adaptive singular value shrinking method is proposed for its highly sparse approximation of image data. Adopting the generalized likelihood ratio as similarity criterion for block matching and an adaptive feature-oriented backward projection strategy, the proposed algorithm can restore better underlying layered structures and details of the OCT image with effective speckle attenuation. The experimental results demonstrate that the proposed algorithm achieves a state-of-the-art despeckling performance in terms of both quantitative measurement and visual interpretation.

Ionospheric-thermospheric UV tomography: 3. A multisensor technique for creating full-orbit reconstructions of atmospheric UV emission

NASA Astrophysics Data System (ADS)

Hei, Matthew A.; Budzien, Scott A.; Dymond, Kenneth F.; Nicholas, Andrew C.; Paxton, Larry J.; Schaefer, Robert K.; Groves, Keith M.

2017-07-01

We present the Volume Emission Rate Tomography (VERT) technique for inverting satellite-based, multisensor limb and nadir measurements of atmospheric ultraviolet emission to create whole-orbit reconstructions of atmospheric volume emission rate. The VERT approach is more general than previous ionospheric tomography methods because it can reconstruct the volume emission rate field irrespective of the particular excitation mechanisms (e.g., radiative recombination, photoelectron impact excitation, and energetic particle precipitation in auroras); physical models are then applied to interpret the airglow. The technique was developed and tested using data from the Special Sensor Ultraviolet Limb Imager and Special Sensor Ultraviolet Spectrographic Imager instruments aboard the Defense Meteorological Satellite Program F-18 spacecraft and planned for use with upcoming remote sensing missions. The technique incorporates several features to optimize the tomographic solutions, such as the use of a nonnegative algorithm (Richardson-Lucy, RL) that explicitly accounts for the Poisson statistics inherent in optical measurements, capability to include extinction effects due to resonant scattering and absorption of the photons from the lines of sight, a pseudodiffusion-based regularization scheme implemented between iterations of the RL code to produce smoother solutions, and the capability to estimate error bars on the solutions. Tests using simulated atmospheric emissions verify that the technique performs well in a variety of situations, including daytime, nighttime, and even in the challenging terminator regions. Lastly, we consider ionospheric nightglow and validate reconstructions of the nighttime electron density against Advanced Research Project Agency (ARPA) Long-range Tracking and Identification Radar (ALTAIR) incoherent scatter radar data.

Zernike phase contrast cryo-electron tomography of whole bacterial cells

PubMed Central

Guerrero-Ferreira, Ricardo C.; Wright, Elizabeth R.

2014-01-01

Cryo-electron tomography (cryo-ET) provides three-dimensional (3D) structural information of bacteria preserved in a native, frozen-hydrated state. The typical low contrast of tilt-series images, a result of both the need for a low electron dose and the use of conventional defocus phase-contrast imaging, is a challenge for high-quality tomograms. We show that Zernike phase-contrast imaging allows the electron dose to be reduced. This limits movement of gold fiducials during the tilt series, which leads to better alignment and a higher-resolution reconstruction. Contrast is also enhanced, improving visibility of weak features. The reduced electron dose also means that more images at more tilt angles could be recorded, further increasing resolution. PMID:24075950

Advances in 6d diffraction contrast tomography

NASA Astrophysics Data System (ADS)

Viganò, N.; Ludwig, W.

2018-04-01

The ability to measure 3D orientation fields and to determine grain boundary character plays a key role in understanding many material science processes, including: crack formation and propagation, grain coarsening, and corrosion processes. X-ray diffraction imaging techniques offer the ability to retrieve such information in a non-destructive manner. Among them, Diffraction Contrast Tomography (DCT) is a monochromatic beam, near-field technique, that uses an extended beam and offers fast mapping of 3D sample volumes. It was previously shown that the six-dimensional extension of DCT can be applied to moderately deformed samples (<= 5% total strain), made from materials that exhibit low levels of elastic deformation of the unit cell (<= 1%). In this article, we improved over the previously proposed 6D-DCT reconstruction method, through the introduction of both a more advanced forward model and reconstruction algorithm. The results obtained with the proposed improvements are compared against the reconstructions previously published in [1], using Electron Backscatter Diffraction (EBSD) measurements as a reference. The result was a noticeably higher quality reconstruction of the grain boundary positions and local orientation fields. The achieved reconstruction quality, together with the low acquisition times, render DCT a valuable tool for the stop-motion study of polycrystalline microstructures, evolving as a function of applied strain or thermal annealing treatments, for selected materials.

Facile multi-dimensional profiling of chemical gradients at the millimetre scale.

PubMed

Chen, Chih-Lin; Hsieh, Kai-Ta; Hsu, Ching-Fong; Urban, Pawel L

2016-01-07

A vast number of conventional physicochemical methods are suitable for the analysis of homogeneous samples. However, in various cases, the samples exhibit intrinsic heterogeneity. Tomography allows one to record approximate distributions of chemical species in the three-dimensional space. Here we develop a simple optical tomography system which enables performing scans of non-homogeneous samples at different wavelengths. It takes advantage of inexpensive open-source electronics and simple algorithms. The analysed samples are illuminated by a miniature LCD/LED screen which emits light at three wavelengths (598, 547 and 455 nm, corresponding to the R, G, and B channels, respectively). On presentation of every wavelength, the sample vial is rotated by ∼180°, and videoed at 30 frames per s. The RGB values of pixels in the obtained digital snapshots are subsequently collated, and processed to produce sinograms. Following the inverse Radon transform, approximate quasi-three-dimensional images are reconstructed for each wavelength. Sample components with distinct visible light absorption spectra (myoglobin, methylene blue) can be resolved. The system was used to follow dynamic changes in non-homogeneous samples in real time, to visualize binary mixtures, to reconstruct reaction-diffusion fronts formed during the reduction of 2,6-dichlorophenolindophenol by ascorbic acid, and to visualize the distribution of fungal mycelium grown in a semi-solid medium.

GPU Accelerated Ultrasonic Tomography Using Propagation and Back Propagation Method

DTIC Science & Technology

2015-09-28

the medical imaging field using GPUs has been done for many years. In [1], Copeland et al. used 2D images , obtained by X - ray projections, to...Index Terms— Medical Imaging , Ultrasonic Tomography, GPU, CUDA, Parallel Computing I. INTRODUCTION GRAPHIC Processing Units (GPUs) are computation... Imaging Algorithm The process of reconstructing images from ultrasonic infor- mation starts with the following acoustical wave equation: ∂2 ∂t2 u ( x

Optical Coherence Tomography (OCT) Device Independent Intraretinal Layer Segmentation

PubMed Central

Ehnes, Alexander; Wenner, Yaroslava; Friedburg, Christoph; Preising, Markus N.; Bowl, Wadim; Sekundo, Walter; zu Bexten, Erdmuthe Meyer; Stieger, Knut; Lorenz, Birgit

2014-01-01

Purpose To develop and test an algorithm to segment intraretinal layers irrespectively of the actual Optical Coherence Tomography (OCT) device used. Methods The developed algorithm is based on the graph theory optimization. The algorithm's performance was evaluated against that of three expert graders for unsigned boundary position difference and thickness measurement of a retinal layer group in 50 and 41 B-scans, respectively. Reproducibility of the algorithm was tested in 30 C-scans of 10 healthy subjects each with the Spectralis and the Stratus OCT. Comparability between different devices was evaluated in 84 C-scans (volume or radial scans) obtained from 21 healthy subjects, two scans per subject with the Spectralis OCT, and one scan per subject each with the Stratus OCT and the RTVue-100 OCT. Each C-scan was segmented and the mean thickness for each retinal layer in sections of the early treatment of diabetic retinopathy study (ETDRS) grid was measured. Results The algorithm was able to segment up to 11 intraretinal layers. Measurements with the algorithm were within the 95% confidence interval of a single grader and the difference was smaller than the interindividual difference between the expert graders themselves. The cross-device examination of ETDRS-grid related layer thicknesses highly agreed between the three OCT devices. The algorithm correctly segmented a C-scan of a patient with X-linked retinitis pigmentosa. Conclusions The segmentation software provides device-independent, reliable, and reproducible analysis of intraretinal layers, similar to what is obtained from expert graders. Translational Relevance Potential application of the software includes routine clinical practice and multicenter clinical trials. PMID:24820053

Reduction of Metal Artifact in Single Photon-Counting Computed Tomography by Spectral-Driven Iterative Reconstruction Technique

PubMed Central

Nasirudin, Radin A.; Mei, Kai; Panchev, Petar; Fehringer, Andreas; Pfeiffer, Franz; Rummeny, Ernst J.; Fiebich, Martin; Noël, Peter B.

2015-01-01

Purpose The exciting prospect of Spectral CT (SCT) using photon-counting detectors (PCD) will lead to new techniques in computed tomography (CT) that take advantage of the additional spectral information provided. We introduce a method to reduce metal artifact in X-ray tomography by incorporating knowledge obtained from SCT into a statistical iterative reconstruction scheme. We call our method Spectral-driven Iterative Reconstruction (SPIR). Method The proposed algorithm consists of two main components: material decomposition and penalized maximum likelihood iterative reconstruction. In this study, the spectral data acquisitions with an energy-resolving PCD were simulated using a Monte-Carlo simulator based on EGSnrc C++ class library. A jaw phantom with a dental implant made of gold was used as an object in this study. A total of three dental implant shapes were simulated separately to test the influence of prior knowledge on the overall performance of the algorithm. The generated projection data was first decomposed into three basis functions: photoelectric absorption, Compton scattering and attenuation of gold. A pseudo-monochromatic sinogram was calculated and used as input in the reconstruction, while the spatial information of the gold implant was used as a prior. The results from the algorithm were assessed and benchmarked with state-of-the-art reconstruction methods. Results Decomposition results illustrate that gold implant of any shape can be distinguished from other components of the phantom. Additionally, the result from the penalized maximum likelihood iterative reconstruction shows that artifacts are significantly reduced in SPIR reconstructed slices in comparison to other known techniques, while at the same time details around the implant are preserved. Quantitatively, the SPIR algorithm best reflects the true attenuation value in comparison to other algorithms. Conclusion It is demonstrated that the combination of the additional information from Spectral CT and statistical reconstruction can significantly improve image quality, especially streaking artifacts caused by the presence of materials with high atomic numbers. PMID:25955019

EDITORIAL: Industrial Process Tomography

NASA Astrophysics Data System (ADS)

Anton Johansen, Geir; Wang, Mi

2008-09-01

There has been tremendous development within measurement science and technology over the past couple of decades. New sensor technologies and compact versatile signal recovery electronics are continuously expanding the limits of what can be measured and the accuracy with which this can be done. Miniaturization of sensors and the use of nanotechnology push these limits further. Also, thanks to powerful and cost-effective computer systems, sophisticated measurement and reconstruction algorithms previously only accessible in advanced laboratories are now available for in situ online measurement systems. The process industries increasingly require more process-related information, motivated by key issues such as improved process control, process utilization and process yields, ultimately driven by cost-effectiveness, quality assurance, environmental and safety demands. Industrial process tomography methods have taken advantage of the general progress in measurement science, and aim at providing more information, both quantitatively and qualitatively, on multiphase systems and their dynamics. The typical approach for such systems has been to carry out one local or bulk measurement and assume that this is representative of the whole system. In some cases, this is sufficient. However, there are many complex systems where the component distribution varies continuously and often unpredictably in space and time. The foundation of industrial tomography is to conduct several measurements around the periphery of a multiphase process, and use these measurements to unravel the cross-sectional distribution of the process components in time and space. This information is used in the design and optimization of industrial processes and process equipment, and also to improve the accuracy of multiphase system measurements in general. In this issue we are proud to present a selection of the 145 papers presented at the 5th World Congress on Industrial Process Tomography in Bergen, September 2007. Interestingly, x-ray technologies, one of the first imaging modalities available, keep on moving the limits on both spatial and temporal measurement resolution; experimental results of less than 100 nm and several thousand frames/s are reported, respectively. Important progress is demonstrated in research and development on sensor technologies and algorithms for data processing and image reconstruction, including unconventional sensor design and adaptation of the sensors to the application in question. The number of applications to which tomographic methods are applied is steadily increasing, and results obtained in a representative selection of applications are included. As guest editors we would like express our appreciation and thanks to all authors who have contributed and to IOP staff for excellent collaboration in the process of finalizing this special feature.

Somatostatin receptor positron emission tomography/computed tomography (PET/CT) in the evaluation of opsoclonus-myoclonus ataxia syndrome.

PubMed

Joshi, Prathamesh; Lele, Vikram

2013-04-01

Opsoclonus-myoclonus ataxia (OMA) syndrome is the most common paraneoplastic neurological syndrome of childhood, associated with occult neuroblastoma in 20%-50% of all cases. OMA is the initial presentation of neuroblastoma in 1%-3% of children. Conventional radiological imaging approaches include chest radiography and abdominal computed tomography (CT). Nuclear medicine techniques, in form of (123)I/(131)I-metaiodobenzylguanidine (MIBG) scintigraphy have been incorporated in various diagnostic algorithms for evaluation of OMA. We describe use of somatostatin receptor PET/CT with (68)Gallium- DOTA-DPhe(1), Tyr(3)-octreotate (DOTATATE) in diagnosis of neuroblastoma in two cases of OMA.

Aberration correction for transcranial photoacoustic tomography of primates employing adjunct image data

NASA Astrophysics Data System (ADS)

Huang, Chao; Nie, Liming; Schoonover, Robert W.; Guo, Zijian; Schirra, Carsten O.; Anastasio, Mark A.; Wang, Lihong V.

2012-06-01

A challenge in photoacoustic tomography (PAT) brain imaging is to compensate for aberrations in the measured photoacoustic data due to their propagation through the skull. By use of information regarding the skull morphology and composition obtained from adjunct x-ray computed tomography image data, we developed a subject-specific imaging model that accounts for such aberrations. A time-reversal-based reconstruction algorithm was employed with this model for image reconstruction. The image reconstruction methodology was evaluated in experimental studies involving phantoms and monkey heads. The results establish that our reconstruction methodology can effectively compensate for skull-induced acoustic aberrations and improve image fidelity in transcranial PAT.

Applications of the JARS method to study levee sites in southern Texas and southern New Mexico

USGS Publications Warehouse

Ivanov, J.; Miller, R.D.; Xia, J.; Dunbar, J.B.

2007-01-01

We apply the joint analysis of refractions with surface waves (JARS) method to several sites and compare its results to traditional refraction-tomography methods in efforts of finding a more realistic solution to the inverse refraction-traveltime problem. The JARS method uses a reference model, derived from surface-wave shear-wave velocity estimates, as a constraint. In all of the cases JARS estimates appear more realistic than those from the conventional refraction-tomography methods. As a result, we consider, the JARS algorithm as the preferred method for finding solutions to the inverse refraction-tomography problems. ?? 2007 Society of Exploration Geophysicists.

Automated discrete electron tomography - Towards routine high-fidelity reconstruction of nanomaterials.

PubMed

Zhuge, Xiaodong; Jinnai, Hiroshi; Dunin-Borkowski, Rafal E; Migunov, Vadim; Bals, Sara; Cool, Pegie; Bons, Anton-Jan; Batenburg, Kees Joost

2017-04-01

Electron tomography is an essential imaging technique for the investigation of morphology and 3D structure of nanomaterials. This method, however, suffers from well-known missing wedge artifacts due to a restricted tilt range, which limits the objectiveness, repeatability and efficiency of quantitative structural analysis. Discrete tomography represents one of the promising reconstruction techniques for materials science, potentially capable of delivering higher fidelity reconstructions by exploiting the prior knowledge of the limited number of material compositions in a specimen. However, the application of discrete tomography to practical datasets remains a difficult task due to the underlying challenging mathematical problem. In practice, it is often hard to obtain consistent reconstructions from experimental datasets. In addition, numerous parameters need to be tuned manually, which can lead to bias and non-repeatability. In this paper, we present the application of a new iterative reconstruction technique, named TVR-DART, for discrete electron tomography. The technique is capable of consistently delivering reconstructions with significantly reduced missing wedge artifacts for a variety of challenging data and imaging conditions, and can automatically estimate its key parameters. We describe the principles of the technique and apply it to datasets from three different types of samples acquired under diverse imaging modes. By further reducing the available tilt range and number of projections, we show that the proposed technique can still produce consistent reconstructions with minimized missing wedge artifacts. This new development promises to provide the electron microscopy community with an easy-to-use and robust tool for high-fidelity 3D characterization of nanomaterials. Copyright © 2017 Elsevier B.V. All rights reserved.

