Bayesian 2D Current Reconstruction from Magnetic Images
NASA Astrophysics Data System (ADS)
Clement, Colin B.; Bierbaum, Matthew K.; Nowack, Katja; Sethna, James P.
We employ a Bayesian image reconstruction scheme to recover 2D currents from magnetic flux imaged with scanning SQUIDs (Superconducting Quantum Interferometric Devices). Magnetic flux imaging is a versatile tool to locally probe currents and magnetic moments, however present reconstruction methods sacrifice resolution due to numerical instability. Using state-of-the-art blind deconvolution techniques we recover the currents, point-spread function and height of the SQUID loop by optimizing the probability of measuring an image. We obtain uncertainties on these quantities by sampling reconstructions. This generative modeling technique could be used to develop calibration protocols for scanning SQUIDs, to diagnose systematic noise in the imaging process, and can be applied to many tools beyond scanning SQUIDs.
3-D Reconstruction From 2-D Radiographic Images and Its Application to Clinical Veterinary Medicine
NASA Astrophysics Data System (ADS)
Hamamoto, Kazuhiko; Sato, Motoyoshi
3D imaging technique is very important and indispensable in diagnosis. The main stream of the technique is one in which 3D image is reconstructed from a set of slice images, such as X-ray CT and MRI. However, these systems require large space and high costs. On the other hand, a low cost and small size 3D imaging system is needed in clinical veterinary medicine, for example, in the case of diagnosis in X-ray car or pasture area. We propose a novel 3D imaging technique using 2-D X-ray radiographic images. This system can be realized by cheaper system than X-ray CT and enables to get 3D image in X-ray car or portable X-ray equipment. In this paper, a 3D visualization technique from 2-D radiographic images is proposed and several reconstructions are shown. These reconstructions are evaluated by veterinarians.
A two-step Hilbert transform method for 2D image reconstruction.
Noo, Frédéric; Clackdoyle, Rolf; Pack, Jed D
2004-09-01
The paper describes a new accurate two-dimensional (2D) image reconstruction method consisting of two steps. In the first step, the backprojected image is formed after taking the derivative of the parallel projection data. In the second step, a Hilbert filtering is applied along certain lines in the differentiated backprojection (DBP) image. Formulae for performing the DBP step in fanbeam geometry are also presented. The advantage of this two-step Hilbert transform approach is that in certain situations, regions of interest (ROIs) can be reconstructed from truncated projection data. Simulation results are presented that illustrate very similar reconstructed image quality using the new method compared to standard filtered backprojection, and that show the capability to correctly handle truncated projections. In particular, a simulation is presented of a wide patient whose projections are truncated laterally yet for which highly accurate ROI reconstruction is obtained. PMID:15470913
SNARK09 - a software package for reconstruction of 2D images from 1D projections.
Klukowska, Joanna; Davidi, Ran; Herman, Gabor T
2013-06-01
The problem of reconstruction of slices and volumes from 1D and 2D projections has arisen in a large number of scientific fields (including computerized tomography, electron microscopy, X-ray microscopy, radiology, radio astronomy and holography). Many different methods (algorithms) have been suggested for its solution. In this paper we present a software package, SNARK09, for reconstruction of 2D images from their 1D projections. In the area of image reconstruction, researchers often desire to compare two or more reconstruction techniques and assess their relative merits. SNARK09 provides a uniform framework to implement algorithms and evaluate their performance. It has been designed to treat both parallel and divergent projection geometries and can either create test data (with or without noise) for use by reconstruction algorithms or use data collected by another software or a physical device. A number of frequently-used classical reconstruction algorithms are incorporated. The package provides a means for easy incorporation of new algorithms for their testing, comparison and evaluation. It comes with tools for statistical analysis of the results and ten worked examples. PMID:23414602
3D reconstruction of a carotid bifurcation from 2D transversal ultrasound images.
Yeom, Eunseop; Nam, Kweon-Ho; Jin, Changzhu; Paeng, Dong-Guk; Lee, Sang-Joon
2014-12-01
Visualizing and analyzing the morphological structure of carotid bifurcations are important for understanding the etiology of carotid atherosclerosis, which is a major cause of stroke and transient ischemic attack. For delineation of vasculatures in the carotid artery, ultrasound examinations have been widely employed because of a noninvasive procedure without ionizing radiation. However, conventional 2D ultrasound imaging has technical limitations in observing the complicated 3D shapes and asymmetric vasodilation of bifurcations. This study aims to propose image-processing techniques for better 3D reconstruction of a carotid bifurcation in a rat by using 2D cross-sectional ultrasound images. A high-resolution ultrasound imaging system with a probe centered at 40MHz was employed to obtain 2D transversal images. The lumen boundaries in each transverse ultrasound image were detected by using three different techniques; an ellipse-fitting, a correlation mapping to visualize the decorrelation of blood flow, and the ellipse-fitting on the correlation map. When the results are compared, the third technique provides relatively good boundary extraction. The incomplete boundaries of arterial lumen caused by acoustic artifacts are somewhat resolved by adopting the correlation mapping and the distortion in the boundary detection near the bifurcation apex was largely reduced by using the ellipse-fitting technique. The 3D lumen geometry of a carotid artery was obtained by volumetric rendering of several 2D slices. For the 3D vasodilatation of the carotid bifurcation, lumen geometries at the contraction and expansion states were simultaneously depicted at various view angles. The present 3D reconstruction methods would be useful for efficient extraction and construction of the 3D lumen geometries of carotid bifurcations from 2D ultrasound images. PMID:24965564
GPU accelerated generation of digitally reconstructed radiographs for 2-D/3-D image registration.
Dorgham, Osama M; Laycock, Stephen D; Fisher, Mark H
2012-09-01
Recent advances in programming languages for graphics processing units (GPUs) provide developers with a convenient way of implementing applications which can be executed on the CPU and GPU interchangeably. GPUs are becoming relatively cheap, powerful, and widely available hardware components, which can be used to perform intensive calculations. The last decade of hardware performance developments shows that GPU-based computation is progressing significantly faster than CPU-based computation, particularly if one considers the execution of highly parallelisable algorithms. Future predictions illustrate that this trend is likely to continue. In this paper, we introduce a way of accelerating 2-D/3-D image registration by developing a hybrid system which executes on the CPU and utilizes the GPU for parallelizing the generation of digitally reconstructed radiographs (DRRs). Based on the advancements of the GPU over the CPU, it is timely to exploit the benefits of many-core GPU technology by developing algorithms for DRR generation. Although some previous work has investigated the rendering of DRRs using the GPU, this paper investigates approximations which reduce the computational overhead while still maintaining a quality consistent with that needed for 2-D/3-D registration with sufficient accuracy to be clinically acceptable in certain applications of radiation oncology. Furthermore, by comparing implementations of 2-D/3-D registration on the CPU and GPU, we investigate current performance and propose an optimal framework for PC implementations addressing the rigid registration problem. Using this framework, we are able to render DRR images from a 256×256×133 CT volume in ~24 ms using an NVidia GeForce 8800 GTX and in ~2 ms using NVidia GeForce GTX 580. In addition to applications requiring fast automatic patient setup, these levels of performance suggest image-guided radiation therapy at video frame rates is technically feasible using relatively low cost PC
An active microwave imaging system for reconstruction of 2-D electrical property distributions.
Meaney, P M; Paulsen, K D; Hartov, A; Crane, R K
1995-10-01
The goal of this work is to develop a microwave-based imaging system for hyperthermia treatment monitoring and assessment. Toward this end, a four transmit channel and four receive channel hardware device and concomitant image reconstruction algorithm have been realized. The hardware is designed to measure electric fields (i.e., amplitude and phase) at various locations in a phantom tank with and without the presence of various heterogeneities using standard heterodyning principles. Particular attention has been paid to designing a receiver with better than 115 dB of linear dynamic range which is necessary for imaging biological tissue which often has very high conductivity, especially for tissues with high water content. A calibration procedure has been developed to compensate for signal loss due to three-dimensional radiation in the measured data, since the reconstruction process is only two-dimensional at the present time. Results are shown which demonstrate the stability and accuracy of the measurement system, the extent to which the forward computational model agrees with the measured field distribution when the electrical properties are known, and image reconstructions of electrically unknown targets of varying diameter. In the latter case, images of both the reactive and resistive component of the electrical property distribution have been recoverable. Quantitative information on object location, size, and electrical properties results when the target is approximately one-half wavelength in size. Images of smaller objects lack the same level of quantitative information, but remain qualitatively correct. PMID:8582719
Defrise, Michel; Gullberg, Grant T.
2006-04-05
We give an overview of the role of Physics in Medicine andBiology in development of tomographic reconstruction algorithms. We focuson imaging modalities involving ionizing radiation, CT, PET and SPECT,and cover a wide spectrum of reconstruction problems, starting withclassical 2D tomogra tomography in the 1970s up to 4D and 5D problemsinvolving dynamic imaging of moving organs.
Assessing 3D tunnel position in ACL reconstruction using a novel single image 3D-2D registration
NASA Astrophysics Data System (ADS)
Kang, X.; Yau, W. P.; Otake, Y.; Cheung, P. Y. S.; Hu, Y.; Taylor, R. H.
2012-02-01
The routinely used procedure for evaluating tunnel positions following anterior cruciate ligament (ACL) reconstructions based on standard X-ray images is known to pose difficulties in terms of obtaining accurate measures, especially in providing three-dimensional tunnel positions. This is largely due to the variability in individual knee joint pose relative to X-ray plates. Accurate results were reported using postoperative CT. However, its extensive usage in clinical routine is hampered by its major requirement of having CT scans of individual patients, which is not available for most ACL reconstructions. These difficulties are addressed through the proposed method, which aligns a knee model to X-ray images using our novel single-image 3D-2D registration method and then estimates the 3D tunnel position. In the proposed method, the alignment is achieved by using a novel contour-based 3D-2D registration method wherein image contours are treated as a set of oriented points. However, instead of using some form of orientation weighting function and multiplying it with a distance function, we formulate the 3D-2D registration as a probability density estimation using a mixture of von Mises-Fisher-Gaussian (vMFG) distributions and solve it through an expectation maximization (EM) algorithm. Compared with the ground-truth established from postoperative CT, our registration method in an experiment using a plastic phantom showed accurate results with errors of (-0.43°+/-1.19°, 0.45°+/-2.17°, 0.23°+/-1.05°) and (0.03+/-0.55, -0.03+/-0.54, -2.73+/-1.64) mm. As for the entry point of the ACL tunnel, one of the key measurements, it was obtained with high accuracy of 0.53+/-0.30 mm distance errors.
Fooprateepsiri, Rerkchai; Kurutach, Werasak
2014-03-01
Face authentication is a biometric classification method that verifies the identity of a user based on image of their face. Accuracy of the authentication is reduced when the pose, illumination and expression of the training face images are different than the testing image. The methods in this paper are designed to improve the accuracy of a features-based face recognition system when the pose between the input images and training images are different. First, an efficient 2D-to-3D integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumination. Second, realistic virtual faces with different poses are synthesized based on the personalized 3D face to characterize the face subspace. Finally, face recognition is conducted based on these representative virtual faces. Compared with other related works, this framework has the following advantages: (1) only one single frontal face is required for face recognition, which avoids the burdensome enrollment work; and (2) the synthesized face samples provide the capability to conduct recognition under difficult conditions like complex pose, illumination and expression. From the experimental results, we conclude that the proposed method improves the accuracy of face recognition by varying the pose, illumination and expression. PMID:24529782
Tomosynthesis imaging with 2D scanning trajectories
NASA Astrophysics Data System (ADS)
Khare, Kedar; Claus, Bernhard E. H.; Eberhard, Jeffrey W.
2011-03-01
Tomosynthesis imaging in chest radiography provides volumetric information with the potential for improved diagnostic value when compared to the standard AP or LAT projections. In this paper we explore the image quality benefits of 2D scanning trajectories when coupled with advanced image reconstruction approaches. It is intuitively clear that 2D trajectories provide projection data that is more complete in terms of Radon space filling, when compared with conventional tomosynthesis using a linearly scanned source. Incorporating this additional information for obtaining improved image quality is, however, not a straightforward problem. The typical tomosynthesis reconstruction algorithms are based on direct inversion methods e.g. Filtered Backprojection (FBP) or iterative algorithms that are variants of the Algebraic Reconstruction Technique (ART). The FBP approach is fast and provides high frequency details in the image but at the same time introduces streaking artifacts degrading the image quality. The iterative methods can reduce the image artifacts by using image priors but suffer from a slow convergence rate, thereby producing images lacking high frequency details. In this paper we propose using a fast converging optimal gradient iterative scheme that has advantages of both the FBP and iterative methods in that it produces images with high frequency details while reducing the image artifacts. We show that using favorable 2D scanning trajectories along with the proposed reconstruction method has the advantage of providing improved depth information for structures such as the spine and potentially producing images with more isotropic resolution.
Stille, Maik; Smith, Edward J; Crum, William R; Modo, Michel
2013-09-30
To validate and add value to non-invasive imaging techniques, the corresponding histology is required to establish biological correlates. We present an efficient, semi-automated image-processing pipeline that uses immunohistochemically stained sections to reconstruct a 3D brain volume from 2D histological images before registering these with the corresponding 3D in vivo magnetic resonance images (MRI). A multistep registration procedure that first aligns the "global" volume by using the centre of mass and then applies a rigid and affine alignment based on signal intensities is described. This technique was applied to a training set of three rat brain volumes before being validated on three normal brains. Application of the approach to register "abnormal" images from a rat model of stroke allowed the neurobiological correlates of the variations in the hyper-intense MRI signal intensity caused by infarction to be investigated. For evaluation, the corresponding anatomical landmarks in MR and histology were defined to measure the registration accuracy. A registration error of 0.249 mm (approximately one in-plane voxel dimension) was evident in healthy rat brains and of 0.323 mm in a rodent model of stroke. The proposed reconstruction and registration pipeline allowed for the precise analysis of non-invasive MRI and corresponding microstructural histological features in 3D. We were thus able to interrogate histology to deduce the cause of MRI signal variations in the lesion cavity and the peri-infarct area. PMID:23816399
Hou, Gary Y.; Provost, Jean; Grondin, Julien; Wang, Shutao; Marquet, Fabrice; Bunting, Ethan; Konofagou, Elisa E.
2015-01-01
Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed High-Intensity Focused Ultrasound (HIFU) treatment monitoring method. HMIFU utilizes an Amplitude-Modulated (fAM = 25 Hz) HIFU beam to induce a localized focal oscillatory motion, which is simultaneously estimated and imaged by confocally-aligned imaging transducer. HMIFU feasibilities have been previously shown in silico, in vitro, and in vivo in 1-D or 2-D monitoring of HIFU treatment. The objective of this study is to develop and show the feasibility of a novel fast beamforming algorithm for image reconstruction using GPU-based sparse-matrix operation with real-time feedback. In this study, the algorithm was implemented onto a fully integrated, clinically relevant HMIFU system composed of a 93-element HIFU transducer (fcenter = 4.5MHz) and coaxially-aligned 64-element phased array (fcenter = 2.5MHz) for displacement excitation and motion estimation, respectively. A single transmit beam with divergent beam transmit was used while fast beamforming was implemented using a GPU-based delay-and-sum method and a sparse-matrix operation. Axial HMI displacements were then estimated from the RF signals using a 1-D normalized cross-correlation method and streamed to a graphic user interface. The present work developed and implemented a sparse matrix beamforming onto a fully-integrated, clinically relevant system, which can stream displacement images up to 15 Hz using a GPU-based processing, an increase of 100 fold in rate of streaming displacement images compared to conventional CPU-based conventional beamforming and reconstruction processing. The achieved feedback rate is also currently the fastest and only approach that does not require interrupting the HIFU treatment amongst the acoustic radiation force based HIFU imaging techniques. Results in phantom experiments showed reproducible displacement imaging, and monitoring of twenty two in vitro HIFU treatments using the new 2D system showed a
Ng, Angela; Nguyen, Thao-Nguyen; Moseley, Joanne L.; Hodgson, David C.; Sharpe, Michael B.; Brock, Kristy K.
2010-03-15
Purpose: Late complications (cardiac toxicities, secondary lung, and breast cancer) remain a significant concern in the radiation treatment of Hodgkin's lymphoma (HL). To address this issue, predictive dose-risk models could potentially be used to estimate radiotherapy-related late toxicities. This study investigates the use of deformable image registration (DIR) and navigator channels (NCs) to reconstruct 3D lung models from 2D radiographic planning images, in order to retrospectively calculate the treatment dose exposure to HL patients treated with 2D planning, which are now experiencing late effects. Methods: Three-dimensional planning CT images of 52 current HL patients were acquired. 12 image sets were used to construct a male and a female population lung model. 23 ''Reference'' images were used to generate lung deformation adaptation templates, constructed by deforming the population model into each patient-specific lung geometry using a biomechanical-based DIR algorithm, MORFEUS. 17 ''Test'' patients were used to test the accuracy of the reconstruction technique by adapting existing templates using 2D digitally reconstructed radiographs. The adaptation process included three steps. First, a Reference patient was matched to a Test patient by thorax measurements. Second, four NCs (small regions of interest) were placed on the lung boundary to calculate 1D differences in lung edges. Third, the Reference lung model was adapted to the Test patient's lung using the 1D edge differences. The Reference-adapted Test model was then compared to the 3D lung contours of the actual Test patient by computing their percentage volume overlap (POL) and Dice coefficient. Results: The average percentage overlapping volumes and Dice coefficient expressed as a percentage between the adapted and actual Test models were found to be 89.2{+-}3.9% (Right lung=88.8%; Left lung=89.6%) and 89.3{+-}2.7% (Right=88.5%; Left=90.2%), respectively. Paired T-tests demonstrated that the
Staring 2-D hadamard transform spectral imager
Gentry, Stephen M.; Wehlburg, Christine M.; Wehlburg, Joseph C.; Smith, Mark W.; Smith, Jody L.
2006-02-07
A staring imaging system inputs a 2D spatial image containing multi-frequency spectral information. This image is encoded in one dimension of the image with a cyclic Hadamarid S-matrix. The resulting image is detecting with a spatial 2D detector; and a computer applies a Hadamard transform to recover the encoded image.
Photorealistic image synthesis and camera validation from 2D images
NASA Astrophysics Data System (ADS)
Santos Ferrer, Juan C.; González Chévere, David; Manian, Vidya
2014-06-01
This paper presents a new 3D scene reconstruction technique using the Unity 3D game engine. The method presented here allow us to reconstruct the shape of simple objects and more complex ones from multiple 2D images, including infrared and digital images from indoor scenes and only digital images from outdoor scenes and then add the reconstructed object to the simulated scene created in Unity 3D, these scenes are then validated with real world scenes. The method used different cameras settings and explores different properties in the reconstructions of the scenes including light, color, texture, shapes and different views. To achieve the highest possible resolution, it was necessary the extraction of partial textures from visible surfaces. To recover the 3D shapes and the depth of simple objects that can be represented by the geometric bodies, there geometric characteristics were used. To estimate the depth of more complex objects the triangulation method was used, for this the intrinsic and extrinsic parameters were calculated using geometric camera calibration. To implement the methods mentioned above the Matlab tool was used. The technique presented here also let's us to simulate small simple videos, by reconstructing a sequence of multiple scenes of the video separated by small margins of time. To measure the quality of the reconstructed images and video scenes the Fast Low Band Model (FLBM) metric from the Video Quality Measurement (VQM) software was used. Low bandwidth perception based features include edges and motion.
Sparse radar imaging using 2D compressed sensing
NASA Astrophysics Data System (ADS)
Hou, Qingkai; Liu, Yang; Chen, Zengping; Su, Shaoying
2014-10-01
Radar imaging is an ill-posed linear inverse problem and compressed sensing (CS) has been proved to have tremendous potential in this field. This paper surveys the theory of radar imaging and a conclusion is drawn that the processing of ISAR imaging can be denoted mathematically as a problem of 2D sparse decomposition. Based on CS, we propose a novel measuring strategy for ISAR imaging radar and utilize random sub-sampling in both range and azimuth dimensions, which will reduce the amount of sampling data tremendously. In order to handle 2D reconstructing problem, the ordinary solution is converting the 2D problem into 1D by Kronecker product, which will increase the size of dictionary and computational cost sharply. In this paper, we introduce the 2D-SL0 algorithm into the reconstruction of imaging. It is proved that 2D-SL0 can achieve equivalent result as other 1D reconstructing methods, but the computational complexity and memory usage is reduced significantly. Moreover, we will state the results of simulating experiments and prove the effectiveness and feasibility of our method.
NASA Astrophysics Data System (ADS)
Siddeq, M. M.; Rodrigues, M. A.
2015-09-01
Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.
Gordon, Jeremy W.; Niles, David J.; Fain, Sean B.; Johnson, Kevin M.
2014-01-01
Purpose To develop a novel imaging technique to reduce the number of excitations and required scan time for hyperpolarized 13C imaging. Methods A least-squares based optimization and reconstruction is developed to simultaneously solve for both spatial and spectral encoding. By jointly solving both domains, spectral imaging can potentially be performed with a spatially oversampled single echo spiral acquisition. Digital simulations, phantom experiments, and initial in vivo hyperpolarized [1-13C]pyruvate experiments were performed to assess the performance of the algorithm as compared to a multi-echo approach. Results Simulations and phantom data indicate that accurate single echo imaging is possible when coupled with oversampling factors greater than six (corresponding to a worst case of pyruvate to metabolite ratio < 9%), even in situations of substantial T2* decay and B0 heterogeneity. With lower oversampling rates, two echoes are required for similar accuracy. These results were confirmed with in vivo data experiments, showing accurate single echo spectral imaging with an oversampling factor of 7 and two echo imaging with an oversampling factor of 4. Conclusion The proposed k-t approach increases data acquisition efficiency by reducing the number of echoes required to generate spectroscopic images, thereby allowing accelerated acquisition speed, preserved polarization, and/or improved temporal or spatial resolution. Magn Reson Med PMID:23716402
2D microwave imaging reflectometer electronics
Spear, A. G.; Domier, C. W. Hu, X.; Muscatello, C. M.; Ren, X.; Luhmann, N. C.; Tobias, B. J.
2014-11-15
A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program.
2D microwave imaging reflectometer electronics
NASA Astrophysics Data System (ADS)
Spear, A. G.; Domier, C. W.; Hu, X.; Muscatello, C. M.; Ren, X.; Tobias, B. J.; Luhmann, N. C.
2014-11-01
A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program.
2D microwave imaging reflectometer electronics.
Spear, A G; Domier, C W; Hu, X; Muscatello, C M; Ren, X; Tobias, B J; Luhmann, N C
2014-11-01
A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program. PMID:25430247
2D/3D Image Registration using Regression Learning
Chou, Chen-Rui; Frederick, Brandon; Mageras, Gig; Chang, Sha; Pizer, Stephen
2013-01-01
In computer vision and image analysis, image registration between 2D projections and a 3D image that achieves high accuracy and near real-time computation is challenging. In this paper, we propose a novel method that can rapidly detect an object’s 3D rigid motion or deformation from a 2D projection image or a small set thereof. The method is called CLARET (Correction via Limited-Angle Residues in External Beam Therapy) and consists of two stages: registration preceded by shape space and regression learning. In the registration stage, linear operators are used to iteratively estimate the motion/deformation parameters based on the current intensity residue between the target projec-tion(s) and the digitally reconstructed radiograph(s) (DRRs) of the estimated 3D image. The method determines the linear operators via a two-step learning process. First, it builds a low-order parametric model of the image region’s motion/deformation shape space from its prior 3D images. Second, using learning-time samples produced from the 3D images, it formulates the relationships between the model parameters and the co-varying 2D projection intensity residues by multi-scale linear regressions. The calculated multi-scale regression matrices yield the coarse-to-fine linear operators used in estimating the model parameters from the 2D projection intensity residues in the registration. The method’s application to Image-guided Radiation Therapy (IGRT) requires only a few seconds and yields good results in localizing a tumor under rigid motion in the head and neck and under respiratory deformation in the lung, using one treatment-time imaging 2D projection or a small set thereof. PMID:24058278
Reconstruction techniques for optoacoustic imaging
NASA Astrophysics Data System (ADS)
Frenz, Martin; Koestli, Kornel P.; Paltauf, Guenther; Schmidt-Kloiber, Heinz; Weber, Heinz P.
2001-06-01
Optoacoustics is a method to gain information from inside a tissue. This is done by irradiating a tissue with a short light pulse, which generates a pressure distribution inside the tissue that mirrors the absorber distribution. The pressure distribution measured on the tissue-surface allows, by applying a back-projection method, to calculate a tomography image of the absorber distribution. This study presents a novel computational algorithm based on Fourier transform, which, at least in principle, yields an exact 3D reconstruction of the distribution of absorbed energy density inside turbid media. The reconstruction is based on 2D pressure distributions captured outside at different times. The FFT reconstruction algorithm is first tested in the back projection of simulated pressure transients of small model absorbers, and finally applied to reconstruct the distribution of artificial blood vessels in three dimensions.
Overview of Image Reconstruction
Marr, R. B.
1980-04-01
Image reconstruction (or computerized tomography, etc.) is any process whereby a function, f, on R^{n} is estimated from empirical data pertaining to its integrals, ∫f(x) dx, for some collection of hyperplanes of dimension k < n. The paper begins with background information on how image reconstruction problems have arisen in practice, and describes some of the application areas of past or current interest; these include radioastronomy, optics, radiology and nuclear medicine, electron microscopy, acoustical imaging, geophysical tomography, nondestructive testing, and NMR zeugmatography. Then the various reconstruction algorithms are discussed in five classes: summation, or simple back-projection; convolution, or filtered back-projection; Fourier and other functional transforms; orthogonal function series expansion; and iterative methods. Certain more technical mathematical aspects of image reconstruction are considered from the standpoint of uniqueness, consistency, and stability of solution. The paper concludes by presenting certain open problems. 73 references. (RWR)
Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.
de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R
2008-01-01
Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |< 0.083 mm for translations and |mu| < 0.023 degrees for rotations. The precision sigma in x-, y-, and z-direction was 0.090, 0.077, and 0.220 mm for translations and 0.155 degrees , 0.243 degrees , and 0.074 degrees for rotations. Our results show that the accuracy and precision of in vitro IBRSA, performed under ideal laboratory conditions, are lower than in vitro standard RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications. PMID:17706656
Optical imaging systems analyzed with a 2D template.
Haim, Harel; Konforti, Naim; Marom, Emanuel
2012-05-10
Present determination of optical imaging systems specifications are based on performance values and modulation transfer function results carried with a 1D resolution template (such as the USAF resolution target or spoke templates). Such a template allows determining image quality, resolution limit, and contrast. Nevertheless, the conventional 1D template does not provide satisfactory results, since most optical imaging systems handle 2D objects for which imaging system response may be different by virtue of some not readily observable spatial frequencies. In this paper we derive and analyze contrast transfer function results obtained with 1D as well as 2D templates. PMID:22614498
Zhou, Zhi; Liu, Xiaoxiao; Long, Brian; Peng, Hanchuan
2016-01-01
Efficient and accurate digital reconstruction of neurons from large-scale 3D microscopic images remains a challenge in neuroscience. We propose a new automatic 3D neuron reconstruction algorithm, TReMAP, which utilizes 3D Virtual Finger (a reverse-mapping technique) to detect 3D neuron structures based on tracing results on 2D projection planes. Our fully automatic tracing strategy achieves close performance with the state-of-the-art neuron tracing algorithms, with the crucial advantage of efficient computation (much less memory consumption and parallel computation) for large-scale images. PMID:26306866
Augmented Likelihood Image Reconstruction.
Stille, Maik; Kleine, Matthias; Hägele, Julian; Barkhausen, Jörg; Buzug, Thorsten M
2016-01-01
The presence of high-density objects remains an open problem in medical CT imaging. Data of projections passing through objects of high density, such as metal implants, are dominated by noise and are highly affected by beam hardening and scatter. Reconstructed images become less diagnostically conclusive because of pronounced artifacts that manifest as dark and bright streaks. A new reconstruction algorithm is proposed with the aim to reduce these artifacts by incorporating information about shape and known attenuation coefficients of a metal implant. Image reconstruction is considered as a variational optimization problem. The afore-mentioned prior knowledge is introduced in terms of equality constraints. An augmented Lagrangian approach is adapted in order to minimize the associated log-likelihood function for transmission CT. During iterations, temporally appearing artifacts are reduced with a bilateral filter and new projection values are calculated, which are used later on for the reconstruction. A detailed evaluation in cooperation with radiologists is performed on software and hardware phantoms, as well as on clinically relevant patient data of subjects with various metal implants. Results show that the proposed reconstruction algorithm is able to outperform contemporary metal artifact reduction methods such as normalized metal artifact reduction. PMID:26208310
Recovering 3D tumor locations from 2D bioluminescence images and registration with CT images
NASA Astrophysics Data System (ADS)
Huang, Xiaolei; Metaxas, Dimitris N.; Menon, Lata G.; Mayer-Kuckuk, Philipp; Bertino, Joseph R.; Banerjee, Debabrata
2006-02-01
In this paper, we introduce a novel and efficient algorithm for reconstructing the 3D locations of tumor sites from a set of 2D bioluminescence images which are taken by a same camera but after continually rotating the object by a small angle. Our approach requires a much simpler set up than those using multiple cameras, and the algorithmic steps in our framework are efficient and robust enough to facilitate its use in analyzing the repeated imaging of a same animal transplanted with gene marked cells. In order to visualize in 3D the structure of the tumor, we also co-register the BLI-reconstructed crude structure with detailed anatomical structure extracted from high-resolution microCT on a single platform. We present our method using both phantom studies and real studies on small animals.
2-D Imaging of Electron Temperature in Tokamak Plasmas
T. Munsat; E. Mazzucato; H. Park; C.W. Domier; M. Johnson; N.C. Luhmann Jr.; J. Wang; Z. Xia; I.G.J. Classen; A.J.H. Donne; M.J. van de Pol
2004-07-08
By taking advantage of recent developments in millimeter wave imaging technology, an Electron Cyclotron Emission Imaging (ECEI) instrument, capable of simultaneously measuring 128 channels of localized electron temperature over a 2-D map in the poloidal plane, has been developed for the TEXTOR tokamak. Data from the new instrument, detailing the MHD activity associated with a sawtooth crash, is presented.
MODEL-BASED IMAGE RECONSTRUCTION FOR MRI
Fessler, Jeffrey A.
2010-01-01
Magnetic resonance imaging (MRI) is a sophisticated and versatile medical imaging modality. Traditionally, MR images are reconstructed from the raw measurements by a simple inverse 2D or 3D fast Fourier transform (FFT). However, there are a growing number of MRI applications where a simple inverse FFT is inadequate, e.g., due to non-Cartesian sampling patterns, non-Fourier physical effects, nonlinear magnetic fields, or deliberate under-sampling to reduce scan times. Such considerations have led to increasing interest in methods for model-based image reconstruction in MRI. PMID:21135916
Image Reconstruction Using Analysis Model Prior.
Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping
2016-01-01
The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171
Image Reconstruction Using Analysis Model Prior
Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping
2016-01-01
The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171
Focusing surface wave imaging with flexible 2D array
NASA Astrophysics Data System (ADS)
Zhou, Shiyuan; Fu, Junqiang; Li, Zhe; Xu, Chunguang; Xiao, Dingguo; Wang, Shaohan
2016-04-01
Curved surface is widely exist in key parts of energy and power equipment, such as, turbine blade cylinder block and so on. Cycling loading and harsh working condition of enable fatigue cracks appear on the surface. The crack should be found in time to avoid catastrophic damage to the equipment. A flexible 2D array transducer was developed. 2D Phased Array focusing method (2DPA), Mode-Spatial Double Phased focusing method (MSDPF) and the imaging method using the flexible 2D array probe are studied. Experiments using these focusing and imaging method are carried out. Surface crack image is obtained with both 2DPA and MSDPF focusing method. It have been proved that MSDPF can be more adaptable for curved surface and more calculate efficient than 2DPA.