Measuring, Understanding, and Responding to Covert Social Networks: Passive and Active Tomography

DTIC Science & Technology

2017-11-11

practical algorithms for sociologically principled detection of small sub- networks. To detect “foreground” networks, we need two competing models...understanding of how to model “background” network clutter, leading to principled approaches to “foreground” sub-network detection. Before the MURI...no frameworks existed for network detection theory or goodness-of-fit, nor were models and algorithms coupled to sound sociological principles

Riemann–Hilbert problem approach for two-dimensional flow inverse scattering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agaltsov, A. D., E-mail: agalets@gmail.com; Novikov, R. G., E-mail: novikov@cmap.polytechnique.fr; IEPT RAS, 117997 Moscow

2014-10-15

We consider inverse scattering for the time-harmonic wave equation with first-order perturbation in two dimensions. This problem arises in particular in the acoustic tomography of moving fluid. We consider linearized and nonlinearized reconstruction algorithms for this problem of inverse scattering. Our nonlinearized reconstruction algorithm is based on the non-local Riemann–Hilbert problem approach. Comparisons with preceding results are given.

Interferometric tomography of fuel cells for monitoring membrane water content.

PubMed

Waller, Laura; Kim, Jungik; Shao-Horn, Yang; Barbastathis, George

2009-08-17

We have developed a system that uses two 1D interferometric phase projections for reconstruction of 2D water content changes over time in situ in a proton exchange membrane (PEM) fuel cell system. By modifying the filtered backprojection tomographic algorithm, we are able to incorporate a priori information about the object distribution into a fast reconstruction algorithm which is suitable for real-time monitoring.

3D structure of eukaryotic flagella in a quiescent state revealed by cryo-electron tomography

PubMed Central

Nicastro, Daniela; McIntosh, J. Richard; Baumeister, Wolfgang

2005-01-01

We have used cryo-electron tomography to investigate the 3D structure and macromolecular organization of intact, frozen-hydrated sea urchin sperm flagella in a quiescent state. The tomographic reconstructions provide information at a resolution better than 6 nm about the in situ arrangements of macromolecules that are key for flagellar motility. We have visualized the heptameric rings of the motor domains in the outer dynein arm complex and determined that they lie parallel to the plane that contains the axes of neighboring flagellar microtubules. Both the material associated with the central pair of microtubules and the radial spokes display a plane of symmetry that helps to explain the planar beat pattern of these flagella. Cryo-electron tomography has proven to be a powerful technique for helping us understand the relationships between flagellar structure and function and the design of macromolecular machines in situ. PMID:16246999

Three-dimensional fine structure of the organization of microtubules in neurite varicosities by ultra-high voltage electron microscope tomography.

PubMed

Nishida, Tomoki; Yoshimura, Ryoichi; Endo, Yasuhisa

2017-09-01

Neurite varicosities are highly specialized compartments that are involved in neurotransmitter/ neuromodulator release and provide a physiological platform for neural functions. However, it remains unclear how microtubule organization contributes to the form of varicosity. Here, we examine the three-dimensional structure of microtubules in varicosities of a differentiated PC12 neural cell line using ultra-high voltage electron microscope tomography. Three-dimensional imaging showed that a part of the varicosities contained an accumulation of organelles that were separated from parallel microtubule arrays. Further detailed analysis using serial sections and whole-mount tomography revealed microtubules running in a spindle shape of swelling in some other types of varicosities. These electron tomographic results showed that the structural diversity and heterogeneity of microtubule organization supported the form of varicosities, suggesting that a different distribution pattern of microtubules in varicosities is crucial to the regulation of varicosities development.

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

PubMed

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2017-01-01

Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

Estimating crustal heterogeneity from double-difference tomography

USGS Publications Warehouse

Got, J.-L.; Monteiller, V.; Virieux, J.; Okubo, P.

2006-01-01

Seismic velocity parameters in limited, but heterogeneous volumes can be inferred using a double-difference tomographic algorithm, but to obtain meaningful results accuracy must be maintained at every step of the computation. MONTEILLER et al. (2005) have devised a double-difference tomographic algorithm that takes full advantage of the accuracy of cross-spectral time-delays of large correlated event sets. This algorithm performs an accurate computation of theoretical travel-time delays in heterogeneous media and applies a suitable inversion scheme based on optimization theory. When applied to Kilauea Volcano, in Hawaii, the double-difference tomography approach shows significant and coherent changes to the velocity model in the well-resolved volumes beneath the Kilauea caldera and the upper east rift. In this paper, we first compare the results obtained using MONTEILLER et al.'s algorithm with those obtained using the classic travel-time tomographic approach. Then, we evaluated the effect of using data series of different accuracies, such as handpicked arrival-time differences ("picking differences"), on the results produced by double-difference tomographic algorithms. We show that picking differences have a non-Gaussian probability density function (pdf). Using a hyperbolic secant pdf instead of a Gaussian pdf allows improvement of the double-difference tomographic result when using picking difference data. We completed our study by investigating the use of spatially discontinuous time-delay data. ?? Birkha??user Verlag, Basel, 2006.

Imaging metallic samples using electrical capacitance tomography: forward modelling and reconstruction algorithms

NASA Astrophysics Data System (ADS)

Hosani, E. Al; Zhang, M.; Abascal, J. F. P. J.; Soleimani, M.

2016-11-01

Electrical capacitance tomography (ECT) is an imaging technology used to reconstruct the permittivity distribution within the sensing region. So far, ECT has been primarily used to image non-conductive media only, since if the conductivity of the imaged object is high, the capacitance measuring circuit will be almost shortened by the conductivity path and a clear image cannot be produced using the standard image reconstruction approaches. This paper tackles the problem of imaging metallic samples using conventional ECT systems by investigating the two main aspects of image reconstruction algorithms, namely the forward problem and the inverse problem. For the forward problem, two different methods to model the region of high conductivity in ECT is presented. On the other hand, for the inverse problem, three different algorithms to reconstruct the high contrast images are examined. The first two methods are the linear single step Tikhonov method and the iterative total variation regularization method, and use two sets of ECT data to reconstruct the image in time difference mode. The third method, namely the level set method, uses absolute ECT measurements and was developed using a metallic forward model. The results indicate that the applications of conventional ECT systems can be extended to metal samples using the suggested algorithms and forward model, especially using a level set algorithm to find the boundary of the metal.

Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography.

PubMed

Kirişli, H A; Schaap, M; Metz, C T; Dharampal, A S; Meijboom, W B; Papadopoulou, S L; Dedic, A; Nieman, K; de Graaf, M A; Meijs, M F L; Cramer, M J; Broersen, A; Cetin, S; Eslami, A; Flórez-Valencia, L; Lor, K L; Matuszewski, B; Melki, I; Mohr, B; Oksüz, I; Shahzad, R; Wang, C; Kitslaar, P H; Unal, G; Katouzian, A; Örkisz, M; Chen, C M; Precioso, F; Najman, L; Masood, S; Ünay, D; van Vliet, L; Moreno, R; Goldenberg, R; Vuçini, E; Krestin, G P; Niessen, W J; van Walsum, T

2013-12-01

Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CTA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: (1) (semi-)automatically detect and quantify stenosis on CTA, in comparison with quantitative coronary angiography (QCA) and CTA consensus reading, and (2) (semi-)automatically segment the coronary lumen on CTA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CTA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that (1) some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that (2) automatic lumen segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through the website, at http://coronary.bigr.nl/stenoses/. Copyright © 2013 Elsevier B.V. All rights reserved.

Laser-Assisted Atom Probe Tomography of Deformed Minerals: A Zircon Case Study.

PubMed

La Fontaine, Alexandre; Piazolo, Sandra; Trimby, Patrick; Yang, Limei; Cairney, Julie M

2017-04-01

The application of atom probe tomography to the study of minerals is a rapidly growing area. Picosecond-pulsed, ultraviolet laser (UV-355 nm) assisted atom probe tomography has been used to analyze trace element mobility within dislocations and low-angle boundaries in plastically deformed specimens of the nonconductive mineral zircon (ZrSiO4), a key material to date the earth's geological events. Here we discuss important experimental aspects inherent in the atom probe tomography investigation of this important mineral, providing insights into the challenges in atom probe tomography characterization of minerals as a whole. We studied the influence of atom probe tomography analysis parameters on features of the mass spectra, such as the thermal tail, as well as the overall data quality. Three zircon samples with different uranium and lead content were analyzed, and particular attention was paid to ion identification in the mass spectra and detection limits of the key trace elements, lead and uranium. We also discuss the correlative use of electron backscattered diffraction in a scanning electron microscope to map the deformation in the zircon grains, and the combined use of transmission Kikuchi diffraction and focused ion beam sample preparation to assist preparation of the final atom probe tip.

Atom Probe Tomography Studies on the Cu(In,Ga)Se2 Grain Boundaries

PubMed Central

Cojocaru-Mirédin, Oana; Schwarz, Torsten; Choi, Pyuck-Pa; Herbig, Michael; Wuerz, Roland; Raabe, Dierk

2013-01-01

Compared with the existent techniques, atom probe tomography is a unique technique able to chemically characterize the internal interfaces at the nanoscale and in three dimensions. Indeed, APT possesses high sensitivity (in the order of ppm) and high spatial resolution (sub nm). Considerable efforts were done here to prepare an APT tip which contains the desired grain boundary with a known structure. Indeed, site-specific sample preparation using combined focused-ion-beam, electron backscatter diffraction, and transmission electron microscopy is presented in this work. This method allows selected grain boundaries with a known structure and location in Cu(In,Ga)Se2 thin-films to be studied by atom probe tomography. Finally, we discuss the advantages and drawbacks of using the atom probe tomography technique to study the grain boundaries in Cu(In,Ga)Se2 thin-film solar cells. PMID:23629452

FIB–SEM tomography of 4th generation PWA 1497 superalloy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ziętara, Maciej, E-mail: zietara@agh.edu.pl; Kruk, Adam, E-mail: kruczek@agh.edu.pl; Gruszczyński, Adam, E-mail: gruszcz@agh.edu.pl

2014-01-15

The effect of creep deformation on the microstructure of the PWA 1497 single crystal Ni-base superalloy developed for turbine blade applications was investigated. The aim of the present study was to characterize quantitatively a superalloy microstructure and subsequent development of rafted γ′ precipitates in the PWA 1497 during creep deformation at 982 °C and 248 MPa up to rupture. The PWA1497 microstructure was characterized by scanning electron microscopy and FIB–SEM electron tomography. The 3D reconstruction of the PWA1497 microstructure is presented and discussed. - Highlights: • The microstructure of PWA1497 superalloy was examined using FIB–SEM tomography. • In case ofmore » modern single crystal superalloys, measurements of A{sub A} are adequate for V{sub V}. • During creep the γ channel width increases from 65 to 193 nm for ruptured specimen. • Tomography is a useful technique for quantitative studies of material microstructure.« less

3D analysis of semiconductor devices: A combination of 3D imaging and 3D elemental analysis

NASA Astrophysics Data System (ADS)

Fu, Bianzhu; Gribelyuk, Michael A.

2018-04-01

3D analysis of semiconductor devices using a combination of scanning transmission electron microscopy (STEM) Z-contrast tomography and energy dispersive spectroscopy (EDS) elemental tomography is presented. 3D STEM Z-contrast tomography is useful in revealing the depth information of the sample. However, it suffers from contrast problems between materials with similar atomic numbers. Examples of EDS elemental tomography are presented using an automated EDS tomography system with batch data processing, which greatly reduces the data collection and processing time. 3D EDS elemental tomography reveals more in-depth information about the defect origin in semiconductor failure analysis. The influence of detector shadowing and X-rays absorption on the EDS tomography's result is also discussed.

Advanced three-dimensional electron microscopy techniques in the quest for better structural and functional materials

PubMed Central

Schryvers, D; Cao, S; Tirry, W; Idrissi, H; Van Aert, S

2013-01-01

After a short review of electron tomography techniques for materials science, this overview will cover some recent results on different shape memory and nanostructured metallic systems obtained by various three-dimensional (3D) electron imaging techniques. In binary Ni–Ti, the 3D morphology and distribution of Ni4Ti3 precipitates are investigated by using FIB/SEM slice-and-view yielding 3D data stacks. Different quantification techniques will be presented including the principal ellipsoid for a given precipitate, shape classification following a Zingg scheme, particle distribution function, distance transform and water penetration. The latter is a novel approach to quantifying the expected matrix transformation in between the precipitates. The different samples investigated include a single crystal annealed with and without compression yielding layered and autocatalytic precipitation, respectively, and a polycrystal revealing different densities and sizes of the precipitates resulting in a multistage transformation process. Electron tomography was used to understand the interaction between focused ion beam-induced Frank loops and long dislocation structures in nanobeams of Al exhibiting special mechanical behaviour measured by on-chip deposition. Atomic resolution electron tomography is demonstrated on Ag nanoparticles in an Al matrix. PMID:27877554

Depth-resolved analytical model and correction algorithm for photothermal optical coherence tomography

PubMed Central

Lapierre-Landry, Maryse; Tucker-Schwartz, Jason M.; Skala, Melissa C.

2016-01-01

Photothermal OCT (PT-OCT) is an emerging molecular imaging technique that occupies a spatial imaging regime between microscopy and whole body imaging. PT-OCT would benefit from a theoretical model to optimize imaging parameters and test image processing algorithms. We propose the first analytical PT-OCT model to replicate an experimental A-scan in homogeneous and layered samples. We also propose the PT-CLEAN algorithm to reduce phase-accumulation and shadowing, two artifacts found in PT-OCT images, and demonstrate it on phantoms and in vivo mouse tumors. PMID:27446693

Zernike phase contrast cryo-electron tomography of whole bacterial cells.

PubMed

Guerrero-Ferreira, Ricardo C; Wright, Elizabeth R

2014-01-01

Cryo-electron tomography (cryo-ET) provides three-dimensional (3D) structural information of bacteria preserved in a native, frozen-hydrated state. The typical low contrast of tilt-series images, a result of both the need for a low electron dose and the use of conventional defocus phase-contrast imaging, is a challenge for high-quality tomograms. We show that Zernike phase-contrast imaging allows the electron dose to be reduced. This limits movement of gold fiducials during the tilt series, which leads to better alignment and a higher-resolution reconstruction. Contrast is also enhanced, improving visibility of weak features. The reduced electron dose also means that more images at more tilt angles could be recorded, further increasing resolution. Copyright © 2013 Elsevier Inc. All rights reserved.

THE CELL CENTERED DATABASE PROJECT: AN UPDATE ON BUILDING COMMUNITY RESOURCES FOR MANAGING AND SHARING 3D IMAGING DATA

PubMed Central

Martone, Maryann E.; Tran, Joshua; Wong, Willy W.; Sargis, Joy; Fong, Lisa; Larson, Stephen; Lamont, Stephan P.; Gupta, Amarnath; Ellisman, Mark H.

2008-01-01

Databases have become integral parts of data management, dissemination and mining in biology. At the Second Annual Conference on Electron Tomography, held in Amsterdam in 2001, we proposed that electron tomography data should be shared in a manner analogous to structural data at the protein and sequence scales. At that time, we outlined our progress in creating a database to bring together cell level imaging data across scales, The Cell Centered Database (CCDB). The CCDB was formally launched in 2002 as an on-line repository of high-resolution 3D light and electron microscopic reconstructions of cells and subcellular structures. It contains 2D, 3D and 4D structural and protein distribution information from confocal, multiphoton and electron microscopy, including correlated light and electron microscopy. Many of the data sets are derived from electron tomography of cells and tissues. In the five years since its debut, we have moved the CCDB from a prototype to a stable resource and expanded the scope of the project to include data management and knowledge engineering. Here we provide an update on the CCDB and how it is used by the scientific community. We also describe our work in developing additional knowledge tools, e.g., ontologies, for annotation and query of electron microscopic data. PMID:18054501

Correlative cryo-fluorescence light microscopy and cryo-electron tomography of Streptomyces.

PubMed

Koning, Roman I; Celler, Katherine; Willemse, Joost; Bos, Erik; van Wezel, Gilles P; Koster, Abraham J

2014-01-01

Light microscopy and electron microscopy are complementary techniques that in a correlative approach enable identification and targeting of fluorescently labeled structures in situ for three-dimensional imaging at nanometer resolution. Correlative imaging allows electron microscopic images to be positioned in a broader temporal and spatial context. We employed cryo-correlative light and electron microscopy (cryo-CLEM), combining cryo-fluorescence light microscopy and cryo-electron tomography, on vitrified Streptomyces bacteria to study cell division. Streptomycetes are mycelial bacteria that grow as long hyphae and reproduce via sporulation. On solid media, Streptomyces subsequently form distinct aerial mycelia where cell division leads to the formation of unigenomic spores which separate and disperse to form new colonies. In liquid media, only vegetative hyphae are present divided by noncell separating crosswalls. Their multicellular life style makes them exciting model systems for the study of bacterial development and cell division. Complex intracellular structures have been visualized with transmission electron microscopy. Here, we describe the methods for cryo-CLEM that we applied for studying Streptomyces. These methods include cell growth, fluorescent labeling, cryo-fixation by vitrification, cryo-light microscopy using a Linkam cryo-stage, image overlay and relocation, cryo-electron tomography using a Titan Krios, and tomographic reconstruction. Additionally, methods for segmentation, volume rendering, and visualization of the correlative data are described. © 2014 Elsevier Inc. All rights reserved.