LOFAR sparse image reconstruction
NASA Astrophysics Data System (ADS)
Garsden, H.; Girard, J. N.; Starck, J. L.; Corbel, S.; Tasse, C.; Woiselle, A.; McKean, J. P.; van Amesfoort, A. S.; Anderson, J.; Avruch, I. M.; Beck, R.; Bentum, M. J.; Best, P.; Breitling, F.; Broderick, J.; Brüggen, M.; Butcher, H. R.; Ciardi, B.; de Gasperin, F.; de Geus, E.; de Vos, M.; Duscha, S.; Eislöffel, J.; Engels, D.; Falcke, H.; Fallows, R. A.; Fender, R.; Ferrari, C.; Frieswijk, W.; Garrett, M. A.; Grießmeier, J.; Gunst, A. W.; Hassall, T. E.; Heald, G.; Hoeft, M.; Hörandel, J.; van der Horst, A.; Juette, E.; Karastergiou, A.; Kondratiev, V. I.; Kramer, M.; Kuniyoshi, M.; Kuper, G.; Mann, G.; Markoff, S.; McFadden, R.; McKay-Bukowski, D.; Mulcahy, D. D.; Munk, H.; Norden, M. J.; Orru, E.; Paas, H.; Pandey-Pommier, M.; Pandey, V. N.; Pietka, G.; Pizzo, R.; Polatidis, A. G.; Renting, A.; Röttgering, H.; Rowlinson, A.; Schwarz, D.; Sluman, J.; Smirnov, O.; Stappers, B. W.; Steinmetz, M.; Stewart, A.; Swinbank, J.; Tagger, M.; Tang, Y.; Tasse, C.; Thoudam, S.; Toribio, C.; Vermeulen, R.; Vocks, C.; van Weeren, R. J.; Wijnholds, S. J.; Wise, M. W.; Wucknitz, O.; Yatawatta, S.; Zarka, P.; Zensus, A.
2015-03-01
Context. The LOw Frequency ARray (LOFAR) radio telescope is a giant digital phased array interferometer with multiple antennas distributed in Europe. It provides discrete sets of Fourier components of the sky brightness. Recovering the original brightness distribution with aperture synthesis forms an inverse problem that can be solved by various deconvolution and minimization methods. Aims: Recent papers have established a clear link between the discrete nature of radio interferometry measurement and the "compressed sensing" (CS) theory, which supports sparse reconstruction methods to form an image from the measured visibilities. Empowered by proximal theory, CS offers a sound framework for efficient global minimization and sparse data representation using fast algorithms. Combined with instrumental direction-dependent effects (DDE) in the scope of a real instrument, we developed and validated a new method based on this framework. Methods: We implemented a sparse reconstruction method in the standard LOFAR imaging tool and compared the photometric and resolution performance of this new imager with that of CLEAN-based methods (CLEAN and MS-CLEAN) with simulated and real LOFAR data. Results: We show that i) sparse reconstruction performs as well as CLEAN in recovering the flux of point sources; ii) performs much better on extended objects (the root mean square error is reduced by a factor of up to 10); and iii) provides a solution with an effective angular resolution 2-3 times better than the CLEAN images. Conclusions: Sparse recovery gives a correct photometry on high dynamic and wide-field images and improved realistic structures of extended sources (of simulated and real LOFAR datasets). This sparse reconstruction method is compatible with modern interferometric imagers that handle DDE corrections (A- and W-projections) required for current and future instruments such as LOFAR and SKA.
Real-time 2-D temperature imaging using ultrasound.
Liu, Dalong; Ebbini, Emad S
2010-01-01
We have previously introduced methods for noninvasive estimation of temperature change using diagnostic ultrasound. The basic principle was validated both in vitro and in vivo by several groups worldwide. Some limitations remain, however, that have prevented these methods from being adopted in monitoring and guidance of minimally invasive thermal therapies, e.g., RF ablation and high-intensity-focused ultrasound (HIFU). In this letter, we present first results from a real-time system for 2-D imaging of temperature change using pulse-echo ultrasound. The front end of the system is a commercially available scanner equipped with a research interface, which allows the control of imaging sequence and access to the RF data in real time. A high-frame-rate 2-D RF acquisition mode, M2D, is used to capture the transients of tissue motion/deformations in response to pulsed HIFU. The M2D RF data is streamlined to the back end of the system, where a 2-D temperature imaging algorithm based on speckle tracking is implemented on a graphics processing unit. The real-time images of temperature change are computed on the same spatial and temporal grid of the M2D RF data, i.e., no decimation. Verification of the algorithm was performed by monitoring localized HIFU-induced heating of a tissue-mimicking elastography phantom. These results clearly demonstrate the repeatability and sensitivity of the algorithm. Furthermore, we present in vitro results demonstrating the possible use of this algorithm for imaging changes in tissue parameters due to HIFU-induced lesions. These results clearly demonstrate the value of the real-time data streaming and processing in monitoring, and guidance of minimally invasive thermotherapy. PMID:19884075
2dx--user-friendly image processing for 2D crystals.
Gipson, Bryant; Zeng, Xiangyan; Zhang, Zi Yan; Stahlberg, Henning
2007-01-01
Electron crystallography determines the structure of two-dimensional (2D) membrane protein crystals and other 2D crystal systems. Cryo-transmission electron microscopy records high-resolution electron micrographs, which require computer processing for three-dimensional structure reconstruction. We present a new software system 2dx, which is designed as a user-friendly, platform-independent software package for electron crystallography. 2dx assists in the management of an image-processing project, guides the user through the processing of 2D crystal images, and provides transparence for processing tasks and results. Algorithms are implemented in the form of script templates reminiscent of c-shell scripts. These templates can be easily modified or replaced by the user and can also execute modular stand-alone programs from the MRC software or from other image processing software packages. 2dx is available under the GNU General Public License at 2dx.org. PMID:17055742
Topology-Preserving Rigid Transformation of 2D Digital Images.
Ngo, Phuc; Passat, Nicolas; Kenmochi, Yukiko; Talbot, Hugues
2014-02-01
We provide conditions under which 2D digital images preserve their topological properties under rigid transformations. We consider the two most common digital topology models, namely dual adjacency and well-composedness. This paper leads to the proposal of optimal preprocessing strategies that ensure the topological invariance of images under arbitrary rigid transformations. These results and methods are proved to be valid for various kinds of images (binary, gray-level, label), thus providing generic and efficient tools, which can be used in particular in the context of image registration and warping. PMID:26270925
Snapshot 2D tomography via coded aperture x-ray scatter imaging
MacCabe, Kenneth P.; Holmgren, Andrew D.; Tornai, Martin P.; Brady, David J.
2015-01-01
This paper describes a fan beam coded aperture x-ray scatter imaging system which acquires a tomographic image from each snapshot. This technique exploits cylindrical symmetry of the scattering cross section to avoid the scanning motion typically required by projection tomography. We use a coded aperture with a harmonic dependence to determine range, and a shift code to determine cross-range. Here we use a forward-scatter configuration to image 2D objects and use serial exposures to acquire tomographic video of motion within a plane. Our reconstruction algorithm also estimates the angular dependence of the scattered radiance, a step toward materials imaging and identification. PMID:23842254
A 2-D ECE Imaging Diagnostic for TEXTOR
NASA Astrophysics Data System (ADS)
Wang, J.; Deng, B. H.; Domier, C. W.; Luhmann, H. Lu, Jr.
2002-11-01
A true 2-D extension to the UC Davis ECE Imaging (ECEI) concept is under development for installation on the TEXTOR tokamak in 2003. This combines the use of linear arrays with multichannel conventional wideband heterodyne ECE radiometers to provide a true 2-D imaging system. This is in contrast to current 1-D ECEI systems in which 2-D images are obtained through the use of multiple plasma discharges (varying the scanned emission frequency each discharge). Here, each array element of the 20 channel mixer array measures plasma emission at 16 simultaneous frequencies to form a 16x20 image of the plasma electron temperature Te. Correlation techniques can then be applied to any pair of the 320 image elements to study both radial and poloidal characteristics of turbulent Te fluctuations. The system relies strongly on the development of low cost, wideband (2-18 GHz) IF detection electronics for use in both ECE Imaging as well as conventional heterodyne ECE radiometry. System details, with a strong focus on the wideband IF electronics development, will be presented. *Supported by U.S. DoE Contracts DE-FG03-95ER54295 and DE-FG03-99ER54531.
Xie, Donghao; Ji, Ding-Kun; Zhang, Yue; Cao, Jun; Zheng, Hu; Liu, Lin; Zang, Yi; Li, Jia; Chen, Guo-Rong; James, Tony D; He, Xiao-Peng
2016-08-01
Here we demonstrate that 2D MoS2 can enhance the receptor-targeting and imaging ability of a fluorophore-labelled ligand. The 2D MoS2 has an enhanced working concentration range when compared with graphene oxide, resulting in the improved imaging of both cell and tissue samples. PMID:27378648
Evaluation of the channelized Hotelling observer for signal detection in 2D tomographic imaging
NASA Astrophysics Data System (ADS)
LaRoque, Samuel J.; Sidky, Emil Y.; Edwards, Darrin C.; Pan, Xiaochuan
2007-03-01
Signal detection by the channelized Hotelling (ch-Hotelling) observer is studied for tomographic application by employing a small, tractable 2D model of a computed tomography (CT) system. The primary goal of this manuscript is to develop a practical method for evaluating the ch-Hotelling observer that can generalize to larger 3D cone-beam CT systems. The use of the ch-Hotelling observer for evaluating tomographic image reconstruction algorithms is also demonstrated. For a realistic model for CT, the ch-Hotelling observer can be a good approximation to the ideal observer. The ch-Hotelling observer is applied to both the projection data and the reconstructed images. The difference in signal-to-noise ratio for signal detection in both of these domains provides a metric for evaluating the image reconstruction algorithm.
Semiregular solid texturing from 2D image exemplars.
Du, Song-Pei; Hu, Shi-Min; Martin, Ralph R
2013-03-01
Solid textures, comprising 3D particles embedded in a matrix in a regular or semiregular pattern, are common in natural and man-made materials, such as brickwork, stone walls, plant cells in a leaf, etc. We present a novel technique for synthesizing such textures, starting from 2D image exemplars which provide cross-sections of the desired volume texture. The shapes and colors of typical particles embedded in the structure are estimated from their 2D cross-sections. Particle positions in the texture images are also used to guide spatial placement of the 3D particles during synthesis of the 3D texture. Our experiments demonstrate that our algorithm can produce higher quality structures than previous approaches; they are both compatible with the input images, and have a plausible 3D nature. PMID:22614330
Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images
NASA Technical Reports Server (NTRS)
Parsons-Wingerter, Patricia; Vickerman, Mary B.; Keith, Patricia A.
2009-01-01
VESGEN is a newly automated, user-interactive program that maps and quantifies the effects of vascular therapeutics and regulators on microvascular form and function. VESGEN analyzes two-dimensional, black and white vascular images by measuring important vessel morphology parameters. This software guides the user through each required step of the analysis process via a concise graphical user interface (GUI). Primary applications of the VESGEN code are 2D vascular images acquired as clinical diagnostic images of the human retina and as experimental studies of the effects of vascular regulators and therapeutics on vessel remodeling.
Real-time SPECT and 2D ultrasound image registration.
Bucki, Marek; Chassat, Fabrice; Galdames, Francisco; Asahi, Takeshi; Pizarro, Daniel; Lobo, Gabriel
2007-01-01
In this paper we present a technique for fully automatic, real-time 3D SPECT (Single Photon Emitting Computed Tomography) and 2D ultrasound image registration. We use this technique in the context of kidney lesion diagnosis. Our registration algorithm allows a physician to perform an ultrasound exam after a SPECT image has been acquired and see in real time the registration of both modalities. An automatic segmentation algorithm has been implemented in order to display in 3D the positions of the acquired US images with respect to the organs. PMID:18044572
Region-based Statistical Analysis of 2D PAGE Images
Li, Feng; Seillier-Moiseiwitsch, Françoise; Korostyshevskiy, Valeriy R.
2011-01-01
A new comprehensive procedure for statistical analysis of two-dimensional polyacrylamide gel electrophoresis (2D PAGE) images is proposed, including protein region quantification, normalization and statistical analysis. Protein regions are defined by the master watershed map that is obtained from the mean gel. By working with these protein regions, the approach bypasses the current bottleneck in the analysis of 2D PAGE images: it does not require spot matching. Background correction is implemented in each protein region by local segmentation. Two-dimensional locally weighted smoothing (LOESS) is proposed to remove any systematic bias after quantification of protein regions. Proteins are separated into mutually independent sets based on detected correlations, and a multivariate analysis is used on each set to detect the group effect. A strategy for multiple hypothesis testing based on this multivariate approach combined with the usual Benjamini-Hochberg FDR procedure is formulated and applied to the differential analysis of 2D PAGE images. Each step in the analytical protocol is shown by using an actual dataset. The effectiveness of the proposed methodology is shown using simulated gels in comparison with the commercial software packages PDQuest and Dymension. We also introduce a new procedure for simulating gel images. PMID:21850152
2D luminescence imaging of pH in vivo
Schreml, Stephan; Meier, Robert J.; Wolfbeis, Otto S.; Landthaler, Michael; Szeimies, Rolf-Markus; Babilas, Philipp
2011-01-01
Luminescence imaging of biological parameters is an emerging field in biomedical sciences. Tools to study 2D pH distribution are needed to gain new insights into complex disease processes, such as wound healing and tumor metabolism. In recent years, luminescence-based methods for pH measurement have been developed. However, for in vivo applications, especially for studies on humans, biocompatibility and reliability under varying conditions have to be ensured. Here, we present a referenced luminescent sensor for 2D high-resolution imaging of pH in vivo. The ratiometric sensing scheme is based on time-domain luminescence imaging of FITC and ruthenium(II)tris-(4,7-diphenyl-1,10-phenanthroline). To create a biocompatible 2D sensor, these dyes were bound to or incorporated into microparticles (aminocellulose and polyacrylonitrile), and particles were immobilized in polyurethane hydrogel on transparent foils. We show sensor precision and validity by conducting in vitro and in vivo experiments, and we show the versatility in imaging pH during physiological and chronic cutaneous wound healing in humans. Implementation of this technique may open vistas in wound healing, tumor biology, and other biomedical fields. PMID:21262842
Filters in 2D and 3D Cardiac SPECT Image Processing
Ploussi, Agapi; Synefia, Stella
2014-01-01
Nuclear cardiac imaging is a noninvasive, sensitive method providing information on cardiac structure and physiology. Single photon emission tomography (SPECT) evaluates myocardial perfusion, viability, and function and is widely used in clinical routine. The quality of the tomographic image is a key for accurate diagnosis. Image filtering, a mathematical processing, compensates for loss of detail in an image while reducing image noise, and it can improve the image resolution and limit the degradation of the image. SPECT images are then reconstructed, either by filter back projection (FBP) analytical technique or iteratively, by algebraic methods. The aim of this study is to review filters in cardiac 2D, 3D, and 4D SPECT applications and how these affect the image quality mirroring the diagnostic accuracy of SPECT images. Several filters, including the Hanning, Butterworth, and Parzen filters, were evaluated in combination with the two reconstruction methods as well as with a specified MatLab program. Results showed that for both 3D and 4D cardiac SPECT the Butterworth filter, for different critical frequencies and orders, produced the best results. Between the two reconstruction methods, the iterative one might be more appropriate for cardiac SPECT, since it improves lesion detectability due to the significant improvement of image contrast. PMID:24804144
3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes
Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun
2016-01-01
By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes. PMID:27019849
2D imaging of functional structures in perfused pig heart
NASA Astrophysics Data System (ADS)
Kessler, Manfred D.; Cristea, Paul D.; Hiller, Michael; Trinks, Tobias
2002-06-01
In 2000 by 2D-imaging we were able for the first time to visualize in subcellular space functional structures of myocardium. For these experiments we used hemoglobin-free perfused pig hearts in our lab. Step by step we learned to understand the meaning of subcellular structures. Principally, the experiment revealed that in subcellular space very fast changes of light scattering can occur. Furthermore, coefficients of different parameters were determined on the basis of multicomponent system theory.
Bayesian image reconstruction in astronomy
NASA Astrophysics Data System (ADS)
Nunez, Jorge; Llacer, Jorge
1990-09-01
This paper presents the development and testing of a new iterative reconstruction algorithm for astronomy. A maximum a posteriori method of image reconstruction in the Bayesian statistical framework is proposed for the Poisson-noise case. The method uses the entropy with an adjustable 'sharpness parameter' to define the prior probability and the likelihood with 'data increment' parameters to define the conditional probability. The method makes it possible to obtain reconstructions with neither the problem of the 'grey' reconstructions associated with the pure Bayesian reconstructions nor the problem of image deterioration, typical of the maximum-likelihood method. The present iterative algorithm is fast and stable, maintains positivity, and converges to feasible images.
Geometrical Correlation and Matching of 2d Image Shapes
NASA Astrophysics Data System (ADS)
Vizilter, Y. V.; Zheltov, S. Y.
2012-07-01
The problem of image correspondence measure selection for image comparison and matching is addressed. Many practical applications require image matching "just by shape" with no dependence on the concrete intensity or color values. Most popular technique for image shape comparison utilizes the mutual information measure based on probabilistic reasoning and information theory background. Another approach was proposed by Pytiev (so called "Pytiev morphology") based on geometrical and algebraic reasoning. In this framework images are considered as piecewise-constant 2D functions, tessellation of image frame by the set of non-intersected connected regions determines the "shape" of image and the projection of image onto the shape of other image is determined. Morphological image comparison is performed using the normalized morphological correlation coefficients. These coefficients estimate the closeness of one image to the shape of other image. Such image analysis technique can be characterized as an ""ntensity-to-geometry" matching. This paper generalizes the Pytiev morphological approach for obtaining the pure "geometry-to-geometry" matching techniques. The generalized intensity-geometrical correlation coefficient is proposed including the linear correlation coefficient and the square of Pytiev correlation coefficient as its partial cases. The morphological shape correlation coefficient is proposed based on the statistical averaging of images with the same shape. Centered morphological correlation coefficient is obtained under the condition of intensity centering of averaged images. Two types of symmetric geometrical normalized correlation coefficients are proposed for comparison of shape-tessellations. The technique for correlation and matching of shapes with ordered intensities is proposed with correlation measures invariant to monotonous intensity transformations. The quality of proposed geometrical correlation measures is experimentally estimated in the task of
Microwave Imaging with Infrared 2-D Lock-in Amplifier
NASA Astrophysics Data System (ADS)
Chiyo, Noritaka; Arai, Mizuki; Tanaka, Yasuhiro; Nishikata, Atsuhiro; Maeno, Takashi
We have developed a 3-D electromagnetic field measurement system using 2-D lock-in amplifier. This system uses an amplitude modulated electromagnetic wave source to heat a resistive screen. A very small change of temperature on a screen illuminated with the modulated electromagnetic wave is measured using an infrared thermograph camera. In this paper, we attempted to apply our system to microwave imaging. By placing conductor patches in front of the resistive screen and illuminating with microwave, the shape of each conductor was clearly observed as the temperature difference image of the screen. In this way, the conductor pattern inside the non-contact type IC card could be visualized. Moreover, we could observe the temperature difference image reflecting the shape of a Konnyaku (a gelatinous food made from devil's-tonge starch) or a dried fishbone, both as non-conducting material resembling human body. These results proved that our method is applicable to microwave see-through imaging.
Heo, Jingu; Savvides, Marios
2012-12-01
In this paper, we propose a novel method for generating a realistic 3D human face from a single 2D face image for the purpose of synthesizing new 2D face images at arbitrary poses using gender and ethnicity specific models. We employ the Generic Elastic Model (GEM) approach, which elastically deforms a generic 3D depth-map based on the sparse observations of an input face image in order to estimate the depth of the face image. Particularly, we show that Gender and Ethnicity specific GEMs (GE-GEMs) can approximate the 3D shape of the input face image more accurately, achieving a better generalization of 3D face modeling and reconstruction compared to the original GEM approach. We qualitatively validate our method using publicly available databases by showing each reconstructed 3D shape generated from a single image and new synthesized poses of the same person at arbitrary angles. For quantitative comparisons, we compare our synthesized results against 3D scanned data and also perform face recognition using synthesized images generated from a single enrollment frontal image. We obtain promising results for handling pose and expression changes based on the proposed method. PMID:22201062
Spot identification on 2D electrophoresis gel images
NASA Astrophysics Data System (ADS)
Wang, Weixing
2006-09-01
2-D electrophoresis gel images can be used for identifying and characterizing many forms of a particular protein encoded by a single gene. Conventional approaches to gel analysis require the three steps: (1) Spot detection on each gel; (2) Spot matching between gels; and (3) Spot quantification and comparison. Many researchers and developers attempt to automate all steps as much as possible, but errors in the detection and matching stages are common. In order to carry out gel image analysis, one first needs to accurately detect and measure the protein spots in a gel image. This paper presents the algorithms for automatically delineating gel spots. The fusion of two types of segmentation algorithms was implemented. One is edge (discontinuity) based type, and the other is region based type. The primary integration of the two types of image segmentation algorithms have been tested too, the test results clearly show that the integrated algorithm can automatically delineate gel spots not only on a simple image and also on a complex image, and it is much better that either only edge based algorithm or only region based algorithm. Based on the testing and analysis results, the fusion of edge information and region information for gel image segmentation is good for this kind of images.
Symmetries of the 2D magnetic particle imaging system matrix.
Weber, A; Knopp, T
2015-05-21
In magnetic particle imaging (MPI), the relation between the particle distribution and the measurement signal can be described by a linear system of equations. For 1D imaging, it can be shown that the system matrix can be expressed as a product of a convolution matrix and a Chebyshev transformation matrix. For multidimensional imaging, the structure of the MPI system matrix is not yet fully explored as the sampling trajectory complicates the physical model. It has been experimentally found that the MPI system matrix rows have symmetries and look similar to the tensor products of Chebyshev polynomials. In this work we will mathematically prove that the 2D MPI system matrix has symmetries that can be used for matrix compression. PMID:25919400
Image Appraisal for 2D and 3D Electromagnetic Inversion
Alumbaugh, D.L.; Newman, G.A.
1999-01-28
Linearized methods are presented for appraising image resolution and parameter accuracy in images generated with two and three dimensional non-linear electromagnetic inversion schemes. When direct matrix inversion is employed, the model resolution and posterior model covariance matrices can be directly calculated. A method to examine how the horizontal and vertical resolution varies spatially within the electromagnetic property image is developed by examining the columns of the model resolution matrix. Plotting the square root of the diagonal of the model covariance matrix yields an estimate of how errors in the inversion process such as data noise and incorrect a priori assumptions about the imaged model map into parameter error. This type of image is shown to be useful in analyzing spatial variations in the image sensitivity to the data. A method is analyzed for statistically estimating the model covariance matrix when the conjugate gradient method is employed rather than a direct inversion technique (for example in 3D inversion). A method for calculating individual columns of the model resolution matrix using the conjugate gradient method is also developed. Examples of the image analysis techniques are provided on 2D and 3D synthetic cross well EM data sets, as well as a field data set collected at the Lost Hills Oil Field in Central California.
Localization and tracking of aortic valve prosthesis in 2D fluoroscopic image sequences
NASA Astrophysics Data System (ADS)
Karar, M.; Chalopin, C.; Merk, D. R.; Jacobs, S.; Walther, T.; Burgert, O.; Falk, V.
2009-02-01
This paper presents a new method for localization and tracking of the aortic valve prosthesis (AVP) in 2D fluoroscopic image sequences to assist the surgeon to reach the safe zone of implantation during transapical aortic valve implantation. The proposed method includes four main steps: First, the fluoroscopic images are preprocessed using a morphological reconstruction and an adaptive Wiener filter to enhance the AVP edges. Second, a target window, defined by a user on the first image of the sequences which includes the AVP, is tracked in all images using a template matching algorithm. In a third step the corners of the AVP are extracted based on the AVP dimensions and orientation in the target window. Finally, the AVP model is generated in the fluoroscopic image sequences. Although the proposed method is not yet validated intraoperatively, it has been applied to different fluoroscopic image sequences with promising results.
2-D Drift Velocities from the IMAGE EUV Plasmaspheric Imager
NASA Technical Reports Server (NTRS)
Gallagher, D. L.
2006-01-01
The IMAGE Mission extreme ultraviolet imager (EW) observes He(+) plasmaspheric ions throughout the inner magnetosphere. Limited by ionizing radiation and viewing close to the Sun, images of the He(+) distribution are available every 10 minutes for many hours as the spacecraft passes through apogee in its highly elliptical orbit. As a consistent constituent at about 15%, He(+) is an excellent surrogate for monitoring all of the processes that control the dynamics of plasmaspheric plasma. In particular, the motion of He' transverse to the ambient magnetic field is a direct indication of convective electric fields. The analysis of boundary motions has already achieved new insights into the electrodynamic coupling processes taking place between energetic magnetospheric plasmas and the ionosphere. Yet to be fulfilled, however, is the original promise that global E W images of the plasmasphere might yield two-dimensional pictures of mesoscale to macro-scale electric fields in the inner magnetosphere. This work details the technique and initial application of an IMAGE EUV analysis that appears capable of following thermal plasma motion on a global basis.
2-D Drift Velocities from the IMAGE EUV Plasmaspheric Imager
NASA Technical Reports Server (NTRS)
Gallagher, D.; Adrian, M.
2007-01-01
The IMAGE Mission extreme ultraviolet imager (EUY) observes He+ plasmaspheric ions throughout the inner magnetosphere. Limited by ionizing radiation and viewing close to the Sun, images of the He+ distribution are available every 10 minutes for many hours as the spacecraft passes through apogee in its highly elliptical orbit. As a consistent constituent at about 15%, He+ is an excellent surrogate for monitoring all of the processes that control the dynamics of plasmaspheric plasma. In particular, the motion ofHe+ transverse to the ambient magnetic field is a direct indication of convective electric fields. The analysis of boundary motions has already achieved new insights into the electrodynamic coupling processes taking place between energetic magnetospheric plasmas and the ionosphere. Yet to be fulfilled, however, is the original promise that global EUY images of the plasmasphere might yield two-dimensional pictures of meso-scale to macro-scale electric fields in the inner magnetosphere. This work details the technique and initial application of an IMAGE EUY analysis that appears capable of following thermal plasma motion on a global basis.
Image Contrast in Holographic Reconstructions
ERIC Educational Resources Information Center
Russell, B. R.
1969-01-01
The fundamental concepts of holography are explained using elementary wave ideas. Discusses wavefront reconstruction and contrast in hemigraphic images. The consequence of recording only the intensity at a given surface and using an oblique reference wave is shown to be an incomplete reconstruction resulting in image of low contrast. (LC)
2D magnetic nanoparticle imaging using magnetization response second harmonic
NASA Astrophysics Data System (ADS)
Tanaka, Saburo; Murata, Hayaki; Oishi, Tomoya; Suzuki, Toshifumi; Zhang, Yi
2015-06-01
A detection method and an imaging technique for magnetic nanoparticles (MNPs) have been investigated. In MNP detection and in magnetic particle imaging (MPI), the most commonly employed method is the detection of the odd harmonics of the magnetization response. We examined the advantage of using the second harmonic response when applying an AC magnetic modulation field and a DC bias field. If the magnetization response is detected by a Cu-wound-coil detection system, the output voltage from the coil is proportional to the change in the flux, dϕ/dt. Thus, the dependence of the derivative of the magnetization, M, on an AC magnetic modulation field and a DC bias field were calculated and investigated. The calculations were in good agreement with the experimental results. We demonstrated that the use of the second harmonic response for the detection of MNPs has an advantage compared with the usage of the third harmonic response, when the Cu-wound-coil detection system is employed and the amplitude of the ratio of the AC modulation field and a knee field Hac/Hk is less than 2. We also constructed a 2D MPI scanner using a pair of permanent ring magnets with a bore of ϕ80 mm separated by 90 mm. The magnets generated a gradient of Gz=3.17 T/m transverse to the imaging bore and Gx=1.33 T/m along the longitudinal axis. An original concentrated 10 μl Resovist solution in a ϕ2×3 mm2 vessel was used as a sample, and it was imaged by the scanner. As a result, a 2D contour map image could be successfully generated using the method with a lock-in amplifier.
3D EIT image reconstruction with GREIT.
Grychtol, Bartłomiej; Müller, Beat; Adler, Andy
2016-06-01
Most applications of thoracic EIT use a single plane of electrodes on the chest from which a transverse image 'slice' is calculated. However, interpretation of EIT images is made difficult by the large region above and below the electrode plane to which EIT is sensitive. Volumetric EIT images using two (or more) electrode planes should help compensate, but are little used currently. The Graz consensus reconstruction algorithm for EIT (GREIT) has become popular in lung EIT. One shortcoming of the original formulation of GREIT is its restriction to reconstruction onto a 2D planar image. We present an extension of the GREIT algorithm to 3D and develop open-source tools to evaluate its performance as a function of the choice of stimulation and measurement pattern. Results show 3D GREIT using two electrode layers has significantly more uniform sensitivity profiles through the chest region. Overall, the advantages of 3D EIT are compelling. PMID:27203184
Preliminary work of real-time ultrasound imaging system for 2-D array transducer.
Li, Xu; Yang, Jiali; Ding, Mingyue; Yuchi, Ming
2015-01-01
Ultrasound (US) has emerged as a non-invasive imaging modality that can provide anatomical structure information in real time. To enable the experimental analysis of new 2-D array ultrasound beamforming methods, a pre-beamformed parallel raw data acquisition system was developed for 3-D data capture of 2D array transducer. The transducer interconnection adopted the row-column addressing (RCA) scheme, where the columns and rows were active in sequential for transmit and receive events, respectively. The DAQ system captured the raw data in parallel and the digitized data were fed through the field programmable gate array (FPGA) to implement the pre-beamforming. Finally, 3-D images were reconstructed through the devised platform in real-time. PMID:26405923
Progressive attenuation fields: Fast 2D-3D image registration without precomputation
Rohlfing, Torsten; Russakoff, Daniel B.; Denzler, Joachim; Mori, Kensaku; Maurer, Calvin R. Jr.
2005-09-15
Computation of digitally reconstructed radiograph (DRR) images is the rate-limiting step in most current intensity-based algorithms for the registration of three-dimensional (3D) images to two-dimensional (2D) projection images. This paper introduces and evaluates the progressive attenuation field (PAF), which is a new method to speed up DRR computation. A PAF is closely related to an attenuation field (AF). A major difference is that a PAF is constructed on the fly as the registration proceeds; it does not require any precomputation time, nor does it make any prior assumptions of the patient pose or limit the permissible range of patient motion. A PAF effectively acts as a cache memory for projection values once they are computed, rather than as a lookup table for precomputed projections like standard AFs. We use a cylindrical attenuation field parametrization, which is better suited for many medical applications of 2D-3D registration than the usual two-plane parametrization. The computed attenuation values are stored in a hash table for time-efficient storage and access. Using clinical gold-standard spine image data sets from five patients, we demonstrate consistent speedups of intensity-based 2D-3D image registration using PAF DRRs by a factor of 10 over conventional ray casting DRRs with no decrease of registration accuracy or robustness.
Decoupled 2D direction-of-arrival estimation based on sparse signal reconstruction
NASA Astrophysics Data System (ADS)
Wang, Feng; Cui, Xiaowei; Lu, Mingquan; Feng, Zhenming
2015-12-01
A new two-dimensional direction-of-arrival estimation algorithm called 2D- l 1-singular value decomposition (SVD) and its improved version called enhanced-2D- l 1-SVD are proposed in this paper. They are designed for rectangular arrays and can also be extended to rectangular arrays with faulty or missing elements. The key idea is to represent direction-of-arrival with two decoupled angles and then successively estimate them. Therefore, two-dimensional direction finding can be achieved by applying several times of one-dimensional sparse reconstruction-based direction finding methods instead of directly extending them to two-dimensional situation. Performance analysis and simulation results reveal that the proposed method has a much lower computational complexity and a similar statistical performance compared with the well-known l 1-SVD algorithm, which has several advantages over conventional direction finding techniques due to the application of sparse signal reconstruction. Moreover, 2D- l 1-SVD has better robustness to the assumed number of sources over l 1-SVD.
3D/2D image registration using weighted histogram of gradient directions
NASA Astrophysics Data System (ADS)
Ghafurian, Soheil; Hacihaliloglu, Ilker; Metaxas, Dimitris N.; Tan, Virak; Li, Kang
2015-03-01
Three dimensional (3D) to two dimensional (2D) image registration is crucial in many medical applications such as image-guided evaluation of musculoskeletal disorders. One of the key problems is to estimate the 3D CT- reconstructed bone model positions (translation and rotation) which maximize the similarity between the digitally reconstructed radiographs (DRRs) and the 2D fluoroscopic images using a registration method. This problem is computational-intensive due to a large search space and the complicated DRR generation process. Also, finding a similarity measure which converges to the global optimum instead of local optima adds to the challenge. To circumvent these issues, most existing registration methods need a manual initialization, which requires user interaction and is prone to human error. In this paper, we introduce a novel feature-based registration method using the weighted histogram of gradient directions of images. This method simplifies the computation by searching the parameter space (rotation and translation) sequentially rather than simultaneously. In our numeric simulation experiments, the proposed registration algorithm was able to achieve sub-millimeter and sub-degree accuracies. Moreover, our method is robust to the initial guess. It can tolerate up to +/-90°rotation offset from the global optimal solution, which minimizes the need for human interaction to initialize the algorithm.
Tracking of deformable target in 2D ultrasound images
NASA Astrophysics Data System (ADS)
Royer, Lucas; Marchal, Maud; Le Bras, Anthony; Dardenne, Guillaume; Krupa, Alexandre
2015-03-01
In this paper, we propose a novel approach for automatically tracking deformable target within 2D ultrasound images. Our approach uses only dense information combined with a physically-based model and has therefore the advantage of not using any fiducial marker nor a priori knowledge on the anatomical environment. The physical model is represented by a mass-spring damper system driven by different types of forces where the external forces are obtained by maximizing image similarity metric between a reference target and a deformed target across the time. This deformation is represented by a parametric warping model where the optimal parameters are estimated from the intensity variation. This warping function is well-suited to represent localized deformations in the ultrasound images because it directly links the forces applied on each mass with the motion of all the pixels in its vicinity. The internal forces constrain the deformation to physically plausible motions, and reduce the sensitivity to the speckle noise. The approach was validated on simulated and real data, both for rigid and free-form motions of soft tissues. The results are very promising since the deformable target could be tracked with a good accuracy for both types of motion. Our approach opens novel possibilities for computer-assisted interventions where deformable organs are involved and could be used as a new tool for interactive tracking of soft tissues in ultrasound images.
A scanning-mode 2D shear wave imaging (s2D-SWI) system for ultrasound elastography.
Qiu, Weibao; Wang, Congzhi; Li, Yongchuan; Zhou, Juan; Yang, Ge; Xiao, Yang; Feng, Ge; Jin, Qiaofeng; Mu, Peitian; Qian, Ming; Zheng, Hairong
2015-09-01
Ultrasound elastography is widely used for the non-invasive measurement of tissue elasticity properties. Shear wave imaging (SWI) is a quantitative method for assessing tissue stiffness. SWI has been demonstrated to be less operator dependent than quasi-static elastography, and has the ability to acquire quantitative elasticity information in contrast with acoustic radiation force impulse (ARFI) imaging. However, traditional SWI implementations cannot acquire two dimensional (2D) quantitative images of the tissue elasticity distribution. This study proposes and evaluates a scanning-mode 2D SWI (s2D-SWI) system. The hardware and image processing algorithms are presented in detail. Programmable devices are used to support flexible control of the system and the image processing algorithms. An analytic signal based cross-correlation method and a Radon transformation based shear wave speed determination method are proposed, which can be implemented using parallel computation. Imaging of tissue mimicking phantoms, and in vitro, and in vivo imaging test are conducted to demonstrate the performance of the proposed system. The s2D-SWI system represents a new choice for the quantitative mapping of tissue elasticity, and has great potential for implementation in commercial ultrasound scanners. PMID:26025508
2D Ultrasound and 3D MR Image Registration of the Prostate for Brachytherapy Surgical Navigation
Zhang, Shihui; Jiang, Shan; Yang, Zhiyong; Liu, Ranlu
2015-01-01
Abstract Two-dimensional (2D) ultrasound (US) images are widely used in minimally invasive prostate procedure for its noninvasive nature and convenience. However, the poor quality of US image makes it difficult to be used as guiding utility. To improve the limitation, we propose a multimodality image guided navigation module that registers 2D US images with magnetic resonance imaging (MRI) based on high quality preoperative models. A 2-step spatial registration method is used to complete the procedure which combines manual alignment and rapid mutual information (MI) optimize algorithm. In addition, a 3-dimensional (3D) reconstruction model of prostate with surrounding organs is employed to combine with the registered images to conduct the navigation. Registration accuracy is measured by calculating the target registration error (TRE). The results show that the error between the US and preoperative MR images of a polyvinyl alcohol hydrogel model phantom is 1.37 ± 0.14 mm, with a similar performance being observed in patient experiments. PMID:26448009
Electron Microscopy: From 2D to 3D Images with Special Reference to Muscle
2015-01-01
This is a brief and necessarily very sketchy presentation of the evolution in electron microscopy (EM) imaging that was driven by the necessity of extracting 3-D views from the essentially 2-D images produced by the electron beam. The lens design of standard transmission electron microscope has not been greatly altered since its inception. However, technical advances in specimen preparation, image collection and analysis gradually induced an astounding progression over a period of about 50 years. From the early images that redefined tissues, cell and cell organelles at the sub-micron level, to the current nano-resolution reconstructions of organelles and proteins the step is very large. The review is written by an investigator who has followed the field for many years, but often from the sidelines, and with great wonder. Her interest in muscle ultrastructure colors the writing. More specific detailed reviews are presented in this issue. PMID:26913146
High Speed 2D Hadamard Transform Spectral Imager
WEHLBURG, JOSEPH C.; WEHLBURG, CHRISTINE M.; SMITH, JODY L.; SPAHN, OLGA B.; SMITH, MARK W.; BONEY, CRAIG M.
2003-02-01
Hadamard Transform Spectrometer (HTS) approaches share the multiplexing advantages found in Fourier transform spectrometers. Interest in Hadamard systems has been limited due to data storage/computational limitations and the inability to perform accurate high order masking in a reasonable amount of time. Advances in digital micro-mirror array (DMA) technology have opened the door to implementing an HTS for a variety of applications including fluorescent microscope imaging and Raman imaging. A Hadamard transform spectral imager (HTSI) for remote sensing offers a variety of unique capabilities in one package such as variable spectral and temporal resolution, no moving parts (other than the micro-mirrors) and vibration tolerance. Two approaches to for 2D HTS systems have been investigated in this LDRD. The first approach involves dispersing the incident light, encoding the dispersed light then recombining the light. This method is referred to as spectral encoding. The other method encodes the incident light then disperses the encoded light. The second technique is called spatial encoding. After creating optical designs for both methods the spatial encoding method was selected as the method that would be implemented because the optical design was less costly to implement.
Personalized x-ray reconstruction of the proximal femur via a non-rigid 2D-3D registration
NASA Astrophysics Data System (ADS)
Yu, Weimin; Zysset, Philippe; Zheng, Guoyan
2015-03-01
In this paper we present a new approach for a personalized X-ray reconstruction of the proximal femur via a non-rigid registration of a 3D volumetric template to 2D calibrated C-arm images. The 2D-3D registration is done with a hierarchical two-stage strategy: the global scaled rigid registration stage followed by a regularized deformable b-spline registration stage. In both stages, a set of control points with uniform spacing are placed over the domain of the 3D volumetric template and the registrations are driven by computing updated positions of these control points, which then allows to accurately register the 3D volumetric template to the reference space of the C-arm images. Comprehensive experiments on simulated images, on images of cadaveric femurs and on clinical datasets are designed and conducted to evaluate the performance of the proposed approach. Quantitative and qualitative evaluation results are given, which demonstrate the efficacy of the present approach.
NASA Astrophysics Data System (ADS)
Laepple, T.; Heue, K.; Friedeburg, C. V.; Wang, P.; Knab, V.; Pundt, I.
2002-12-01
Tomographic-Differential-Optical-Absorption-Spectroscopy (Tom-DOAS) is a new application of the DOAS method designed to measure 2-3-dimensional concentration fields of different trace gases (e.g. NO2, HCHO, Ozone) in the troposphere. Numerical reconstruction techniques are used to obtain spatially resolved data from the slant column densities provided by DOAS instruments. We discuss the detection of emission plumes by AMAX (Airborne Multi AXis) DOAS Systems which measure sunlight by telescopes pointing in different directions. 2D distributions are reconstructed from slant columns by using airmass factor matrices and inversion techniques. We discuss possibilities and limitations of this technique gained with the use of simulated test fields. Therefore the effect of the parameter choice (e.g. flight track, algorithm changes) and measurement errors is investigated. Further, first results from the Partenavia aircraft measurements over Milano (Italy) during the European FORMAT campaign will be presented.
Estimating mass of crushed limestone particles from 2D images
NASA Astrophysics Data System (ADS)
Banta, Larry E.; Cheng, Ken; Zaniewski, John P.
2002-02-01
In the construction of asphalt pavements, the stability of the asphalt is determined in large part by the gradation, or size distribution of the mineral aggregates that make up the matrix. Gradation is specified on the basis of sieve sizes and percent passing, where the latter is a cumulative measure of the mass of the aggregate passing the sieve as fraction of the total mass in the batch. In this paper, an approach for predicting particle mass based on 2D electronic images is explored. Images of crushed limestone aggregates were acquired using backlighting to create silhouettes. A morphological erosion process was used to separate touching and overlapping particles. Useful features of the particle silhouettes, such as area, centroid and shape descriptors were collected. Several dimensionless parameters were defined and were used as regressor variables in a multiple linear regression model to predict particle mass. Regressor coefficients were found by fitting to a sample of 501 particles ranging in size from 4.75 mm < particle sieve size < 25 mm. When tested against a different aggregate sample, the model predicted the mass of the batch to within +/- 2%.
Three-dimensional reconstruction of liver from 2-D tomographic slices
NASA Astrophysics Data System (ADS)
Chou, Jin-Shin; Chen, Chin-Tu; Giger, Maryellen L.; Kahn, Charles E., Jr.; Bae, Kyongtae T.; Lin, Wei-Chung
1991-03-01
Visualization of liver image data in three dimensions (3-D) can reveal new information to aid physicians in volume calculation and surgical planning. Liver image data are first extracted from a series of 2-D cross-sectional abdominal images by using an automated segmentation technique. An interpolation technique is then applied to construct a 3-D liver image data set having the same spatial resolution in all three directions. This 3-D liver image data set is used as an input in surface rendering and volume rendering to generate two sets of 3-D liver displays. We have applied our methods to clinical liver images obtained from cases of a living-donor liver transplant program. 1.
Reconstructing the shape of an object from its mirror image
NASA Astrophysics Data System (ADS)
Hutt, T.; Simonetti, F.
2010-09-01
An image of an object can be achieved by sending multiple waves toward it and recording the reflections. In order to achieve a complete reconstruction it is usually necessary to send and receive waves from every possible direction [360° for two-dimensional (2D) imaging]. In practice this is often not possible and imaging must be performed with a limited view, which degrades the reconstruction. A proposed solution is to use a strongly scattering planar interface as a mirror to "look behind" the object. The mirror provides additional views that result in an improved reconstruction. We describe this technique and how it is implemented in the context of 2D acoustic imaging. The effect of the mirror on imaging is demonstrated by means of numerical examples that are also used to study the effects of noise. This technique could be used with many imaging methods and wave types, including microwaves, ultrasound, sonar, and seismic waves.
NASA Astrophysics Data System (ADS)
Han, Tao; Lai, Chao-Jen; Chen, Lingyun; Liu, Xinming; Shen, Youtao; Zhong, Yuncheng; Ge, Shuaiping; Yi, Ying; Wang, Tianpeng; Yang, Wei T.; Shaw, Chris C.
2009-02-01
Breast density has been recognized as one of the major risk factors for breast cancer. However, breast density is currently estimated using mammograms which are intrinsically 2D in nature and cannot accurately represent the real breast anatomy. In this study, a novel technique for measuring breast density based on the segmentation of 3D cone beam CT (CBCT) images was developed and the results were compared to those obtained from 2D digital mammograms. 16 mastectomy breast specimens were imaged with a bench top flat-panel based CBCT system. The reconstructed 3D CT images were corrected for the cupping artifacts and then filtered to reduce the noise level, followed by using threshold-based segmentation to separate the dense tissue from the adipose tissue. For each breast specimen, volumes of the dense tissue structures and the entire breast were computed and used to calculate the volumetric breast density. BI-RADS categories were derived from the measured breast densities and compared with those estimated from conventional digital mammograms. The results show that in 10 of 16 cases the BI-RADS categories derived from the CBCT images were lower than those derived from the mammograms by one category. Thus, breasts considered as dense in mammographic examinations may not be considered as dense with the CBCT images. This result indicates that the relation between breast cancer risk and true (volumetric) breast density needs to be further investigated.
2D Imaging in a Lightweight Portable MRI Scanner without Gradient Coils
Cooley, Clarissa Zimmerman; Stockmann, Jason P.; Armstrong, Brandon D.; Sarracanie, Mathieu; Lev, Michael H.; Rosen, Matthew S.; Wald, Lawrence L.
2014-01-01
Purpose As the premiere modality for brain imaging, MRI could find wider applicability if lightweight, portable systems were available for siting in unconventional locations such as Intensive Care Units, physician offices, surgical suites, ambulances, emergency rooms, sports facilities, or rural healthcare sites. Methods We construct and validate a truly portable (<100kg) and silent proof-of-concept MRI scanner which replaces conventional gradient encoding with a rotating lightweight cryogen-free, low-field magnet. When rotated about the object, the inhomogeneous field pattern is used as a rotating Spatial Encoding Magnetic field (rSEM) to create generalized projections which encode the iteratively reconstructed 2D image. Multiple receive channels are used to disambiguate the non-bijective encoding field. Results The system is validated with experimental images of 2D test phantoms. Similar to other non-linear field encoding schemes, the spatial resolution is position dependent with blurring in the center, but is shown to be likely sufficient for many medical applications. Conclusion The presented MRI scanner demonstrates the potential for portability by simultaneously relaxing the magnet homogeneity criteria and eliminating the gradient coil. This new architecture and encoding scheme shows convincing proof of concept images that are expected to be further improved with refinement of the calibration and methodology. PMID:24668520
Technology Transfer Automated Retrieval System (TEKTRAN)
Reconstruction of 3D images from a series of 2D images has been restricted by the limited capacity to decrease the opacity of surrounding tissue. Commercial software that allows color-keying and manipulation of 2D images in true 3D space allowed us to produce 3D reconstructions from pixel based imag...
NASA Astrophysics Data System (ADS)
Liao, Rui; Xu, Ning; Sun, Yiyong
2008-03-01
Presentation of detailed anatomical structures via 3D Computed Tomographic (CT) volumes helps visualization and navigation in electrophysiology procedures (EP). Registration of the CT volume with the online fluoroscopy however is a challenging task for EP applications due to the lack of discernable features in fluoroscopic images. In this paper, we propose to use the coronary sinus (CS) catheter in bi-plane fluoroscopic images and the coronary sinus in the CT volume as a location constraint to accomplish 2D-3D registration. Two automatic registration algorithms are proposed in this study, and their performances are investigated on both simulated and real data. It is shown that compared to registration using mono-plane fluoroscopy, registration using bi-plane images results in substantially higher accuracy in 3D and enhanced robustness. In addition, compared to registering the projection of CS to the 2D CS catheter, it is more desirable to reconstruct a 3D CS catheter from the bi-plane fluoroscopy and then perform a 3D-3D registration between the CS and the reconstructed CS catheter. Quantitative validation based on simulation and visual inspection on real data demonstrates the feasibility of the proposed workflow in EP procedures.
Development of ultra-fast 2D ion Doppler tomography using image intensified CMOS fast camera
NASA Astrophysics Data System (ADS)
Tanabe, Hiroshi; Kuwahata, Akihiro; Yamanaka, Haruki; Inomoto, Michiaki; Ono, Yasushi; TS-group Team
2015-11-01
The world fastest novel time-resolved 2D ion Doppler tomography diagnostics has been developed using fast camera with high-speed gated image intensifier (frame rate: 200kfps. phosphor decay time: ~ 1 μ s). Time evolution of line-integrated spectra are diffracted from a f=1m, F/8.3 and g=2400L/mm Czerny-Turner polychromator, whose output is intensified and recorded to a high-speed camera with spectral resolution of ~0.005nm/pixel. The system can accommodate up to 36 (9 ×4) spatial points recorded at 5 μs time resolution, tomographic reconstruction is applied for the line-integrated spectra, time-resolved (5 μs/frame) local 2D ion temperature measurement has been achieved without any assumption of shot repeatability. Ion heating during intermittent reconnection event which tends to happen during high guide field merging tokamak was measured around diffusion region in UTST. The measured 2D profile shows ion heating inside the acceleration channel of reconnection outflow jet, stagnation point and downstream region where reconnected field forms thick closed flux surface as in MAST. Achieved maximum ion temperature increases as a function of Brec2 and shows good fit with MAST experiment, demonstrating promising CS-less startup scenario for spherical tokamak. This work is supported by JSPS KAKENHI Grant Number 15H05750 and 15K20921.
Li, Guang; Yang, T. Jonathan; Furtado, Hugo; Birkfellner, Wolfgang; Ballangrud, Åse; Powell, Simon N.; Mechalakos, James
2015-01-01
To provide a comprehensive assessment of patient setup accuracy in 6 degrees of freedom (DOFs) using 2-dimensional/3-dimensional (2D/3D) image registration with on-board 2-dimensional kilovoltage (OB-2DkV) radiographic images, we evaluated cranial, head and neck (HN), and thoracic and abdominal sites under clinical conditions. A fast 2D/3D image registration method using graphics processing unit GPU was modified for registration between OB-2DkV and 3D simulation computed tomography (simCT) images, with 3D/3D registration as the gold standard for 6DOF alignment. In 2D/3D registration, body roll rotation was obtained solely by matching orthogonal OB-2DkV images with a series of digitally reconstructed radiographs (DRRs) from simCT with a small rotational increment along the gantry rotation axis. The window/level adjustments for optimal visualization of the bone in OB-2DkV and DRRs were performed prior to registration. Ideal patient alignment at the isocenter was calculated and used as an initial registration position. In 3D/3D registration, cone-beam CT (CBCT) was aligned to simCT on bony structures using a bone density filter in 6DOF. Included in this retrospective study were 37 patients treated in 55 fractions with frameless stereotactic radiosurgery or stereotactic body radiotherapy for cranial and paraspinal cancer. A cranial phantom was used to serve as a control. In all cases, CBCT images were acquired for patient setup with subsequent OB-2DkV verification. It was found that the accuracy of the 2D/3D registration was 0.0 ± 0.5 mm and 0.1° ± 0.4° in phantom. In patient, it is site dependent due to deformation of the anatomy: 0.2 ± 1.6 mm and −0.4° ± 1.2° on average for each dimension for the cranial site, 0.7 ± 1.6 mm and 0.3° ± 1.3° for HN, 0.7 ± 2.0 mm and −0.7° ± 1.1° for the thorax, and 1.1 ± 2.6 mm and −0.5° ± 1.9° for the abdomen. Anatomical deformation and presence of soft tissue in 2D/3D registration affect the consistency with
Li, Guang; Yang, T Jonathan; Furtado, Hugo; Birkfellner, Wolfgang; Ballangrud, Åse; Powell, Simon N; Mechalakos, James
2015-06-01
To provide a comprehensive assessment of patient setup accuracy in 6 degrees of freedom (DOFs) using 2-dimensional/3-dimensional (2D/3D) image registration with on-board 2-dimensional kilovoltage (OB-2 DkV) radiographic images, we evaluated cranial, head and neck (HN), and thoracic and abdominal sites under clinical conditions. A fast 2D/3D image registration method using graphics processing unit GPU was modified for registration between OB-2 DkV and 3D simulation computed tomography (simCT) images, with 3D/3D registration as the gold standard for 6 DOF alignment. In 2D/3D registration, body roll rotation was obtained solely by matching orthogonal OB-2 DkV images with a series of digitally reconstructed radiographs (DRRs) from simCT with a small rotational increment along the gantry rotation axis. The window/level adjustments for optimal visualization of the bone in OB-2 DkV and DRRs were performed prior to registration. Ideal patient alignment at the isocenter was calculated and used as an initial registration position. In 3D/3D registration, cone-beam CT (CBCT) was aligned to simCT on bony structures using a bone density filter in 6DOF. Included in this retrospective study were 37 patients treated in 55 fractions with frameless stereotactic radiosurgery or stereotactic body radiotherapy for cranial and paraspinal cancer. A cranial phantom was used to serve as a control. In all cases, CBCT images were acquired for patient setup with subsequent OB-2 DkV verification. It was found that the accuracy of the 2D/3D registration was 0.0 ± 0.5 mm and 0.1° ± 0.4° in phantom. In patient, it is site dependent due to deformation of the anatomy: 0.2 ± 1.6 mm and -0.4° ± 1.2° on average for each dimension for the cranial site, 0.7 ± 1.6 mm and 0.3° ± 1.3° for HN, 0.7 ± 2.0 mm and -0.7° ± 1.1° for the thorax, and 1.1 ± 2.6 mm and -0.5° ± 1.9° for the abdomen. Anatomical deformation and presence of soft tissue in 2D/3D registration affect the consistency with
2D and 3D visualization methods of endoscopic panoramic bladder images
NASA Astrophysics Data System (ADS)
Behrens, Alexander; Heisterklaus, Iris; Müller, Yannick; Stehle, Thomas; Gross, Sebastian; Aach, Til
2011-03-01
While several mosaicking algorithms have been developed to compose endoscopic images of the internal urinary bladder wall into panoramic images, the quantitative evaluation of these output images in terms of geometrical distortions have often not been discussed. However, the visualization of the distortion level is highly desired for an objective image-based medical diagnosis. Thus, we present in this paper a method to create quality maps from the characteristics of transformation parameters, which were applied to the endoscopic images during the registration process of the mosaicking algorithm. For a global first view impression, the quality maps are laid over the panoramic image and highlight image regions in pseudo-colors according to their local distortions. This illustration supports then surgeons to identify geometrically distorted structures easily in the panoramic image, which allow more objective medical interpretations of tumor tissue in shape and size. Aside from introducing quality maps in 2-D, we also discuss a visualization method to map panoramic images onto a 3-D spherical bladder model. Reference points are manually selected by the surgeon in the panoramic image and the 3-D model. Then the panoramic image is mapped by the Hammer-Aitoff equal-area projection onto the 3-D surface using texture mapping. Finally the textured bladder model can be freely moved in a virtual environment for inspection. Using a two-hemisphere bladder representation, references between panoramic image regions and their corresponding space coordinates within the bladder model are reconstructed. This additional spatial 3-D information thus assists the surgeon in navigation, documentation, as well as surgical planning.
High resolution human diffusion tensor imaging using 2-D navigated multi-shot SENSE EPI at 7 Tesla
Jeong, Ha-Kyu; Gore, John C.; Anderson, Adam W.
2012-01-01
The combination of parallel imaging with partial Fourier acquisition has greatly improved the performance of diffusion-weighted single-shot EPI and is the preferred method for acquisitions at low to medium magnetic field strength such as 1.5 or 3 Tesla. Increased off-resonance effects and reduced transverse relaxation times at 7 Tesla, however, generate more significant artifacts than at lower magnetic field strength and limit data acquisition. Additional acceleration of k-space traversal using a multi-shot approach, which acquires a subset of k-space data after each excitation, reduces these artifacts relative to conventional single-shot acquisitions. However, corrections for motion-induced phase errors are not straightforward in accelerated, diffusion-weighted multi-shot EPI because of phase aliasing. In this study, we introduce a simple acquisition and corresponding reconstruction method for diffusion-weighted multi-shot EPI with parallel imaging suitable for use at high field. The reconstruction uses a simple modification of the standard SENSE algorithm to account for shot-to-shot phase errors; the method is called Image Reconstruction using Image-space Sampling functions (IRIS). Using this approach, reconstruction from highly aliased in vivo image data using 2-D navigator phase information is demonstrated for human diffusion-weighted imaging studies at 7 Tesla. The final reconstructed images show submillimeter in-plane resolution with no ghosts and much reduced blurring and off-resonance artifacts. PMID:22592941
Chen, Mingqing; Bai, Junjie; Siochi, R Alfredo C
2013-02-01
To present a new method of estimating 3D positions of the ipsi-lateral hemi-diaphragm apex (IHDA) from 2D projection images of mega-voltage cone beam CT (MVCBCT). The detection framework reconstructs a 3D volume from all the 2D projection images. An initial estimated 3D IHDA position is determined in this volume based on an imaging processing pipeline, including Otsu thresholding, connected component labeling and template matching. This initial position is then projected onto each 2D projection image to create a region of interest (ROI). To accurately detect the IHDA position in 2D projection space, two methods, dynamic Hough transform (DHT) and a tracking approach based on a joint probability density function (PDF) are developed. Both methods utilize a double-parabola model to fit the 2D diaphragm boundary. The 3D IHDA motion in the superior-inferior (SI) direction is estimated from the initial static 3D position and the detected 2D positions in projection space. The two Hough-based detection methods are tested on 35 MVCBCT scans from 15 patients. The detection is compared to manually identified IHDA positions in 2D projection space by three clinicians. An average and standard deviation of 4.252 ± 3.354 and 2.485 ± 1.750 mm was achieved for DHT and tracking-based approaches respectively, compared with the inter-expert variance among three experts of 1.822 ± 1.106 mm. Based on the results of the scans, the PDF tracking-based approach appears more robust than the DHT. The combination of the automatic ROI localization and the tracking-based approach is a quicker and more accurate method of extracting 3D IHDA motion from 2D projection images. PMID:23321998
Enhanced detection of the vertebrae in 2D CT-images
NASA Astrophysics Data System (ADS)
Graf, Franz; Greil, Robert; Kriegel, Hans-Peter; Schubert, Matthias; Cavallaro, Alexander
2012-02-01
In recent years, a considerable amount of methods have been proposed for detecting and reconstructing the spine and the vertebrae from CT and MR scans. The results are either used for examining the vertebrae or serve as a preprocessing step for further detection and annotation tasks. In this paper, we propose a method for reliably detecting the position of the vertebrae on a single slice of a transversal body CT scan. Thus, our method is not restricted by the available portion of the 3D scan, but even suffices with a single 2D image. A further advantage of our method is that detection does not require adjusting parameters or direct user interaction. Technically, our method is based on an imaging pipeline comprising five steps: The input image is preprocessed. The relevant region of the image is extracted. Then, a set of candidate locations is selected based on bone density. In the next step, image features are extracted from the surrounding of the candidate locations and an instance-based learning approach is used for selecting the best candidate. Finally, a refinement step optimizes the best candidate region. Our proposed method is validated on a large diverse data set of more than 8 000 images and improves the accuracy in terms of area overlap and distance from the true position significantly compared to the only other method being proposed for this task so far.
Image processing and reconstruction
Chartrand, Rick
2012-06-15
This talk will examine some mathematical methods for image processing and the solution of underdetermined, linear inverse problems. The talk will have a tutorial flavor, mostly accessible to undergraduates, while still presenting research results. The primary approach is the use of optimization problems. We will find that relaxing the usual assumption of convexity will give us much better results.
NASA Astrophysics Data System (ADS)
Tang, Xiangyang; Ning, Ruola; Yu, Rongfeng; Conover, David L.
1999-05-01
The application of the newly developed flat panel x-ray imaging detector in cone beam volume CT has attracted increasing interest recently. Due to an imperfect solid state array manufacturing process, however, defective elements, gain non-uniformity and offset image unavoidably exist in all kinds of flat panel x-ray imaging detectors, which will cause severe streak and ring artifacts in a cone beam reconstruction image and severely degrade image quality. A calibration technique, in which the artifacts resulting from the defective elements, gain non-uniformity and offset image can be reduced significantly, is presented in this paper. The detection of defective elements is distinctively based upon two-dimensional (2D) wavelet analysis. Because of its inherent localizability in recognizing singularities or discontinuities, wavelet analysis possesses the capability of detecting defective elements over a rather large x-ray exposure range, e.g., 20% to approximately 60% of the dynamic range of the detector used. Three-dimensional (3D) images of a low-contrast CT phantom have been reconstructed from projection images acquired by a flat panel x-ray imaging detector with and without calibration process applied. The artifacts caused individually by defective elements, gain non-uniformity and offset image have been separated and investigated in detail, and the correlation with each other have also been exposed explicitly. The investigation is enforced by quantitative analysis of the signal to noise ratio (SNR) and the image uniformity of the cone beam reconstruction image. It has been demonstrated that the ring and streak artifacts resulting from the imperfect performance of a flat panel x-ray imaging detector can be reduced dramatically, and then the image qualities of a cone beam reconstruction image, such as contrast resolution and image uniformity are improved significantly. Furthermore, with little modification, the calibration technique presented here is also applicable
2D/4D marker-free tumor tracking using 4D CBCT as the reference image
NASA Astrophysics Data System (ADS)
Wang, Mengjiao; Sharp, Gregory C.; Rit, Simon; Delmon, Vivien; Wang, Guangzhi
2014-05-01
Tumor motion caused by respiration is an important issue in image-guided radiotherapy. A 2D/4D matching method between 4D volumes derived from cone beam computed tomography (CBCT) and 2D fluoroscopic images was implemented to track the tumor motion without the use of implanted markers. In this method, firstly, 3DCBCT and phase-rebinned 4DCBCT are reconstructed from cone beam acquisition. Secondly, 4DCBCT volumes and a streak-free 3DCBCT volume are combined to improve the image quality of the digitally reconstructed radiographs (DRRs). Finally, the 2D/4D matching problem is converted into a 2D/2D matching between incoming projections and DRR images from each phase of the 4DCBCT. The diaphragm is used as a target surrogate for matching instead of using the tumor position directly. This relies on the assumption that if a patient has the same breathing phase and diaphragm position as the reference 4DCBCT, then the tumor position is the same. From the matching results, the phase information, diaphragm position and tumor position at the time of each incoming projection acquisition can be derived. The accuracy of this method was verified using 16 candidate datasets, representing lung and liver applications and one-minute and two-minute acquisitions. The criteria for the eligibility of datasets were described: 11 eligible datasets were selected to verify the accuracy of diaphragm tracking, and one eligible dataset was chosen to verify the accuracy of tumor tracking. The diaphragm matching accuracy was 1.88 ± 1.35 mm in the isocenter plane and the 2D tumor tracking accuracy was 2.13 ± 1.26 mm in the isocenter plane. These features make this method feasible for real-time marker-free tumor motion tracking purposes.
NASA Astrophysics Data System (ADS)
Gross, H.; Richter, J.; Rathsfeld, A.; Bär, M.