Algorithms for calculating mass-velocity and Darwin relativistic corrections with n-electron explicitly correlated Gaussians with shifted centers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanke, Monika, E-mail: monika@fizyka.umk.pl; Palikot, Ewa, E-mail: epalikot@doktorant.umk.pl; Adamowicz, Ludwik, E-mail: ludwik@email.arizona.edu

2016-05-07

Algorithms for calculating the leading mass-velocity (MV) and Darwin (D) relativistic corrections are derived for electronic wave functions expanded in terms of n-electron explicitly correlated Gaussian functions with shifted centers and without pre-exponential angular factors. The algorithms are implemented and tested in calculations of MV and D corrections for several points on the ground-state potential energy curves of the H{sub 2} and LiH molecules. The algorithms are general and can be applied in calculations of systems with an arbitrary number of electrons.

High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography

NASA Astrophysics Data System (ADS)

Kim, Kyoohyun; Yoon, HyeOk; Diez-Silva, Monica; Dao, Ming; Dasari, Ramachandra R.; Park, YongKeun

2014-01-01

We present high-resolution optical tomographic images of human red blood cells (RBC) parasitized by malaria-inducing Plasmodium falciparum (Pf)-RBCs. Three-dimensional (3-D) refractive index (RI) tomograms are reconstructed by recourse to a diffraction algorithm from multiple two-dimensional holograms with various angles of illumination. These 3-D RI tomograms of Pf-RBCs show cellular and subcellular structures of host RBCs and invaded parasites in fine detail. Full asexual intraerythrocytic stages of parasite maturation (ring to trophozoite to schizont stages) are then systematically investigated using optical diffraction tomography algorithms. These analyses provide quantitative information on the structural and chemical characteristics of individual host Pf-RBCs, parasitophorous vacuole, and cytoplasm. The in situ structural evolution and chemical characteristics of subcellular hemozoin crystals are also elucidated.

Automated boundary detection of the optic disc and layer segmentation of the peripapillary retina in volumetric structural and angiographic optical coherence tomography.

PubMed

Zang, Pengxiao; Gao, Simon S; Hwang, Thomas S; Flaxel, Christina J; Wilson, David J; Morrison, John C; Huang, David; Li, Dengwang; Jia, Yali

2017-03-01

To improve optic disc boundary detection and peripapillary retinal layer segmentation, we propose an automated approach for structural and angiographic optical coherence tomography. The algorithm was performed on radial cross-sectional B-scans. The disc boundary was detected by searching for the position of Bruch's membrane opening, and retinal layer boundaries were detected using a dynamic programming-based graph search algorithm on each B-scan without the disc region. A comparison of the disc boundary using our method with that determined by manual delineation showed good accuracy, with an average Dice similarity coefficient ≥0.90 in healthy eyes and eyes with diabetic retinopathy and glaucoma. The layer segmentation accuracy in the same cases was on average less than one pixel (3.13 μm).

Automated boundary detection of the optic disc and layer segmentation of the peripapillary retina in volumetric structural and angiographic optical coherence tomography

PubMed Central

Zang, Pengxiao; Gao, Simon S.; Hwang, Thomas S.; Flaxel, Christina J.; Wilson, David J.; Morrison, John C.; Huang, David; Li, Dengwang; Jia, Yali

2017-01-01

To improve optic disc boundary detection and peripapillary retinal layer segmentation, we propose an automated approach for structural and angiographic optical coherence tomography. The algorithm was performed on radial cross-sectional B-scans. The disc boundary was detected by searching for the position of Bruch’s membrane opening, and retinal layer boundaries were detected using a dynamic programming-based graph search algorithm on each B-scan without the disc region. A comparison of the disc boundary using our method with that determined by manual delineation showed good accuracy, with an average Dice similarity coefficient ≥0.90 in healthy eyes and eyes with diabetic retinopathy and glaucoma. The layer segmentation accuracy in the same cases was on average less than one pixel (3.13 μm). PMID:28663830

An algebraic iterative reconstruction technique for differential X-ray phase-contrast computed tomography.

PubMed

Fu, Jian; Schleede, Simone; Tan, Renbo; Chen, Liyuan; Bech, Martin; Achterhold, Klaus; Gifford, Martin; Loewen, Rod; Ruth, Ronald; Pfeiffer, Franz

2013-09-01

Iterative reconstruction has a wide spectrum of proven advantages in the field of conventional X-ray absorption-based computed tomography (CT). In this paper, we report on an algebraic iterative reconstruction technique for grating-based differential phase-contrast CT (DPC-CT). Due to the differential nature of DPC-CT projections, a differential operator and a smoothing operator are added to the iterative reconstruction, compared to the one commonly used for absorption-based CT data. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured at a two-grating interferometer setup. Since the algorithm is easy to implement and allows for the extension to various regularization possibilities, we expect a significant impact of the method for improving future medical and industrial DPC-CT applications. Copyright © 2012. Published by Elsevier GmbH.

High-resolution three-dimensional imaging of red blood cells parasitized by Plasmodium falciparum and in situ hemozoin crystals using optical diffraction tomography

PubMed Central

Kim, Kyoohyun; Yoon, HyeOk; Diez-Silva, Monica; Dao, Ming; Dasari, Ramachandra R.

2013-01-01

Abstract. We present high-resolution optical tomographic images of human red blood cells (RBC) parasitized by malaria-inducing Plasmodium falciparum (Pf)-RBCs. Three-dimensional (3-D) refractive index (RI) tomograms are reconstructed by recourse to a diffraction algorithm from multiple two-dimensional holograms with various angles of illumination. These 3-D RI tomograms of Pf-RBCs show cellular and subcellular structures of host RBCs and invaded parasites in fine detail. Full asexual intraerythrocytic stages of parasite maturation (ring to trophozoite to schizont stages) are then systematically investigated using optical diffraction tomography algorithms. These analyses provide quantitative information on the structural and chemical characteristics of individual host Pf-RBCs, parasitophorous vacuole, and cytoplasm. The in situ structural evolution and chemical characteristics of subcellular hemozoin crystals are also elucidated. PMID:23797986

Optical-fiber-based Mueller optical coherence tomography.

PubMed

Jiao, Shuliang; Yu, Wurong; Stoica, George; Wang, Lihong V

2003-07-15

An optical-fiber-based multichannel polarization-sensitive Mueller optical coherence tomography (OCT) system was built to acquire the Jones or Mueller matrix of a scattering medium, such as biological tissue. For the first time to our knowledge, fiber-based polarization-sensitive OCT was dynamically calibrated to eliminate the polarization distortion caused by the single-mode optical fiber in the sample arm, thereby overcoming a key technical impediment to the application of optical fibers in this technology. The round-trip Jones matrix of the sampling fiber was acquired from the reflecting surface of the sample for each depth scan (A scan) with our OCT system. A new rigorous algorithm was then used to retrieve the calibrated polarization properties of the sample. This algorithm was validated with experimental data. The skin of a rat was imaged with this fiber-based system.

Automatic segmentation of the choroid in enhanced depth imaging optical coherence tomography images.

PubMed

Tian, Jing; Marziliano, Pina; Baskaran, Mani; Tun, Tin Aung; Aung, Tin

2013-03-01

Enhanced Depth Imaging (EDI) optical coherence tomography (OCT) provides high-definition cross-sectional images of the choroid in vivo, and hence is used in many clinical studies. However, the quantification of the choroid depends on the manual labelings of two boundaries, Bruch's membrane and the choroidal-scleral interface. This labeling process is tedious and subjective of inter-observer differences, hence, automatic segmentation of the choroid layer is highly desirable. In this paper, we present a fast and accurate algorithm that could segment the choroid automatically. Bruch's membrane is detected by searching the pixel with the biggest gradient value above the retinal pigment epithelium (RPE) and the choroidal-scleral interface is delineated by finding the shortest path of the graph formed by valley pixels using Dijkstra's algorithm. The experiments comparing automatic segmentation results with the manual labelings are conducted on 45 EDI-OCT images and the average of Dice's Coefficient is 90.5%, which shows good consistency of the algorithm with the manual labelings. The processing time for each image is about 1.25 seconds.

Estimation of anomaly location and size using electrical impedance tomography.

PubMed

Kwon, Ohin; Yoon, Jeong Rock; Seo, Jin Keun; Woo, Eung Je; Cho, Young Gu

2003-01-01

We developed a new algorithm that estimates locations and sizes of anomalies in electrically conducting medium based on electrical impedance tomography (EIT) technique. When only the boundary current and voltage measurements are available, it is not practically feasible to reconstruct accurate high-resolution cross-sectional conductivity or resistivity images of a subject. In this paper, we focus our attention on the estimation of locations and sizes of anomalies with different conductivity values compared with the background tissues. We showed the performance of the algorithm from experimental results using a 32-channel EIT system and saline phantom. With about 1.73% measurement error in boundary current-voltage data, we found that the minimal size (area) of the detectable anomaly is about 0.72% of the size (area) of the phantom. Potential applications include the monitoring of impedance related physiological events and bubble detection in two-phase flow. Since this new algorithm requires neither any forward solver nor time-consuming minimization process, it is fast enough for various real-time applications in medicine and nondestructive testing.

Three-dimensional electrical impedance tomography: a topology optimization approach.

PubMed

Mello, Luís Augusto Motta; de Lima, Cícero Ribeiro; Amato, Marcelo Britto Passos; Lima, Raul Gonzalez; Silva, Emílio Carlos Nelli

2008-02-01

Electrical impedance tomography is a technique to estimate the impedance distribution within a domain, based on measurements on its boundary. In other words, given the mathematical model of the domain, its geometry and boundary conditions, a nonlinear inverse problem of estimating the electric impedance distribution can be solved. Several impedance estimation algorithms have been proposed to solve this problem. In this paper, we present a three-dimensional algorithm, based on the topology optimization method, as an alternative. A sequence of linear programming problems, allowing for constraints, is solved utilizing this method. In each iteration, the finite element method provides the electric potential field within the model of the domain. An electrode model is also proposed (thus, increasing the accuracy of the finite element results). The algorithm is tested using numerically simulated data and also experimental data, and absolute resistivity values are obtained. These results, corresponding to phantoms with two different conductive materials, exhibit relatively well-defined boundaries between them, and show that this is a practical and potentially useful technique to be applied to monitor lung aeration, including the possibility of imaging a pneumothorax.

Application of Novel Software Algorithms to Spectral-Domain Optical Coherence Tomography for Automated Detection of Diabetic Retinopathy.

PubMed

Adhi, Mehreen; Semy, Salim K; Stein, David W; Potter, Daniel M; Kuklinski, Walter S; Sleeper, Harry A; Duker, Jay S; Waheed, Nadia K

2016-05-01

To present novel software algorithms applied to spectral-domain optical coherence tomography (SD-OCT) for automated detection of diabetic retinopathy (DR). Thirty-one diabetic patients (44 eyes) and 18 healthy, nondiabetic controls (20 eyes) who underwent volumetric SD-OCT imaging and fundus photography were retrospectively identified. A retina specialist independently graded DR stage. Trained automated software generated a retinal thickness score signifying macular edema and a cluster score signifying microaneurysms and/or hard exudates for each volumetric SD-OCT. Of 44 diabetic eyes, 38 had DR and six eyes did not have DR. Leave-one-out cross-validation using a linear discriminant at missed detection/false alarm ratio of 3.00 computed software sensitivity and specificity of 92% and 69%, respectively, for DR detection when compared to clinical assessment. Novel software algorithms applied to commercially available SD-OCT can successfully detect DR and may have potential as a viable screening tool for DR in future. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:410-417.]. Copyright 2016, SLACK Incorporated.

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images.

PubMed

Lingley-Papadopoulos, Colleen A; Loew, Murray H; Zara, Jason M

2009-01-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Improvement of resolution in full-view linear-array photoacoustic computed tomography using a novel adaptive weighting method

NASA Astrophysics Data System (ADS)

Omidi, Parsa; Diop, Mamadou; Carson, Jeffrey; Nasiriavanaki, Mohammadreza

2017-03-01

Linear-array-based photoacoustic computed tomography is a popular methodology for deep and high resolution imaging. However, issues such as phase aberration, side-lobe effects, and propagation limitations deteriorate the resolution. The effect of phase aberration due to acoustic attenuation and constant assumption of the speed of sound (SoS) can be reduced by applying an adaptive weighting method such as the coherence factor (CF). Utilizing an adaptive beamforming algorithm such as the minimum variance (MV) can improve the resolution at the focal point by eliminating the side-lobes. Moreover, invisibility of directional objects emitting parallel to the detection plane, such as vessels and other absorbing structures stretched in the direction perpendicular to the detection plane can degrade resolution. In this study, we propose a full-view array level weighting algorithm in which different weighs are assigned to different positions of the linear array based on an orientation algorithm which uses the histogram of oriented gradient (HOG). Simulation results obtained from a synthetic phantom show the superior performance of the proposed method over the existing reconstruction methods.

An interior-point method for total variation regularized positron emission tomography image reconstruction

NASA Astrophysics Data System (ADS)

Bai, Bing

2012-03-01

There has been a lot of work on total variation (TV) regularized tomographic image reconstruction recently. Many of them use gradient-based optimization algorithms with a differentiable approximation of the TV functional. In this paper we apply TV regularization in Positron Emission Tomography (PET) image reconstruction. We reconstruct the PET image in a Bayesian framework, using Poisson noise model and TV prior functional. The original optimization problem is transformed to an equivalent problem with inequality constraints by adding auxiliary variables. Then we use an interior point method with logarithmic barrier functions to solve the constrained optimization problem. In this method, a series of points approaching the solution from inside the feasible region are found by solving a sequence of subproblems characterized by an increasing positive parameter. We use preconditioned conjugate gradient (PCG) algorithm to solve the subproblems directly. The nonnegativity constraint is enforced by bend line search. The exact expression of the TV functional is used in our calculations. Simulation results show that the algorithm converges fast and the convergence is insensitive to the values of the regularization and reconstruction parameters.

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography

PubMed Central

Sidky, Emil Y.; Kraemer, David N.; Roth, Erin G.; Ullberg, Christer; Reiser, Ingrid S.; Pan, Xiaochuan

2014-01-01

Abstract. One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data. PMID:25685824

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography.

PubMed

Sidky, Emil Y; Kraemer, David N; Roth, Erin G; Ullberg, Christer; Reiser, Ingrid S; Pan, Xiaochuan

2014-10-03

One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data.

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images

NASA Astrophysics Data System (ADS)

Lingley-Papadopoulos, Colleen A.; Loew, Murray H.; Zara, Jason M.

2009-07-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Automatic Segmentation and Quantification of Filamentous Structures in Electron Tomography

PubMed Central

Loss, Leandro A.; Bebis, George; Chang, Hang; Auer, Manfred; Sarkar, Purbasha; Parvin, Bahram

2016-01-01

Electron tomography is a promising technology for imaging ultrastructures at nanoscale resolutions. However, image and quantitative analyses are often hindered by high levels of noise, staining heterogeneity, and material damage either as a result of the electron beam or sample preparation. We have developed and built a framework that allows for automatic segmentation and quantification of filamentous objects in 3D electron tomography. Our approach consists of three steps: (i) local enhancement of filaments by Hessian filtering; (ii) detection and completion (e.g., gap filling) of filamentous structures through tensor voting; and (iii) delineation of the filamentous networks. Our approach allows for quantification of filamentous networks in terms of their compositional and morphological features. We first validate our approach using a set of specifically designed synthetic data. We then apply our segmentation framework to tomograms of plant cell walls that have undergone different chemical treatments for polysaccharide extraction. The subsequent compositional and morphological analyses of the plant cell walls reveal their organizational characteristics and the effects of the different chemical protocols on specific polysaccharides. PMID:28090597

Automatic Segmentation and Quantification of Filamentous Structures in Electron Tomography.

PubMed

Loss, Leandro A; Bebis, George; Chang, Hang; Auer, Manfred; Sarkar, Purbasha; Parvin, Bahram

2012-10-01

Electron tomography is a promising technology for imaging ultrastructures at nanoscale resolutions. However, image and quantitative analyses are often hindered by high levels of noise, staining heterogeneity, and material damage either as a result of the electron beam or sample preparation. We have developed and built a framework that allows for automatic segmentation and quantification of filamentous objects in 3D electron tomography. Our approach consists of three steps: (i) local enhancement of filaments by Hessian filtering; (ii) detection and completion (e.g., gap filling) of filamentous structures through tensor voting; and (iii) delineation of the filamentous networks. Our approach allows for quantification of filamentous networks in terms of their compositional and morphological features. We first validate our approach using a set of specifically designed synthetic data. We then apply our segmentation framework to tomograms of plant cell walls that have undergone different chemical treatments for polysaccharide extraction. The subsequent compositional and morphological analyses of the plant cell walls reveal their organizational characteristics and the effects of the different chemical protocols on specific polysaccharides.

Preparation of cryofixed cells for improved 3D ultrastructure with scanning transmission electron tomography.

PubMed

Höhn, Katharina; Sailer, Michaela; Wang, Li; Lorenz, Myriam; Schneider, Marion E; Walther, Paul

2011-01-01

Scanning transmission electron tomography offers enhanced contrast compared to regular transmission electron microscopy, and thicker samples, up to 1 μm or more, can be analyzed, since the depth of focus and inelastic scattering are not limitations. In this study, we combine this novel imaging approach with state of the art specimen preparation by using novel light transparent sapphire specimen carrier for high-pressure freezing and a freeze substitution protocol for better contrast of membranes. This combination allows for imaging membranes and other subcellular structures with unsurpassed quality. This is demonstrated with mitochondria, where the inner and outer mitochondrial membranes as well as the membranes in the cristae appear in very close apposition with a minimal intermembrane space. These findings correspond well with old observations using freeze fracturing. In 880-nm thick sections of hemophagocytes, the three-dimensional structure of membrane sheets could be observed in the virtual sections of the tomogram. Microtubules, actin and intermediate filaments could be visualized within one sample. Intermediate filaments, however, could even be better observed in 3D using surface scanning electron tomography.

Structure resolution by electron diffraction tomography of the complex layered iron-rich Fe-2234-type Sr{sub 5}Fe{sub 6}O{sub 15.4}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lepoittevin, Christophe, E-mail: christophe.lepoittevin@neel.cnrs.fr

2016-10-15

The crystal structure of the strontium ferrite Sr{sub 5}Fe{sub 6}O{sub 15.4}, was solved by direct methods on electron diffraction tomography data acquired on a transmission electron microscope. The refined cell parameters are a=27.4047(3) Å, b=5.48590(7) Å and c=42.7442(4) Å in Fm2m symmetry. Its structure is built up from the intergrowth sequence between a quadruple perovskite-type layer with a complex rock-salt (RS)-type block. In the latter iron atoms are found in two different environments : tetragonal pyramid and tetrahedron. The structural model was refined by Rietveld method based on the powder X-ray diffraction pattern. - Highlights: • Complex structure of Sr{submore » 5}Fe{sub 6}O{sub 15.4} solved by electron diffraction tomography. • Observed Fourier maps allow determining missing oxygen atoms in the structure. • Structural model refined from powder X-ray diffraction data. • Intergrowth between quadruple perovskite layer with double rock-salt-type layer.« less

Physically motivated global alignment method for electron tomography

DOE PAGES

Sanders, Toby; Prange, Micah; Akatay, Cem; ...

2015-04-08

Electron tomography is widely used for nanoscale determination of 3-D structures in many areas of science. Determining the 3-D structure of a sample from electron tomography involves three major steps: acquisition of sequence of 2-D projection images of the sample with the electron microscope, alignment of the images to a common coordinate system, and 3-D reconstruction and segmentation of the sample from the aligned image data. The resolution of the 3-D reconstruction is directly influenced by the accuracy of the alignment, and therefore, it is crucial to have a robust and dependable alignment method. In this paper, we develop amore » new alignment method which avoids the use of markers and instead traces the computed paths of many identifiable ‘local’ center-of-mass points as the sample is rotated. Compared with traditional correlation schemes, the alignment method presented here is resistant to cumulative error observed from correlation techniques, has very rigorous mathematical justification, and is very robust since many points and paths are used, all of which inevitably improves the quality of the reconstruction and confidence in the scientific results.« less

Obtaining 3D Chemical Maps by Energy Filtered Transmission Electron Microscopy Tomography.

PubMed

Roiban, Lucian; Sorbier, Loïc; Hirlimann, Charles; Ersen, Ovidiu

2018-06-09

Energy filtered transmission electron microscopy tomography (EFTEM tomography) can provide three-dimensional (3D) chemical maps of materials at a nanometric scale. EFTEM tomography can separate chemical elements that are very difficult to distinguish using other imaging techniques. The experimental protocol described here shows how to create 3D chemical maps to understand the chemical distribution and morphology of a material. Sample preparation steps for data segmentation are presented. This protocol permits the 3D distribution analysis of chemical elements in a nanometric sample. However, it should be noted that currently, the 3D chemical maps can only be generated for samples that are not beam sensitive, since the recording of filtered images requires long exposure times to an intense electron beam. The protocol was applied to quantify the chemical distribution of the components of two different heterogeneous catalyst supports. In the first study, the chemical distribution of aluminum and titanium in titania-alumina supports was analyzed. The samples were prepared using the swing-pH method. In the second, the chemical distribution of aluminum and silicon in silica-alumina supports that were prepared using the sol-powder and mechanical mixture methods was examined.

Algebraic reconstruction for 3D magnetic resonance-electrical impedance tomography (MREIT) using one component of magnetic flux density.

PubMed

Ider, Y Ziya; Onart, Serkan

2004-02-01

Magnetic resonance-electrical impedance tomography (MREIT) algorithms fall into two categories: those utilizing internal current density and those utilizing only one component of measured magnetic flux density. The latter group of algorithms have the advantage that the object does not have to be rotated in the magnetic resonance imaging (MRI) system. A new algorithm which uses only one component of measured magnetic flux density is developed. In this method, the imaging problem is formulated as the solution of a non-linear matrix equation which is solved iteratively to reconstruct resistivity. Numerical simulations are performed to test the algorithm both for noise-free and noisy cases. The uniqueness of the solution is monitored by looking at the singular value behavior of the matrix and it is shown that at least two current injection profiles are necessary. The method is also modified to handle region-of-interest reconstructions. In particular it is shown that, if the image of a certain xy-slice is sought for, then it suffices to measure the z-component of magnetic flux density up to a distance above and below that slice. The method is robust and has good convergence behavior for the simulation phantoms used.

Automatic Solitary Lung Nodule Detection in Computed Tomography Images Slices

NASA Astrophysics Data System (ADS)

Sentana, I. W. B.; Jawas, N.; Asri, S. A.

2018-01-01

Lung nodule is an early indicator of some lung diseases, including lung cancer. In Computed Tomography (CT) based image, nodule is known as a shape that appears brighter than lung surrounding. This research aim to develop an application that automatically detect lung nodule in CT images. There are some steps in algorithm such as image acquisition and conversion, image binarization, lung segmentation, blob detection, and classification. Data acquisition is a step to taking image slice by slice from the original *.dicom format and then each image slices is converted into *.tif image format. Binarization that tailoring Otsu algorithm, than separated the background and foreground part of each image slices. After removing the background part, the next step is to segment part of the lung only so the nodule can localized easier. Once again Otsu algorithm is use to detect nodule blob in localized lung area. The final step is tailoring Support Vector Machine (SVM) to classify the nodule. The application has succeed detecting near round nodule with a certain threshold of size. Those detecting result shows drawback in part of thresholding size and shape of nodule that need to enhance in the next part of the research. The algorithm also cannot detect nodule that attached to wall and Lung Chanel, since it depend the searching only on colour differences.

Penalized weighted least-squares approach for multienergy computed tomography image reconstruction via structure tensor total variation regularization.

PubMed

Zeng, Dong; Gao, Yuanyuan; Huang, Jing; Bian, Zhaoying; Zhang, Hua; Lu, Lijun; Ma, Jianhua

2016-10-01

Multienergy computed tomography (MECT) allows identifying and differentiating different materials through simultaneous capture of multiple sets of energy-selective data belonging to specific energy windows. However, because sufficient photon counts are not available in each energy window compared with that in the whole energy window, the MECT images reconstructed by the analytical approach often suffer from poor signal-to-noise and strong streak artifacts. To address the particular challenge, this work presents a penalized weighted least-squares (PWLS) scheme by incorporating the new concept of structure tensor total variation (STV) regularization, which is henceforth referred to as 'PWLS-STV' for simplicity. Specifically, the STV regularization is derived by penalizing higher-order derivatives of the desired MECT images. Thus it could provide more robust measures of image variation, which can eliminate the patchy artifacts often observed in total variation (TV) regularization. Subsequently, an alternating optimization algorithm was adopted to minimize the objective function. Extensive experiments with a digital XCAT phantom and meat specimen clearly demonstrate that the present PWLS-STV algorithm can achieve more gains than the existing TV-based algorithms and the conventional filtered backpeojection (FBP) algorithm in terms of both quantitative and visual quality evaluations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fast kinematic ray tracing of first- and later-arriving global seismic phases

NASA Astrophysics Data System (ADS)

Bijwaard, Harmen; Spakman, Wim

1999-11-01

We have developed a ray tracing algorithm that traces first- and later-arriving global seismic phases precisely (traveltime errors of the order of 0.1 s), and with great computational efficiency (15 rays s- 1). To achieve this, we have extended and adapted two existing ray tracing techniques: a graph method and a perturbation method. The two resulting algorithms are able to trace (critically) refracted, (multiply) reflected, some diffracted (Pdiff), and (multiply) converted seismic phases in a 3-D spherical geometry, thus including the largest part of seismic phases that are commonly observed on seismograms. We have tested and compared the two methods in 2-D and 3-D Cartesian and spherical models, for which both algorithms have yielded precise paths and traveltimes. These tests indicate that only the perturbation method is computationally efficient enough to perform 3-D ray tracing on global data sets of several million phases. To demonstrate its potential for non-linear tomography, we have applied the ray perturbation algorithm to a data set of 7.6 million P and pP phases used by Bijwaard et al. (1998) for linearized tomography. This showed that the expected heterogeneity within the Earth's mantle leads to significant non-linear effects on traveltimes for 10 per cent of the applied phases.

Incomplete projection reconstruction of computed tomography based on the modified discrete algebraic reconstruction technique

NASA Astrophysics Data System (ADS)

Yang, Fuqiang; Zhang, Dinghua; Huang, Kuidong; Gao, Zongzhao; Yang, YaFei

2018-02-01

Based on the discrete algebraic reconstruction technique (DART), this study aims to address and test a new improved algorithm applied to incomplete projection data to generate a high quality reconstruction image by reducing the artifacts and noise in computed tomography. For the incomplete projections, an augmented Lagrangian based on compressed sensing is first used in the initial reconstruction for segmentation of the DART to get higher contrast graphics for boundary and non-boundary pixels. Then, the block matching 3D filtering operator was used to suppress the noise and to improve the gray distribution of the reconstructed image. Finally, simulation studies on the polychromatic spectrum were performed to test the performance of the new algorithm. Study results show a significant improvement in the signal-to-noise ratios (SNRs) and average gradients (AGs) of the images reconstructed from incomplete data. The SNRs and AGs of the new images reconstructed by DART-ALBM were on average 30%-40% and 10% higher than the images reconstructed by DART algorithms. Since the improved DART-ALBM algorithm has a better robustness to limited-view reconstruction, which not only makes the edge of the image clear but also makes the gray distribution of non-boundary pixels better, it has the potential to improve image quality from incomplete projections or sparse projections.

Iterative image reconstruction for multienergy computed tomography via structure tensor total variation regularization

NASA Astrophysics Data System (ADS)

Zeng, Dong; Bian, Zhaoying; Gong, Changfei; Huang, Jing; He, Ji; Zhang, Hua; Lu, Lijun; Feng, Qianjin; Liang, Zhengrong; Ma, Jianhua

2016-03-01

Multienergy computed tomography (MECT) has the potential to simultaneously offer multiple sets of energy- selective data belonging to specific energy windows. However, because sufficient photon counts are not available in the specific energy windows compared with that in the whole energy window, the MECT images reconstructed by the analytical approach often suffer from poor signal-to-noise (SNR) and strong streak artifacts. To eliminate this drawback, in this work we present a penalized weighted least-squares (PWLS) scheme by incorporating the new concept of structure tensor total variation (STV) regularization to improve the MECT images quality from low-milliampere-seconds (low-mAs) data acquisitions. Henceforth the present scheme is referred to as `PWLS- STV' for simplicity. Specifically, the STV regularization is derived by penalizing the eigenvalues of the structure tensor of every point in the MECT images. Thus it can provide more robust measures of image variation, which can eliminate the patchy artifacts often observed in total variation regularization. Subsequently, an alternating optimization algorithm was adopted to minimize the objective function. Experiments with a digital XCAT phantom clearly demonstrate that the present PWLS-STV algorithm can achieve more gains than the existing TV-based algorithms and the conventional filtered backpeojection (FBP) algorithm in terms of noise-induced artifacts suppression, resolution preservation, and material decomposition assessment.

Automated pharmaceutical tablet coating layer evaluation of optical coherence tomography images

NASA Astrophysics Data System (ADS)

Markl, Daniel; Hannesschläger, Günther; Sacher, Stephan; Leitner, Michael; Khinast, Johannes G.; Buchsbaum, Andreas

2015-03-01

Film coating of pharmaceutical tablets is often applied to influence the drug release behaviour. The coating characteristics such as thickness and uniformity are critical quality parameters, which need to be precisely controlled. Optical coherence tomography (OCT) shows not only high potential for off-line quality control of film-coated tablets but also for in-line monitoring of coating processes. However, an in-line quality control tool must be able to determine coating thickness measurements automatically and in real-time. This study proposes an automatic thickness evaluation algorithm for bi-convex tables, which provides about 1000 thickness measurements within 1 s. Beside the segmentation of the coating layer, optical distortions due to refraction of the beam by the air/coating interface are corrected. Moreover, during in-line monitoring the tablets might be in oblique orientation, which needs to be considered in the algorithm design. Experiments were conducted where the tablet was rotated to specified angles. Manual and automatic thickness measurements were compared for varying coating thicknesses, angles of rotations, and beam displacements (i.e. lateral displacement between successive depth scans). The automatic thickness determination algorithm provides highly accurate results up to an angle of rotation of 30°. The computation time was reduced to 0.53 s for 700 thickness measurements by introducing feasibility constraints in the algorithm.

Are We Ready for Positron Emission Tomography/Computed Tomography-based Target Volume Definition in Lymphoma Radiation Therapy?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yeoh, Kheng-Wei; Mikhaeel, N. George, E-mail: George.Mikhaeel@gstt.nhs.uk

2013-01-01

Fluorine-18 fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) has become indispensable for the clinical management of lymphomas. With consistent evidence that it is more accurate than anatomic imaging in the staging and response assessment of many lymphoma subtypes, its utility continues to increase. There have therefore been efforts to incorporate PET/CT data into radiation therapy decision making and in the planning process. Further, there have also been studies investigating target volume definition for radiation therapy using PET/CT data. This article will critically review the literature and ongoing studies on the above topics, examining the value and methods of adding PET/CTmore » data to the radiation therapy treatment algorithm. We will also discuss the various challenges and the areas where more evidence is required.« less

X-ray analysis of electron Bernstein wave heating in MST

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seltzman, A. H., E-mail: seltzman@wisc.edu; Anderson, J. K.; DuBois, A. M.

2016-11-15

A pulse height analyzing x-ray tomography system has been developed to detect x-rays from electron Bernstein wave heated electrons in the Madison symmetric torus reversed field pinch (RFP). Cadmium zinc telluride detectors are arranged in a parallel beam array with two orthogonal multi-chord detectors that may be used for tomography. In addition a repositionable 16 channel fan beam camera with a 55° field of view is used to augment data collected with the Hard X-ray array. The chord integrated signals identify target emission from RF heated electrons striking a limiter located 12° toroidally away from the RF injection port. Thismore » provides information on heated electron spectrum, transport, and diffusion. RF induced x-ray emission from absorption on harmonic electron cyclotron resonances in low current (<250 kA) RFP discharges has been observed.« less

Large volume serial section tomography by Xe Plasma FIB dual beam microscopy.