2010-09-01
Scatterometry as a non-imaging indirect optical method in wafer metrology is applicable to lithography masks designed for extreme ultraviolet (EUV) lithography , where light with wavelengths of about 13.5 nm is applied. The main goal is to reconstruct the critical dimensions (CD) of the mask, i.e., profile parameters such as line width, line height, and side-wall angle, from the measured diffracted light pattern and to estimate the associated uncertainties. The numerical simulation of the diffraction process for periodic 2D structures can be realized by the finite element solution of the two-dimensional Helmholtz equation. The inverse problem is expressed as a non-linear operator equation where the operator maps the sought mask parameters to the efficiencies of the diffracted plane wave modes. To solve this operator equation, the deviation of the measured efficiencies from the ones obtained computationally is minimized by a Gauss-Newton type iterative method. In the present paper, the admissibility of rectangular profile models for the evaluations of CD uniformity is studied. More precisely, several sets of typical measurement data are simulated for trapezoidal shaped EUV masks with different mask signatures characterized by various line widths, heights and side-wall angles slightly smaller than 90 degree. Using these sets, but assuming rectangular structures as the basic profiles of the numerical reconstruction algorithm, approximate line height and width parameters are determined as the critical dimensions of the mask. Finally, the model error due to the simplified shapes is analyzed by checking the deviations of the reconstructed parameters from their nominal values.
NASA Astrophysics Data System (ADS)
Park, Hye-Suk; Kim, Ye-Seul; Lee, Haeng-Hwa; Gang, Won-Suk; Kim, Hee-Joung; Choi, Young-Wook; Choi, JaeGu
2015-08-01
The purpose of this study is to determine the optimal non-uniform angular dose distribution to improve the quality of the 3D reconstructed images and to acquire extra 2D projection images. In this analysis, 7 acquisition sets were generated by using four different values for the number of projections (11, 15, 21, and 29) and total angular range (±14°, ±17.5°, ±21°, and ±24.5° ). For all acquisition sets, the zero-degree projection was used as the 2D image that was close to that of standard conventional mammography (CM). Exposures used were 50, 100, 150, and 200 mR for the zero-degree projection, and the remaining dose was distributed over the remaining projection angles. To quantitatively evaluate image quality, we computed the CNR (contrast-to-noise ratio) and the ASF (artifact spread function) for the same radiation dose. The results indicate that, for microcalcifications, acquisition sets with approximately 4 times higher exposure on the zero-degree projection than the average exposure for the remaining projection angles yielded higher CNR values and were 3% higher than the uniform distribution. However, very high dose concentrations toward the zero-degree projection may reduce the quality of the reconstructed images due to increasing noise in the peripheral views. The zero-degree projection of the non-uniform dose distribution offers a 2D image similar to that of standard CM, but with a significantly lower radiation dose. Therefore, we need to evaluate the diagnostic potential of extra 2D projection image when diagnose breast cancer by using 3D images with non-uniform angular dose distributions.
Fast Confocal Raman Imaging Using a 2-D Multifocal Array for Parallel Hyperspectral Detection.
Kong, Lingbo; Navas-Moreno, Maria; Chan, James W
2016-01-19
We present the development of a novel confocal hyperspectral Raman microscope capable of imaging at speeds up to 100 times faster than conventional point-scan Raman microscopy under high noise conditions. The microscope utilizes scanning galvomirrors to generate a two-dimensional (2-D) multifocal array at the sample plane, generating Raman signals simultaneously at each focus of the array pattern. The signals are combined into a single beam and delivered through a confocal pinhole before being focused through the slit of a spectrometer. To separate the signals from each row of the array, a synchronized scan mirror placed in front of the spectrometer slit positions the Raman signals onto different pixel rows of the detector. We devised an approach to deconvolve the superimposed signals and retrieve the individual spectra at each focal position within a given row. The galvomirrors were programmed to scan different focal arrays following Hadamard encoding patterns. A key feature of the Hadamard detection is the reconstruction of individual spectra with improved signal-to-noise ratio. Using polystyrene beads as test samples, we demonstrated not only that our system images faster than a conventional point-scan method but that it is especially advantageous under noisy conditions, such as when the CCD detector operates at fast read-out rates and high temperatures. This is the first demonstration of multifocal confocal Raman imaging in which parallel spectral detection is implemented along both axes of the CCD detector chip. We envision this novel 2-D multifocal spectral detection technique can be used to develop faster imaging spontaneous Raman microscopes with lower cost detectors. PMID:26654100
Antenna-coupled microbolometer based uncooled 2D array and camera for 2D real-time terahertz imaging
NASA Astrophysics Data System (ADS)
Simoens, F.; Meilhan, J.; Gidon, S.; Lasfargues, G.; Lalanne Dera, J.; Ouvrier-Buffet, J. L.; Pocas, S.; Rabaud, W.; Guellec, F.; Dupont, B.; Martin, S.; Simon, A. C.
2013-09-01
CEA-Leti has developed a monolithic large focal plane array bolometric technology optimized for 2D real-time imaging in the terahertz range. Each pixel consists in a silicon microbolometer coupled to specific antennas and a resonant quarter-wavelength cavity. First prototypes of imaging arrays have been designed and manufactured for optimized sensing in the 1-3.5THz range where THz quantum cascade lasers are delivering high optical power. NEP in the order of 1 pW/sqrt(Hz) has been assessed at 2.5 THz. This paper reports the steps of this development, starting from the pixel level, to an array associated monolithically to its CMOS ROIC and finally a stand-alone camera. For each step, modeling, technological prototyping and experimental characterizations are presented.
3D-2D registration of cerebral angiograms: a method and evaluation on clinical images.
Mitrovic, Uroš; Špiclin, Žiga; Likar, Boštjan; Pernuš, Franjo
2013-08-01
Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D-2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of 10 patients undergoing cerebral EIGI and established "gold standard" registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 s. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI. PMID:23649179
List-Mode Likelihood: EM Algorithm and Image Quality Estimation Demonstrated on 2-D PET
Barrett, Harrison H.
2010-01-01
Using a theory of list-mode maximum-likelihood (ML) source reconstruction presented recently by Barrett et al. [1], this paper formulates a corresponding expectation-maximization (EM) algorithm, as well as a method for estimating noise properties at the ML estimate. List-mode ML is of interest in cases where the dimensionality of the measurement space impedes a binning of the measurement data. It can be advantageous in cases where a better forward model can be obtained by including more measurement coordinates provided by a given detector. Different figures of merit for the detector performance can be computed from the Fisher information matrix (FIM). This paper uses the observed FIM, which requires a single data set, thus, avoiding costly ensemble statistics. The proposed techniques are demonstrated for an idealized two-dimensional (2-D) positron emission tomography (PET) [2-D PET] detector. We compute from simulation data the improved image quality obtained by including the time of flight of the coincident quanta. PMID:9688154
NASA Astrophysics Data System (ADS)
Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David
2008-03-01
Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio
Rigid 2D/3D registration of intraoperative digital x-ray images and preoperative CT and MR images
NASA Astrophysics Data System (ADS)
Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo
2002-05-01
This paper describes a novel approach to register 3D computed tomography (CT) or magnetic resonance (MR) images to a set of 2D X-ray images. Such a registration may be a valuable tool for intraoperative determination of the precise position and orientation of some anatomy of interest, defined in preoperative images. The registration is based solely on the information present in 2D and 3D images. It does not require fiducial markers, X-ray image segmentation, or construction of digitally reconstructed radiographs. The originality of the approach is in using normals to bone surfaces, preoperatively defined in 3D MR or CT data, and gradients of intraoperative X-ray images, which are back-projected towards the X-ray source. The registration is then concerned with finding that rigid transformation of a CT or MR volume, which provides the best match between surface normals and back projected gradients, considering their amplitudes and orientations. The method is tested on a lumbar spine phantom. Gold standard registration is obtained by fidicual markers attached to the phantom. Volumes of interest, containing single vertebrae, are registered to different pairs of X-ray images from different starting positions, chosen randomly and uniformly around the gold standard position. Target registration errors and rotation errors are in order of 0.3 mm and 0.35 degrees for the CT to X-ray registration and 1.3 mm and 1.5 degrees for MR to X-ray registration. The registration is shown to be fast and accurate.
Geometric Neural Computing for 2D Contour and 3D Surface Reconstruction
NASA Astrophysics Data System (ADS)
Rivera-Rovelo, Jorge; Bayro-Corrochano, Eduardo; Dillmann, Ruediger
In this work we present an algorithm to approximate the surface of 2D or 3D objects combining concepts from geometric algebra and artificial neural networks. Our approach is based on the self-organized neural network called Growing Neural Gas (GNG), incorporating versors of the geometric algebra in its neural units; such versors are the transformations that will be determined during the training stage and then applied to a point to approximate the surface of the object. We also incorporate the information given by the generalized gradient vector flow to select automatically the input patterns, and also in the learning stage in order to improve the performance of the net. Several examples using medical images are presented, as well as images of automatic visual inspection. We compared the results obtained using snakes against the GSOM incorporating the gradient information and using versors. Such results confirm that our approach is very promising. As a second application, a kind of morphing or registration procedure is shown; namely the algorithm can be used when transforming one model at time t 1 into another at time t 2. We include also examples applying the same procedure, now extended to models based on spheres.
2D Seismic Imaging of Elastic Parameters by Frequency Domain Full Waveform Inversion
NASA Astrophysics Data System (ADS)
Brossier, R.; Virieux, J.; Operto, S.
2008-12-01
Thanks to recent advances in parallel computing, full waveform inversion is today a tractable seismic imaging method to reconstruct physical parameters of the earth interior at different scales ranging from the near- surface to the deep crust. We present a massively parallel 2D frequency-domain full-waveform algorithm for imaging visco-elastic media from multi-component seismic data. The forward problem (i.e. the resolution of the frequency-domain 2D PSV elastodynamics equations) is based on low-order Discontinuous Galerkin (DG) method (P0 and/or P1 interpolations). Thanks to triangular unstructured meshes, the DG method allows accurate modeling of both body waves and surface waves in case of complex topography for a discretization of 10 to 15 cells per shear wavelength. The frequency-domain DG system is solved efficiently for multiple sources with the parallel direct solver MUMPS. The local inversion procedure (i.e. minimization of residuals between observed and computed data) is based on the adjoint-state method which allows to efficiently compute the gradient of the objective function. Applying the inversion hierarchically from the low frequencies to the higher ones defines a multiresolution imaging strategy which helps convergence towards the global minimum. In place of expensive Newton algorithm, the combined use of the diagonal terms of the approximate Hessian matrix and optimization algorithms based on quasi-Newton methods (Conjugate Gradient, LBFGS, ...) allows to improve the convergence of the iterative inversion. The distribution of forward problem solutions over processors driven by a mesh partitioning performed by METIS allows to apply most of the inversion in parallel. We shall present the main features of the parallel modeling/inversion algorithm, assess its scalability and illustrate its performances with realistic synthetic case studies.
High-resolution GPR imaging using a nonstandard 2D EEMD technique
NASA Astrophysics Data System (ADS)
Chen, Chih-Sung; Jeng*, Yih; Yu, Hung-Ming
2013-04-01
Ground Penetrating Radar (GPR) data are affected by a variety of factors. Linear and nonlinear data processing methods each have been widely applied to the GPR use in geophysical and engineering investigations. For complicated data such as the shallow earth image of urban area, a better result can be achieved by integrating both approaches. In this study, we introduce a nonstandard 2D EEMD approach, which integrates the natural logarithm transformed (NLT) ensemble empirical mode decomposition (EEMD) method with the linear filtering technique to process GPR images. The NLT converts the data into logarithmic values; therefore, it permits a wide dynamic range for the recorded GPR data to be presented. The EEMD dyadic filter bank decomposes the data into multiple components ready for image reconstruction. Consequently, the NLT EEMD method provides a new way of nonlinear energy compensating and noise filtering with results having minimal artifacts. However, horizontal noise in the GPR time-distance section may be enhanced after NLT process in some cases. To solve the dilemma, we process the data two dimensionally. At first, the vertical background noise of each GPR trace is removed by using a standard linear method, the background noise removal algorithm, or simply by performing the sliding background removal filter. After that, the NLT is applied to the data for examining the horizontal coherent energy. Next, we employ the EEMD filter bank horizontally at each time step to remove the horizontal coherent energy. After removing the vertical background noise and horizontal coherent energy, a vertical EEMD method is then applied to generate a filter bank of the GPR time-distance section for final image reconstruction. Two buried models imitating common shallow earth targets are used to verify the effectiveness of the proposed scheme. One model is a brick cistern buried in a disturbed site of poor reflection quality. The other model is a buried two-stack metallic target
Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media
NASA Technical Reports Server (NTRS)
Alfano, Robert R. (Inventor); Cai, Wei (Inventor); Gayen, Swapan K. (Inventor)
2000-01-01
A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise,
Time-resolved diffusion tomographic 2D and 3D imaging in highly scattering turbid media
NASA Technical Reports Server (NTRS)
Alfano, Robert R. (Inventor); Cai, Wei (Inventor); Liu, Feng (Inventor); Lax, Melvin (Inventor); Das, Bidyut B. (Inventor)
1999-01-01
A method for imaging objects in highly scattering turbid media. According to one embodiment of the invention, the method involves using a plurality of intersecting source/detectors sets and time-resolving equipment to generate a plurality of time-resolved intensity curves for the diffusive component of light emergent from the medium. For each of the curves, the intensities at a plurality of times are then inputted into the following inverse reconstruction algorithm to form an image of the medium: ##EQU1## wherein W is a matrix relating output at source and detector positions r.sub.s and r.sub.d, at time t, to position r, .LAMBDA. is a regularization matrix, chosen for convenience to be diagonal, but selected in a way related to the ratio of the noise,
Self-calibration of cone-beam CT geometry using 3D–2D image registration
Ouadah, S; Stayman, J W; Gang, G J; Ehtiati, T; Siewerdsen, J H
2016-01-01
Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a ‘self-calibration’ of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM—e.g. on the CBCT bench, FWHM = 0.86 mm for conventional calibration compared to 0.65 mm for self-calibration (p < 0.001). Similar improvements were measured in RPE—e.g. on the robotic C-arm, RPE = 0.73 mm for conventional calibration compared to 0.55 mm for self-calibration (p < 0.001). Visible improvement was evident in CBCT reconstructions using self-calibration, particularly about high-contrast, high-frequency objects (e.g. temporal bone air cells and a surgical needle). The results indicate that self-calibration can improve even upon systems with presumably accurate geometric calibration and is applicable to situations where conventional
Self-calibration of cone-beam CT geometry using 3D-2D image registration.
Ouadah, S; Stayman, J W; Gang, G J; Ehtiati, T; Siewerdsen, J H
2016-04-01
Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a 'self-calibration' of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM-e.g. on the CBCT bench, FWHM = 0.86 mm for conventional calibration compared to 0.65 mm for self-calibration (p < 0.001). Similar improvements were measured in RPE-e.g. on the robotic C-arm, RPE = 0.73 mm for conventional calibration compared to 0.55 mm for self-calibration (p < 0.001). Visible improvement was evident in CBCT reconstructions using self-calibration, particularly about high-contrast, high-frequency objects (e.g. temporal bone air cells and a surgical needle). The results indicate that self-calibration can improve even upon systems with presumably accurate geometric calibration and is
Self-calibration of cone-beam CT geometry using 3D-2D image registration
NASA Astrophysics Data System (ADS)
Ouadah, S.; Stayman, J. W.; Gang, G. J.; Ehtiati, T.; Siewerdsen, J. H.
2016-04-01
Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a ‘self-calibration’ of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM—e.g. on the CBCT bench, FWHM = 0.86 mm for conventional calibration compared to 0.65 mm for self-calibration (p < 0.001). Similar improvements were measured in RPE—e.g. on the robotic C-arm, RPE = 0.73 mm for conventional calibration compared to 0.55 mm for self-calibration (p < 0.001). Visible improvement was evident in CBCT reconstructions using self-calibration, particularly about high-contrast, high-frequency objects (e.g. temporal bone air cells and a surgical needle). The results indicate that self-calibration can improve even upon systems with presumably accurate geometric calibration and is
Image appraisal for 2D and 3D electromagnetic inversion
Alumbaugh, D.L.; Newman, G.A.
1998-04-01
Linearized methods are presented for appraising image resolution and parameter accuracy in images generated with two and three dimensional non-linear electromagnetic inversion schemes. When direct matrix inversion is employed, the model resolution and model covariance matrices can be directly calculated. The columns of the model resolution matrix are shown to yield empirical estimates of the horizontal and vertical resolution throughout the imaging region. Plotting the square root of the diagonal of the model covariance matrix yields an estimate of how the estimated data noise maps into parameter error. When the conjugate gradient method is employed rather than a direct inversion technique (for example in 3D inversion), an iterative method can be applied to statistically estimate the model covariance matrix, as well as a regularization covariance matrix. The latter estimates the error in the inverted results caused by small variations in the regularization parameter. A method for calculating individual columns of the model resolution matrix using the conjugate gradient method is also developed. Examples of the image analysis techniques are provided on a synthetic cross well EM data set.
Multifractal analysis of 2D gray soil images
NASA Astrophysics Data System (ADS)
González-Torres, Ivan; Losada, Juan Carlos; Heck, Richard; Tarquis, Ana M.
2015-04-01
Soil structure, understood as the spatial arrangement of soil pores, is one of the key factors in soil modelling processes. Geometric properties of individual and interpretation of the morphological parameters of pores can be estimated from thin sections or 3D Computed Tomography images (Tarquis et al., 2003), but there is no satisfactory method to binarized these images and quantify the complexity of their spatial arrangement (Tarquis et al., 2008, Tarquis et al., 2009; Baveye et al., 2010). The objective of this work was to apply a multifractal technique, their singularities (α) and f(α) spectra, to quantify it without applying any threshold (Gónzalez-Torres, 2014). Intact soil samples were collected from four horizons of an Argisol, formed on the Tertiary Barreiras group of formations in Pernambuco state, Brazil (Itapirema Experimental Station). The natural vegetation of the region is tropical, coastal rainforest. From each horizon, showing different porosities and spatial arrangements, three adjacent samples were taken having a set of twelve samples. The intact soil samples were imaged using an EVS (now GE Medical. London, Canada) MS-8 MicroCT scanner with 45 μm pixel-1 resolution (256x256 pixels). Though some samples required paring to fit the 64 mm diameter imaging tubes, field orientation was maintained. References Baveye, P.C., M. Laba, W. Otten, L. Bouckaert, P. Dello, R.R. Goswami, D. Grinev, A. Houston, Yaoping Hu, Jianli Liu, S. Mooney, R. Pajor, S. Sleutel, A. Tarquis, Wei Wang, Qiao Wei, Mehmet Sezgin. Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data. Geoderma, 157, 51-63, 2010. González-Torres, Iván. Theory and application of multifractal analysis methods in images for the study of soil structure. Master thesis, UPM, 2014. Tarquis, A.M., R.J. Heck, J.B. Grau; J. Fabregat, M.E. Sanchez and J.M. Antón. Influence of Thresholding in Mass and Entropy Dimension of 3-D
2D/4D marker-free tumor tracking using 4D CBCT as the reference image
Wang, Mengjiao; Rit, Simon; Delmon, Vivien; Wang, Guangzhi
2014-01-01
Tumor motion caused by respiration is an important issue in image guided radiotherapy. A 2D/4D matching method between 4D volumes derived from cone beam computed tomography (CBCT) and 2D fluoroscopic images was implemented to track the tumor motion without the use of implanted markers. In this method, firstly, 3DCBCT and phase-rebinned 4DCBCT are reconstructed from cone beam acquisition. Secondly, 4DCBCT volumes and streak free 3DCBCT volume are combined to improve the image quality of the DRRs. Finally, the 2D/4D matching problem is converted into a 2D/2D matching between incoming projections and DRR images from each phase of the 4DCBCT. The diaphragm is used as a target surrogate for matching instead of using the tumor position directly. This relies on the assumption that if a patient has the same breathing phase and diaphragm position as the reference 4DCBCT, then the tumor position is the same. From the matching results, the phase information, diaphragm position and tumor position at the time of each incoming projection acquisition can be derived. The accuracy of this method was verified using 16 candidate datasets, representing lung and liver applications and 1-minute and 2-minute acquisitions. The criteria for the eligibility of datasets were described: 11 eligible datasets were selected to verify the accuracy of diaphragm tracking, and one eligible dataset was chosen to verify the accuracy of tumor tracking. Diaphragm matching accuracy was 1.88±1.35mm in the isocenter plane, the 2D tumor tracking accuracy was 2.13±1.26mm in the isocenter plane. These features make this method feasible for real-time marker-free tumor motion tracking purpose. PMID:24710793
Filtering in SPECT Image Reconstruction
Lyra, Maria; Ploussi, Agapi
2011-01-01
Single photon emission computed tomography (SPECT) imaging is widely implemented in nuclear medicine as its clinical role in the diagnosis and management of several diseases is, many times, very helpful (e.g., myocardium perfusion imaging). The quality of SPECT images are degraded by several factors such as noise because of the limited number of counts, attenuation, or scatter of photons. Image filtering is necessary to compensate these effects and, therefore, to improve image quality. The goal of filtering in tomographic images is to suppress statistical noise and simultaneously to preserve spatial resolution and contrast. The aim of this work is to describe the most widely used filters in SPECT applications and how these affect the image quality. The choice of the filter type, the cut-off frequency and the order is a major problem in clinical routine. In many clinical cases, information for specific parameters is not provided, and findings cannot be extrapolated to other similar SPECT imaging applications. A literature review for the determination of the mostly used filters in cardiac, brain, bone, liver, kidneys, and thyroid applications is also presented. As resulting from the overview, no filter is perfect, and the selection of the proper filters, most of the times, is done empirically. The standardization of image-processing results may limit the filter types for each SPECT examination to certain few filters and some of their parameters. Standardization, also, helps in reducing image processing time, as the filters and their parameters must be standardised before being put to clinical use. Commercial reconstruction software selections lead to comparable results interdepartmentally. The manufacturers normally supply default filters/parameters, but these may not be relevant in various clinical situations. After proper standardisation, it is possible to use many suitable filters or one optimal filter. PMID:21760768
Noel, B.W.; Borella, H.M. ); Beshears, D.L.; Sartory, W.K.; Tobin, K.W.; Williams, R.K. ); Turley, W.D. . Santa Barbara Operations)
1991-07-01
This report describes a new leadless two-dimensional imaging optical heat-flux gauge. The gauge is made by depositing arrays of thermorgraphic-phosphor (TP) spots onto the faces of a polymethylpentene is insulator. In the first section of the report, we describe several gauge configurations and their prototype realizations. A satisfactory configuration is an array of right triangles on each face that overlay to form squares when the gauge is viewed normal to the surface. The next section of the report treats the thermal conductivity of TPs. We set up an experiment using a comparative longitudinal heat-flow apparatus to measure the previously unknown thermal conductivity of these materials. The thermal conductivity of one TP, Y{sub 2}O{sub 3}:Eu, is 0.0137 W/cm{center dot}K over the temperature range from about 300 to 360 K. The theories underlying the time response of TP gauges and the imaging characteristics are discussed in the next section. Then we discuss several laboratory experiments to (1) demonstrate that the TP heat-flux gauge can be used in imaging applications; (2) obtain a quantum yield that enumerates what typical optical output signal amplitudes can be obtained from TP heat-flux gauges; and (3) determine whether LANL-designed intensified video cameras have sufficient sensitivity to acquire images from the heat-flux gauges. We obtained positive results from all the measurements. Throughout the text, we note limitations, areas where improvements are needed, and where further research is necessary. 12 refs., 25 figs., 4 tabs.
Reconstruction of coded aperture images
NASA Technical Reports Server (NTRS)
Bielefeld, Michael J.; Yin, Lo I.
1987-01-01
Balanced correlation method and the Maximum Entropy Method (MEM) were implemented to reconstruct a laboratory X-ray source as imaged by a Uniformly Redundant Array (URA) system. Although the MEM method has advantages over the balanced correlation method, it is computationally time consuming because of the iterative nature of its solution. Massively Parallel Processing, with its parallel array structure is ideally suited for such computations. These preliminary results indicate that it is possible to use the MEM method in future coded-aperture experiments with the help of the MPP.
NASA Astrophysics Data System (ADS)
Choi, Doo-Won; Jeon, Min-Gyu; Cho, Gyeong-Rae; Kamimoto, Takahiro; Deguchi, Yoshihiro; Doh, Deog-Hee
2016-02-01
Performance improvement was attained in data reconstructions of 2-dimensional tunable diode laser absorption spectroscopy (TDLAS). Multiplicative Algebraic Reconstruction Technique (MART) algorithm was adopted for data reconstruction. The data obtained in an experiment for the measurement of temperature and concentration fields of gas flows were used. The measurement theory is based upon the Beer-Lambert law, and the measurement system consists of a tunable laser, collimators, detectors, and an analyzer. Methane was used as a fuel for combustion with air in the Bunsen-type burner. The data used for the reconstruction are from the optical signals of 8-laser beams passed on a cross-section of the methane flame. The performances of MART algorithm in data reconstruction were validated and compared with those obtained by Algebraic Reconstruction Technique (ART) algorithm.
Reboul, Cyril F; Bonnet, Frederic; Elmlund, Dominika; Elmlund, Hans
2016-06-01
A critical step in the analysis of novel cryogenic electron microscopy (cryo-EM) single-particle datasets is the identification of homogeneous subsets of images. Methods for solving this problem are important for data quality assessment, ab initio 3D reconstruction, and analysis of population diversity due to the heterogeneous nature of macromolecules. Here we formulate a stochastic algorithm for identification of homogeneous subsets of images. The purpose of the method is to generate improved 2D class averages that can be used to produce a reliable 3D starting model in a rapid and unbiased fashion. We show that our method overcomes inherent limitations of widely used clustering approaches and proceed to test the approach on six publicly available experimental cryo-EM datasets. We conclude that, in each instance, ab initio 3D reconstructions of quality suitable for initialization of high-resolution refinement are produced from the cluster centers. PMID:27184214
Method for position emission mammography image reconstruction
Smith, Mark Frederick
2004-10-12
An image reconstruction method comprising accepting coincidence datat from either a data file or in real time from a pair of detector heads, culling event data that is outside a desired energy range, optionally saving the desired data for each detector position or for each pair of detector pixels on the two detector heads, and then reconstructing the image either by backprojection image reconstruction or by iterative image reconstruction. In the backprojection image reconstruction mode, rays are traced between centers of lines of response (LOR's), counts are then either allocated by nearest pixel interpolation or allocated by an overlap method and then corrected for geometric effects and attenuation and the data file updated. If the iterative image reconstruction option is selected, one implementation is to compute a grid Siddon retracing, and to perform maximum likelihood expectation maiximization (MLEM) computed by either: a) tracing parallel rays between subpixels on opposite detector heads; or b) tracing rays between randomized endpoint locations on opposite detector heads.
Light field display and 3D image reconstruction
NASA Astrophysics Data System (ADS)
Iwane, Toru
2016-06-01
Light field optics and its applications become rather popular in these days. With light field optics or light field thesis, real 3D space can be described in 2D plane as 4D data, which we call as light field data. This process can be divided in two procedures. First, real3D scene is optically reduced with imaging lens. Second, this optically reduced 3D image is encoded into light field data. In later procedure we can say that 3D information is encoded onto a plane as 2D data by lens array plate. This transformation is reversible and acquired light field data can be decoded again into 3D image with the arrayed lens plate. "Refocusing" (focusing image on your favorite point after taking a picture), light-field camera's most popular function, is some kind of sectioning process from encoded 3D data (light field data) to 2D image. In this paper at first I show our actual light field camera and our 3D display using acquired and computer-simulated light field data, on which real 3D image is reconstructed. In second I explain our data processing method whose arithmetic operation is performed not in Fourier domain but in real domain. Then our 3D display system is characterized by a few features; reconstructed image is of finer resolutions than density of arrayed lenses and it is not necessary to adjust lens array plate to flat display on which light field data is displayed.
Development of 2D imaging of SXR plasma radiation by means of GEM detectors
NASA Astrophysics Data System (ADS)
Chernyshova, M.; Czarski, T.; Jabłoński, S.; Kowalska-Strzeciwilk, E.; Poźniak, K.; Kasprowicz, G.; Zabołotny, W.; Wojeński, A.; Byszuk, A.; Burza, M.; Juszczyk, B.; Zienkiewicz, P.
2014-11-01
Presented 2D gaseous detector system has been developed and designed to provide energy resolved fast dynamic plasma radiation imaging in the soft X-Ray region with 0.1 kHz exposure frequency for online, made in real time, data acquisition (DAQ) mode. The detection structure is based on triple Gas Electron Multiplier (GEM) amplification structure followed by the pixel readout electrode. The efficiency of detecting unit was adjusted for the radiation energy region of tungsten in high-temperature plasma, the main candidate for the plasma facing material for future thermonuclear reactors. Here we present preliminary laboratory results and detector parameters obtained for the developed system. The operational characteristics and conditions of the detector were designed to work in the X-Ray range of 2-17 keV. The detector linearity was checked using the fluorescence lines of different elements and was found to be sufficient for good photon energy reconstruction. Images of two sources through various screens were performed with an X-Ray laboratory source and 55Fe source showing a good imaging capability. Finally offline stream-handling data acquisition mode has been developed for the detecting system with timing down to the ADC sampling frequency rate (~13 ns), up to 2.5 MHz of exposure frequency, which could pave the way to invaluable physics information about plasma dynamics due to very good time resolving ability. Here we present results of studied spatial resolution and imaging properties of the detector for conditions of laboratory moderate counting rates and high gain.
Imaging 2-D Structures With Receiver Functions Using Harmonic Stripping
NASA Astrophysics Data System (ADS)
Schulte-Pelkum, V.
2010-12-01
I present a novel technique to image dipping and anisotropic structures using receiver functions. Receiver functions isolate phase conversions from interfaces close to the seismic station. Standard analysis assumes a quasi-flat layered structure and dampens arrivals from dipping interfaces and anisotropic layers, with attempts to extract information on such structures relying on cumbersome and nonunique forward modeling. I use a simple relationship between the radial and transverse component receiver function to detect dipping and anisotropic layers and map their depth and orientation. For dipping interfaces, layers with horizontal or plunging axis anisotropy, and point scatterers, the following relationships hold: After subtracting the azimuthally invariant portion of the radial receiver functions, the remaining signal is an azimuthally shifted version of the transverse receiver functions. The strike of the dipping interface or anisotropy is given by the azimuth of polarity reversals, and the type of structure can be inferred from the amount of phase shift between the components. For a known structure type, the phase shift between the two components provides pseudoevents from back-azimuths with little seismicity. The technique allows structural mapping at depth akin to geological mapping of rock fabric and dipping layers at the surface. It reduces complex wavefield effects to two simple and geologically meaningful parameters, similar to shear wave splitting. I demonstrate the method on the Wind River Thrust as well as other structures within the Transportable Array footprint.
Imaging Excited State Dynamics with 2d Electronic Spectroscopy
NASA Astrophysics Data System (ADS)
Engel, Gregory S.
2012-06-01
Excited states in the condensed phase have extremely high chemical potentials making them highly reactive and difficult to control. Yet in biology, excited state dynamics operate with exquisite precision driving solar light harvesting in photosynthetic complexes though excitonic transport and photochemistry through non-radiative relaxation to photochemical products. Optimized by evolution, these biological systems display manifestly quantum mechanical behaviors including coherent energy transfer, steering wavepacket trajectories through conical intersections and protection of long-lived quantum coherence. To image the underlying excited state dynamics, we have developed a new spectroscopic method allowing us to capture excitonic structure in real time. Through this method and other ultrafast multidimensional spectroscopies, we have captured coherent dynamics within photosynthetic antenna complexes. The data not only reveal how biological systems operate, but these same spectral signatures can be exploited to create new spectroscopic tools to elucidate the underlying Hamiltonian. New data on the role of the protein in photosynthetic systems indicates that the chromophores mix strongly with some bath modes within the system. The implications of this mixing for excitonic transport will be discussed along with prospects for transferring underlying design principles to synthetic systems.