PubMed

Burnett, T L; Kelley, R; Winiarski, B; Contreras, L; Daly, M; Gholinia, A; Burke, M G; Withers, P J

2016-02-01

Ga(+) Focused Ion Beam-Scanning Electron Microscopes (FIB-SEM) have revolutionised the level of microstructural information that can be recovered in 3D by block face serial section tomography (SST), as well as enabling the site-specific removal of smaller regions for subsequent transmission electron microscope (TEM) examination. However, Ga(+) FIB material removal rates limit the volumes and depths that can be probed to dimensions in the tens of microns range. Emerging Xe(+) Plasma Focused Ion Beam-Scanning Electron Microscope (PFIB-SEM) systems promise faster removal rates. Here we examine the potential of the method for large volume serial section tomography as applied to bainitic steel and WC-Co hard metals. Our studies demonstrate that with careful control of milling parameters precise automated serial sectioning can be achieved with low levels of milling artefacts at removal rates some 60× faster. Volumes that are hundreds of microns in dimension have been collected using fully automated SST routines in feasible timescales (<24h) showing good grain orientation contrast and capturing microstructural features at the tens of nanometres to the tens of microns scale. Accompanying electron back scattered diffraction (EBSD) maps show high indexing rates suggesting low levels of surface damage. Further, under high current Ga(+) FIB milling WC-Co is prone to amorphisation of WC surface layers and phase transformation of the Co phase, neither of which have been observed at PFIB currents as high as 60nA at 30kV. Xe(+) PFIB dual beam microscopes promise to radically extend our capability for 3D tomography, 3D EDX, 3D EBSD as well as correlative tomography. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

LBP-based penalized weighted least-squares approach to low-dose cone-beam computed tomography reconstruction

NASA Astrophysics Data System (ADS)

Ma, Ming; Wang, Huafeng; Liu, Yan; Zhang, Hao; Gu, Xianfeng; Liang, Zhengrong

2014-03-01

Cone-beam computed tomography (CBCT) has attracted growing interest of researchers in image reconstruction. The mAs level of the X-ray tube current, in practical application of CBCT, is mitigated in order to reduce the CBCT dose. The lowering of the X-ray tube current, however, results in the degradation of image quality. Thus, low-dose CBCT image reconstruction is in effect a noise problem. To acquire clinically acceptable quality of image, and keep the X-ray tube current as low as achievable in the meanwhile, some penalized weighted least-squares (PWLS)-based image reconstruction algorithms have been developed. One representative strategy in previous work is to model the prior information for solution regularization using an anisotropic penalty term. To enhance the edge preserving and noise suppressing in a finer scale, a novel algorithm combining the local binary pattern (LBP) with penalized weighted leastsquares (PWLS), called LBP-PWLS-based image reconstruction algorithm, is proposed in this work. The proposed LBP-PWLS-based algorithm adaptively encourages strong diffusion on the local spot/flat region around a voxel and less diffusion on edge/corner ones by adjusting the penalty for cost function, after the LBP is utilized to detect the region around the voxel as spot, flat and edge ones. The LBP-PWLS-based reconstruction algorithm was evaluated using the sinogram data acquired by a clinical CT scanner from the CatPhan® 600 phantom. Experimental results on the noiseresolution tradeoff measurement and other quantitative measurements demonstrated its feasibility and effectiveness in edge preserving and noise suppressing in comparison with a previous PWLS reconstruction algorithm.

Automatic elastic image registration by interpolation of 3D rotations and translations from discrete rigid-body transformations.

PubMed

Walimbe, Vivek; Shekhar, Raj

2006-12-01

We present an algorithm for automatic elastic registration of three-dimensional (3D) medical images. Our algorithm initially recovers the global spatial mismatch between the reference and floating images, followed by hierarchical octree-based subdivision of the reference image and independent registration of the floating image with the individual subvolumes of the reference image at each hierarchical level. Global as well as local registrations use the six-parameter full rigid-body transformation model and are based on maximization of normalized mutual information (NMI). To ensure robustness of the subvolume registration with low voxel counts, we calculate NMI using a combination of current and prior mutual histograms. To generate a smooth deformation field, we perform direct interpolation of six-parameter rigid-body subvolume transformations obtained at the last subdivision level. Our interpolation scheme involves scalar interpolation of the 3D translations and quaternion interpolation of the 3D rotational pose. We analyzed the performance of our algorithm through experiments involving registration of synthetically deformed computed tomography (CT) images. Our algorithm is general and can be applied to image pairs of any two modalities of most organs. We have demonstrated successful registration of clinical whole-body CT and positron emission tomography (PET) images using this algorithm. The registration accuracy for this application was evaluated, based on validation using expert-identified anatomical landmarks in 15 CT-PET image pairs. The algorithm's performance was comparable to the average accuracy observed for three expert-determined registrations in the same 15 image pairs.

A new linear back projection algorithm to electrical tomography based on measuring data decomposition

NASA Astrophysics Data System (ADS)

Sun, Benyuan; Yue, Shihong; Cui, Ziqiang; Wang, Huaxiang

2015-12-01

As an advanced measurement technique of non-radiant, non-intrusive, rapid response, and low cost, the electrical tomography (ET) technique has developed rapidly in recent decades. The ET imaging algorithm plays an important role in the ET imaging process. Linear back projection (LBP) is the most used ET algorithm due to its advantages of dynamic imaging process, real-time response, and easy realization. But the LBP algorithm is of low spatial resolution due to the natural ‘soft field’ effect and ‘ill-posed solution’ problems; thus its applicable ranges are greatly limited. In this paper, an original data decomposition method is proposed, and every ET measuring data are decomposed into two independent new data based on the positive and negative sensing areas of the measuring data. Consequently, the number of total measuring data is extended to twice as many as the number of the original data, thus effectively reducing the ‘ill-posed solution’. On the other hand, an index to measure the ‘soft field’ effect is proposed. The index shows that the decomposed data can distinguish between different contributions of various units (pixels) for any ET measuring data, and can efficiently reduce the ‘soft field’ effect of the ET imaging process. In light of the data decomposition method, a new linear back projection algorithm is proposed to improve the spatial resolution of the ET image. A series of simulations and experiments are applied to validate the proposed algorithm by the real-time performances and the progress of spatial resolutions.

The cosmic ray muon tomography facility based on large scale MRPC detectors

NASA Astrophysics Data System (ADS)

Wang, Xuewu; Zeng, Ming; Zeng, Zhi; Wang, Yi; Zhao, Ziran; Yue, Xiaoguang; Luo, Zhifei; Yi, Hengguan; Yu, Baihui; Cheng, Jianping

2015-06-01

Cosmic ray muon tomography is a novel technology to detect high-Z material. A prototype of TUMUTY with 73.6 cm×73.6 cm large scale position sensitive MRPC detectors has been developed and is introduced in this paper. Three test kits have been tested and image is reconstructed using MAP algorithm. The reconstruction results show that the prototype is working well and the objects with complex structure and small size (20 mm) can be imaged on it, while the high-Z material is distinguishable from the low-Z one. This prototype provides a good platform for our further studies of the physical characteristics and the performances of cosmic ray muon tomography.

Optical Coherence Tomography Angiography

PubMed Central

Gao, Simon S.; Jia, Yali; Zhang, Miao; Su, Johnny P.; Liu, Gangjun; Hwang, Thomas S.; Bailey, Steven T.; Huang, David

2016-01-01

Optical coherence tomography angiography (OCTA) is a noninvasive approach that can visualize blood vessels down to the capillary level. With the advent of high-speed OCT and efficient algorithms, practical OCTA of ocular circulation is now available to ophthalmologists. Clinical investigations that used OCTA have increased exponentially in the past few years. This review will cover the history of OCTA and survey its most important clinical applications. The salient problems in the interpretation and analysis of OCTA are described, and recent advances are highlighted. PMID:27409483

Structure of junctions of multiwalled carbon nanotubes with tetragonal cross section and flattened nanotubes revealed by electron-beam tomography

NASA Astrophysics Data System (ADS)

Nagano, Yuta; Kohno, Hideo

2017-11-01

Multiwalled carbon nanotubes with tetragonal cross section frequently form junctions with flattened multi-walled carbon nanotubes, a kind of carbon nanoribbon. The three-dimensional structure of the junctions is revealed by transmission-electron-microscopy-based tomography. Two types of junction, parallel and diagonal, are found. The formation mechanism of these two types of junction is discussed in terms of the origami mechanism that was previously proposed to explain the formation of carbon nanoribbons and nanotetrahedra.

In Vitro Validation of an Artefact Suppression Algorithm in X-Ray Phase-Contrast Computed Tomography.

PubMed

Sunaguchi, Naoki; Yuasa, Tetsuya; Hirano, Shin-Ichi; Gupta, Rajiv; Ando, Masami

2015-01-01

X-ray phase-contrast tomography can significantly increase the contrast-resolution of conventional attenuation-contrast imaging, especially for soft-tissue structures that have very similar attenuation. Just as in attenuation-based tomography, phase contrast tomography requires a linear dependence of aggregate beam direction on the incremental direction alteration caused by individual voxels along the path of the X-ray beam. Dense objects such as calcifications in biological specimens violate this condition. There are extensive beam deflection artefacts in the vicinity of such structures because they result in large distortion of wave front due to the large difference of refractive index; for such large changes in beam direction, the transmittance of the silicon analyzer crystal saturates and is no longer linearly dependent on the angle of refraction. This paper describes a method by which these effects can be overcome and excellent soft-tissue contrast of phase tomography can be preserved in the vicinity of such artefact-producing structures.

Holography and tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Howells, M.

This session includes a collection of outlines of pertinent information, diagrams, graphs, electron micrographs, and color photographs pertaining to historical aspects and recent advances in the development of X-ray Gabor Holography. Many of the photographs feature or pertain to instrumentation used in holography, tomography, and cryo-holography.

Design of a portable optical emission tomography system for microwave induced compact plasma for visible to near-infrared emission lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rathore, Kavita, E-mail: kavira@iitk.ac.in, E-mail: pmunshi@iitk.ac.in, E-mail: sudeepb@iitk.ac.in; Munshi, Prabhat, E-mail: kavira@iitk.ac.in, E-mail: pmunshi@iitk.ac.in, E-mail: sudeepb@iitk.ac.in; Bhattacharjee, Sudeep, E-mail: kavira@iitk.ac.in, E-mail: pmunshi@iitk.ac.in, E-mail: sudeepb@iitk.ac.in

A new non-invasive diagnostic system is developed for Microwave Induced Plasma (MIP) to reconstruct tomographic images of a 2D emission profile. A compact MIP system has wide application in industry as well as research application such as thrusters for space propulsion, high current ion beams, and creation of negative ions for heating of fusion plasma. Emission profile depends on two crucial parameters, namely, the electron temperature and density (over the entire spatial extent) of the plasma system. Emission tomography provides basic understanding of plasmas and it is very useful to monitor internal structure of plasma phenomena without disturbing its actualmore » processes. This paper presents development of a compact, modular, and versatile Optical Emission Tomography (OET) tool for a cylindrical, magnetically confined MIP system. It has eight slit-hole cameras and each consisting of a complementary metal–oxide–semiconductor linear image sensor for light detection. The optical noise is reduced by using aspheric lens and interference band-pass filters in each camera. The entire cylindrical plasma can be scanned with automated sliding ring mechanism arranged in fan-beam data collection geometry. The design of the camera includes a unique possibility to incorporate different filters to get the particular wavelength light from the plasma. This OET system includes selected band-pass filters for particular argon emission 750 nm, 772 nm, and 811 nm lines and hydrogen emission H{sub α} (656 nm) and H{sub β} (486 nm) lines. Convolution back projection algorithm is used to obtain the tomographic images of plasma emission line. The paper mainly focuses on (a) design of OET system in detail and (b) study of emission profile for 750 nm argon emission lines to validate the system design.« less

Non-invasive coronary angiography with multislice computed tomography. Technology, methods, preliminary experience and prospects.

PubMed

Traversi, Egidio; Bertoli, Giuseppe; Barazzoni, Giancarlo; Baldi, Maurizia; Tramarin, Roberto

2004-02-01

The recent technical developments in multislice computed tomography (MSCT), with ECG retro-gated image reconstruction, have elicited great interest in the possibility of accurate non-invasive imaging of the coronary arteries. The latest generation of MSCT systems with 8-16 rows of detectors permits acquisition of the whole cardiac volume during a single 15-20 s breath-hold with a submillimetric definition of the images and an outstanding signal-to-noise ratio. Thus the race which, between MSCT, electron beam computed tomography and cardiac magnetic resonance imaging, can best provide routine and reliable imaging of the coronary arteries in clinical practice has recommenced. Currently available MSCT systems offer different options for both cardiac image acquisition and reconstruction, including multiplanar and curved multiplanar reconstruction, three-dimensional volume rendering, maximum intensity projection, and virtual angioscopy. In our preliminary experience including 176 patients suffering from known or suspected coronary artery disease, MSCT was feasible in 161 (91.5%) and showed a sensitivity of 80.4% and a specificity of 80.3%, with respect to standard coronary angiography, in detecting critical stenosis in coronary arteries and artery or venous bypass grafts. These results correspond to a positive predictive value of 58.6% and a negative predictive value of 92.2%. The true role that MSCT is likely to play in the future in non-invasive coronary imaging is still to be defined. Nevertheless, the huge amount of data obtainable by MSCT along with the rapid technological advances, shorter acquisition times and reconstruction algorithm developments will make the technique stronger, and possible applications are expected not only for non-invasive coronary angiography, but also for cardiac function and myocardial perfusion evaluation, as an all-in-one examination.

Validation of elastic registration algorithms based on adaptive irregular grids for medical applications

NASA Astrophysics Data System (ADS)

Franz, Astrid; Carlsen, Ingwer C.; Renisch, Steffen; Wischmann, Hans-Aloys

2006-03-01

Elastic registration of medical images is an active field of current research. Registration algorithms have to be validated in order to show that they fulfill the requirements of a particular clinical application. Furthermore, validation strategies compare the performance of different registration algorithms and can hence judge which algorithm is best suited for a target application. In the literature, validation strategies for rigid registration algorithms have been analyzed. For a known ground truth they assess the displacement error at a few landmarks, which is not sufficient for elastic transformations described by a huge number of parameters. Hence we consider the displacement error averaged over all pixels in the whole image or in a region-of-interest of clinical relevance. Using artificially, but realistically deformed images of the application domain, we use this quality measure to analyze an elastic registration based on transformations defined on adaptive irregular grids for the following clinical applications: Magnetic Resonance (MR) images of freely moving joints for orthopedic investigations, thoracic Computed Tomography (CT) images for the detection of pulmonary embolisms, and transmission images as used for the attenuation correction and registration of independently acquired Positron Emission Tomography (PET) and CT images. The definition of a region-of-interest allows to restrict the analysis of the registration accuracy to clinically relevant image areas. The behaviour of the displacement error as a function of the number of transformation control points and their placement can be used for identifying the best strategy for the initial placement of the control points.

Adaptive-weighted Total Variation Minimization for Sparse Data toward Low-dose X-ray Computed Tomography Image Reconstruction

PubMed Central

Liu, Yan; Ma, Jianhua; Fan, Yi; Liang, Zhengrong

2012-01-01

Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and other constraints, a piecewise-smooth X-ray computed tomography (CT) can be reconstructed from sparse-view projection data without introducing noticeable artifacts. However, due to the piecewise constant assumption for the image, a conventional TV minimization algorithm often suffers from over-smoothness on the edges of the resulting image. To mitigate this drawback, we present an adaptive-weighted TV (AwTV) minimization algorithm in this paper. The presented AwTV model is derived by considering the anisotropic edge property among neighboring image voxels, where the associated weights are expressed as an exponential function and can be adaptively adjusted by the local image-intensity gradient for the purpose of preserving the edge details. Inspired by the previously-reported TV-POCS (projection onto convex sets) implementation, a similar AwTV-POCS implementation was developed to minimize the AwTV subject to data and other constraints for the purpose of sparse-view low-dose CT image reconstruction. To evaluate the presented AwTV-POCS algorithm, both qualitative and quantitative studies were performed by computer simulations and phantom experiments. The results show that the presented AwTV-POCS algorithm can yield images with several noticeable gains, in terms of noise-resolution tradeoff plots and full width at half maximum values, as compared to the corresponding conventional TV-POCS algorithm. PMID:23154621

Adaptive-weighted total variation minimization for sparse data toward low-dose x-ray computed tomography image reconstruction.

PubMed

Liu, Yan; Ma, Jianhua; Fan, Yi; Liang, Zhengrong

2012-12-07

Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and other constraints, piecewise-smooth x-ray computed tomography (CT) can be reconstructed from sparse-view projection data without introducing notable artifacts. However, due to the piecewise constant assumption for the image, a conventional TV minimization algorithm often suffers from over-smoothness on the edges of the resulting image. To mitigate this drawback, we present an adaptive-weighted TV (AwTV) minimization algorithm in this paper. The presented AwTV model is derived by considering the anisotropic edge property among neighboring image voxels, where the associated weights are expressed as an exponential function and can be adaptively adjusted by the local image-intensity gradient for the purpose of preserving the edge details. Inspired by the previously reported TV-POCS (projection onto convex sets) implementation, a similar AwTV-POCS implementation was developed to minimize the AwTV subject to data and other constraints for the purpose of sparse-view low-dose CT image reconstruction. To evaluate the presented AwTV-POCS algorithm, both qualitative and quantitative studies were performed by computer simulations and phantom experiments. The results show that the presented AwTV-POCS algorithm can yield images with several notable gains, in terms of noise-resolution tradeoff plots and full-width at half-maximum values, as compared to the corresponding conventional TV-POCS algorithm.

Automatic measurement of epidermal thickness from optical coherence tomography images using a new algorithm.

PubMed

Josse, G; George, J; Black, D

2011-08-01

Optical coherence tomography (OCT) is an imaging system that enables in vivo epidermal thickness (ET) measurement. In order to use OCT in large-scale clinical studies, automatic algorithm detection of the dermo-epidermal junction (DEJ) is needed. This may be difficult due to image noise from optical speckle, which requires specific image treatment procedures to reduce this. In the present work, a description of the position of the DEJ is given, and an algorithm for boundary detection is presented. Twenty-nine images were taken from the skin of normal healthy subjects, from five different body sites. Seven expert assessors were asked to trace the DEJ for ET measurement on each of the images. The variability between experts was compared with a new image processing method. Between-expert variability was relatively low with a mean standard deviation of 3.4 μm. However, local positioning of the DEJ between experts was often different. The described algorithm performed adequately on all images. ET was automatically measured with a precision of < 5 μm compared with the experts on all sites studied except that of the back. Moreover, the local algorithm positioning was verified. The new image processing method for measuring ET from OCT images significantly reduces calculation time for this parameter, and avoids user intervention. The main advantages of this are that data can be analyzed more rapidly and reproducibly in clinical trials. © 2011 John Wiley & Sons A/S.

Ultrasonic guided wave tomography of pipes: A development of new techniques for the nondestructive evaluation of cylindrical geometries and guided wave multi-mode analysis

NASA Astrophysics Data System (ADS)

Leonard, Kevin Raymond

This dissertation concentrates on the development of two new tomographic techniques that enable wide-area inspection of pipe-like structures. By envisioning a pipe as a plate wrapped around upon itself, the previous Lamb Wave Tomography (LWT) techniques are adapted to cylindrical structures. Helical Ultrasound Tomography (HUT) uses Lamb-like guided wave modes transmitted and received by two circumferential arrays in a single crosshole geometry. Meridional Ultrasound Tomography (MUT) creates the same crosshole geometry with a linear array of transducers along the axis of the cylinder. However, even though these new scanning geometries are similar to plates, additional complexities arise because they are cylindrical structures. First, because it is a single crosshole geometry, the wave vector coverage is poorer than in the full LWT system. Second, since waves can travel in both directions around the circumference of the pipe, modes can also constructively and destructively interfere with each other. These complexities necessitate improved signal processing algorithms to produce accurate and unambiguous tomographic reconstructions. Consequently, this work also describes a new algorithm for improving the extraction of multi-mode arrivals from guided wave signals. Previous work has relied solely on the first arriving mode for the time-of-flight measurements. In order to improve the LWT, HUT and MUT systems reconstructions, improved signal processing methods are needed to extract information about the arrival times of the later arriving modes. Because each mode has different through-thickness displacement values, they are sensitive to different types of flaws, and the information gained from the multi-mode analysis improves understanding of the structural integrity of the inspected material. Both tomographic frequency compounding and mode sorting algorithms are introduced. It is also shown that each of these methods improve the reconstructed images both qualitatively and quantitatively.

In vivo examination of the cortical cytoskeleton in multiciliated cells using electron tomography.

PubMed

Clare, Daniel K; Dumoux, Maud; Delacour, Delphine

2015-01-01

Multiciliated cells are characterized by coordinated arrays of motile cilia. In the respiratory tract, the maintenance of this array is essential to ensure proper ciliary and mucus clearance. The establishment and the maintenance of the ciliary set are mediated by the correct positioning of basal bodies at the cell cortex. While microtubule and actin cytoskeletons have been reported to regulate basal body lattices, an understanding of their detailed organization was missing until recently. Here, we describe how electron tomography can highlight the arrangement of the cytoskeletal networks and their interplay with basal bodies in ciliated cells in their tissular environment. Thanks to this approach, information in fine detail on large parts of the cell, dense in organelles, is provided. In combination with other approaches, such as transgenic animal models, electron tomography constitutes a powerful technique giving an overview of tissues and cells concomitantly with acquisition of three-dimensional detail. Copyright © 2015 Elsevier Inc. All rights reserved.

Hardening mechanisms in olivine single crystal deformed at 1090 °C: an electron tomography study

NASA Astrophysics Data System (ADS)

Mussi, Alexandre; Cordier, Patrick; Demouchy, Sylvie; Hue, Benoit

2017-11-01

The dislocation microstructures in a single crystal of olivine deformed experimentally in uniaxial compression at 1090 °C and under a confining pressure of 300 MPa, have been investigated by transmission electron tomography in order to better understand deformation mechanisms at the microscale relevant for lithospheric mantle deformations. Investigation by electron tomography reveals microstructures, which are more complex than previously described, composed of ? and ? dislocations commonly exhibiting 3D configurations. Numerous mechanisms such as climb, cross-slip, double cross-slip as well as interactions like junction formations and collinear annihilations are the source of this complexity. The diversity observed advocates for microscale deformation of olivine significantly less simple than classic dislocation creep reported in metals or ice close to melting temperature. Deciphering mechanism of hardening in olivine at temperatures where ionic diffusion is slow and is then expected to play very little role is crucial to better understand and thus model deformation at larger scale and at temperatures (900-1100 °C) highly relevant for the lithospheric mantle.

3D tomography of midlatitude sporadic-E in Japan from GNSS-TEC data

NASA Astrophysics Data System (ADS)

Muafiry, Ihsan Naufal; Heki, Kosuke; Maeda, Jun

2018-03-01

We studied ionospheric irregularities caused by midlatitude sporadic-E ( Es) in Japan using ionospheric total electron content (TEC) data from a dense GNSS array, GEONET, with a 3D (three-dimensional) tomography technique. Es is a thin layer of unusually high ionization that appears at altitudes of 100 km. Here, we studied five cases of Es irregularities in 2010 and 2012, also reported in previous studies, over the Kanto and Kyushu Districts. We used slant TEC residuals as the input and estimated the number of electron density anomalies of more than 2000 small blocks with dimensions of 20-30 km covering a horizontal region of 300 × 500 km. We applied a continuity constraint to stabilize the solution and performed several different resolution tests with synthetic data to assess the accuracy of the results. The tomography results showed that positive electron density anomalies occurred at the E region height, and the morphology and dynamics were consistent with those reported by earlier studies.

A fast cross-validation method for alignment of electron tomography images based on Beer-Lambert law.

PubMed

Yan, Rui; Edwards, Thomas J; Pankratz, Logan M; Kuhn, Richard J; Lanman, Jason K; Liu, Jun; Jiang, Wen

2015-11-01

In electron tomography, accurate alignment of tilt series is an essential step in attaining high-resolution 3D reconstructions. Nevertheless, quantitative assessment of alignment quality has remained a challenging issue, even though many alignment methods have been reported. Here, we report a fast and accurate method, tomoAlignEval, based on the Beer-Lambert law, for the evaluation of alignment quality. Our method is able to globally estimate the alignment accuracy by measuring the goodness of log-linear relationship of the beam intensity attenuations at different tilt angles. Extensive tests with experimental data demonstrated its robust performance with stained and cryo samples. Our method is not only significantly faster but also more sensitive than measurements of tomogram resolution using Fourier shell correlation method (FSCe/o). From these tests, we also conclude that while current alignment methods are sufficiently accurate for stained samples, inaccurate alignments remain a major limitation for high resolution cryo-electron tomography. Copyright © 2015 Elsevier Inc. All rights reserved.

A fast cross-validation method for alignment of electron tomography images based on Beer-Lambert law

PubMed Central

Yan, Rui; Edwards, Thomas J.; Pankratz, Logan M.; Kuhn, Richard J.; Lanman, Jason K.; Liu, Jun; Jiang, Wen

2015-01-01

In electron tomography, accurate alignment of tilt series is an essential step in attaining high-resolution 3D reconstructions. Nevertheless, quantitative assessment of alignment quality has remained a challenging issue, even though many alignment methods have been reported. Here, we report a fast and accurate method, tomoAlignEval, based on the Beer-Lambert law, for the evaluation of alignment quality. Our method is able to globally estimate the alignment accuracy by measuring the goodness of log-linear relationship of the beam intensity attenuations at different tilt angles. Extensive tests with experimental data demonstrated its robust performance with stained and cryo samples. Our method is not only significantly faster but also more sensitive than measurements of tomogram resolution using Fourier shell correlation method (FSCe/o). From these tests, we also conclude that while current alignment methods are sufficiently accurate for stained samples, inaccurate alignments remain a major limitation for high resolution cryo-electron tomography. PMID:26455556

Three-dimensional visualization of gammaherpesvirus life cycle in host cells by electron tomography.

PubMed

Peng, Li; Ryazantsev, Sergey; Sun, Ren; Zhou, Z Hong

2010-01-13

Gammaherpesviruses are etiologically associated with human tumors. A three-dimensional (3D) examination of their life cycle in the host is lacking, significantly limiting our understanding of the structural and molecular basis of virus-host interactions. Here, we report the first 3D visualization of key stages of the murine gammaherpesvirus 68 life cycle in NIH 3T3 cells, including viral attachment, entry, assembly, and egress, by dual-axis electron tomography. In particular, we revealed the transient processes of incoming capsids injecting viral DNA through nuclear pore complexes and nascent DNA being packaged into progeny capsids in vivo as a spool coaxial with the putative portal vertex. We discovered that intranuclear invagination of both nuclear membranes is involved in nuclear egress of herpesvirus capsids. Taken together, our results provide the structural basis for a detailed mechanistic description of gammaherpesvirus life cycle and also demonstrate the advantage of electron tomography in dissecting complex cellular processes of viral infection.

Long helical filaments are not seen encircling cells in electron cryotomograms of rod-shaped bacteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swulius, Matthew T.; Chen, Songye; Jane Ding, H.

2011-04-22

Highlights: {yields} No long helical filaments are seen near or along rod-shaped bacterial inner membranes by electron cryo-tomography. {yields} Electron cryo-tomography has the resolution to detect single filaments in vivo. -- Abstract: How rod-shaped bacteria form and maintain their shape is an important question in bacterial cell biology. Results from fluorescent light microscopy have led many to believe that the actin homolog MreB and a number of other proteins form long helical filaments along the inner membrane of the cell. Here we show using electron cryotomography of six different rod-shaped bacterial species, at macromolecular resolution, that no long (>80 nm)more » helical filaments exist near or along either surface of the inner membrane. We also use correlated cryo-fluorescent light microscopy (cryo-fLM) and electron cryo-tomography (ECT) to identify cytoplasmic bundles of MreB, showing that MreB filaments are detectable by ECT. In light of these results, the structure and function of MreB must be reconsidered: instead of acting as a large, rigid scaffold that localizes cell-wall synthetic machinery, moving MreB complexes may apply tension to growing peptidoglycan strands to ensure their orderly, linear insertion.« less

A direct method for nonlinear ill-posed problems

NASA Astrophysics Data System (ADS)

Lakhal, A.

2018-02-01

We propose a direct method for solving nonlinear ill-posed problems in Banach-spaces. The method is based on a stable inversion formula we explicitly compute by applying techniques for analytic functions. Furthermore, we investigate the convergence and stability of the method and prove that the derived noniterative algorithm is a regularization. The inversion formula provides a systematic sensitivity analysis. The approach is applicable to a wide range of nonlinear ill-posed problems. We test the algorithm on a nonlinear problem of travel-time inversion in seismic tomography. Numerical results illustrate the robustness and efficiency of the algorithm.

Automated interferometric synthetic aperture microscopy and computational adaptive optics for improved optical coherence tomography.

PubMed

Xu, Yang; Liu, Yuan-Zhi; Boppart, Stephen A; Carney, P Scott

2016-03-10

In this paper, we introduce an algorithm framework for the automation of interferometric synthetic aperture microscopy (ISAM). Under this framework, common processing steps such as dispersion correction, Fourier domain resampling, and computational adaptive optics aberration correction are carried out as metrics-assisted parameter search problems. We further present the results of this algorithm applied to phantom and biological tissue samples and compare with manually adjusted results. With the automated algorithm, near-optimal ISAM reconstruction can be achieved without manual adjustment. At the same time, the technical barrier for the nonexpert using ISAM imaging is also significantly lowered.

Kinetic filtering of [18F]Fluorothymidine in positron emission tomography studies

NASA Astrophysics Data System (ADS)

Gray, Katherine R.; Contractor, Kaiyumars B.; Kenny, Laura M.; Al-Nahhas, Adil; Shousha, Sami; Stebbing, Justin; Wasan, Harpreet S.; Coombes, R. Charles; Aboagye, Eric O.; Turkheimer, Federico E.; Rosso, Lula

2010-02-01

[18F]Fluorothymidine (FLT) is a cell proliferation marker that undergoes predominantly hepatic metabolism and therefore shows a high level of accumulation in the liver, as well as in rapidly proliferating tumours. Furthermore, the tracer's uptake is substantial in other organs including the heart. We present a nonlinear kinetic filtering technique which enhances the visualization of tumours imaged with FLT positron emission tomography (FLT-PET). A classification algorithm to isolate cancerous tissue from healthy organs was developed and validated using 29 scan data from patients with locally advanced or metastatic breast cancer. A large reduction in signal from the liver and heart of 80% was observed following application of the kinetic filter, whilst the majority of signal from both primary tumours and metastases was retained. A scan acquisition time of 60 min has been shown to be sufficient to obtain the necessary kinetic data. The algorithm extends utility of FLT-PET imaging in oncology research.

Fully Convolutional Architecture for Low-Dose CT Image Noise Reduction

NASA Astrophysics Data System (ADS)

Badretale, S.; Shaker, F.; Babyn, P.; Alirezaie, J.

2017-10-01

One of the critical topics in medical low-dose Computed Tomography (CT) imaging is how best to maintain image quality. As the quality of images decreases with lowering the X-ray radiation dose, improving image quality is extremely important and challenging. We have proposed a novel approach to denoise low-dose CT images. Our algorithm learns directly from an end-to-end mapping from the low-dose Computed Tomography images for denoising the normal-dose CT images. Our method is based on a deep convolutional neural network with rectified linear units. By learning various low-level to high-level features from a low-dose image the proposed algorithm is capable of creating a high-quality denoised image. We demonstrate the superiority of our technique by comparing the results with two other state-of-the-art methods in terms of the peak signal to noise ratio, root mean square error, and a structural similarity index.

Introducing minimum Fisher regularisation tomography to AXUV and soft x-ray diagnostic systems of the COMPASS tokamak

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mlynar, J.; Weinzettl, V.; Imrisek, M.

2012-10-15

The contribution focuses on plasma tomography via the minimum Fisher regularisation (MFR) algorithm applied on data from the recently commissioned tomographic diagnostics on the COMPASS tokamak. The MFR expertise is based on previous applications at Joint European Torus (JET), as exemplified in a new case study of the plasma position analyses based on JET soft x-ray (SXR) tomographic reconstruction. Subsequent application of the MFR algorithm on COMPASS data from cameras with absolute extreme ultraviolet (AXUV) photodiodes disclosed a peaked radiating region near the limiter. Moreover, its time evolution indicates transient plasma edge cooling following a radial plasma shift. In themore » SXR data, MFR demonstrated that a high resolution plasma positioning independent of the magnetic diagnostics would be possible provided that a proper calibration of the cameras on an x-ray source is undertaken.« less

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques.

PubMed

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images.

Online learning in optical tomography: a stochastic approach

NASA Astrophysics Data System (ADS)

Chen, Ke; Li, Qin; Liu, Jian-Guo

2018-07-01

We study the inverse problem of radiative transfer equation (RTE) using stochastic gradient descent method (SGD) in this paper. Mathematically, optical tomography amounts to recovering the optical parameters in RTE using the incoming–outgoing pair of light intensity. We formulate it as a PDE-constraint optimization problem, where the mismatch of computed and measured outgoing data is minimized with same initial data and RTE constraint. The memory and computation cost it requires, however, is typically prohibitive, especially in high dimensional space. Smart iterative solvers that only use partial information in each step is called for thereafter. Stochastic gradient descent method is an online learning algorithm that randomly selects data for minimizing the mismatch. It requires minimum memory and computation, and advances fast, therefore perfectly serves the purpose. In this paper we formulate the problem, in both nonlinear and its linearized setting, apply SGD algorithm and analyze the convergence performance.