Kolbun, N; Adolfsson, E; Gustafsson, H; Lund, E
2014-06-01
Electron paramagnetic resonance imaging (EPRI) was performed to visualise 2D dose distributions of homogenously irradiated potassium dithionate tablets and to demonstrate determination of 1D dose profiles along the height of the tablets. Mathematical correction was applied for each relative dose profile in order to take into account the inhomogeneous response of the resonator using X-band EPRI. The dose profiles are presented with the spatial resolution of 0.6 mm from the acquired 2D images; this value is limited by pixel size, and 1D dose profiles from 1D imaging with spatial resolution of 0.3 mm limited by the intrinsic line-width of potassium dithionate. In this paper, dose profiles from 2D reconstructed electron paramagnetic resonance (EPR) images using the Xepr software package by Bruker are focussed. The conclusion is that using potassium dithionate, the resolution 0.3 mm is sufficient for mapping steep dose gradients if the dosemeters are covering only ±2 mm around the centre of the resonator. PMID:24748487
Chang, Chih-Ju; Lin, Geng-Li; Tse, Alex; Chu, Hong-Yu; Tseng, Ching-Shiow
2015-01-01
C-Arm image-assisted surgical navigation system has been broadly applied to spinal surgery. However, accurate path planning on the C-Arm AP-view image is difficult. This research studies 2D-3D image registration methods to obtain the optimum transformation matrix between C-Arm and CT image frames. Through the transformation matrix, the surgical path planned on preoperative CT images can be transformed and displayed on the C-Arm images for surgical guidance. The positions of surgical instruments will also be displayed on both CT and C-Arm in the real time. Five similarity measure methods of 2D-3D image registration including Normalized Cross-Correlation, Gradient Correlation, Pattern Intensity, Gradient Difference Correlation, and Mutual Information combined with three optimization methods including Powell's method, Downhill simplex algorithm, and genetic algorithm are applied to evaluate their performance in converge range, efficiency, and accuracy. Experimental results show that the combination of Normalized Cross-Correlation measure method with Downhill simplex algorithm obtains maximum correlation and similarity in C-Arm and Digital Reconstructed Radiograph (DRR) images. Spine saw bones are used in the experiment to evaluate 2D-3D image registration accuracy. The average error in displacement is 0.22 mm. The success rate is approximately 90% and average registration time takes 16 seconds. PMID:27018859
Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery
Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.
2016-01-01
During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.
Structured image reconstruction for three-dimensional ghost imaging lidar.
Yu, Hong; Li, Enrong; Gong, Wenlin; Han, Shensheng
2015-06-01
A structured image reconstruction method has been proposed to obtain high quality images in three-dimensional ghost imaging lidar. By considering the spatial structure relationship between recovered images of scene slices at different longitudinal distances, orthogonality constraint has been incorporated to reconstruct the three-dimensional scenes in remote sensing. Numerical simulations have been performed to demonstrate that scene slices with various sparse ratios can be recovered more accurately by applying orthogonality constraint, and the enhancement is significant especially for ghost imaging with less measurements. A simulated three-dimensional city scene has been successfully reconstructed by using structured image reconstruction in three-dimensional ghost imaging lidar. PMID:26072814
2D and 3D Refraction Based X-ray Imaging Suitable for Clinical and Pathological Diagnosis
Ando, Masami; Bando, Hiroko; Ueno, Ei
2007-01-19
The first observation of micro papillary (MP) breast cancer by x-ray dark-field imaging (XDFI) and the first observation of the 3D x-ray internal structure of another breast cancer, ductal carcinoma in-situ (DCIS), are reported. The specimen size for the sheet-shaped MP was 26 mm x 22 mm x 2.8 mm, and that for the rod-shaped DCIS was 3.6 mm in diameter and 4.7 mm in height. The experiment was performed at the Photon Factory, KEK: High Energy Accelerator Research Organization. We achieved a high-contrast x-ray image by adopting a thickness-controlled transmission-type angular analyzer that allows only refraction components from the object for 2D imaging. This provides a high-contrast image of cancer-cell nests, cancer cells and stroma. For x-ray 3D imaging, a new algorithm due to the refraction for x-ray CT was created. The angular information was acquired by x-ray optics diffraction-enhanced imaging (DEI). The number of data was 900 for each reconstruction. A reconstructed CT image may include ductus lactiferi, micro calcification and the breast gland. This modality has the possibility to open up a new clinical and pathological diagnosis using x-ray, offering more precise inspection and detection of early signs of breast cancer.
2D and 3D Refraction Based X-ray Imaging Suitable for Clinical and Pathological Diagnosis
NASA Astrophysics Data System (ADS)
Ando, Masami; Bando, Hiroko; Chen, Zhihua; Chikaura, Yoshinori; Choi, Chang-Hyuk; Endo, Tokiko; Esumi, Hiroyasu; Gang, Li; Hashimoto, Eiko; Hirano, Keiichi; Hyodo, Kazuyuki; Ichihara, Shu; Jheon, SangHoon; Kim, HongTae; Kim, JongKi; Kimura, Tatsuro; Lee, ChangHyun; Maksimenko, Anton; Ohbayashi, Chiho; Park, SungHwan; Shimao, Daisuke; Sugiyama, Hiroshi; Tang, Jintian; Ueno, Ei; Yamasaki, Katsuhito; Yuasa, Tetsuya
2007-01-01
The first observation of micro papillary (MP) breast cancer by x-ray dark-field imaging (XDFI) and the first observation of the 3D x-ray internal structure of another breast cancer, ductal carcinoma in-situ (DCIS), are reported. The specimen size for the sheet-shaped MP was 26 mm × 22 mm × 2.8 mm, and that for the rod-shaped DCIS was 3.6 mm in diameter and 4.7 mm in height. The experiment was performed at the Photon Factory, KEK: High Energy Accelerator Research Organization. We achieved a high-contrast x-ray image by adopting a thickness-controlled transmission-type angular analyzer that allows only refraction components from the object for 2D imaging. This provides a high-contrast image of cancer-cell nests, cancer cells and stroma. For x-ray 3D imaging, a new algorithm due to the refraction for x-ray CT was created. The angular information was acquired by x-ray optics diffraction-enhanced imaging (DEI). The number of data was 900 for each reconstruction. A reconstructed CT image may include ductus lactiferi, micro calcification and the breast gland. This modality has the possibility to open up a new clinical and pathological diagnosis using x-ray, offering more precise inspection and detection of early signs of breast cancer.
Twin robotic x-ray system for 2D radiographic and 3D cone-beam CT imaging
NASA Astrophysics Data System (ADS)
Fieselmann, Andreas; Steinbrener, Jan; Jerebko, Anna K.; Voigt, Johannes M.; Scholz, Rosemarie; Ritschl, Ludwig; Mertelmeier, Thomas
2016-03-01
In this work, we provide an initial characterization of a novel twin robotic X-ray system. This system is equipped with two motor-driven telescopic arms carrying X-ray tube and flat-panel detector, respectively. 2D radiographs and fluoroscopic image sequences can be obtained from different viewing angles. Projection data for 3D cone-beam CT reconstruction can be acquired during simultaneous movement of the arms along dedicated scanning trajectories. We provide an initial evaluation of the 3D image quality based on phantom scans and clinical images. Furthermore, initial evaluation of patient dose is conducted. The results show that the system delivers high image quality for a range of medical applications. In particular, high spatial resolution enables adequate visualization of bone structures. This system allows 3D X-ray scanning of patients in standing and weight-bearing position. It could enable new 2D/3D imaging workflows in musculoskeletal imaging and improve diagnosis of musculoskeletal disorders.
A new gold-standard dataset for 2D/3D image registration evaluation
NASA Astrophysics Data System (ADS)
Pawiro, Supriyanto; Markelj, Primoz; Gendrin, Christelle; Figl, Michael; Stock, Markus; Bloch, Christoph; Weber, Christoph; Unger, Ewald; Nöbauer, Iris; Kainberger, Franz; Bergmeister, Helga; Georg, Dietmar; Bergmann, Helmar; Birkfellner, Wolfgang
2010-02-01
In this paper, we propose a new gold standard data set for the validation of 2D/3D image registration algorithms for image guided radiotherapy. A gold standard data set was calculated using a pig head with attached fiducial markers. We used several imaging modalities common in diagnostic imaging or radiotherapy which include 64-slice computed tomography (CT), magnetic resonance imaging (MRI) using T1, T2 and proton density (PD) sequences, and cone beam CT (CBCT) imaging data. Radiographic data were acquired using kilovoltage (kV) and megavoltage (MV) imaging techniques. The image information reflects both anatomy and reliable fiducial marker information, and improves over existing data sets by the level of anatomical detail and image data quality. The markers of three dimensional (3D) and two dimensional (2D) images were segmented using Analyze 9.0 (AnalyzeDirect, Inc) and an in-house software. The projection distance errors (PDE) and the expected target registration errors (TRE) over all the image data sets were found to be less than 1.7 mm and 1.3 mm, respectively. The gold standard data set, obtained with state-of-the-art imaging technology, has the potential to improve the validation of 2D/3D registration algorithms for image guided therapy.
Research on reconstruction algorithms for 2D temperature field based on TDLAS
NASA Astrophysics Data System (ADS)
Peng, Dong; Jin, Yi; Zhai, Chao
2015-10-01
Tunable Diode Laser Absorption Tomography(TDLAT), as a promising technique which combines Tunable Diode Laser Absorption Spectroscopy(TDLAS) and computer tomography, has shown the advantages of high spatial resolution for temperature measurement. Given the large number of tomography algorithms, it is necessary to understand the feature of tomography algorithms and find suitable ones for the specific experiment. This paper illustrates two different algorithms including algebraic reconstruction technique (ART) and simulated annealing (SA) which are implemented using Matlab. The reconstruction simulations of unimodal and bimodal temperature phantom were done under different conditions, and the results of the simulation were analyzed. It shows that for the unimodal temperature phantom, the both algorithms work well, the reconstruction quality is acceptable under suitable conditions and the result of ART is better. But for the bimodal temperature phantom, the result of SA is much better. More specifically, the reconstruction quality of ART is mainly affected by the ray coverage, the maximum deviation for the unimodal temperature phantom is 5.9%, while for the bimodal temperature field, it is up to 25%. The reconstruction quality of SA is mainly affected by the number of the transitions, the maximum deviation for the unimodal temperature phantom is 9.2% when 6 transitions are used which is a little worse than the result of ART; however, the maximum deviation for the bimodal temperature phantom is much better than ART's, which is about 5.2% when 6 transitions are used.
Lin, L. Ding, W. X.; Brower, D. L.
2014-11-15
Combined polarimetry-interferometry capability permits simultaneous measurement of line-integrated density and Faraday effect with fast time response (∼1 μs) and high sensitivity. Faraday effect fluctuations with phase shift of order 0.05° associated with global tearing modes are resolved with an uncertainty ∼0.01°. For physics investigations, local density fluctuations are obtained by inverting the line-integrated interferometry data. The local magnetic and current density fluctuations are then reconstructed using a parameterized fit of the polarimetry data. Reconstructed 2D images of density and magnetic field fluctuations in a poloidal cross section exhibit significantly different spatial structure. Combined with their relative phase, the magnetic-fluctuation-induced particle transport flux and its spatial distribution are resolved.
Auto-masked 2D/3D image registration and its validation with clinical cone-beam computed tomography
NASA Astrophysics Data System (ADS)
Steininger, P.; Neuner, M.; Weichenberger, H.; Sharp, G. C.; Winey, B.; Kametriser, G.; Sedlmayer, F.; Deutschmann, H.
2012-07-01
Image-guided alignment procedures in radiotherapy aim at minimizing discrepancies between the planned and the real patient setup. For that purpose, we developed a 2D/3D approach which rigidly registers a computed tomography (CT) with two x-rays by maximizing the agreement in pixel intensity between the x-rays and the corresponding reconstructed radiographs from the CT. Moreover, the algorithm selects regions of interest (masks) in the x-rays based on 3D segmentations from the pre-planning stage. For validation, orthogonal x-ray pairs from different viewing directions of 80 pelvic cone-beam CT (CBCT) raw data sets were used. The 2D/3D results were compared to corresponding standard 3D/3D CBCT-to-CT alignments. Outcome over 8400 2D/3D experiments showed that parametric errors in root mean square were <0.18° (rotations) and <0.73 mm (translations), respectively, using rank correlation as intensity metric. This corresponds to a mean target registration error, related to the voxels of the lesser pelvis, of <2 mm in 94.1% of the cases. From the results we conclude that 2D/3D registration based on sequentially acquired orthogonal x-rays of the pelvis is a viable alternative to CBCT-based approaches if rigid alignment on bony anatomy is sufficient, no volumetric intra-interventional data set is required and the expected error range fits the individual treatment prescription.
Auto-masked 2D/3D image registration and its validation with clinical cone-beam computed tomography.
Steininger, P; Neuner, M; Weichenberger, H; Sharp, G C; Winey, B; Kametriser, G; Sedlmayer, F; Deutschmann, H
2012-07-01
Image-guided alignment procedures in radiotherapy aim at minimizing discrepancies between the planned and the real patient setup. For that purpose, we developed a 2D/3D approach which rigidly registers a computed tomography (CT) with two x-rays by maximizing the agreement in pixel intensity between the x-rays and the corresponding reconstructed radiographs from the CT. Moreover, the algorithm selects regions of interest (masks) in the x-rays based on 3D segmentations from the pre-planning stage. For validation, orthogonal x-ray pairs from different viewing directions of 80 pelvic cone-beam CT (CBCT) raw data sets were used. The 2D/3D results were compared to corresponding standard 3D/3D CBCT-to-CT alignments. Outcome over 8400 2D/3D experiments showed that parametric errors in root mean square were <0.18° (rotations) and <0.73 mm (translations), respectively, using rank correlation as intensity metric. This corresponds to a mean target registration error, related to the voxels of the lesser pelvis, of <2 mm in 94.1% of the cases. From the results we conclude that 2D/3D registration based on sequentially acquired orthogonal x-rays of the pelvis is a viable alternative to CBCT-based approaches if rigid alignment on bony anatomy is sufficient, no volumetric intra-interventional data set is required and the expected error range fits the individual treatment prescription. PMID:22705709
Studies on image compression and image reconstruction
NASA Technical Reports Server (NTRS)
Sayood, Khalid; Nori, Sekhar; Araj, A.
1994-01-01
During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.
Pragmatic fully 3D image reconstruction for the MiCES mouse imaging PET scanner
NASA Astrophysics Data System (ADS)
Lee, Kisung; Kinahan, Paul E.; Fessler, Jeffrey A.; Miyaoka, Robert S.; Janes, Marie; Lewellen, Tom K.
2004-10-01
We present a pragmatic approach to image reconstruction for data from the micro crystal elements system (MiCES) fully 3D mouse imaging positron emission tomography (PET) scanner under construction at the University of Washington. Our approach is modelled on fully 3D image reconstruction used in clinical PET scanners, which is based on Fourier rebinning (FORE) followed by 2D iterative image reconstruction using ordered-subsets expectation-maximization (OSEM). The use of iterative methods allows modelling of physical effects (e.g., statistical noise, detector blurring, attenuation, etc), while FORE accelerates the reconstruction process by reducing the fully 3D data to a stacked set of independent 2D sinograms. Previous investigations have indicated that non-stationary detector point-spread response effects, which are typically ignored for clinical imaging, significantly impact image quality for the MiCES scanner geometry. To model the effect of non-stationary detector blurring (DB) in the FORE+OSEM(DB) algorithm, we have added a factorized system matrix to the ASPIRE reconstruction library. Initial results indicate that the proposed approach produces an improvement in resolution without an undue increase in noise and without a significant increase in the computational burden. The impact on task performance, however, remains to be evaluated.
Incremental volume reconstruction and rendering for 3-D ultrasound imaging
NASA Astrophysics Data System (ADS)
Ohbuchi, Ryutarou; Chen, David; Fuchs, Henry
1992-09-01
In this paper, we present approaches toward an interactive visualization of a real time input, applied to 3-D visualizations of 2-D ultrasound echography data. The first, 3 degrees-of- freedom (DOF) incremental system visualizes a 3-D volume acquired as a stream of 2-D slices with location and orientation with 3 DOF. As each slice arrives, the system reconstructs a regular 3-D volume and renders it. Rendering is done by an incremental image-order ray- casting algorithm which stores and reuses the results of expensive resampling along the rays for speed. The second is our first experiment toward real-time 6 DOF acquisition and visualization. Two-dimensional slices with 6 DOF are reconstructed off-line, and visualized at an interactive rate using a parallel volume rendering code running on the graphics multicomputer Pixel-Planes 5.
First results from ideal 2-D MHD reconstruction: magnetopause reconnection event seen by Cluster
NASA Astrophysics Data System (ADS)
Teh, W.-L.; Ã-. Sonnerup, B. U.
2008-09-01
We have applied a new reconstruction method (Sonnerup and Teh, 2008), based on the ideal single-fluid MHD equations in a steady-state, two-dimensional geometry, to a reconnection event observed by the Cluster-3 (C3) spacecraft on 5 July 2001, 06:23 UT, at the dawn-side Northern-Hemisphere magnetopause. The event has been previously studied by use of Grad-Shafranov (GS) reconstruction, performed in the deHoffmann-Teller frame, and using the assumption that the flow effects were either negligible or the flow was aligned with the magnetic field. Our new method allows the reconstruction to be performed in the frame of reference moving with the reconnection site (the X-line). In the event studied, this motion is tailward/equatorward at 140 km/s. The principal result of the study is that the new method functions well, generating a magnetic field map that is qualitatively similar to those obtained in the earlier GS-based reconstructions but now includes the reconnection site itself. In comparison with the earlier map by Hasegawa et al. (2004), our new map has a slightly improved ability (cc=0.979 versus cc=0.975) to predict the fields measured by the other three Cluster spacecraft, at distances from C3 ranging from 2132 km (C1) to 2646 km (C4). The new field map indicates the presence of a magnetic X-point, located some 5300 km tailward/equatorward of C3 at the time of its traversal of the magnetopause. In the immediate vicinity of the X-point, the ideal-MHD assumption breaks down, i.e. resistive and/or other effects should be included. We have circumvented this problem by an ad-hoc procedure in which we allow the axial part of convection electric field to be non-constant near the reconnection site. The new reconstruction method also provides a map of the velocity field, in which the inflow into the wedge of reconnected field lines and the plasma jet within it can be seen, and maps of the electric potential and of the electric current distribution. Even though the
Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms
NASA Astrophysics Data System (ADS)
Sidky, Emil Y.; Jørgensen, Jakob H.; Pan, Xiaochuan
2012-03-01
Image reconstruction from sparse-view data in 2D fan-beam CT is investigated by constrained, total-variation minimization. This optimization problem exploits possible sparsity in the gradient magnitude image (GMI). The investigation is performed in simulation under ideal, noiseless data conditions in order to reveal a possible link between GMI sparsity and the necessary number of projection views for reconstructing an accurate image. Results are shown for two, quite different phantoms of similar GMI sparsity.
Comparison of Parallel MRI Reconstruction Methods for Accelerated 3D Fast Spin-Echo Imaging
Xiao, Zhikui; Hoge, W. Scott; Mulkern, R.V.; Zhao, Lei; Hu, Guangshu; Kyriakos, Walid E.
2014-01-01
Parallel MRI (pMRI) achieves imaging acceleration by partially substituting gradient-encoding steps with spatial information contained in the component coils of the acquisition array. Variable-density subsampling in pMRI was previously shown to yield improved two-dimensional (2D) imaging in comparison to uniform subsampling, but has yet to be used routinely in clinical practice. In an effort to reduce acquisition time for 3D fast spin-echo (3D-FSE) sequences, this work explores a specific nonuniform sampling scheme for 3D imaging, subsampling along two phase-encoding (PE) directions on a rectilinear grid. We use two reconstruction methods—2D-GRAPPA-Operator and 2D-SPACE RIP—and present a comparison between them. We show that high-quality images can be reconstructed using both techniques. To evaluate the proposed sampling method and reconstruction schemes, results via simulation, phantom study, and in vivo 3D human data are shown. We find that fewer artifacts can be seen in the 2D-SPACE RIP reconstructions than in 2D-GRAPPA-Operator reconstructions, with comparable reconstruction times. PMID:18727083
Restoration and reconstruction from overlapping images
NASA Technical Reports Server (NTRS)
Reichenbach, Stephen E.; Kaiser, Daniel J.; Hanson, Andrew L.; Li, Jing
1997-01-01
This paper describes a technique for restoring and reconstructing a scene from overlapping images. In situations where there are multiple, overlapping images of the same scene, it may be desirable to create a single image that most closely approximates the scene, based on all of the data in the available images. For example, successive swaths acquired by NASA's planned Moderate Imaging Spectrometer (MODIS) will overlap, particularly at wide scan angles, creating a severe visual artifact in the output image. Resampling the overlapping swaths to produce a more accurate image on a uniform grid requires restoration and reconstruction. The one-pass restoration and reconstruction technique developed in this paper yields mean-square-optimal resampling, based on a comprehensive end-to-end system model that accounts for image overlap, and subject to user-defined and data-availability constraints on the spatial support of the filter.
A 2-D orientation-adaptive prediction filter in lifting structures for image coding.
Gerek, Omer N; Cetin, A Enis
2006-01-01
Lifting-style implementations of wavelets are widely used in image coders. A two-dimensional (2-D) edge adaptive lifting structure, which is similar to Daubechies 5/3 wavelet, is presented. The 2-D prediction filter predicts the value of the next polyphase component according to an edge orientation estimator of the image. Consequently, the prediction domain is allowed to rotate +/-45 degrees in regions with diagonal gradient. The gradient estimator is computationally inexpensive with additional costs of only six subtractions per lifting instruction, and no multiplications are required. PMID:16435541
2-D nonlinear IIR-filters for image processing - An exploratory analysis
NASA Technical Reports Server (NTRS)
Bauer, P. H.; Sartori, M.
1991-01-01
A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.
Peters, Dana C.; Ennis, Daniel B.; Rohatgi, Pratik; Syed, Mushabbar A.; McVeigh, Elliot R.; Arai, Andrew E.
2007-01-01
Purpose: To develop and validate a three-dimensional (3D) single breath-hold, projection reconstruction (PR), balanced steady state free precession (SSFP) method for cardiac function evaluation against a two-dimensional (2D) multislice Fourier (Cartesian) transform (FT) SSFP method. Materials and Methods: The 3D PR SSFP sequence used projections in the x-y plane and partitions in z, providing 70–80 msec temporal resolution and 1.7 × 1.7 × 8–10 mm in a 24-heartbeat breath hold. A total of 10 volunteers were imaged with both methods, and the measurements of global cardiac function were compared. Results: Mean signal-to-noise ratios (SNRs) for the blood and myocardium were 114 and 42 (2D) and 59 and 21 (3D). Bland-Altman analysis comparing the 2D and 3D ejection fraction (EF), left ventricular end diastolic volume (LVEDV) and end systolic volume (LVESV), and end diastolic myocardial mass (LVEDM) provided values of bias ±2 SD of 0.6% ± 7.7 % for LVEF, 5.9 mL ± 20 mL for LVEDV, −2.8 mL ± 12 mL for LVESV, and −0.61 g ± 13 g for LVEDM. 3D interobserver variability was greater than 2D for LVEDM and LVESV. Conclusion: In a single breath hold, the 3D PR method provides comparable information to the standard 2D FT method, which employs 10–12 breath holds. PMID:15332248
NASA Astrophysics Data System (ADS)
Zanchi, Andrea; Agliardi, Federico; Crosta, Giovanni B.; Villa, Alberto; Bistacchi, Andrea; Iudica, Gaetano
2015-04-01
points based on their normal vector orientations to identify and map bedding and fractures. Combined stereographic analysis of bedding orientations and use of filters allowed the quantification of fold hinge and limb geometries and their 3D reconstruction in GOCAD. Fracture patterns derived from points clouds and field data allowed identifying different geomechanical domains associated to the folded structure. Our results encourage the integrated analysis of high-resolution point clouds and detailed structural and geomechanical field data as inputs to the 3D geometrical reconstruction and modelling of folded rock masses. Validation of virtual outcrop reconstructions through a comparison with field structural measurements suggests that very precise geometrical constraints can be obtained by TLS on geological bodies with complex geometrical features. However, additional constraints on TLS survey layout design are required to optimise the reconstruction and distinction of specific structural elements associated to folding as bedding and fold-related fracture systems.
Separation of image parts using 2-D parallel form recursive filters.
Sivaramakrishna, R
1996-01-01
This correspondence deals with a new technique to separate objects or image parts in a composite image. A parallel form extension of a 2-D Steiglitz-McBride method is applied to the discrete cosine transform (DCT) of the image containing the objects that are to be separated. The obtained parallel form is the sum of several filters or systems, where the impulse response of each filter corresponds to the DCT of one object in the original image. Preliminary results on an image with two objects show that the algorithm works well, even in the case where one object occludes another as well as in the case of moderate noise. PMID:18285105
Gated cardiac NMR imaging and 2D echocardiography in the detection of intracardial neoplasm
Go, R.T.; O'Donnell, J.K.; Salcedo, E.E.; Feiglin, D.H.; Underwood, D.A.; MacIntyre, W.J.; Meaney, T.F.
1985-05-01
Noninvasive 2D echocardiography has replaced contrast angiography as the procedure of choice in the diagnosis of intracardiac neoplasm. The purpose of this study was to determine whether intracardiac neoplasm can be detected as well by gated cardiac NMR. Four patients with known intracardiac neoplasm previously diagnosed by 2D echocardiography had gated cardiac NMR imaging using a superconductive 0.6 Tesla magnet. All patients were performed using a Tl weighted spin echo pulse sequence with a TE of 30 msec and TR of one R-R interval. Two-dimensional planar single or multiple slice techniques were used. In one patient, imaging at different times along the R-R interval were performed for cine display. The results of the present study show detection of the intracardiac neoplasm in all four cases by gated cardiac NMR imaging and the results were comparable to 2D echocardiography. The former imaging technique showed superior spatial resolution. Despite its early stage of development, gated cardiac NMR imaging appears at least equal to 2D echocardiography in the detection of intracardiac neoplasm. The availability of multislice coupled with multiframe acquisition techniques now being developed will provide a cinematic display that will be more effective in the display of the tumor in motion within the cardiac chamber involved and facilitate visualization of the relationship of the tumor to adjacent cardiac structures.
Bosi, Susanna; Rauti, Rossana; Laishram, Jummi; Turco, Antonio; Lonardoni, Davide; Nieus, Thierry; Prato, Maurizio; Scaini, Denis; Ballerini, Laura
2015-01-01
To recreate in vitro 3D neuronal circuits will ultimately increase the relevance of results from cultured to whole-brain networks and will promote enabling technologies for neuro-engineering applications. Here we fabricate novel elastomeric scaffolds able to instruct 3D growth of living primary neurons. Such systems allow investigating the emerging activity, in terms of calcium signals, of small clusters of neurons as a function of the interplay between the 2D or 3D architectures and network dynamics. We report the ability of 3D geometry to improve functional organization and synchronization in small neuronal assemblies. We propose a mathematical modelling of network dynamics that supports such a result. Entrapping carbon nanotubes in the scaffolds remarkably boosted synaptic activity, thus allowing for the first time to exploit nanomaterial/cell interfacing in 3D growth support. Our 3D system represents a simple and reliable construct, able to improve the complexity of current tissue culture models. PMID:25910072
Spectral image reconstruction through the PCA transform
NASA Astrophysics Data System (ADS)
Ma, Long; Qiu, Xuewei; Cong, Yangming
2015-12-01
Digital color image reproduction based on spectral information has become a field of much interest and practical importance in recent years. The representation of color in digital form with multi-band images is not very accurate, hence the use of spectral image is justified. Reconstructing high-dimensional spectral reflectance images from relatively low-dimensional camera signals is generally an ill-posed problem. The aim of this study is to use the Principal component analysis (PCA) transform in spectral reflectance images reconstruction. The performance is evaluated by the mean, median and standard deviation of color difference values. The values of mean, median and standard deviation of root mean square (GFC) errors between the reconstructed and the actual spectral image were also calculated. Simulation experiments conducted on a six-channel camera system and on spectral test images show the performance of the suggested method.
Comparative study on 3D-2D convertible integral imaging systems
NASA Astrophysics Data System (ADS)
Choi, Heejin; Kim, Joohwan; Kim, Yunhee; Lee, Byoungho
2006-02-01
In spite of significant improvements in three-dimensional (3D) display fields, the commercialization of a 3D-only display system is not achieved yet. The mainstream of display market is a high performance two-dimensional (2D) flat panel display (FPD) and the beginning of the high-definition (HD) broadcasting accelerates the opening of the golden age of HD FPDs. Therefore, a 3D display system needs to be able to display a 2D image with high quality. In this paper, two different 3D-2D convertible methods based on integral imaging are compared and categorized for its applications. One method uses a point light source array and a polymer-dispersed liquid crystal and one display panel. The other system adopts two display panels and a lens array. The former system is suitable for mobile applications while the latter is for home applications such as monitors and TVs.
Tensor representation of color images and fast 2D quaternion discrete Fourier transform
NASA Astrophysics Data System (ADS)
Grigoryan, Artyom M.; Agaian, Sos S.
2015-03-01
In this paper, a general, efficient, split algorithm to compute the two-dimensional quaternion discrete Fourier transform (2-D QDFT), by using the special partitioning in the frequency domain, is introduced. The partition determines an effective transformation, or color image representation in the form of 1-D quaternion signals which allow for splitting the N × M-point 2-D QDFT into a set of 1-D QDFTs. Comparative estimates revealing the efficiency of the proposed algorithms with respect to the known ones are given. In particular, a proposed method of calculating the 2r × 2r -point 2-D QDFT uses 18N2 less multiplications than the well-known column-row method and method of calculation based on the symplectic decomposition. The proposed algorithm is simple to apply and design, which makes it very practical in color image processing in the frequency domain.
Automatic 2D-to-3D image conversion using 3D examples from the internet
NASA Astrophysics Data System (ADS)
Konrad, J.; Brown, G.; Wang, M.; Ishwar, P.; Wu, C.; Mukherjee, D.