A Review of Algorithms for Segmentation of Optical Coherence Tomography from Retina

PubMed Central

Kafieh, Raheleh; Rabbani, Hossein; Kermani, Saeed

2013-01-01

Optical coherence tomography (OCT) is a recently established imaging technique to describe different information about the internal structures of an object and to image various aspects of biological tissues. OCT image segmentation is mostly introduced on retinal OCT to localize the intra-retinal boundaries. Here, we review some of the important image segmentation methods for processing retinal OCT images. We may classify the OCT segmentation approaches into five distinct groups according to the image domain subjected to the segmentation algorithm. Current researches in OCT segmentation are mostly based on improving the accuracy and precision, and on reducing the required processing time. There is no doubt that current 3-D imaging modalities are now moving the research projects toward volume segmentation along with 3-D rendering and visualization. It is also important to develop robust methods capable of dealing with pathologic cases in OCT imaging. PMID:24083137

ADART: an adaptive algebraic reconstruction algorithm for discrete tomography.

PubMed

Maestre-Deusto, F Javier; Scavello, Giovanni; Pizarro, Joaquín; Galindo, Pedro L

2011-08-01

In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques

PubMed Central

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Background: Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. Methods: In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Results: Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Conclusions: Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images. PMID:29535920

Adaptive panoramic tomography with a circular rotational movement for the formation of multifocal image layers

NASA Astrophysics Data System (ADS)

Kim, D. S.; Cho, H. S.; Park, Y. O.; Je, U. K.; Hong, D. K.; Choi, S. I.; Koo, Y. S.

2012-02-01

Panoramic radiography with which only structures within a certain image layer are in focus and others out of focus on the panoramic image has become a popular imaging technique especially in dentistry. However, the major drawback to the technique is a mismatch between the structures to be focused and the predefined image layer mainly due to the various shapes and sizes of dental arches and/or to malpositioning of the patient. These result in image quality typically inferior to that obtained using intraoral radiographic techniques. In this paper, to overcome these difficulties, we suggest a new panoramic reconstruction algorithm, the so-called adaptive panoramic tomography ( APT), capable of reconstructing multifocal image layers with no additional exposure. In order to verify the effectiveness of the proposed algorithm, we performed systematic simulation studies with a circular rotational movement and investigated the image performance.

Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform

PubMed Central

Mayer, Markus A.; Boretsky, Adam R.; van Kuijk, Frederik J.; Motamedi, Massoud

2012-01-01

Abstract. Image enhancement of retinal structures, in optical coherence tomography (OCT) scans through denoising, has the potential to aid in the diagnosis of several eye diseases. In this paper, a locally adaptive denoising algorithm using double-density dual-tree complex wavelet transform, a combination of the double-density wavelet transform and the dual-tree complex wavelet transform, is applied to reduce speckle noise in OCT images of the retina. The algorithm overcomes the limitations of commonly used multiple frame averaging technique, namely the limited number of frames that can be recorded due to eye movements, by providing a comparable image quality in significantly less acquisition time equal to an order of magnitude less time compared to the averaging method. In addition, improvements of image quality metrics and 5 dB increase in the signal-to-noise ratio are attained. PMID:23117804

Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform.

PubMed

Chitchian, Shahab; Mayer, Markus A; Boretsky, Adam R; van Kuijk, Frederik J; Motamedi, Massoud

2012-11-01

ABSTRACT. Image enhancement of retinal structures, in optical coherence tomography (OCT) scans through denoising, has the potential to aid in the diagnosis of several eye diseases. In this paper, a locally adaptive denoising algorithm using double-density dual-tree complex wavelet transform, a combination of the double-density wavelet transform and the dual-tree complex wavelet transform, is applied to reduce speckle noise in OCT images of the retina. The algorithm overcomes the limitations of commonly used multiple frame averaging technique, namely the limited number of frames that can be recorded due to eye movements, by providing a comparable image quality in significantly less acquisition time equal to an order of magnitude less time compared to the averaging method. In addition, improvements of image quality metrics and 5 dB increase in the signal-to-noise ratio are attained.

New imaging algorithm in diffusion tomography

NASA Astrophysics Data System (ADS)

Klibanov, Michael V.; Lucas, Thomas R.; Frank, Robert M.

1997-08-01

A novel imaging algorithm for diffusion/optical tomography is presented for the case of the time dependent diffusion equation. Numerical tests are conducted for ranges of parameters realistic for applications to an early breast cancer diagnosis using ultrafast laser pulses. This is a perturbation-like method which works for both homogeneous a heterogeneous background media. Its main innovation lies in a new approach for a novel linearized problem (LP). Such an LP is derived and reduced to a boundary value problem for a coupled system of elliptic partial differential equations. As is well known, the solution of such a system amounts to the factorization of well conditioned, sparse matrices with few non-zero entries clustered along the diagonal, which can be done very rapidly. Thus, the main advantages of this technique are that it is fast and accurate. The authors call this approach the elliptic systems method (ESM). The ESM can be extended for other data collection schemes.

Small-angle X-ray scattering tensor tomography: model of the three-dimensional reciprocal-space map, reconstruction algorithm and angular sampling requirements.

PubMed

Liebi, Marianne; Georgiadis, Marios; Kohlbrecher, Joachim; Holler, Mirko; Raabe, Jörg; Usov, Ivan; Menzel, Andreas; Schneider, Philipp; Bunk, Oliver; Guizar-Sicairos, Manuel

2018-01-01

Small-angle X-ray scattering tensor tomography, which allows reconstruction of the local three-dimensional reciprocal-space map within a three-dimensional sample as introduced by Liebi et al. [Nature (2015), 527, 349-352], is described in more detail with regard to the mathematical framework and the optimization algorithm. For the case of trabecular bone samples from vertebrae it is shown that the model of the three-dimensional reciprocal-space map using spherical harmonics can adequately describe the measured data. The method enables the determination of nanostructure orientation and degree of orientation as demonstrated previously in a single momentum transfer q range. This article presents a reconstruction of the complete reciprocal-space map for the case of bone over extended ranges of q. In addition, it is shown that uniform angular sampling and advanced regularization strategies help to reduce the amount of data required.

Conservative algorithms for non-Maxwellian plasma kinetics

DOE PAGES

Le, Hai P.; Cambier, Jean -Luc

2017-12-08

Here, we present a numerical model and a set of conservative algorithms for Non-Maxwellian plasma kinetics with inelastic collisions. These algorithms self-consistently solve for the time evolution of an isotropic electron energy distribution function interacting with an atomic state distribution function of an arbitrary number of levels through collisional excitation, deexcitation, as well as ionization and recombination. Electron-electron collisions, responsible for thermalization of the electron distribution, are also included in the model. The proposed algorithms guarantee mass/charge and energy conservation in a single step, and is applied to the case of non-uniform gridding of the energy axis in the phasemore » space of the electron distribution function. Numerical test cases are shown to demonstrate the accuracy of the method and its conservation properties.« less

[Evaluation of three methods for constructing craniofacial mid-sagittal plane based on the cone beam computed tomography].

PubMed

Wang, S W; Li, M; Yang, H F; Zhao, Y J; Wang, Y; Liu, Y

2016-04-18

To compare the accuracyof interactive closet point (ICP) algorithm, Procrustes analysis (PA) algorithm,and a landmark-independent method to construct the mid-sagittal plane (MSP) of the cone beam computed tomography.To provide theoretical basis for establishing coordinate systemof CBCT images and symmetric analysis. Ten patients were selected and scanned by CBCT before orthodontic treatment.The scan data was imported into Mimics 10.0 to reconstructthree dimensional skulls.And the MSP of each skull was generated by ICP algorithm, PA algorithm and landmark-independent method. MSP extracted by ICP algorithm or PA algorithm involvedthree steps. First, the 3D skull processing was performed by reverse engineering software geomagic studio 2012 to obtain the mirror skull. Then, the original and its mirror skull was registered separately by ICP algorithm in geomagic studio 2012 and PA algorithm in NX Imageware 11.0. Finally, the registered data were united into new data to calculate the MSP of the originaldata in geomagic studio 2012. The mid-sagittal plane was determined by SELLA (S), nasion (N), basion (Ba) as traditional landmark-dependent methodconducted in software InVivoDental 5.0. The distance from 9 pairs of symmetric anatomical marked points to three sagittal plane were measured and calculated to compare the differences of the absolute value. The one-way ANOVA test was used to analyze the variable differences among the 3 MSPs. The pairwise comparison was performed with LSD method. MSPs calculated by the three methods were available for clinic analysis, which could be concluded from the front view.However, there was significant differences among the distances from the 9 pairs of symmetric anatomical marked points to the MSPs (F=10.932,P=0.001).LSD test showed there was no significant difference between the ICP algorithm and landmark-independent method (P=0.11), while there was significant difference between the PA algorithm and landmark-independent methods (P=0.01) . Mid-sagittal plane of 3D skulls could be generated base on ICP algorithm or PA algorithm. There was no significant difference between the ICP algorithm and landmark-independent method. For the subjects with no evident asymmetry, ICP algorithm is feasible in clinical analysis.

Modern Focused-Ion-Beam-Based Site-Specific Specimen Preparation for Atom Probe Tomography.

PubMed

Prosa, Ty J; Larson, David J

2017-04-01

Approximately 30 years after the first use of focused ion beam (FIB) instruments to prepare atom probe tomography specimens, this technique has grown to be used by hundreds of researchers around the world. This past decade has seen tremendous advances in atom probe applications, enabled by the continued development of FIB-based specimen preparation methodologies. In this work, we provide a short review of the origin of the FIB method and the standard methods used today for lift-out and sharpening, using the annular milling method as applied to atom probe tomography specimens. Key steps for enabling correlative analysis with transmission electron-beam backscatter diffraction, transmission electron microscopy, and atom probe tomography are presented, and strategies for preparing specimens for modern microelectronic device structures are reviewed and discussed in detail. Examples are used for discussion of the steps for each of these methods. We conclude with examples of the challenges presented by complex topologies such as nanowires, nanoparticles, and organic materials.

Human cardiac telocytes: 3D imaging by FIB-SEM tomography

PubMed Central

Cretoiu, D; Hummel, E; Zimmermann, H; Gherghiceanu, M; Popescu, L M

2014-01-01

Telocyte (TC) is a newly identified type of cell in the cardiac interstitium (www.telocytes.com). TCs are described by classical transmission electron microscopy as cells with very thin and long telopodes (Tps; cellular prolongations) having podoms (dilations) and podomers (very thin segments). TCs’ three-dimensional (3D) morphology is still unknown. Cardiac TCs seem to be particularly involved in long and short distance intercellular signalling and, therefore, their 3D architecture is important for understanding their spatial connections. Using focused ion beam scanning electron microscopy (FIB-SEM) we show, for the first time, the whole ultrastructural anatomy of cardiac TCs. 3D reconstruction of cardiac TCs by FIB-SEM tomography confirms that they have long, narrow but flattened (ribbon-like) telopodes, with humps generated by the podoms. FIB-SEM tomography also confirms the network made by TCs in the cardiac interstitium through adherens junctions. This study provides the first FIB-SEM tomography of a human cell type. PMID:25327290

Fisher's method of scoring in statistical image reconstruction: comparison of Jacobi and Gauss-Seidel iterative schemes.

PubMed

Hudson, H M; Ma, J; Green, P

1994-01-01

Many algorithms for medical image reconstruction adopt versions of the expectation-maximization (EM) algorithm. In this approach, parameter estimates are obtained which maximize a complete data likelihood or penalized likelihood, in each iteration. Implicitly (and sometimes explicitly) penalized algorithms require smoothing of the current reconstruction in the image domain as part of their iteration scheme. In this paper, we discuss alternatives to EM which adapt Fisher's method of scoring (FS) and other methods for direct maximization of the incomplete data likelihood. Jacobi and Gauss-Seidel methods for non-linear optimization provide efficient algorithms applying FS in tomography. One approach uses smoothed projection data in its iterations. We investigate the convergence of Jacobi and Gauss-Seidel algorithms with clinical tomographic projection data.

Development of the algorithm of measurement data and tomographic section reconstruction results processing for evaluating the respiratory activity of the lungs using the multi-angle electric impedance tomography

NASA Astrophysics Data System (ADS)

Aleksanyan, Grayr; Shcherbakov, Ivan; Kucher, Artem; Sulyz, Andrew

2018-04-01

Continuous monitoring of the patient's breathing by the method of multi-angle electric impedance tomography allows to obtain images of conduction change in the chest cavity during the monitoring. Direct analysis of images is difficult due to the large amount of information and low resolution images obtained by multi-angle electrical impedance tomography. This work presents a method for obtaining a graph of respiratory activity of the lungs based on the results of continuous lung monitoring using the multi-angle electrical impedance tomography method. The method makes it possible to obtain a graph of the respiratory activity of the left and right lungs separately, as well as a summary graph, to which it is possible to apply methods of processing the results of spirography.

Electron cryo-tomography captures macromolecular complexes in native environments.

PubMed

Baker, Lindsay A; Grange, Michael; Grünewald, Kay

2017-10-01

Transmission electron microscopy has a long history in cellular biology. Fixed and stained samples have been used for cellular imaging for over 50 years, but suffer from sample preparation induced artifacts. Electron cryo-tomography (cryoET) instead uses frozen-hydrated samples, without chemical modification, to determine the structure of macromolecular complexes in their native environment. Recent developments in electron microscopes and associated technologies have greatly expanded our ability to visualize cellular features and determine the structures of macromolecular complexes in situ. This review highlights the technological improvements and the new areas of biology these advances have made accessible. We discuss the potential of cryoET to reveal novel and significant biological information on the nanometer or subnanometer scale, and directions for further work. Copyright © 2017. Published by Elsevier Ltd.

Modified Monte Carlo method for study of electron transport in degenerate electron gas in the presence of electron-electron interactions, application to graphene

NASA Astrophysics Data System (ADS)

Borowik, Piotr; Thobel, Jean-Luc; Adamowicz, Leszek

2017-07-01

Standard computational methods used to take account of the Pauli Exclusion Principle into Monte Carlo (MC) simulations of electron transport in semiconductors may give unphysical results in low field regime, where obtained electron distribution function takes values exceeding unity. Modified algorithms were already proposed and allow to correctly account for electron scattering on phonons or impurities. Present paper extends this approach and proposes improved simulation scheme allowing including Pauli exclusion principle for electron-electron (e-e) scattering into MC simulations. Simulations with significantly reduced computational cost recreate correct values of the electron distribution function. Proposed algorithm is applied to study transport properties of degenerate electrons in graphene with e-e interactions. This required adapting the treatment of e-e scattering in the case of linear band dispersion relation. Hence, this part of the simulation algorithm is described in details.

CoCrMo cellular structures made by Electron Beam Melting studied by local tomography and finite element modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petit, Clémence; Maire, Eric, E-mail: eric.maire@insa-lyon.fr; Meille, Sylvain

The work focuses on the structural and mechanical characterization of Co-Cr-Mo cellular samples with cubic pore structure made by Electron Beam Melting (EBM). X-ray tomography was used to characterize the architecture of the sample. High resolution images were also obtained thanks to local tomography in which the specimen is placed close to the X-ray source. These images enabled to observe some defects due to the fabrication process: small pores in the solid phase, partially melted particles attached to the surface. Then, in situ compression tests were performed in the tomograph. The images of the deformed sample show a progressive bucklingmore » of the vertical struts leading to final fracture. The deformation initiated where the defects were present in the strut i.e. in regions with reduced local thickness. The finite element modelling confirmed the high stress concentrations of these weak points leading to the fracture of the sample. - Highlights: • CoCrMo samples fabricated by Electron Beam Melting (EBM) process are considered. • X-ray Computed Tomography is used to observe the structure of the sample. • The mechanical properties are tested thanks to an in situ test in the tomograph. • A finite element model is developed to model the mechanical behaviour.« less

FIB-SEM tomography of human skin telocytes and their extracellular vesicles

PubMed Central

Cretoiu, Dragos; Gherghiceanu, Mihaela; Hummel, Eric; Zimmermann, Hans; Simionescu, Olga; Popescu, Laurentiu M

2015-01-01

We have shown in 2012 the existence of telocytes (TCs) in human dermis. TCs were described by transmission electron microscopy (TEM) as interstitial cells located in non-epithelial spaces (stroma) of many organs (see www.telocytes.com). TCs have very long prolongations (tens to hundreds micrometers) named Telopodes (Tps). These Tps have a special conformation with dilated portions named podoms (containing mitochondria, endoplasmic reticulum and caveolae) and very thin segments (below resolving power of light microscopy), called podomers. To show the real 3D architecture of TC network, we used the most advanced available electron microscope technology: focused ion beam scanning electron microscopy (FIB-SEM) tomography. Generally, 3D reconstruction of dermal TCs by FIB-SEM tomography revealed the existence of Tps with various conformations: (i) long, flattened irregular veils (ribbon-like segments) with knobs, corresponding to podoms, and (ii) tubular structures (podomers) with uneven calibre because of irregular dilations (knobs) – the podoms. FIB-SEM tomography also showed numerous extracellular vesicles (diameter 438.6 ± 149.1 nm, n = 30) released by a human dermal TC. Our data might be useful for understanding the role(s) of TCs in intercellular signalling and communication, as well as for comprehension of pathologies like scleroderma, multiple sclerosis, psoriasis, etc. PMID:25823591

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

Surface hopping with a manifold of electronic states. I. Incorporating surface-leaking to capture lifetimes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ouyang, Wenjun; Dou, Wenjie; Subotnik, Joseph E., E-mail: subotnik@sas.upenn.edu

2015-02-28

We investigate the incorporation of the surface-leaking (SL) algorithm into Tully’s fewest-switches surface hopping (FSSH) algorithm to simulate some electronic relaxation induced by an electronic bath in conjunction with some electronic transitions between discrete states. The resulting SL-FSSH algorithm is benchmarked against exact quantum scattering calculations for three one-dimensional model problems. The results show excellent agreement between SL-FSSH and exact quantum dynamics in the wide band limit, suggesting the potential for a SL-FSSH algorithm. Discrepancies and failures are investigated in detail to understand the factors that will limit the reliability of SL-FSSH, especially the wide band approximation. Considering the easinessmore » of implementation and the low computational cost, we expect this method to be useful in studying processes involving both a continuum of electronic states (where electronic dynamics are probabilistic) and processes involving only a few electronic states (where non-adiabatic processes cannot ignore short-time coherence)« less

SU-D-201-06: Random Walk Algorithm Seed Localization Parameters in Lung Positron Emission Tomography (PET) Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soufi, M; Asl, A Kamali; Geramifar, P

2015-06-15

Purpose: The objective of this study was to find the best seed localization parameters in random walk algorithm application to lung tumor delineation in Positron Emission Tomography (PET) images. Methods: PET images suffer from statistical noise and therefore tumor delineation in these images is a challenging task. Random walk algorithm, a graph based image segmentation technique, has reliable image noise robustness. Also its fast computation and fast editing characteristics make it powerful for clinical purposes. We implemented the random walk algorithm using MATLAB codes. The validation and verification of the algorithm have been done by 4D-NCAT phantom with spherical lungmore » lesions in different diameters from 20 to 90 mm (with incremental steps of 10 mm) and different tumor to background ratios of 4:1 and 8:1. STIR (Software for Tomographic Image Reconstruction) has been applied to reconstruct the phantom PET images with different pixel sizes of 2×2×2 and 4×4×4 mm{sup 3}. For seed localization, we selected pixels with different maximum Standardized Uptake Value (SUVmax) percentages, at least (70%, 80%, 90% and 100%) SUVmax for foreground seeds and up to (20% to 55%, 5% increment) SUVmax for background seeds. Also, for investigation of algorithm performance on clinical data, 19 patients with lung tumor were studied. The resulted contours from algorithm have been compared with nuclear medicine expert manual contouring as ground truth. Results: Phantom and clinical lesion segmentation have shown that the best segmentation results obtained by selecting the pixels with at least 70% SUVmax as foreground seeds and pixels up to 30% SUVmax as background seeds respectively. The mean Dice Similarity Coefficient of 94% ± 5% (83% ± 6%) and mean Hausdorff Distance of 1 (2) pixels have been obtained for phantom (clinical) study. Conclusion: The accurate results of random walk algorithm in PET image segmentation assure its application for radiation treatment planning and diagnosis.« less

Comparisons of ionospheric electron density distributions reconstructed by GPS computerized tomography, backscatter ionograms, and vertical ionograms

NASA Astrophysics Data System (ADS)

Zhou, Chen; Lei, Yong; Li, Bofeng; An, Jiachun; Zhu, Peng; Jiang, Chunhua; Zhao, Zhengyu; Zhang, Yuannong; Ni, Binbin; Wang, Zemin; Zhou, Xuhua

2015-12-01

Global Positioning System (GPS) computerized ionosphere tomography (CIT) and ionospheric sky wave ground backscatter radar are both capable of measuring the large-scale, two-dimensional (2-D) distributions of ionospheric electron density (IED). Here we report the spatial and temporal electron density results obtained by GPS CIT and backscatter ionogram (BSI) inversion for three individual experiments. Both the GPS CIT and BSI inversion techniques demonstrate the capability and the consistency of reconstructing large-scale IED distributions. To validate the results, electron density profiles obtained from GPS CIT and BSI inversion are quantitatively compared to the vertical ionosonde data, which clearly manifests that both methods output accurate information of ionopsheric electron density and thereby provide reliable approaches to ionospheric soundings. Our study can improve current understanding of the capability and insufficiency of these two methods on the large-scale IED reconstruction.

Quantum State Tomography via Linear Regression Estimation

PubMed Central

Qi, Bo; Hou, Zhibo; Li, Li; Dong, Daoyi; Xiang, Guoyong; Guo, Guangcan

2013-01-01

A simple yet efficient state reconstruction algorithm of linear regression estimation (LRE) is presented for quantum state tomography. In this method, quantum state reconstruction is converted into a parameter estimation problem of a linear regression model and the least-squares method is employed to estimate the unknown parameters. An asymptotic mean squared error (MSE) upper bound for all possible states to be estimated is given analytically, which depends explicitly upon the involved measurement bases. This analytical MSE upper bound can guide one to choose optimal measurement sets. The computational complexity of LRE is O(d4) where d is the dimension of the quantum state. Numerical examples show that LRE is much faster than maximum-likelihood estimation for quantum state tomography. PMID:24336519

Acoustic vector tomography and its application to magnetoacoustic tomography with magnetic induction (MAT-MI).

PubMed

Li, Xu; Xia, Rongmin; He, Bin

2008-01-01

A new tomographic algorithm for reconstructing a curl-free vector field, whose divergence serves as acoustic source is proposed. It is shown that under certain conditions, the scalar acoustic measurements obtained from a surface enclosing the source area can be vectorized according to the known measurement geometry and then be used to reconstruct the vector field. The proposed method is validated by numerical experiments. This method can be easily applied to magnetoacoustic tomography with magnetic induction (MAT-MI). A simulation study of applying this method to MAT-MI shows that compared to existing methods, the proposed method can give an accurate estimation of the induced current distribution and a better reconstruction of electrical conductivity within an object.

Micro-tomography based Geometry Modeling of Three-Dimensional Braided Composites

NASA Astrophysics Data System (ADS)

Fang, Guodong; Chen, Chenghua; Yuan, Shenggang; Meng, Songhe; Liang, Jun

2018-06-01

A tracking and recognizing algorithm is proposed to automatically generate irregular cross-sections and central path of braid yarn within the 3D braided composites by using sets of high resolution tomography images. Only the initial cross-sections of braid yarns in a tomography image after treatment are required to be calibrated manually as searching cross-section template. The virtual geometry of 3D braided composites including some detailed geometry information, such as the braid yarn squeezing deformation, braid yarn distortion and braid yarn path deviation etc., can be reconstructed. The reconstructed geometry model can reflect the change of braid configurations during solidification process. The geometry configurations and mechanical properties of the braided composites are analyzed by using the reconstructed geometry model.

Comparison and assessment of semi-automatic image segmentation in computed tomography scans for image-guided kidney surgery.

PubMed

Glisson, Courtenay L; Altamar, Hernan O; Herrell, S Duke; Clark, Peter; Galloway, Robert L

2011-11-01

Image segmentation is integral to implementing intraoperative guidance for kidney tumor resection. Results seen in computed tomography (CT) data are affected by target organ physiology as well as by the segmentation algorithm used. This work studies variables involved in using level set methods found in the Insight Toolkit to segment kidneys from CT scans and applies the results to an image guidance setting. A composite algorithm drawing on the strengths of multiple level set approaches was built using the Insight Toolkit. This algorithm requires image contrast state and seed points to be identified as input, and functions independently thereafter, selecting and altering method and variable choice as needed. Semi-automatic results were compared to expert hand segmentation results directly and by the use of the resultant surfaces for registration of intraoperative data. Direct comparison using the Dice metric showed average agreement of 0.93 between semi-automatic and hand segmentation results. Use of the segmented surfaces in closest point registration of intraoperative laser range scan data yielded average closest point distances of approximately 1 mm. Application of both inverse registration transforms from the previous step to all hand segmented image space points revealed that the distance variability introduced by registering to the semi-automatically segmented surface versus the hand segmented surface was typically less than 3 mm both near the tumor target and at distal points, including subsurface points. Use of the algorithm shortened user interaction time and provided results which were comparable to the gold standard of hand segmentation. Further, the use of the algorithm's resultant surfaces in image registration provided comparable transformations to surfaces produced by hand segmentation. These data support the applicability and utility of such an algorithm as part of an image guidance workflow.

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography.

PubMed

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-07

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography

NASA Astrophysics Data System (ADS)

Berthon, Beatrice; Marshall, Christopher; Evans, Mererid; Spezi, Emiliano

2016-07-01

Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on the optimal method to use, as different algorithms appear to perform better for different types of tumours. This work aimed to develop a predictive segmentation model, trained to automatically select and apply the best PET-AS method, according to the tumour characteristics. ATLAAS, the automatic decision tree-based learning algorithm for advanced segmentation is based on supervised machine learning using decision trees. The model includes nine PET-AS methods and was trained on a 100 PET scans with known true contour. A decision tree was built for each PET-AS algorithm to predict its accuracy, quantified using the Dice similarity coefficient (DSC), according to the tumour volume, tumour peak to background SUV ratio and a regional texture metric. The performance of ATLAAS was evaluated for 85 PET scans obtained from fillable and printed subresolution sandwich phantoms. ATLAAS showed excellent accuracy across a wide range of phantom data and predicted the best or near-best segmentation algorithm in 93% of cases. ATLAAS outperformed all single PET-AS methods on fillable phantom data with a DSC of 0.881, while the DSC for H&N phantom data was 0.819. DSCs higher than 0.650 were achieved in all cases. ATLAAS is an advanced automatic image segmentation algorithm based on decision tree predictive modelling, which can be trained on images with known true contour, to predict the best PET-AS method when the true contour is unknown. ATLAAS provides robust and accurate image segmentation with potential applications to radiation oncology.

A New Method of Synthetic Aperture Radar Image Reconstruction Using Modified Convolution Back-Projection Algorithm.

DTIC Science & Technology

1986-08-01

SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTIONAVAILABILITY OF REPORT N/A \\pproved for public release, 21b. OECLASS FI) CAT ) ON/OOWNGRAOING SCMEOLLE...from this set of projections. The Convolution Back-Projection (CBP) algorithm is widely used technique in Computer Aide Tomography ( CAT ). In this work...University of Illinois at Urbana-Champaign. 1985 Ac % DTICEl_ FCTE " AUG 1 11986 Urbana. Illinois U,) I A NEW METHOD OF SYNTHETIC APERTURE RADAR IMAGE

EIT image regularization by a new Multi-Objective Simulated Annealing algorithm.

PubMed

Castro Martins, Thiago; Sales Guerra Tsuzuki, Marcos

2015-01-01

Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

3D algebraic iterative reconstruction for cone-beam x-ray differential phase-contrast computed tomography.

PubMed

Fu, Jian; Hu, Xinhua; Velroyen, Astrid; Bech, Martin; Jiang, Ming; Pfeiffer, Franz

2015-01-01

Due to the potential of compact imaging systems with magnified spatial resolution and contrast, cone-beam x-ray differential phase-contrast computed tomography (DPC-CT) has attracted significant interest. The current proposed FDK reconstruction algorithm with the Hilbert imaginary filter will induce severe cone-beam artifacts when the cone-beam angle becomes large. In this paper, we propose an algebraic iterative reconstruction (AIR) method for cone-beam DPC-CT and report its experiment results. This approach considers the reconstruction process as the optimization of a discrete representation of the object function to satisfy a system of equations that describes the cone-beam DPC-CT imaging modality. Unlike the conventional iterative algorithms for absorption-based CT, it involves the derivative operation to the forward projections of the reconstructed intermediate image to take into account the differential nature of the DPC projections. This method is based on the algebraic reconstruction technique, reconstructs the image ray by ray, and is expected to provide better derivative estimates in iterations. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured with a three-grating interferometer and a mini-focus x-ray tube source. It is shown that the proposed method can reduce the cone-beam artifacts and performs better than FDK under large cone-beam angles. This algorithm is of interest for future cone-beam DPC-CT applications.

CT brush and CancerZap!: two video games for computed tomography dose minimization.

PubMed

Alvare, Graham; Gordon, Richard

2015-05-12

X-ray dose from computed tomography (CT) scanners has become a significant public health concern. All CT scanners spray x-ray photons across a patient, including those using compressive sensing algorithms. New technologies make it possible to aim x-ray beams where they are most needed to form a diagnostic or screening image. We have designed a computer game, CT Brush, that takes advantage of this new flexibility. It uses a standard MART algorithm (Multiplicative Algebraic Reconstruction Technique), but with a user defined dynamically selected subset of the rays. The image appears as the player moves the CT brush over an initially blank scene, with dose accumulating with every "mouse down" move. The goal is to find the "tumor" with as few moves (least dose) as possible. We have successfully implemented CT Brush in Java and made it available publicly, requesting crowdsourced feedback on improving the open source code. With this experience, we also outline a "shoot 'em up game" CancerZap! for photon limited CT. We anticipate that human computing games like these, analyzed by methods similar to those used to understand eye tracking, will lead to new object dependent CT algorithms that will require significantly less dose than object independent nonlinear and compressive sensing algorithms that depend on sprayed photons. Preliminary results suggest substantial dose reduction is achievable.

Anatomy-based algorithm for automatic segmentation of human diaphragm in noncontrast computed tomography images

PubMed Central

Karami, Elham; Wang, Yong; Gaede, Stewart; Lee, Ting-Yim; Samani, Abbas

2016-01-01

Abstract. In-depth understanding of the diaphragm’s anatomy and physiology has been of great interest to the medical community, as it is the most important muscle of the respiratory system. While noncontrast four-dimensional (4-D) computed tomography (CT) imaging provides an interesting opportunity for effective acquisition of anatomical and/or functional information from a single modality, segmenting the diaphragm in such images is very challenging not only because of the diaphragm’s lack of image contrast with its surrounding organs but also because of respiration-induced motion artifacts in 4-D CT images. To account for such limitations, we present an automatic segmentation algorithm, which is based on a priori knowledge of diaphragm anatomy. The novelty of the algorithm lies in using the diaphragm’s easy-to-segment contacting organs—including the lungs, heart, aorta, and ribcage—to guide the diaphragm’s segmentation. Obtained results indicate that average mean distance to the closest point between diaphragms segmented using the proposed technique and corresponding manual segmentation is 2.55±0.39  mm, which is favorable. An important feature of the proposed technique is that it is the first algorithm to delineate the entire diaphragm. Such delineation facilitates applications, where the diaphragm boundary conditions are required such as biomechanical modeling for in-depth understanding of the diaphragm physiology. PMID:27921072

Image recovery by removing stochastic artefacts identified as local asymmetries

NASA Astrophysics Data System (ADS)

Osterloh, K.; Bücherl, T.; Zscherpel, U.; Ewert, U.

2012-04-01

Stochastic artefacts are frequently encountered in digital radiography and tomography with neutrons. Most obviously, they are caused by ubiquitous scattered radiation hitting the CCD-sensor. They appear as scattered dots and, at higher frequency of occurrence, they may obscure the image. Some of these dotted interferences vary with time, however, a large portion of them remains persistent so the problem cannot be resolved by collecting stacks of images and to merge them to a median image. The situation becomes even worse in computed tomography (CT) where each artefact causes a circular pattern in the reconstructed plane. Therefore, these stochastic artefacts have to be removed completely and automatically while leaving the original image content untouched. A simplified image acquisition and artefact removal tool was developed at BAM and is available to interested users. Furthermore, an algorithm complying with all the requirements mentioned above was developed that reliably removes artefacts that could even exceed the size of a single pixel without affecting other parts of the image. It consists of an iterative two-step algorithm adjusting pixel values within a 3 × 3 matrix inside of a 5 × 5 kernel and the centre pixel only within a 3 × 3 kernel, resp. It has been applied to thousands of images obtained from the NECTAR facility at the FRM II in Garching, Germany, without any need of a visual control. In essence, the procedure consists of identifying and tackling asymmetric intensity distributions locally with recording each treatment of a pixel. Searching for the local asymmetry with subsequent correction rather than replacing individually identified pixels constitutes the basic idea of the algorithm. The efficiency of the proposed algorithm is demonstrated with a severely spoiled example of neutron radiography and tomography as compared with median filtering, the most convenient alternative approach by visual check, histogram and power spectra analysis.