2012-03-01
The availability of 3D hardware has so far outpaced the production of 3D content. Although to date many methods have been proposed to convert 2D images to 3D stereopairs, the most successful ones involve human operators and, therefore, are time-consuming and costly, while the fully-automatic ones have not yet achieved the same level of quality. This subpar performance is due to the fact that automatic methods usually rely on assumptions about the captured 3D scene that are often violated in practice. In this paper, we explore a radically different approach inspired by our work on saliency detection in images. Instead of relying on a deterministic scene model for the input 2D image, we propose to "learn" the model from a large dictionary of stereopairs, such as YouTube 3D. Our new approach is built upon a key observation and an assumption. The key observation is that among millions of stereopairs available on-line, there likely exist many stereopairs whose 3D content matches that of the 2D input (query). We assume that two stereopairs whose left images are photometrically similar are likely to have similar disparity fields. Our approach first finds a number of on-line stereopairs whose left image is a close photometric match to the 2D query and then extracts depth information from these stereopairs. Since disparities for the selected stereopairs differ due to differences in underlying image content, level of noise, distortions, etc., we combine them by using the median. We apply the resulting median disparity field to the 2D query to obtain the corresponding right image, while handling occlusions and newly-exposed areas in the usual way. We have applied our method in two scenarios. First, we used YouTube 3D videos in search of the most similar frames. Then, we repeated the experiments on a small, but carefully-selected, dictionary of stereopairs closely matching the query. This, to a degree, emulates the results one would expect from the use of an extremely large 3D
Atherosclerosis imaging using 3D black blood TSE SPACE vs 2D TSE
Wong, Stephanie K; Mobolaji-Iawal, Motunrayo; Arama, Leron; Cambe, Joy; Biso, Sylvia; Alie, Nadia; Fayad, Zahi A; Mani, Venkatesh
2014-01-01
AIM: To compare 3D Black Blood turbo spin echo (TSE) sampling perfection with application-optimized contrast using different flip angle evolution (SPACE) vs 2D TSE in evaluating atherosclerotic plaques in multiple vascular territories. METHODS: The carotid, aortic, and femoral arterial walls of 16 patients at risk for cardiovascular or atherosclerotic disease were studied using both 3D black blood magnetic resonance imaging SPACE and conventional 2D multi-contrast TSE sequences using a consolidated imaging approach in the same imaging session. Qualitative and quantitative analyses were performed on the images. Agreement of morphometric measurements between the two imaging sequences was assessed using a two-sample t-test, calculation of the intra-class correlation coefficient and by the method of linear regression and Bland-Altman analyses. RESULTS: No statistically significant qualitative differences were found between the 3D SPACE and 2D TSE techniques for images of the carotids and aorta. For images of the femoral arteries, however, there were statistically significant differences in all four qualitative scores between the two techniques. Using the current approach, 3D SPACE is suboptimal for femoral imaging. However, this may be due to coils not being optimized for femoral imaging. Quantitatively, in our study, higher mean total vessel area measurements for the 3D SPACE technique across all three vascular beds were observed. No significant differences in lumen area for both the right and left carotids were observed between the two techniques. Overall, a significant-correlation existed between measures obtained between the two approaches. CONCLUSION: Qualitative and quantitative measurements between 3D SPACE and 2D TSE techniques are comparable. 3D-SPACE may be a feasible approach in the evaluation of cardiovascular patients. PMID:24876923
Parameterising root system growth models using 2D neutron radiography images
NASA Astrophysics Data System (ADS)
Schnepf, Andrea; Felderer, Bernd; Vontobel, Peter; Leitner, Daniel
2013-04-01
Root architecture is a key factor for plant acquisition of water and nutrients from soil. In particular in view of a second green revolution where the below ground parts of agricultural crops are important, it is essential to characterise and quantify root architecture and its effect on plant resource acquisition. Mathematical models can help to understand the processes occurring in the soil-plant system, they can be used to quantify the effect of root and rhizosphere traits on resource acquisition and the response to environmental conditions. In order to do so, root architectural models are coupled with a model of water and solute transport in soil. However, dynamic root architectural models are difficult to parameterise. Novel imaging techniques such as x-ray computed tomography, neutron radiography and magnetic resonance imaging enable the in situ visualisation of plant root systems. Therefore, these images facilitate the parameterisation of dynamic root architecture models. These imaging techniques are capable of producing 3D or 2D images. Moreover, 2D images are also available in the form of hand drawings or from images of standard cameras. While full 3D imaging tools are still limited in resolutions, 2D techniques are a more accurate and less expensive option for observing roots in their environment. However, analysis of 2D images has additional difficulties compared to the 3D case, because of overlapping roots. We present a novel algorithm for the parameterisation of root system growth models based on 2D images of root system. The algorithm analyses dynamic image data. These are a series of 2D images of the root system at different points in time. Image data has already been adjusted for missing links and artefacts and segmentation was performed by applying a matched filter response. From this time series of binary 2D images, we parameterise the dynamic root architecture model in the following way: First, a morphological skeleton is derived from the binary
4D image reconstruction for emission tomography
NASA Astrophysics Data System (ADS)
Reader, Andrew J.; Verhaeghe, Jeroen
2014-11-01
An overview of the theory of 4D image reconstruction for emission tomography is given along with a review of the current state of the art, covering both positron emission tomography and single photon emission computed tomography (SPECT). By viewing 4D image reconstruction as a matter of either linear or non-linear parameter estimation for a set of spatiotemporal functions chosen to approximately represent the radiotracer distribution, the areas of so-called ‘fully 4D’ image reconstruction and ‘direct kinetic parameter estimation’ are unified within a common framework. Many choices of linear and non-linear parameterization of these functions are considered (including the important case where the parameters have direct biological meaning), along with a review of the algorithms which are able to estimate these often non-linear parameters from emission tomography data. The other crucial components to image reconstruction (the objective function, the system model and the raw data format) are also covered, but in less detail due to the relatively straightforward extension from their corresponding components in conventional 3D image reconstruction. The key unifying concept is that maximum likelihood or maximum a posteriori (MAP) estimation of either linear or non-linear model parameters can be achieved in image space after carrying out a conventional expectation maximization (EM) update of the dynamic image series, using a Kullback-Leibler distance metric (comparing the modeled image values with the EM image values), to optimize the desired parameters. For MAP, an image-space penalty for regularization purposes is required. The benefits of 4D and direct reconstruction reported in the literature are reviewed, and furthermore demonstrated with simple simulation examples. It is clear that the future of reconstructing dynamic or functional emission tomography images, which often exhibit high levels of spatially correlated noise, should ideally exploit these 4D
Blockwise conjugate gradient methods for image reconstruction in volumetric CT.
Qiu, W; Titley-Peloquin, D; Soleimani, M
2012-11-01
Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. PMID:22325240
Image reconstruction for robot assisted ultrasound tomography
NASA Astrophysics Data System (ADS)
Aalamifar, Fereshteh; Zhang, Haichong K.; Rahmim, Arman; Boctor, Emad M.
2016-04-01
An investigation of several image reconstruction methods for robot-assisted ultrasound (US) tomography setup is presented. In the robot-assisted setup, an expert moves the US probe to the location of interest, and a robotic arm automatically aligns another US probe with it. The two aligned probes can then transmit and receive US signals which are subsequently used for tomographic reconstruction. This study focuses on reconstruction of the speed of sound. In various simulation evaluations as well as in an experiment with a millimeter-range inaccuracy, we demonstrate that the limited data provided by two probes can be used to reconstruct pixel-wise images differentiating between media with different speeds of sound. Combining the results of this investigation with the developed robot-assisted US tomography setup, we envision feasibility of this setup for tomographic imaging in applications beyond breast imaging, with potentially significant efficacy in cancer diagnosis.
2D electron temperature diagnostic using soft x-ray imaging technique
Nishimura, K. Sanpei, A. Tanaka, H.; Ishii, G.; Kodera, R.; Ueba, R.; Himura, H.; Masamune, S.; Ohdachi, S.; Mizuguchi, N.
2014-03-15
We have developed a two-dimensional (2D) electron temperature (T{sub e}) diagnostic system for thermal structure studies in a low-aspect-ratio reversed field pinch (RFP). The system consists of a soft x-ray (SXR) camera with two pin holes for two-kinds of absorber foils, combined with a high-speed camera. Two SXR images with almost the same viewing area are formed through different absorber foils on a single micro-channel plate (MCP). A 2D T{sub e} image can then be obtained by calculating the intensity ratio for each element of the images. We have succeeded in distinguishing T{sub e} image in quasi-single helicity (QSH) from that in multi-helicity (MH) RFP states, where the former is characterized by concentrated magnetic fluctuation spectrum and the latter, by broad spectrum of edge magnetic fluctuations.
2D imaging and 3D sensing data acquisition and mutual registration for painting conservation
NASA Astrophysics Data System (ADS)
Fontana, Raffaella; Gambino, Maria Chiara; Greco, Marinella; Marras, Luciano; Pampaloni, Enrico M.; Pelagotti, Anna; Pezzati, Luca; Poggi, Pasquale
2005-01-01
We describe the application of 2D and 3D data acquisition and mutual registration to the conservation of paintings. RGB color image acquisition, IR and UV fluorescence imaging, together with the more recent hyperspectral imaging (32 bands) are among the most useful techniques in this field. They generally are meant to provide information on the painting materials, on the employed techniques and on the object state of conservation. However, only when the various images are perfectly registered on each other and on the 3D model, no ambiguity is possible and safe conclusions may be drawn. We present the integration of 2D and 3D measurements carried out on two different paintings: "Madonna of the Yarnwinder" by Leonardo da Vinci, and "Portrait of Lionello d'Este", by Pisanello, both painted in the XV century.
2D imaging and 3D sensing data acquisition and mutual registration for painting conservation
NASA Astrophysics Data System (ADS)
Fontana, Raffaella; Gambino, Maria Chiara; Greco, Marinella; Marras, Luciano; Pampaloni, Enrico M.; Pelagotti, Anna; Pezzati, Luca; Poggi, Pasquale
2004-12-01
We describe the application of 2D and 3D data acquisition and mutual registration to the conservation of paintings. RGB color image acquisition, IR and UV fluorescence imaging, together with the more recent hyperspectral imaging (32 bands) are among the most useful techniques in this field. They generally are meant to provide information on the painting materials, on the employed techniques and on the object state of conservation. However, only when the various images are perfectly registered on each other and on the 3D model, no ambiguity is possible and safe conclusions may be drawn. We present the integration of 2D and 3D measurements carried out on two different paintings: "Madonna of the Yarnwinder" by Leonardo da Vinci, and "Portrait of Lionello d'Este", by Pisanello, both painted in the XV century.
3D multiple-point statistics simulation using 2D training images
NASA Astrophysics Data System (ADS)
Comunian, A.; Renard, P.; Straubhaar, J.
2012-03-01
One of the main issues in the application of multiple-point statistics (MPS) to the simulation of three-dimensional (3D) blocks is the lack of a suitable 3D training image. In this work, we compare three methods of overcoming this issue using information coming from bidimensional (2D) training images. One approach is based on the aggregation of probabilities. The other approaches are novel. One relies on merging the lists obtained using the impala algorithm from diverse 2D training images, creating a list of compatible data events that is then used for the MPS simulation. The other (s2Dcd) is based on sequential simulations of 2D slices constrained by the conditioning data computed at the previous simulation steps. These three methods are tested on the reproduction of two 3D images that are used as references, and on a real case study where two training images of sedimentary structures are considered. The tests show that it is possible to obtain 3D MPS simulations with at least two 2D training images. The simulations obtained, in particular those obtained with the s2Dcd method, are close to the references, according to a number of comparison criteria. The CPU time required to simulate with the method s2Dcd is from two to four orders of magnitude smaller than the one required by a MPS simulation performed using a 3D training image, while the results obtained are comparable. This computational efficiency and the possibility of using MPS for 3D simulation without the need for a 3D training image facilitates the inclusion of MPS in Monte Carlo, uncertainty evaluation, and stochastic inverse problems frameworks.
Combining 2D synchrosqueezed wave packet transform with optimization for crystal image analysis
NASA Astrophysics Data System (ADS)
Lu, Jianfeng; Wirth, Benedikt; Yang, Haizhao
2016-04-01
We develop a variational optimization method for crystal analysis in atomic resolution images, which uses information from a 2D synchrosqueezed transform (SST) as input. The synchrosqueezed transform is applied to extract initial information from atomic crystal images: crystal defects, rotations and the gradient of elastic deformation. The deformation gradient estimate is then improved outside the identified defect region via a variational approach, to obtain more robust results agreeing better with the physical constraints. The variational model is optimized by a nonlinear projected conjugate gradient method. Both examples of images from computer simulations and imaging experiments are analyzed, with results demonstrating the effectiveness of the proposed method.
Image Reconstruction for Prostate Specific Nuclear Medicine imagers
Mark Smith
2007-01-11
There is increasing interest in the design and construction of nuclear medicine detectors for dedicated prostate imaging. These include detectors designed for imaging the biodistribution of radiopharmaceuticals labeled with single gamma as well as positron-emitting radionuclides. New detectors and acquisition geometries present challenges and opportunities for image reconstruction. In this contribution various strategies for image reconstruction for these special purpose imagers are reviewed. Iterative statistical algorithms provide a framework for reconstructing prostate images from a wide variety of detectors and acquisition geometries for PET and SPECT. The key to their success is modeling the physics of photon transport and data acquisition and the Poisson statistics of nuclear decay. Analytic image reconstruction methods can be fast and are useful for favorable acquisition geometries. Future perspectives on algorithm development and data analysis for prostate imaging are presented.
2D and 3D imaging resolution trade-offs in quantifying pore throats for prediction of permeability
Beckingham, Lauren E.; Peters, Catherine A.; Um, Wooyong; Jones, Keith W.; Lindquist, W.Brent
2013-09-03
Although the impact of subsurface geochemical reactions on porosity is relatively well understood, changes in permeability remain difficult to estimate. In this work, pore-network modeling was used to predict permeability based on pore- and pore-throat size distributions determined from analysis of 2D scanning electron microscopy (SEM) images of thin sections and 3D X-ray computed microtomography (CMT) data. The analyzed specimens were a Viking sandstone sample from the Alberta sedimentary basin and an experimental column of reacted Hanford sediments. For the column, a decrease in permeability due to mineral precipitation was estimated, but the permeability estimates were dependent on imaging technique and resolution. X-ray CT imaging has the advantage of reconstructing a 3D pore network while 2D SEM imaging can easily analyze sub-grain and intragranular variations in mineralogy. Pore network models informed by analyses of 2D and 3D images at comparable resolutions produced permeability esti- mates with relatively good agreement. Large discrepancies in predicted permeabilities resulted from small variations in image resolution. Images with resolutions 0.4 to 4 lm predicted permeabilities differ- ing by orders of magnitude. While lower-resolution scans can analyze larger specimens, small pore throats may be missed due to resolution limitations, which in turn overestimates permeability in a pore-network model in which pore-to-pore conductances are statistically assigned. Conversely, high-res- olution scans are capable of capturing small pore throats, but if they are not actually flow-conducting predicted permeabilities will be below expected values. In addition, permeability is underestimated due to misinterpreting surface-roughness features as small pore throats. Comparison of permeability pre- dictions with expected and measured permeability values showed that the largest discrepancies resulted from the highest resolution images and the best predictions of
Tracking objects outside the line of sight using 2D intensity images
Klein, Jonathan; Peters, Christoph; Martín, Jaime; Laurenzis, Martin; Hullin, Matthias B.
2016-01-01
The observation of objects located in inaccessible regions is a recurring challenge in a wide variety of important applications. Recent work has shown that using rare and expensive optical setups, indirect diffuse light reflections can be used to reconstruct objects and two-dimensional (2D) patterns around a corner. Here we show that occluded objects can be tracked in real time using much simpler means, namely a standard 2D camera and a laser pointer. Our method fundamentally differs from previous solutions by approaching the problem in an analysis-by-synthesis sense. By repeatedly simulating light transport through the scene, we determine the set of object parameters that most closely fits the measured intensity distribution. We experimentally demonstrate that this approach is capable of following the translation of unknown objects, and translation and orientation of a known object, in real time. PMID:27577969
Tracking objects outside the line of sight using 2D intensity images.
Klein, Jonathan; Peters, Christoph; Martín, Jaime; Laurenzis, Martin; Hullin, Matthias B
2016-01-01
The observation of objects located in inaccessible regions is a recurring challenge in a wide variety of important applications. Recent work has shown that using rare and expensive optical setups, indirect diffuse light reflections can be used to reconstruct objects and two-dimensional (2D) patterns around a corner. Here we show that occluded objects can be tracked in real time using much simpler means, namely a standard 2D camera and a laser pointer. Our method fundamentally differs from previous solutions by approaching the problem in an analysis-by-synthesis sense. By repeatedly simulating light transport through the scene, we determine the set of object parameters that most closely fits the measured intensity distribution. We experimentally demonstrate that this approach is capable of following the translation of unknown objects, and translation and orientation of a known object, in real time. PMID:27577969
A comparison of 2D and 3D digital image correlation for a membrane under inflation
NASA Astrophysics Data System (ADS)
Murienne, Barbara J.; Nguyen, Thao D.
2016-02-01
Three-dimensional (3D) digital image correlation (DIC) is becoming widely used to characterize the behavior of structures undergoing 3D deformations. However, the use of 3D-DIC can be challenging under certain conditions, such as high magnification, and therefore small depth of field, or a highly controlled environment with limited access for two-angled cameras. The purpose of this study is to compare 2D-DIC and 3D-DIC for the same inflation experiment and evaluate whether 2D-DIC can be used when conditions discourage the use of a stereo-vision system. A latex membrane was inflated vertically to 5.41 kPa (reference pressure), then to 7.87 kPa (deformed pressure). A two-camera stereo-vision system acquired top-down images of the membrane, while a single camera system simultaneously recorded images of the membrane in profile. 2D-DIC and 3D-DIC were used to calculate horizontal (in the membrane plane) and vertical (out of the membrane plane) displacements, and meridional strain. Under static conditions, the baseline uncertainty in horizontal displacement and strain were smaller for 3D-DIC than 2D-DIC. However, the opposite was observed for the vertical displacement, for which 2D-DIC had a smaller baseline uncertainty. The baseline absolute error in vertical displacement and strain were similar for both DIC methods, but it was larger for 2D-DIC than 3D-DIC for the horizontal displacement. Under inflation, the variability in the measurements were larger than under static conditions for both DIC methods. 2D-DIC showed a smaller variability in displacements than 3D-DIC, especially for the vertical displacement, but a similar strain uncertainty. The absolute difference in the average displacements and strain between 3D-DIC and 2D-DIC were in the range of the 3D-DIC variability. Those findings suggest that 2D-DIC might be used as an alternative to 3D-DIC to study the inflation response of materials under certain conditions.
CT cardiac imaging: evolution from 2D to 3D backprojection
NASA Astrophysics Data System (ADS)
Tang, Xiangyang; Pan, Tinsu; Sasaki, Kosuke
2004-04-01
The state-of-the-art multiple detector-row CT, which usually employs fan beam reconstruction algorithms by approximating a cone beam geometry into a fan beam geometry, has been well recognized as an important modality for cardiac imaging. At present, the multiple detector-row CT is evolving into volumetric CT, in which cone beam reconstruction algorithms are needed to combat cone beam artifacts caused by large cone angle. An ECG-gated cardiac cone beam reconstruction algorithm based upon the so-called semi-CB geometry is implemented in this study. To get the highest temporal resolution, only the projection data corresponding to 180° plus the cone angle are row-wise rebinned into the semi-CB geometry for three-dimensional reconstruction. Data extrapolation is utilized to extend the z-coverage of the ECG-gated cardiac cone beam reconstruction algorithm approaching the edge of a CT detector. A helical body phantom is used to evaluate the ECG-gated cone beam reconstruction algorithm"s z-coverage and capability of suppressing cone beam artifacts. Furthermore, two sets of cardiac data scanned by a multiple detector-row CT scanner at 16 x 1.25 (mm) and normalized pitch 0.275 and 0.3 respectively are used to evaluate the ECG-gated CB reconstruction algorithm"s imaging performance. As a reference, the images reconstructed by a fan beam reconstruction algorithm for multiple detector-row CT are also presented. The qualitative evaluation shows that, the ECG-gated cone beam reconstruction algorithm outperforms its fan beam counterpart from the perspective of cone beam artifact suppression and z-coverage while the temporal resolution is well maintained. Consequently, the scan speed can be increased to reduce the contrast agent amount and injection time, improve the patient comfort and x-ray dose efficiency. Based up on the comparison, it is believed that, with the transition of multiple detector-row CT into volumetric CT, ECG-gated cone beam reconstruction algorithms will
Bayesian image reconstruction: Application to emission tomography
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
Knee imaging after anterior cruciate ligament reconstruction.
Rodrigues, M B; Silva, J J; Homsi, C; Stump, X M; Lecouvet, F E
2001-01-01
An increasing number of reconstructions of the anterior cruciate ligament (ACL) are performed every year, due to both the increasing occurrence of sport related injuries and the development of diagnostic and surgical techniques. The most used surgical procedure for the torn ACL reconstruction is the use of autogenous material, most often the patellar and semitendinosus tendons. Magnetic resonance (MR) imaging and spiral-CT performed after arthrography with multiplanar reconstructions are the imaging methods of choice for post-operative evaluation of ACL ligamentoplasty. This paper provides a brief bibliographic and more extensive pictorial review of the normal evolution and possible complications after ACL repair. PMID:11817479
2D Doppler backscattering using synthetic aperture microwave imaging of MAST edge plasmas
NASA Astrophysics Data System (ADS)
Thomas, D. A.; Brunner, K. J.; Freethy, S. J.; Huang, B. K.; Shevchenko, V. F.; Vann, R. G. L.
2016-02-01
Doppler backscattering (DBS) is already established as a powerful diagnostic; its extension to 2D enables imaging of turbulence characteristics from an extended region of the cut-off surface. The Synthetic Aperture Microwave Imaging (SAMI) diagnostic has conducted proof-of-principle 2D DBS experiments of MAST edge plasma. SAMI actively probes the plasma edge using a wide (±40° vertical and horizontal) and tuneable (10-34.5 GHz) beam. The Doppler backscattered signal is digitised in vector form using an array of eight Vivaldi PCB antennas. This allows the receiving array to be focused in any direction within the field of view simultaneously to an angular range of 6-24° FWHM at 10-34.5 GHz. This capability is unique to SAMI and is a novel way of conducting DBS experiments. In this paper the feasibility of conducting 2D DBS experiments is explored. Initial observations of phenomena previously measured by conventional DBS experiments are presented; such as momentum injection from neutral beams and an abrupt change in power and turbulence velocity coinciding with the onset of H-mode. In addition, being able to carry out 2D DBS imaging allows a measurement of magnetic pitch angle to be made; preliminary results are presented. Capabilities gained through steering a beam using a phased array and the limitations of this technique are discussed.
NASA Astrophysics Data System (ADS)
Hirose, Yusuke; Sapkota, Achyut; Sugawara, Michiko; Takei, Masahiro
2016-01-01
This study has launched a concept to image a real-time 2D temperature distribution noninvasively by a combination of the electrical capacitance tomography (ECT) technique and a permittivity-temperature calibration equation for the plastic pellet cooling process. The concept has two steps, which are the relative permittivity calculation from the measured capacitance among the many electrodes by the ECT technique, and the temperature distribution imaging from the relative permittivity by the permittivity-temperature calibration equation. An ECT sensor with 12 electrodes was designed to image the cross-sectional temperature distribution during the polymethyl methacrylate pellets cooling process. The images of temperature distribution were successfully reconstructed from the relative permittivity distribution at every time step during the process. The images reasonably indicate the temperature diffusion in a 2D space and time within a 0.0065 and 0.0175 time-dependent temperature deviation, as compared to an analytical thermal conductance simulation and thermocouple measurement.
Shilling, Richard Z; Robbie, Trevor Q; Bailloeul, Timothée; Mewes, Klaus; Mersereau, Russell M; Brummer, Marijn E
2009-05-01
A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach. PMID:19272995
Using Membrane Computing for Obtaining Homology Groups of Binary 2D Digital Images
NASA Astrophysics Data System (ADS)
Christinal, Hepzibah A.; Díaz-Pernil, Daniel; Jurado, Pedro Real
Membrane Computing is a new paradigm inspired from cellular communication. Until now, P systems have been used in research areas like modeling chemical process, several ecosystems, etc. In this paper, we apply P systems to Computational Topology within the context of the Digital Image. We work with a variant of P systems called tissue-like P systems to calculate in a general maximally parallel manner the homology groups of 2D images. In fact, homology computation for binary pixel-based 2D digital images can be reduced to connected component labeling of white and black regions. Finally, we use a software called Tissue Simulator to show with some examples how these systems work.
A faster method for 3D/2D medical image registration--a simulation study.
Birkfellner, Wolfgang; Wirth, Joachim; Burgstaller, Wolfgang; Baumann, Bernard; Staedele, Harald; Hammer, Beat; Gellrich, Niels Claudius; Jacob, Augustinus Ludwig; Regazzoni, Pietro; Messmer, Peter
2003-08-21
3D/2D patient-to-computed-tomography (CT) registration is a method to determine a transformation that maps two coordinate systems by comparing a projection image rendered from CT to a real projection image. Iterative variation of the CT's position between rendering steps finally leads to exact registration. Applications include exact patient positioning in radiation therapy, calibration of surgical robots, and pose estimation in computer-aided surgery. One of the problems associated with 3D/2D registration is the fact that finding a registration includes solving a minimization problem in six degrees of freedom (dof) in motion. This results in considerable time requirements since for each iteration step at least one volume rendering has to be computed. We show that by choosing an appropriate world coordinate system and by applying a 2D/2D registration method in each iteration step, the number of iterations can be grossly reduced from n6 to n5. Here, n is the number of discrete variations around a given coordinate. Depending on the configuration of the optimization algorithm, this reduces the total number of iterations necessary to at least 1/3 of it's original value. The method was implemented and extensively tested on simulated x-ray images of a tibia, a pelvis and a skull base. When using one projective image and a discrete full parameter space search for solving the optimization problem, average accuracy was found to be 1.0 +/- 0.6(degrees) and 4.1 +/- 1.9 (mm) for a registration in six parameters, and 1.0 +/- 0.7(degrees) and 4.2 +/- 1.6 (mm) when using the 5 + 1 dof method described in this paper. Time requirements were reduced by a factor 3.1. We conclude that this hardware-independent optimization of 3D/2D registration is a step towards increasing the acceptance of this promising method for a wide number of clinical applications. PMID:12974581
Microwave Imaging for Breast Cancer Detection: Advances in Three–Dimensional Image Reconstruction
Golnabi, Amir H.; Meaney, Paul M.; Epstein, Neil R.; Paulsen, Keith D.
2013-01-01
Microwave imaging is based on the electrical property (permittivity and conductivity) differences in materials. Microwave imaging for biomedical applications is particularly interesting, mainly due to the fact that available range of dielectric properties for different tissues can provide important functional information about their health. Under the assumption that a 3D scattering problem can be reasonably represented as a simplified 2D model, one can take advantage of the simplicity and lower computational cost of 2D models to characterize such 3D phenomenon. Nonetheless, by eliminating excessive model simplifications, 3D microwave imaging provides potentially more valuable information over 2Dtechniques, and as a result, more accurate dielectric property maps may be obtained. In this paper, we present some advances we have made in three–dimensional image reconstruction, and show the results from a 3D breast phantom experiment using our clinical microwave imaging system at Dartmouth Hitchcock Medical Center (DHMC), NH. PMID:22255641
NASA Astrophysics Data System (ADS)
Shah, Jainil; Mann, Steve D.; Tornai, Martin P.; Richmond, Michelle; Zentai, George
2014-03-01
The 2D and 3D modulation transfer functions (MTFs) of a custom made, large 40x30cm2 area, 600- micron CsI-TFT based flat panel imager having 127-micron pixellation, along with the micro-fiber scintillator structure, were characterized in detail using various techniques. The larger area detector yields a reconstructed FOV of 25cm diameter with an 80cm SID in CT mode. The MTFs were determined with 1x1 (intrinsic) binning. The 2D MTFs were determined using a 50.8 micron tungsten wire and a solid lead edge, and the 3D MTF was measured using a custom made phantom consisting of three nearly orthogonal 50.8 micron tungsten wires suspended in an acrylic cubic frame. The 2D projection data was reconstructed using an iterative OSC algorithm using 16 subsets and 5 iterations. As additional verification of the resolution, along with scatter, the Catphan® phantom was also imaged and reconstructed with identical parameters. The measured 2D MTF was ~4% using the wire technique and ~1% using the edge technique at the 3.94 lp/mm Nyquist cut-off frequency. The average 3D MTF measured along the wires was ~8% at the Nyquist. At 50% MTF, the resolutions were 1.2 and 2.1 lp/mm in 2D and 3D, respectively. In the Catphan® phantom, the 1.7 lp/mm bars were easily observed. Lastly, the 3D MTF measured on the three wires has an observed 5.9% RMSD, indicating that the resolution of the imaging system is uniform and spatially independent. This high performance detector is integrated into a dedicated breast SPECT-CT imaging system.
Mitrović, Uroš; Pernuš, Franjo; Likar, Boštjan; Špiclin, Žiga
2015-11-15
Purpose: Three-dimensional to two-dimensional (3D–2D) image registration is a key to fusion and simultaneous visualization of valuable information contained in 3D pre-interventional and 2D intra-interventional images with the final goal of image guidance of a procedure. In this paper, the authors focus on 3D–2D image registration within the context of intracranial endovascular image-guided interventions (EIGIs), where the 3D and 2D images are generally acquired with the same C-arm system. The accuracy and robustness of any 3D–2D registration method, to be used in a clinical setting, is influenced by (1) the method itself, (2) uncertainty of initial pose of the 3D image from which registration starts, (3) uncertainty of C-arm’s geometry and pose, and (4) the number of 2D intra-interventional images used for registration, which is generally one and at most two. The study of these influences requires rigorous and objective validation of any 3D–2D registration method against a highly accurate reference or “gold standard” registration, performed on clinical image datasets acquired in the context of the intervention. Methods: The registration process is split into two sequential, i.e., initial and final, registration stages. The initial stage is either machine-based or template matching. The latter aims to reduce possibly large in-plane translation errors by matching a projection of the 3D vessel model and 2D image. In the final registration stage, four state-of-the-art intrinsic image-based 3D–2D registration methods, which involve simultaneous refinement of rigid-body and C-arm parameters, are evaluated. For objective validation, the authors acquired an image database of 15 patients undergoing cerebral EIGI, for which accurate gold standard registrations were established by fiducial marker coregistration. Results: Based on target registration error, the obtained success rates of 3D to a single 2D image registration after initial machine-based and
Heuristic optimization in penumbral image for high resolution reconstructed image
Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.
2010-10-15
Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.
BIOFILM IMAGE RECONSTRUCTION FOR ASSESSING STRUCTURAL PARAMETERS
Renslow, Ryan; Lewandowski, Zbigniew; Beyenal, Haluk
2011-01-01
The structure of biofilms can be numerically quantified from microscopy images using structural parameters. These parameters are used in biofilm image analysis to compare biofilms, to monitor temporal variation in biofilm structure, to quantify the effects of antibiotics on biofilm structure and to determine the effects of environmental conditions on biofilm structure. It is often hypothesized that biofilms with similar structural parameter values will have similar structures; however, this hypothesis has never been tested. The main goal was to test the hypothesis that the commonly used structural parameters can characterize the differences or similarities between biofilm structures. To achieve this goal 1) biofilm image reconstruction was developed as a new tool for assessing structural parameters, 2) independent reconstructions using the same starting structural parameters were tested to see how they differed from each other, 3) the effect of the original image parameter values on reconstruction success was evaluated and 4) the effect of the number and type of the parameters on reconstruction success was evaluated. It was found that two biofilms characterized by identical commonly used structural parameter values may look different, that the number and size of clusters in the original biofilm image affect image reconstruction success and that, in general, a small set of arbitrarily selected parameters may not reveal relevant differences between biofilm structures. PMID:21280029
Approach for reconstructing anisoplanatic adaptive optics images.
Aubailly, Mathieu; Roggemann, Michael C; Schulz, Timothy J
2007-08-20
Atmospheric turbulence corrupts astronomical images formed by ground-based telescopes. Adaptive optics systems allow the effects of turbulence-induced aberrations to be reduced for a narrow field of view corresponding approximately to the isoplanatic angle theta(0). For field angles larger than theta(0), the point spread function (PSF) gradually degrades as the field angle increases. We present a technique to estimate the PSF of an adaptive optics telescope as function of the field angle, and use this information in a space-varying image reconstruction technique. Simulated anisoplanatic intensity images of a star field are reconstructed by means of a block-processing method using the predicted local PSF. Two methods for image recovery are used: matrix inversion with Tikhonov regularization, and the Lucy-Richardson algorithm. Image reconstruction results obtained using the space-varying predicted PSF are compared to space invariant deconvolution results obtained using the on-axis PSF. The anisoplanatic reconstruction technique using the predicted PSF provides a significant improvement of the mean squared error between the reconstructed image and the object compared to the deconvolution performed using the on-axis PSF. PMID:17712366
Efficient MR image reconstruction for compressed MR imaging.
Huang, Junzhou; Zhang, Shaoting; Metaxas, Dimitris
2011-10-01
In this paper, we propose an efficient algorithm for MR image reconstruction. The algorithm minimizes a linear combination of three terms corresponding to a least square data fitting, total variation (TV) and L1 norm regularization. This has been shown to be very powerful for the MR image reconstruction. First, we decompose the original problem into L1 and TV norm regularization subproblems respectively. Then, these two subproblems are efficiently solved by existing techniques. Finally, the reconstructed image is obtained from the weighted average of solutions from two subproblems in an iterative framework. We compare the proposed algorithm with previous methods in term of the reconstruction accuracy and computation complexity. Numerous experiments demonstrate the superior performance of the proposed algorithm for compressed MR image reconstruction. PMID:21742542
Efficient MR image reconstruction for compressed MR imaging.
Huang, Junzhou; Zhang, Shaoting; Metaxas, Dimitris
2010-01-01
In this paper, we propose an efficient algorithm for MR image reconstruction. The algorithm minimizes a linear combination of three terms corresponding to a least square data fitting, total variation (TV) and L1 norm regularization. This has been shown to be very powerful for the MR image reconstruction. First, we decompose the original problem into L1 and TV norm regularization subproblems respectively. Then, these two subproblems are efficiently solved by existing techniques. Finally, the reconstructed image is obtained from the weighted average of solutions from two subproblems in an iterative framework. We compare the proposed algorithm with previous methods in term of the reconstruction accuracy and computation complexity. Numerous experiments demonstrate the superior performance of the proposed algorithm for compressed MR image reconstruction. PMID:20879224
Browne, Jacinta E; Watson, Amanda J; Hoskins, Peter R; Elliott, Alex T
2005-07-01
Tissue harmonic imaging (THI) has been reported to improve contrast resolution, tissue differentiation and overall image quality in clinical examinations. However, a study carried out previously by the authors (Brown et al. 2004) found improvements only in spatial resolution and not in contrast resolution or anechoic target detection. This result may have been due to the homogeneity of the phantom. Biologic tissues are generally inhomogeneous and THI has been reported to improve image quality in the presence of large amounts of subcutaneous fat. The aims of the study were to simulate the distortion caused by subcutaneous fat to image quality and thus investigate further the improvements reported in anechoic target detection and contrast resolution performance with THI compared with 2D conventional imaging. In addition, the effect of three different types of fat-mimicking layer on image quality was examined. The abdominal transducer of two ultrasound scanners with 2D conventional imaging and THI were tested, the 4C1 (Aspen-Acuson, Siemens Co., CA, USA) and the C5-2 (ATL HDI 5000, ATL/Philips, Amsterdam, The Netherlands). An ex vivo subcutaneous pig fat layer was used to replicate beam distortion and phase aberration seen clinically in the presence of subcutaneous fat. Three different types of fat-mimicking layers (olive oil, lard and lard with fish oil capsules) were evaluated. The subcutaneous pig fat layer demonstrated an improvement in anechoic target detection with THI compared with 2D conventional imaging, but no improvement was demonstrated in contrast resolution performance; a similar result was found in a previous study conducted by this research group (Brown et al. 2004) while using this tissue-mimicking phantom without a fat layer. Similarly, while using the layers of olive oil, lard and lard with fish oil capsules, improvements due to THI were found in anechoic target detection but, again, no improvements were found for contrast resolution for any of the
Singh, Gurmeet; Raj, Ashish; Kressler, Bryan; Nguyen, Thanh D.; Spincemaille, Pascal; Zabih, Ramin; Wang, Yi
2010-01-01
Among recent parallel MR imaging reconstruction advances, a Bayesian method called Edge-preserving Parallel Imaging with GRAph cut Minimization (EPIGRAM) has been demonstrated to significantly improve signal to noise ratio (SNR) compared to conventional regularized sensitivity encoding (SENSE) method. However, EPIGRAM requires a large number of iterations in proportion to the number of intensity labels in the image, making it computationally expensive for high dynamic range images. The objective of this study is to develop a Fast EPIGRAM reconstruction based on the efficient binary jump move algorithm that provides a logarithmic reduction in reconstruction time while maintaining image quality. Preliminary in vivo validation of the proposed algorithm is presented for 2D cardiac cine MR imaging and 3D coronary MR angiography at acceleration factors of 2-4. Fast EPIGRAM was found to provide similar image quality to EPIGRAM and maintain the previously reported SNR improvement over regularized SENSE, while reducing EPIGRAM reconstruction time by 25-50 times. PMID:20939095
Interpretation of Line-Integrated Signals from 2-D Phase Contrast Imaging on LHD
NASA Astrophysics Data System (ADS)
Michael, Clive; Tanaka, Kenji; Vyacheslavov, Leonid; Sanin, Andrei; Kawahata, Kazuo; Okajima, S.
Two dimensional (2D) phase contrast imaging (PCI) is an excellent method to measure core and edge turbulence with good spatial resolution (Δρ ˜ 0.1). General analytical consideration is given to the signal interpretation of the line-integrated signals, with specific application to images from 2D PCI. It is shown that the Fourier components of fluctuations having any non-zero component propagating along the line of sight are not detected. The ramifications of this constraint are discussed, including consideration of the angle between the sight line and flux surface normal. In the experimental geometry, at the point where the flux surfaces are tangent to the sight line, it is shown that it may be possible to detect large poloidally extended (though with small radial wavelength) structures, such as GAMS. The spatial localization technique of this diagnostic is illustrated with experimental data.
Radiometer uncertainty equation research of 2D planar scanning PMMW imaging system
NASA Astrophysics Data System (ADS)
Hu, Taiyang; Xu, Jianzhong; Xiao, Zelong
2009-07-01
With advances in millimeter-wave technology, passive millimeter-wave (PMMW) imaging technology has received considerable concerns, and it has established itself in a wide range of military and civil practical applications, such as in the areas of remote sensing, blind landing, precision guidance and security inspection. Both the high transparency of clothing at millimeter wavelengths and the spatial resolution required to generate adequate images combine to make imaging at millimeter wavelengths a natural approach of screening people for concealed contraband detection. And at the same time, the passive operation mode does not present a safety hazard to the person who is under inspection. Based on the description to the design and engineering implementation of a W-band two-dimensional (2D) planar scanning imaging system, a series of scanning methods utilized in PMMW imaging are generally compared and analyzed, followed by a discussion on the operational principle of the mode of 2D planar scanning particularly. Furthermore, it is found that the traditional radiometer uncertainty equation, which is derived from a moving platform, does not hold under this 2D planar scanning mode due to the fact that there is no absolute connection between the scanning rates in horizontal direction and vertical direction. Consequently, an improved radiometer uncertainty equation is carried out in this paper, by means of taking the total time spent on scanning and imaging into consideration, with the purpose of solving the problem mentioned above. In addition, the related factors which affect the quality of radiometric images are further investigated under the improved radiometer uncertainty equation, and ultimately some original results are presented and analyzed to demonstrate the significance and validity of this new methodology.
Geometric reconstruction using tracked ultrasound strain imaging
NASA Astrophysics Data System (ADS)
Pheiffer, Thomas S.; Simpson, Amber L.; Ondrake, Janet E.; Miga, Michael I.
2013-03-01
The accurate identification of tumor margins during neurosurgery is a primary concern for the surgeon in order to maximize resection of malignant tissue while preserving normal function. The use of preoperative imaging for guidance is standard of care, but tumor margins are not always clear even when contrast agents are used, and so margins are often determined intraoperatively by visual and tactile feedback. Ultrasound strain imaging creates a quantitative representation of tissue stiffness which can be used in real-time. The information offered by strain imaging can be placed within a conventional image-guidance workflow by tracking the ultrasound probe and calibrating the image plane, which facilitates interpretation of the data by placing it within a common coordinate space with preoperative imaging. Tumor geometry in strain imaging is then directly comparable to the geometry in preoperative imaging. This paper presents a tracked ultrasound strain imaging system capable of co-registering with preoperative tomograms and also of reconstructing a 3D surface using the border of the strain lesion. In a preliminary study using four phantoms with subsurface tumors, tracked strain imaging was registered to preoperative image volumes and then tumor surfaces were reconstructed using contours extracted from strain image slices. The volumes of the phantom tumors reconstructed from tracked strain imaging were approximately between 1.5 to 2.4 cm3, which was similar to the CT volumes of 1.0 to 2.3 cm3. Future work will be done to robustly characterize the reconstruction accuracy of the system.
Imaging collective magnonic modes in 2D arrays of magnetic nanoelements.
Kruglyak, V V; Keatley, P S; Neudert, A; Hicken, R J; Childress, J R; Katine, J A
2010-01-15
We have used time resolved scanning Kerr microscopy to image collective spin wave modes within a 2D array of magnetic nanoelements. Long wavelength spin waves are confined within the array as if it was a continuous element of the same size but with effective material properties determined by the structure of the array and its constituent nanoelements. The array is an example of a magnonic metamaterial, the demonstration of which provides new opportunities within the emerging field of magnonics. PMID:20366622
Imaging Collective Magnonic Modes in 2D Arrays of Magnetic Nanoelements
NASA Astrophysics Data System (ADS)
Kruglyak, V. V.; Keatley, P. S.; Neudert, A.; Hicken, R. J.; Childress, J. R.; Katine, J. A.
2010-01-01
We have used time resolved scanning Kerr microscopy to image collective spin wave modes within a 2D array of magnetic nanoelements. Long wavelength spin waves are confined within the array as if it was a continuous element of the same size but with effective material properties determined by the structure of the array and its constituent nanoelements. The array is an example of a magnonic metamaterial, the demonstration of which provides new opportunities within the emerging field of magnonics.
PET Image Reconstruction Using Kernel Method
Wang, Guobao; Qi, Jinyi
2014-01-01
Image reconstruction from low-count PET projection data is challenging because the inverse problem is ill-posed. Prior information can be used to improve image quality. Inspired by the kernel methods in machine learning, this paper proposes a kernel based method that models PET image intensity in each pixel as a function of a set of features obtained from prior information. The kernel-based image model is incorporated into the forward model of PET projection data and the coefficients can be readily estimated by the maximum likelihood (ML) or penalized likelihood image reconstruction. A kernelized expectation-maximization (EM) algorithm is presented to obtain the ML estimate. Computer simulations show that the proposed approach can achieve better bias versus variance trade-off and higher contrast recovery for dynamic PET image reconstruction than the conventional maximum likelihood method with and without post-reconstruction denoising. Compared with other regularization-based methods, the kernel method is easier to implement and provides better image quality for low-count data. Application of the proposed kernel method to a 4D dynamic PET patient dataset showed promising results. PMID:25095249
PET image reconstruction using kernel method.
Wang, Guobao; Qi, Jinyi
2015-01-01
Image reconstruction from low-count positron emission tomography (PET) projection data is challenging because the inverse problem is ill-posed. Prior information can be used to improve image quality. Inspired by the kernel methods in machine learning, this paper proposes a kernel based method that models PET image intensity in each pixel as a function of a set of features obtained from prior information. The kernel-based image model is incorporated into the forward model of PET projection data and the coefficients can be readily estimated by the maximum likelihood (ML) or penalized likelihood image reconstruction. A kernelized expectation-maximization algorithm is presented to obtain the ML estimate. Computer simulations show that the proposed approach can achieve better bias versus variance trade-off and higher contrast recovery for dynamic PET image reconstruction than the conventional maximum likelihood method with and without post-reconstruction denoising. Compared with other regularization-based methods, the kernel method is easier to implement and provides better image quality for low-count data. Application of the proposed kernel method to a 4-D dynamic PET patient dataset showed promising results. PMID:25095249
Terahertz wavefront assessment based on 2D electro-optic imaging
NASA Astrophysics Data System (ADS)
Cahyadi, Harsono; Ichikawa, Ryuji; Degert, Jérôme; Freysz, Eric; Yasui, Takeshi; Abraham, Emmanuel
2015-03-01
Complete characterization of terahertz (THz) radiation becomes an interesting yet challenging study for many years. In visible optical region, the wavefront assessment has been proved as a powerful tool for the beam profiling and characterization, which consequently requires 2-dimension (2D) single-shot acquisition of the beam cross-section to provide the spatial profile in time- and frequency-domain. In THz region, the main problem is the lack of effective THz cameras to satisfy this need. In this communication, we propose a simple setup based on free-space collinear 2D electrooptic sampling in a ZnTe crystal for the characterization of THz wavefronts. In principle, we map the optically converted, time-resolved data of the THz pulse by changing the time delay between the probe pulse and the generated THz pulse. The temporal waveforms from different lens-ZnTe distances can clearly indicate the evolution of THz beam as it is converged, focused, or diverged. From the Fourier transform of the temporal waveforms, we can obtain the spectral profile of a broadband THz wave, which in this case within the 0.1-2 THz range. The spectral profile also provides the frequency dependency of the THz pulse amplitude. The comparison between experimental and theoretical results at certain frequencies (here we choose 0.285 and 1.035 THz) is in a good agreement suggesting that our system is capable of THz wavefront characterization. Furthermore, the implementation of Hartmann/Shack-Hartmann sensor principle enables the reconstruction of THz wavefront. We demonstrate the reconstruction of THz wavefronts which are changed from planar wave to spherical one due to the insertion of convex THz lens in the THz beam path. We apply and compare two different reconstruction methods: linear integration and Zernike polynomial. Roughly we conclude that the Zernike method provide smoother wavefront shape that can be elaborated later into quantitative-qualitative analysis about the wavefront
Fully automatic detection of the vertebrae in 2D CT images
NASA Astrophysics Data System (ADS)
Graf, Franz; Kriegel, Hans-Peter; Schubert, Matthias; Strukelj, Michael; Cavallaro, Alexander
2011-03-01
Knowledge about the vertebrae is a valuable source of information for several annotation tasks. In recent years, the research community spent a considerable effort for detecting, segmenting and analyzing the vertebrae and the spine in various image modalities like CT or MR. Most of these methods rely on prior knowledge like the location of the vertebrae or other initial information like the manual detection of the spine. Furthermore, the majority of these methods require a complete volume scan. With the existence of use cases where only a single slice is available, there arises a demand for methods allowing the detection of the vertebrae in 2D images. In this paper, we propose a fully automatic and parameterless algorithm for detecting the vertebrae in 2D CT images. Our algorithm starts with detecting candidate locations by taking the density of bone-like structures into account. Afterwards, the candidate locations are extended into candidate regions for which certain image features are extracted. The resulting feature vectors are compared to a sample set of previously annotated and processed images in order to determine the best candidate region. In a final step, the result region is readjusted until convergence to a locally optimal position. Our new method is validated on a real world data set of more than 9 329 images of 34 patients being annotated by a clinician in order to provide a realistic ground truth.
Image restoration using 2D autoregressive texture model and structure curve construction
NASA Astrophysics Data System (ADS)
Voronin, V. V.; Marchuk, V. I.; Petrosov, S. P.; Svirin, I.; Agaian, S.; Egiazarian, K.
2015-05-01
In this paper an image inpainting approach based on the construction of a composite curve for the restoration of the edges of objects in an image using the concepts of parametric and geometric continuity is presented. It is shown that this approach allows to restore the curved edges and provide more flexibility for curve design in damaged image by interpolating the boundaries of objects by cubic splines. After edge restoration stage, a texture restoration using 2D autoregressive texture model is carried out. The image intensity is locally modeled by a first spatial autoregressive model with support in a strongly causal prediction region on the plane. Model parameters are estimated by Yule-Walker method. Several examples considered in this paper show the effectiveness of the proposed approach for large objects removal as well as recovery of small regions on several test images.
NASA Astrophysics Data System (ADS)
Zhou, Nanrun; Li, Haolin; Wang, Di; Pan, Shumin; Zhou, Zhihong
2015-05-01
Most of the existing image encryption techniques bear security risks for taking linear transform or suffer encryption data expansion for adopting nonlinear transformation directly. To overcome these difficulties, a novel image compression-encryption scheme is proposed by combining 2D compressive sensing with nonlinear fractional Mellin transform. In this scheme, the original image is measured by measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the nonlinear fractional Mellin transform. The measurement matrices are controlled by chaos map. The Newton Smoothed l0 Norm (NSL0) algorithm is adopted to obtain the decryption image. Simulation results verify the validity and the reliability of this scheme.
Multiple-perturbation two-dimensional (2D) correlation analysis for spectroscopic imaging data
NASA Astrophysics Data System (ADS)
Shinzawa, Hideyuki; Hashimoto, Kosuke; Sato, Hidetoshi; Kanematsu, Wataru; Noda, Isao
2014-07-01
A series of data analysis techniques, including multiple-perturbation two-dimensional (2D) correlation spectroscopy and kernel analysis, were used to demonstrate how these techniques can sort out convoluted information content underlying spectroscopic imaging data. A set of Raman spectra of polymer blends consisting of poly(methyl methacrylate) (PMMA) and polyethylene glycol (PEG) were collected under varying spatial coordinates and subjected to multiple-perturbation 2D correlation analysis and kernel analysis by using the coordinates as perturbation variables. Cross-peaks appearing in asynchronous correlation spectra indicated that the change in the spectral intensity of the free Cdbnd O band of the PMMA band occurs before that of the Cdbnd O⋯Hsbnd O band arising from the molecular interaction between PMMA and PEG. Kernel matrices, generated by carrying out 2D correlation analysis on principal component analysis (PCA) score images, revealed subtle but important discrepancy between the patterns of the images, providing additional interpretation to the PCA in an intuitively understandable manner. Consequently, the results provided apparent spectroscopic evidence that PMMA and PEG in the blends are partially miscible at the molecular level, allowing the PMMAs to respond to the perturbations in different manner.
Image reconstruction algorithms with wavelet filtering for optoacoustic imaging
NASA Astrophysics Data System (ADS)
Gawali, S.; Leggio, L.; Broadway, C.; González, P.; Sánchez, M.; Rodríguez, S.; Lamela, H.
2016-03-01
Optoacoustic imaging (OAI) is a hybrid biomedical imaging modality based on the generation and detection of ultrasound by illuminating the target tissue by laser light. Typically, laser light in visible or near infrared spectrum is used as an excitation source. OAI is based on the implementation of image reconstruction algorithms using the spatial distribution of optical absorption in tissues. In this work, we apply a time-domain back-projection (BP) reconstruction algorithm and a wavelet filtering for point and line detection, respectively. A comparative study between point detection and integrated line detection has been carried out by evaluating their effects on the image reconstructed. Our results demonstrate that the back-projection algorithm proposed is efficient for reconstructing high-resolution images of absorbing spheres embedded in a non-absorbing medium when it is combined with the wavelet filtering.
Multi-contrast magnetic resonance image reconstruction
NASA Astrophysics Data System (ADS)
Liu, Meng; Chen, Yunmei; Zhang, Hao; Huang, Feng
2015-03-01
In clinical exams, multi-contrast images from conventional MRI are scanned with the same field of view (FOV) for complementary diagnostic information, such as proton density- (PD-), T1- and T2-weighted images. Their sharable information can be utilized for more robust and accurate image reconstruction. In this work, we propose a novel model and an efficient algorithm for joint image reconstruction and coil sensitivity estimation in multi-contrast partially parallel imaging (PPI) in MRI. Our algorithm restores the multi-contrast images by minimizing an energy function consisting of an L2-norm fidelity term to reduce construction errors caused by motion, a regularization term of underlying images to preserve common anatomical features by using vectorial total variation (VTV) regularizer, and updating sensitivity maps by Tikhonov smoothness based on their physical property. We present the numerical results including T1- and T2-weighted MR images recovered from partially scanned k-space data and provide the comparisons between our results and those obtained from the related existing works. Our numerical results indicate that the proposed method using vectorial TV and penalties on sensitivities can be made promising and widely used for multi-contrast multi-channel MR image reconstruction.
Image denoising with 2D scale-mixing complex wavelet transforms.
Remenyi, Norbert; Nicolis, Orietta; Nason, Guy; Vidakovic, Brani
2014-12-01
This paper introduces an image denoising procedure based on a 2D scale-mixing complex-valued wavelet transform. Both the minimal (unitary) and redundant (maximum overlap) versions of the transform are used. The covariance structure of white noise in wavelet domain is established. Estimation is performed via empirical Bayesian techniques, including versions that preserve the phase of the complex-valued wavelet coefficients and those that do not. The new procedure exhibits excellent quantitative and visual performance, which is demonstrated by simulation on standard test images. PMID:25312931
2D-CELL: image processing software for extraction and analysis of 2-dimensional cellular structures
NASA Astrophysics Data System (ADS)
Righetti, F.; Telley, H.; Leibling, Th. M.; Mocellin, A.
1992-01-01
2D-CELL is a software package for the processing and analyzing of photographic images of cellular structures in a largely interactive way. Starting from a binary digitized image, the programs extract the line network (skeleton) of the structure and determine the graph representation that best models it. Provision is made for manually correcting defects such as incorrect node positions or dangling bonds. Then a suitable algorithm retrieves polygonal contours which define individual cells — local boundary curvatures are neglected for simplicity. Using elementary analytical geometry relations, a range of metric and topological parameters describing the population are then computed, organized into statistical distributions and graphically displayed.
2D image classification for 3D anatomy localization: employing deep convolutional neural networks
NASA Astrophysics Data System (ADS)
de Vos, Bob D.; Wolterink, Jelmer M.; de Jong, Pim A.; Viergever, Max A.; Išgum, Ivana
2016-03-01
Localization of anatomical regions of interest (ROIs) is a preprocessing step in many medical image analysis tasks. While trivial for humans, it is complex for automatic methods. Classic machine learning approaches require the challenge of hand crafting features to describe differences between ROIs and background. Deep convolutional neural networks (CNNs) alleviate this by automatically finding hierarchical feature representations from raw images. We employ this trait to detect anatomical ROIs in 2D image slices in order to localize them in 3D. In 100 low-dose non-contrast enhanced non-ECG synchronized screening chest CT scans, a reference standard was defined by manually delineating rectangular bounding boxes around three anatomical ROIs -- heart, aortic arch, and descending aorta. Every anatomical ROI was automatically identified using a combination of three CNNs, each analyzing one orthogonal image plane. While single CNNs predicted presence or absence of a specific ROI in the given plane, the combination of their results provided a 3D bounding box around it. Classification performance of each CNN, expressed in area under the receiver operating characteristic curve, was >=0.988. Additionally, the performance of ROI localization was evaluated. Median Dice scores for automatically determined bounding boxes around the heart, aortic arch, and descending aorta were 0.89, 0.70, and 0.85 respectively. The results demonstrate that accurate automatic 3D localization of anatomical structures by CNN-based 2D image classification is feasible.
Non-rigid target tracking in 2D ultrasound images using hierarchical grid interpolation
NASA Astrophysics Data System (ADS)
Royer, Lucas; Babel, Marie; Krupa, Alexandre
2014-03-01
In this paper, we present a new non-rigid target tracking method within 2D ultrasound (US) image sequence. Due to the poor quality of US images, the motion tracking of a tumor or cyst during needle insertion is considered as an open research issue. Our approach is based on well-known compression algorithm in order to make our method work in real-time which is a necessary condition for many clinical applications. Toward that end, we employed a dedicated hierarchical grid interpolation algorithm (HGI) which can represent a large variety of deformations compared to other motion estimation algorithms such as Overlapped Block Motion Compensation (OBMC), or Block Motion Algorithm (BMA). The sum of squared difference of image intensity is selected as similarity criterion because it provides a good trade-off between computation time and motion estimation quality. Contrary to the others methods proposed in the literature, our approach has the ability to distinguish both rigid and non-rigid motions which are observed in ultrasound image modality. Furthermore, this technique does not take into account any prior knowledge about the target, and limits the user interaction which usually complicates the medical validation process. Finally, a technique aiming at identifying the main phases of a periodic motion (e.g. breathing motion) is introduced. The new approach has been validated from 2D ultrasound images of real human tissues which undergo rigid and non-rigid deformations.
Kothapalli, Sri-Rajasekhar; Ma, Te-Jen; Vaithilingam, Srikant; Oralkan, Ömer
2014-01-01
In this paper, we demonstrate 3-D photoacoustic imaging (PAI) of light absorbing objects embedded as deep as 5 cm inside strong optically scattering phantoms using a miniaturized (4 mm × 4 mm × 500 µm), 2-D capacitive micromachined ultrasonic transducer (CMUT) array of 16 × 16 elements with a center frequency of 5.5 MHz. Two-dimensional tomographic images and 3-D volumetric images of the objects placed at different depths are presented. In addition, we studied the sensitivity of CMUT-based PAI to the concentration of indocyanine green dye at 5 cm depth inside the phantom. Under optimized experimental conditions, the objects at 5 cm depth can be imaged with SNR of about 35 dB and a spatial resolution of approximately 500 µm. Results demonstrate that CMUTs with integrated front-end amplifier circuits are an attractive choice for achieving relatively high depth sensitivity for PAI. PMID:22249594
A software tool for automatic classification and segmentation of 2D/3D medical images
NASA Astrophysics Data System (ADS)
Strzelecki, Michal; Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur
2013-02-01
Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided.
2D dose distribution images of a hybrid low field MRI-γ detector
NASA Astrophysics Data System (ADS)
Abril, A.; Agulles-Pedrós, L.
2016-07-01
The proposed hybrid system is a combination of a low field MRI and dosimetric gel as a γ detector. The readout system is based on the polymerization process induced by the gel radiation. A gel dose map is obtained which represents the functional part of hybrid image alongside with the anatomical MRI one. Both images should be taken while the patient with a radiopharmaceutical is located inside the MRI system with a gel detector matrix. A relevant aspect of this proposal is that the dosimetric gel has never been used to acquire medical images. The results presented show the interaction of the 99mTc source with the dosimetric gel simulated in Geant4. The purpose was to obtain the planar γ 2D-image. The different source configurations are studied to explore the ability of the gel as radiation detector through the following parameters; resolution, shape definition and radio-pharmaceutical concentration.
Image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing
NASA Astrophysics Data System (ADS)
Zhou, Nanrun; Pan, Shumin; Cheng, Shan; Zhou, Zhihong
2016-08-01
Most image encryption algorithms based on low-dimensional chaos systems bear security risks and suffer encryption data expansion when adopting nonlinear transformation directly. To overcome these weaknesses and reduce the possible transmission burden, an efficient image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing is proposed. The original image is measured by the measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the cycle shift operation controlled by a hyper-chaotic system. Cycle shift operation can change the values of the pixels efficiently. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys distribution simultaneously as a nonlinear encryption system. Simulation results verify the validity and the reliability of the proposed algorithm with acceptable compression and security performance.
Image and Data-analysis Tools For Paleoclimatic Reconstructions
NASA Astrophysics Data System (ADS)
Pozzi, M.
It comes here proposed a directory of instruments and computer science resources chosen in order to resolve the problematic ones that regard the paleoclimatic recon- structions. They will come discussed in particular the following points: 1) Numerical analysis of paleo-data (fossils abundances, species analyses, isotopic signals, chemical-physical parameters, biological data): a) statistical analyses (uni- variate, diversity, rarefaction, correlation, ANOVA, F and T tests, Chi^2) b) multidi- mensional analyses (principal components, corrispondence, cluster analysis, seriation, discriminant, autocorrelation, spectral analysis) neural analyses (backpropagation net, kohonen feature map, hopfield net genetic algorithms) 2) Graphical analysis (visu- alization tools) of paleo-data (quantitative and qualitative fossils abundances, species analyses, isotopic signals, chemical-physical parameters): a) 2-D data analyses (graph, histogram, ternary, survivorship) b) 3-D data analyses (direct volume rendering, iso- surfaces, segmentation, surface reconstruction, surface simplification,generation of tetrahedral grids). 3) Quantitative and qualitative digital image analysis (macro and microfossils image analysis, Scanning Electron Microscope. and Optical Polarized Microscope images capture and analysis, morphometric data analysis, 3-D reconstruc- tions): a) 2D image analysis (correction of image defects, enhancement of image de- tail, converting texture and directionality to grey scale or colour differences, visual enhancement using pseudo-colour, pseudo-3D, thresholding of image features, binary image processing, measurements, stereological measurements, measuring features on a white background) b) 3D image analysis (basic stereological procedures, two dimen- sional structures; area fraction from the point count, volume fraction from the point count, three dimensional structures: surface area and the line intercept count, three dimensional microstructures; line length and the
A 3D Feature Descriptor Recovered from a Single 2D Palmprint Image.
Zheng, Qian; Kumar, Ajay; Pan, Gang
2016-06-01
Design and development of efficient and accurate feature descriptors is critical for the success of many computer vision applications. This paper proposes a new feature descriptor, referred to as DoN, for the 2D palmprint matching. The descriptor is extracted for each point on the palmprint. It is based on the ordinal measure which partially describes the difference of the neighboring points' normal vectors. DoN has at least two advantages: 1) it describes the 3D information, which is expected to be highly stable under commonly occurring illumination variations during contactless imaging; 2) the size of DoN for each point is only one bit, which is computationally simple to extract, easy to match, and efficient to storage. We show that such 3D information can be extracted from a single 2D palmprint image. The analysis for the effectiveness of ordinal measure for palmprint matching is also provided. Four publicly available 2D palmprint databases are used to evaluate the effectiveness of DoN, both for identification and the verification. Our method on all these databases achieves the state-of-the-art performance. PMID:27164564
Accelerated Compressed Sensing Based CT Image Reconstruction
Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R.; Paul, Narinder S.; Cobbold, Richard S. C.
2015-01-01
In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization. PMID:26167200
Image reconstruction from fan-beam projections on less than a short scan.
Noo, Frédéric; Defrise, Michel; Clackdoyle, Rolf; Kudo, Hiroyuki
2002-07-21
This work is concerned with 2D image reconstruction from fan-beam projections. It is shown that exact and stable reconstruction of a given region-of-interest in the object does not require all lines passing through the object to be measured. Complete (non-truncated) fan-beam projections provide sufficient information for reconstruction when 'every line passing through the region-of-interest intersects the vertex path in a non-tangential way'. The practical implications of this condition are discussed and a new filtered-backprojection algorithm is derived for reconstruction. Experiments with computer-simulated data are performed to support the mathematical results. PMID:12171338
Medical Imaging Inspired Vertex Reconstruction at LHC
NASA Astrophysics Data System (ADS)
Hageböck, S.; von Toerne, E.
2012-12-01
Three-dimensional image reconstruction in medical applications (PET or X-ray CT) utilizes sophisticated filter algorithms to linear trajectories of coincident photon pairs or x-rays. The goal is to reconstruct an image of an emitter density distribution. In a similar manner, tracks in particle physics originate from vertices that need to be distinguished from background track combinations. In this study it is investigated if vertex reconstruction in high energy proton collisions may benefit from medical imaging methods. A new method of vertex finding, the Medical Imaging Vertexer (MIV), is presented based on a three-dimensional filtered backprojection algorithm. It is compared to the open-source RAVE vertexing package. The performance of the vertex finding algorithms is evaluated as a function of instantaneous luminosity using simulated LHC collisions. Tracks in these collisions are described by a simplified detector model which is inspired by the tracking performance of the LHC experiments. At high luminosities (25 pileup vertices and more), the medical imaging approach finds vertices with a higher efficiency and purity than the RAVE “Adaptive Vertex Reconstructor” algorithm. It is also much faster if more than 25 vertices are to be reconstructed because the amount of CPU time rises linearly with the number of tracks whereas it rises quadratically for the adaptive vertex fitter AVR.
Volumetric synthetic aperture imaging with a piezoelectric 2D row-column probe
NASA Astrophysics Data System (ADS)
Bouzari, Hamed; Engholm, Mathias; Christiansen, Thomas Lehrmann; Beers, Christopher; Lei, Anders; Stuart, Matthias Bo; Nikolov, Svetoslav Ivanov; Thomsen, Erik Vilain; Jensen, Jørgen Arendt
2016-04-01
The synthetic aperture (SA) technique can be used for achieving real-time volumetric ultrasound imaging using 2-D row-column addressed transducers. This paper investigates SA volumetric imaging performance of an in-house prototyped 3 MHz λ/2-pitch 62+62 element piezoelectric 2-D row-column addressed transducer array. Utilizing single element transmit events, a volume rate of 90 Hz down to 14 cm deep is achieved. Data are obtained using the experimental ultrasound scanner SARUS with a 70 MHz sampling frequency and beamformed using a delay-and-sum (DAS) approach. A signal-to-noise ratio of up to 32 dB is measured on the beamformed images of a tissue mimicking phantom with attenuation of 0.5 dB cm-1 MHz-1, from the surface of the probe to the penetration depth of 300λ. Measured lateral resolution as Full-Width-at-Half-Maximum (FWHM) is between 4λ and 10λ for 18% to 65% of the penetration depth from the surface of the probe. The averaged contrast is 13 dB for the same range. The imaging performance assessment results may represent a reference guide for possible applications of such an array in different medical fields.
Image reconstruction for a Positron Emission Tomograph optimized for breast cancer imaging
Virador, Patrick R.G.
2000-04-01
The author performs image reconstruction for a novel Positron Emission Tomography camera that is optimized for breast cancer imaging. This work addresses for the first time, the problem of fully-3D, tomographic reconstruction using a septa-less, stationary, (i.e. no rotation or linear motion), and rectangular camera whose Field of View (FOV) encompasses the entire volume enclosed by detector modules capable of measuring Depth of Interaction (DOI) information. The camera is rectangular in shape in order to accommodate breasts of varying sizes while allowing for soft compression of the breast during the scan. This non-standard geometry of the camera exacerbates two problems: (a) radial elongation due to crystal penetration and (b) reconstructing images from irregularly sampled data. Packing considerations also give rise to regions in projection space that are not sampled which lead to missing information. The author presents new Fourier Methods based image reconstruction algorithms that incorporate DOI information and accommodate the irregular sampling of the camera in a consistent manner by defining lines of responses (LORs) between the measured interaction points instead of rebinning the events into predefined crystal face LORs which is the only other method to handle DOI information proposed thus far. The new procedures maximize the use of the increased sampling provided by the DOI while minimizing interpolation in the data. The new algorithms use fixed-width evenly spaced radial bins in order to take advantage of the speed of the Fast Fourier Transform (FFT), which necessitates the use of irregular angular sampling in order to minimize the number of unnormalizable Zero-Efficiency Bins (ZEBs). In order to address the persisting ZEBs and the issue of missing information originating from packing considerations, the algorithms (a) perform nearest neighbor smoothing in 2D in the radial bins (b) employ a semi-iterative procedure in order to estimate the unsampled data
Image reconstructions with the rotating RF coil.
Trakic, A; Wang, H; Weber, E; Li, B K; Poole, M; Liu, F; Crozier, S
2009-12-01
Recent studies have shown that rotating a single RF transceive coil (RRFC) provides a uniform coverage of the object and brings a number of hardware advantages (i.e. requires only one RF channel, averts coil-coil coupling interactions and facilitates large-scale multi-nuclear imaging). Motion of the RF coil sensitivity profile however violates the standard Fourier Transform definition of a time-invariant signal, and the images reconstructed in this conventional manner can be degraded by ghosting artifacts. To overcome this problem, this paper presents Time Division Multiplexed-Sensitivity Encoding (TDM-SENSE), as a new image reconstruction scheme that exploits the rotation of the RF coil sensitivity profile to facilitate ghost-free image reconstructions and reductions in image acquisition time. A transceive RRFC system for head imaging at 2 Tesla was constructed and applied in a number of in vivo experiments. In this initial study, alias-free head images were obtained in half the usual scan time. It is hoped that new sequences and methods will be developed by taking advantage of coil motion. PMID:19800824
Image reconstructions with the rotating RF coil
NASA Astrophysics Data System (ADS)
Trakic, A.; Wang, H.; Weber, E.; Li, B. K.; Poole, M.; Liu, F.; Crozier, S.
2009-12-01
Recent studies have shown that rotating a single RF transceive coil (RRFC) provides a uniform coverage of the object and brings a number of hardware advantages (i.e. requires only one RF channel, averts coil-coil coupling interactions and facilitates large-scale multi-nuclear imaging). Motion of the RF coil sensitivity profile however violates the standard Fourier Transform definition of a time-invariant signal, and the images reconstructed in this conventional manner can be degraded by ghosting artifacts. To overcome this problem, this paper presents Time Division Multiplexed — Sensitivity Encoding (TDM-SENSE), as a new image reconstruction scheme that exploits the rotation of the RF coil sensitivity profile to facilitate ghost-free image reconstructions and reductions in image acquisition time. A transceive RRFC system for head imaging at 2 Tesla was constructed and applied in a number of in vivo experiments. In this initial study, alias-free head images were obtained in half the usual scan time. It is hoped that new sequences and methods will be developed by taking advantage of coil motion.
Designing of sparse 2D arrays for Lamb wave imaging using coarray concept
NASA Astrophysics Data System (ADS)
Ambroziński, Łukasz; Stepinski, Tadeusz; Uhl, Tadeusz
2015-03-01
2D ultrasonic arrays have considerable application potential in Lamb wave based SHM systems, since they enable equivocal damage imaging and even in some cases wave-mode selection. Recently, it has been shown that the 2D arrays can be used in SHM applications in a synthetic focusing (SF) mode, which is much more effective than the classical phase array mode commonly used in NDT. The SF mode assumes a single element excitation of subsequent transmitters and off-line processing the acquired data. In the simplest implementation of the technique, only single multiplexed input and output channels are required, which results in significant hardware simplification. Application of the SF mode for 2D arrays creates additional degrees of freedom during the design of the array topology, which complicates the array design process, however, it enables sparse array designs with performance similar to that of the fully populated dense arrays. In this paper we present the coarray concept to facilitate synthesis process of an array's aperture used in the multistatic synthetic focusing approach in Lamb waves-based imaging systems. In the coherent imaging, performed in the transmit/receive mode, the sum coarray is a morphological convolution of the transmit/receive sub-arrays. It can be calculated as the set of sums of the individual sub-arrays' elements locations. The coarray framework will be presented here using a an example of a star-shaped array. The approach will be discussed in terms of beampatterns of the resulting imaging systems. Both simulated and experimental results will be included.
Designing of sparse 2D arrays for Lamb wave imaging using coarray concept
Ambroziński, Łukasz Stepinski, Tadeusz Uhl, Tadeusz
2015-03-31
2D ultrasonic arrays have considerable application potential in Lamb wave based SHM systems, since they enable equivocal damage imaging and even in some cases wave-mode selection. Recently, it has been shown that the 2D arrays can be used in SHM applications in a synthetic focusing (SF) mode, which is much more effective than the classical phase array mode commonly used in NDT. The SF mode assumes a single element excitation of subsequent transmitters and off-line processing the acquired data. In the simplest implementation of the technique, only single multiplexed input and output channels are required, which results in significant hardware simplification. Application of the SF mode for 2D arrays creates additional degrees of freedom during the design of the array topology, which complicates the array design process, however, it enables sparse array designs with performance similar to that of the fully populated dense arrays. In this paper we present the coarray concept to facilitate synthesis process of an array’s aperture used in the multistatic synthetic focusing approach in Lamb waves-based imaging systems. In the coherent imaging, performed in the transmit/receive mode, the sum coarray is a morphological convolution of the transmit/receive sub-arrays. It can be calculated as the set of sums of the individual sub-arrays’ elements locations. The coarray framework will be presented here using a an example of a star-shaped array. The approach will be discussed in terms of beampatterns of the resulting imaging systems. Both simulated and experimental results will be included.
2D and 3D MALDI-imaging: conceptual strategies for visualization and data mining.
Thiele, Herbert; Heldmann, Stefan; Trede, Dennis; Strehlow, Jan; Wirtz, Stefan; Dreher, Wolfgang; Berger, Judith; Oetjen, Janina; Kobarg, Jan Hendrik; Fischer, Bernd; Maass, Peter
2014-01-01
3D imaging has a significant impact on many challenges in life sciences, because biology is a 3-dimensional phenomenon. Current 3D imaging-technologies (various types MRI, PET, SPECT) are labeled, i.e. they trace the localization of a specific compound in the body. In contrast, 3D MALDI mass spectrometry-imaging (MALDI-MSI) is a label-free method imaging the spatial distribution of molecular compounds. It complements 3D imaging labeled methods, immunohistochemistry, and genetics-based methods. However, 3D MALDI-MSI cannot tap its full potential due to the lack of statistical methods for analysis and interpretation of large and complex 3D datasets. To overcome this, we established a complete and robust 3D MALDI-MSI pipeline combined with efficient computational data analysis methods for 3D edge preserving image denoising, 3D spatial segmentation as well as finding colocalized m/z values, which will be reviewed here in detail. Furthermore, we explain, why the integration and correlation of the MALDI imaging data with other imaging modalities allows to enhance the interpretation of the molecular data and provides visualization of molecular patterns that may otherwise not be apparent. Therefore, a 3D data acquisition workflow is described generating a set of 3 different dimensional images representing the same anatomies. First, an in-vitro MRI measurement is performed which results in a three-dimensional image modality representing the 3D structure of the measured object. After sectioning the 3D object into N consecutive slices, all N slices are scanned using an optical digital scanner, enabling for performing the MS measurements. Scanning the individual sections results into low-resolution images, which define the base coordinate system for the whole pipeline. The scanned images conclude the information from the spatial (MRI) and the mass spectrometric (MALDI-MSI) dimension and are used for the spatial three-dimensional reconstruction of the object performed by image
Adaptive optofluidic lens(es) for switchable 2D and 3D imaging
NASA Astrophysics Data System (ADS)
Huang, Hanyang; Wei, Kang; Zhao, Yi
2016-03-01
The stereoscopic image is often captured using dual cameras arranged side-by-side and optical path switching systems such as two separate solid lenses or biprism/mirrors. The miniaturization of the overall size of current stereoscopic devices down to several millimeters is at a sacrifice of further device size shrinkage. The limited light entry worsens the final image resolution and brightness. It is known that optofluidics offer good re-configurability for imaging systems. Leveraging this technique, we report a reconfigurable optofluidic system whose optical layout can be swapped between a singlet lens with 10 mm in diameter and a pair of binocular lenses with each lens of 3 mm in diameter for switchable two-dimensional (2D) and three-dimensional (3D) imaging. The singlet and the binoculars share the same optical path and the same imaging sensor. The singlet acquires a 3D image with better resolution and brightness, while the binoculars capture stereoscopic image pairs for 3D vision and depth perception. The focusing power tuning capability of the singlet and the binoculars enable image acquisition at varied object planes by adjusting the hydrostatic pressure across the lens membrane. The vari-focal singlet and binoculars thus work interchangeably and complementarily. The device is thus expected to have applications in robotic vision, stereoscopy, laparoendoscopy and miniaturized zoom lens system.
Fast Image Reconstruction with L2-Regularization
Bilgic, Berkin; Chatnuntawech, Itthi; Fan, Audrey P.; Setsompop, Kawin; Cauley, Stephen F.; Wald, Lawrence L.; Adalsteinsson, Elfar
2014-01-01
Purpose We introduce L2-regularized reconstruction algorithms with closed-form solutions that achieve dramatic computational speed-up relative to state of the art L1- and L2-based iterative algorithms while maintaining similar image quality for various applications in MRI reconstruction. Materials and Methods We compare fast L2-based methods to state of the art algorithms employing iterative L1- and L2-regularization in numerical phantom and in vivo data in three applications; 1) Fast Quantitative Susceptibility Mapping (QSD), 2) Lipid artifact suppression in Magnetic Resonance Spectroscopic Imaging (MRSI), and 3) Diffusion Spectrum Imaging (DSI). In all cases, proposed L2-based methods are compared with the state of the art algorithms, and two to three orders of magnitude speed up is demonstrated with similar reconstruction quality. Results The closed-form solution developed for regularized QSM allows processing of a 3D volume under 5 seconds, the proposed lipid suppression algorithm takes under 1 second to reconstruct single-slice MRSI data, while the PCA based DSI algorithm estimates diffusion propagators from undersampled q-space for a single slice under 30 seconds, all running in Matlab using a standard workstation. Conclusion For the applications considered herein, closed-form L2-regularization can be a faster alternative to its iterative counterpart or L1-based iterative algorithms, without compromising image quality. PMID:24395184
Calibration of an Ultrasound Tomography System for Medical Imaging with 2D Contrast-Source Inversion
NASA Astrophysics Data System (ADS)
Faucher, Gabriel Paul
This dissertation describes two possible methods for the calibration of an ultrasound tomography system developed at University of Manitoba's Electromagnetic Imaging Laboratory for imaging with the contrast-source inversion algorithm. The calibration techniques are adapted from existing procedures employed for microwave tomography. A theoretical model of these calibration principles is developed in order to provide a rationale for the effectiveness of the proposed procedures. The applicability of such an imaging algorithm and calibration methods in the context of ultrasound are discussed. Also presented are 2D and 3D finite-difference time-domain update equations for the simulation of acoustic wave propagation in inhomogeneous media. Details regarding the application of an absorbing boundary-condition, point-source modelling and the treatment of penetrable objects are included in this document.
NASA Astrophysics Data System (ADS)
Mikulka, J.; Gescheidtova, E.; Bartusek, K.
2012-01-01
The paper deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It focuses primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR). It is easy to describe edges of the sought objects using segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction. The proposed solutions can be used for the classification of healthy/unhealthy tissues in MR or other imaging. Application examples of the proposed segmentation methods are shown. Research in the area of image segmentation focuses on methods based on solving partial differential equations. This is a modern method for image processing, often called the active contour method. It is of great advantage in the segmentation of real images degraded by noise with fuzzy edges and transitions between objects. In the paper, results of the segmentation of medical images by the active contour method are compared with results of the segmentation by other existing methods. Experimental applications which demonstrate the very good properties of the active contour method are given.
Optimal Statistical Approach to Optoacoustic Image Reconstruction
NASA Astrophysics Data System (ADS)
Zhulina, Yulia V.
2000-11-01
An optimal statistical approach is applied to the task of image reconstruction in photoacoustics. The physical essence of the task is as follows: Pulse laser irradiation induces an ultrasound wave on the inhomogeneities inside the investigated volume. This acoustic wave is received by the set of receivers outside this volume. It is necessary to reconstruct a spatial image of these inhomogeneities. Developed mathematical techniques of the radio location theory are used for solving the task. An algorithm of maximum likelihood is synthesized for the image reconstruction. The obtained algorithm is investigated by digital modeling. The number of receivers and their disposition in space are arbitrary. Results of the synthesis are applied to noninvasive medical diagnostics (breast cancer). The capability of the algorithm is tested on real signals. The image is built with use of signals obtained in vitro . The essence of the algorithm includes (i) summing of all signals in the image plane with the transform from the time coordinates of signals to the spatial coordinates of the image and (ii) optimal spatial filtration of this sum. The results are shown in the figures.
Stochastic image reconstruction for a dual-particle imaging system
NASA Astrophysics Data System (ADS)
Hamel, M. C.; Polack, J. K.; Poitrasson-Rivière, A.; Flaska, M.; Clarke, S. D.; Pozzi, S. A.; Tomanin, A.; Peerani, P.
2016-02-01
Stochastic image reconstruction has been applied to a dual-particle imaging system being designed for nuclear safeguards applications. The dual-particle imager (DPI) is a combined Compton-scatter and neutron-scatter camera capable of producing separate neutron and photon images. The stochastic origin ensembles (SOE) method was investigated as an imaging method for the DPI because only a minimal estimation of system response is required to produce images with quality that is comparable to common maximum-likelihood methods. This work contains neutron and photon SOE image reconstructions for a 252Cf point source, two mixed-oxide (MOX) fuel canisters representing point sources, and the MOX fuel canisters representing a distributed source. Simulation of the DPI using MCNPX-PoliMi is validated by comparison of simulated and measured results. Because image quality is dependent on the number of counts and iterations used, the relationship between these quantities is investigated.
Photoacoustic imaging for deep targets in the breast using a multichannel 2D array transducer
NASA Astrophysics Data System (ADS)
Xie, Zhixing; Wang, Xueding; Morris, Richard F.; Padilla, Frederic R.; Lecarpentier, Gerald L.; Carson, Paul L.
2011-03-01
A photoacoustic (PA) imaging system was developed to achieve high sensitivity for the detection and characterization of vascular anomalies in the breast in the mammographic geometry. Signal detection from deep in the breast was achieved by a broadband 2D PVDF planar array that has a round shape with one side trimmed straight to improve fit near the chest wall. This array has 572 active elements and a -6dB bandwidth of 0.6-1.7 MHz. The low frequency enhances imaging depth and increases the size of vascular collections displayed without edge enhancement. The PA signals from all the elements go through low noise preamplifiers in the probe that are very close to the array elements for optimized noise control. Driven by 20 independent on-probe signal processing channels, imaging with both high sensitivity and good speed was achieved. To evaluate the imaging depth and the spatial resolution of this system,2.38mm I.D. artificial vessels embedded deeply in ex vivo breasts harvested from fresh cadavers and a 3mm I.D. tube in breast mimicking phantoms made of pork loin and fat tissues were imaged. Using near-infrared laser light with incident energy density within the ANSI safety limit, imaging depths of up to 49 mm in human breasts and 52 mm in phantoms were achieved. With a high power tunable laser working on multiple wavelengths, this system might contribute to 3D noninvasive imaging of morphological and physiological tissue features throughout the breast.
A preliminary evaluation work on a 3D ultrasound imaging system for 2D array transducer
NASA Astrophysics Data System (ADS)
Zhong, Xiaoli; Li, Xu; Yang, Jiali; Li, Chunyu; Song, Junjie; Ding, Mingyue; Yuchi, Ming
2016-04-01
This paper presents a preliminary evaluation work on a pre-designed 3-D ultrasound imaging system. The system mainly consists of four parts, a 7.5MHz, 24×24 2-D array transducer, the transmit/receive circuit, power supply, data acquisition and real-time imaging module. The row-column addressing scheme is adopted for the transducer fabrication, which greatly reduces the number of active channels . The element area of the transducer is 4.6mm by 4.6mm. Four kinds of tests were carried out to evaluate the imaging performance, including the penetration depth range, axial and lateral resolution, positioning accuracy and 3-D imaging frame rate. Several strong reflection metal objects , fixed in a water tank, were selected for the purpose of imaging due to a low signal-to-noise ratio of the transducer. The distance between the transducer and the tested objects , the thickness of aluminum, and the seam width of the aluminum sheet were measured by a calibrated micrometer to evaluate the penetration depth, the axial and lateral resolution, respectively. The experiment al results showed that the imaging penetration depth range was from 1.0cm to 6.2cm, the axial and lateral resolution were 0.32mm and 1.37mm respectively, the imaging speed was up to 27 frames per second and the positioning accuracy was 9.2%.
Simultaneous algebraic reconstruction technique based on guided image filtering.
Ji, Dongjiang; Qu, Gangrong; Liu, Baodong
2016-07-11
The challenge of computed tomography is to reconstruct high-quality images from few-view projections. Using a prior guidance image, guided image filtering smoothes images while preserving edge features. The prior guidance image can be incorporated into the image reconstruction process to improve image quality. We propose a new simultaneous algebraic reconstruction technique based on guided image filtering. Specifically, the prior guidance image is updated in the image reconstruction process, merging information iteratively. To validate the algorithm practicality and efficiency, experiments were performed with numerical phantom projection data and real projection data. The results demonstrate that the proposed method is effective and efficient for nondestructive testing and rock mechanics. PMID:27410859
2D aperture synthesis for Lamb wave imaging using co-arrays
NASA Astrophysics Data System (ADS)
Ambrozinski, Lukasz; Stepinski, Tadeusz; Uhl, Tadeusz
2014-03-01
2D ultrasonic arrays in Lamb wave based SHM systems can operate in the phased array (PA) or synthetic focusing (SF) mode. In the real-time PA approach, multiple electronically delayed signals excite transmitting elements to form the desired wave-front, whereas receiving elements are used to sense scattered waves. Due to that, the PA mode requires multi channeled hardware and multiple excitations at numerous azimuths to scan the inspected region of interest. To the contrary, the SF mode, assumes a single element excitation of subsequent transmitters and off-line processing of the acquired data. In the simplest implementation of the SF technique, a single multiplexed input and output channels are required, which results in significant hardware simplification. Performance of a 2D imaging array depends on many parameters, such as, its topology, number of its transducers and their spacing in terms of wavelength as well as the type of weighting function (apodization). Moreover, it is possible to use sparse arrays, which means that not all array elements are used for transmitting and/ or receiving. In this paper the co-array concept is applied to facilitate the synthesis process of an array's aperture used in the multistatic synthetic focusing approach in Lamb waves-based imaging systems. In the coherent imaging, performed in the transmit/receive mode, the sum co-array is a morphological convolution of the transmit/receive sub-arrays. It can be calculated as the set of sums of the individual elements' locations in the sub-arrays used for imaging. The coarray framework will be presented here using two different array topologies, aID uniform linear array and a cross-shaped array that will result in a square coarray. The approach will be discussed in terms of array patterns and beam patterns of the resulting imaging systems. Both, theoretical and experimental results will be given.
Visualizing 3D Objects from 2D Cross Sectional Images Displayed "In-Situ" versus "Ex-Situ"
ERIC Educational Resources Information Center
Wu, Bing; Klatzky, Roberta L.; Stetten, George
2010-01-01
The present research investigates how mental visualization of a 3D object from 2D cross sectional images is influenced by displacing the images from the source object, as is customary in medical imaging. Three experiments were conducted to assess people's ability to integrate spatial information over a series of cross sectional images in order to…
Optimal Discretization Resolution in Algebraic Image Reconstruction
NASA Astrophysics Data System (ADS)
Sharif, Behzad; Kamalabadi, Farzad
2005-11-01
In this paper, we focus on data-limited tomographic imaging problems where the underlying linear inverse problem is ill-posed. A typical regularized reconstruction algorithm uses algebraic formulation with a predetermined discretization resolution. If the selected resolution is too low, we may loose useful details of the underlying image and if it is too high, the reconstruction will be unstable and the representation will fit irrelevant features. In this work, two approaches are introduced to address this issue. The first approach is using Mallow's CL method or generalized cross-validation. For each of the two methods, a joint estimator of regularization parameter and discretization resolution is proposed and their asymptotic optimality is investigated. The second approach is a Bayesian estimator of the model order using a complexity-penalizing prior. Numerical experiments focus on a space imaging application from a set of limited-angle tomographic observations.
NASA Astrophysics Data System (ADS)
Chen, Shaohua; Kirubanandham, Antony; Chawla, Nikhilesh; Jiao, Yang
2016-03-01
An accurate knowledge of the 3D polycrystalline microstructure of a material is crucial to its property prediction, performance optimization, and design. Here, we present a multi-scale computational scheme that allows one to stochastically reconstruct the 3D microstructure of a highly heterogeneous polycrystalline material with large variation in grain size, morphology, and spatial distribution, as well as the distribution of second-phase particles, from single-2D electron back-scattered diffraction (EBSD) micrograph. Specifically, the two-point correlation functions S 2 are employed to statistically characterize grain morphology, orientation, and spatial distribution and are incorporated into the simulated annealing procedure for microstructure reconstruction. During the reconstruction, the original polycrystalline microstructure is coarsened such that the large grains are reconstructed first and the smaller ones are generated later. The second-phase particles are then inserted into the reconstructed polycrystalline material based on the pair-correlation function g 2 sampled from the 2D back-scattered electron micrograph. The utility of our multi-scale scheme is demonstrated by successfully reconstructing a highly heterogeneous polycrystalline Sn-rich solder joint with Cu6Sn5 intermetallic particles. The accuracy of our reconstruction is ascertained by comparing the virtual microstructure with the actual 3D structure of the joint obtained via serial sectioning techniques.
Diesel combustion and emissions formation using multiple 2-D imaging diagnostics
Dec, J.E.
1997-12-31
Understanding how emissions are formed during diesel combustion is central to developing new engines that can comply with increasingly stringent emission standards while maintaining or improving performance levels. Laser-based planar imaging diagnostics are uniquely capable of providing the temporally and spatially resolved information required for this understanding. Using an optically accessible research engine, a variety of two-dimensional (2-D) imaging diagnostics have been applied to investigators of direct-injection (DI) diesel combustion and emissions formation. These optical measurements have included the following laser-sheet imaging data: Mie scattering to determine liquid-phase fuel distributions, Rayleigh scattering for quantitative vapor-phase-fuel/air mixture images, laser induced incandescence (LII) for relative soot concentrations, simultaneous LII and Rayleigh scattering for relative soot particle-size distributions, planar laser-induced fluorescence (PLIF) to obtain early PAH (polyaromatic hydrocarbon) distributions, PLIF images of the OH radical that show the diffusion flame structure, and PLIF images of the NO radical showing the onset of NO{sub x} production. In addition, natural-emission chemiluminescence images were obtained to investigate autoignition. The experimental setup is described, and the image data showing the most relevant results are presented. Then the conceptual model of diesel combustion is summarized in a series of idealized schematics depicting the temporal and spatial evolution of a reacting diesel fuel jet during the time period investigated. Finally, recent PLIF images of the NO distribution are presented and shown to support the timing and location of NO formation hypothesized from the conceptual model.
3D face reconstruction from limited images based on differential evolution
NASA Astrophysics Data System (ADS)
Wang, Qun; Li, Jiang; Asari, Vijayan K.; Karim, Mohammad A.
2011-09-01
3D face modeling has been one of the greatest challenges for researchers in computer graphics for many years. Various methods have been used to model the shape and texture of faces under varying illumination and pose conditions from a single given image. In this paper, we propose a novel method for the 3D face synthesis and reconstruction by using a simple and efficient global optimizer. A 3D-2D matching algorithm which employs the integration of the 3D morphable model (3DMM) and the differential evolution (DE) algorithm is addressed. In 3DMM, the estimation process of fitting shape and texture information into 2D images is considered as the problem of searching for the global minimum in a high dimensional feature space, in which optimization is apt to have local convergence. Unlike the traditional scheme used in 3DMM, DE appears to be robust against stagnation in local minima and sensitiveness to initial values in face reconstruction. Benefitting from DE's successful performance, 3D face models can be created based on a single 2D image with respect to various illuminating and pose contexts. Preliminary results demonstrate that we are able to automatically create a virtual 3D face from a single 2D image with high performance. The validation process shows that there is only an insignificant difference between the input image and the 2D face image projected by the 3D model.
2-D array for 3-D Ultrasound Imaging Using Synthetic Aperture Techniques
Daher, Nadim M.; Yen, Jesse T.
2010-01-01
A 2-D array of 256 × 256 = 65,536 elements, with total area 4 × 4 = 16 cm2, serves as a flexible platform for developing acquisition schemes for 3-D rectilinear ultrasound imaging at 10 MHz using synthetic aperture techniques. This innovative system combines a simplified interconnect scheme and synthetic aperture techniques with a 2-D array for 3-D imaging. A row-column addressing scheme is used to access different elements for different transmit events. This addressing scheme is achieved through a simple interconnect, consisting of one top, one bottom single layer flex circuits, which, compared to multi-layer flex circuits, are simpler to design, cheaper to manufacture and thinner so their effect on the acoustic response is minimized. We present three designs that prioritize different design objectives: volume acquisiton time, resolution, and sensitivity, while maintaining acceptable figures for the other design objectives. For example, one design overlooks time acquisition requirements, assumes good noise conditions, and optimizes for resolution, achieving −6 dB and −20 dB beamwidths of less than 0.2 and 0.5 millimeters, respectively, for an F/2 aperture. Another design can acquire an entire volume in 256 transmit events, with −6dB and −20 dB beamwidths in the order of 0.4 and 0.8 millimeters, respectively. PMID:16764446
NASA Astrophysics Data System (ADS)
Alrowaili, Z. A.; Lerch, M. L. F.; Carolan, M.; Fuduli, I.; Porumb, C.; Petasecca, M.; Metcalfe, P.; Rosenfeld, A. B.
2015-09-01
Summary: the photon irradiation response of a 2D solid state transmission detector array mounted in a linac block tray is used to reconstruct the projected 2D dose map in a homogenous phantom along rays that diverge from the X-ray source and pass through each of the 121 detector elements. A unique diode response-to-dose scaling factor, applied to all detectors, is utilised in the reconstruction to demonstrate that real time QA during radiotherapy treatment is feasible. Purpose: to quantitatively demonstrate reconstruction of the real time radiation dose from the irradiation response of the 11×11 silicon Magic Plate (MP) detector array operated in Transmission Mode (MPTM). Methods and Materials: in transmission mode the MP is positioned in the block tray of a linac so that the central detector of the array lies on the central axis of the radiation beam. This central detector is used to determine the conversion factor from measured irradiation response to reconstructed dose at any point on the central axis within a homogenous solid water phantom. The same unique conversion factor is used for all MP detector elements lying within the irradiation field. Using the two sets of data, the 2D or 3D dose map is able to be reconstructed in the homogenous phantom. The technique we have developed is illustrated here for different depths and irradiation field sizes, (5 × 5 cm2 to 40 × 40 cm2) as well as a highly non uniform irradiation field. Results: we find that the MPTM response is proportional to the projected 2D dose map measured at a specific phantom depth, the "sweet depth". A single factor, for several irradiation field sizes and depths, is derived to reconstruct the dose in the phantom along rays projected from the photon source through each MPTM detector element. We demonstrate that for all field sizes using the above method, the 2D reconstructed and measured doses agree to within ± 2.48% (2 standard deviation) for all in-field MP detector elements. Conclusions: a
Quantitative accuracy of MAP reconstruction for dynamic PET imaging in small animals
Cheng, Ju-Chieh (Kevin); Shoghi, Kooresh; Laforest, Richard
2012-01-01
Purpose: Iterative reconstruction algorithms are becoming more commonly employed in positron emission tomography (PET) imaging; however, the quantitative accuracy of the reconstructed images still requires validation for various levels of contrast and counting statistics. Methods: The authors present an evaluation of the quantitative accuracy of the 3D maximum a posteriori (3D-MAP) image reconstruction algorithm for dynamic PET imaging with comparisons to two of the most widely used reconstruction algorithms: the 2D filtered-backprojection (2D-FBP) and 2D-ordered subsets expectation maximization (2D-OSEM) on the Siemens microPET scanners. The study was performed for various levels of count density encountered in typical dynamic scanning as well as the imaging of cardiac activity concentration in small animal studies on the Focus 120. Specially designed phantoms were used for evaluation of the spatial resolution, image quality, and quantitative accuracy. A normal mouse was employed to evaluate the accuracy of the blood time activity concentration extracted from left ventricle regions of interest (ROIs) within the images as compared to the actual blood activity concentration measured from arterial blood sampling. Results: For MAP reconstructions, the spatial resolution and contrast have been found to reach a stable value after 20 iterations independent of the β values (i.e., hyper parameter which controls the weight of the penalty term) and count density within the frame. The spatial resolution obtained with 3D-MAP reaches values of ∼1.0 mm with a β of 0.01 while the 2D-FBP has value of 1.8 mm and 2D-OSEM has a value of 1.6 mm. It has been observed that the lower the hyper parameter β used in MAP, more iterations are needed to reach the stable noise level (i.e., image roughness). The spatial resolution is improved by using a lower β value at the expense of higher image noise. However, with similar noise level the spatial resolution achieved by 3D-MAP was
Building reconstruction from images and laser scanning
NASA Astrophysics Data System (ADS)
Brenner, Claus
2005-03-01
The automatic extraction of objects from laser scans and images has been a topic of research for decades. Nowadays, with new services expected, especially in the area of navigation systems, location based services, and augmented reality, the need for automated, efficient extraction systems becomes more urgent than ever. This paper reviews a number of automatic and semi-automatic reconstruction methods in more detail in order to reveal their underlying principles. It then discusses some general properties of reconstruction approaches which have evolved. This shows that, although research is still far from the goal of the initially envisioned fully automatic reconstruction systems, there is now a much better understanding of the problem and the ways it can be tackled.
Propagation phasor approach for holographic image reconstruction
NASA Astrophysics Data System (ADS)
Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan
2016-03-01
To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears.
Context dependent anti-aliasing image reconstruction
NASA Technical Reports Server (NTRS)
Beaudet, Paul R.; Hunt, A.; Arlia, N.
1989-01-01
Image Reconstruction has been mostly confined to context free linear processes; the traditional continuum interpretation of digital array data uses a linear interpolator with or without an enhancement filter. Here, anti-aliasing context dependent interpretation techniques are investigated for image reconstruction. Pattern classification is applied to each neighborhood to assign it a context class; a different interpolation/filter is applied to neighborhoods of differing context. It is shown how the context dependent interpolation is computed through ensemble average statistics using high resolution training imagery from which the lower resolution image array data is obtained (simulation). A quadratic least squares (LS) context-free image quality model is described from which the context dependent interpolation coefficients are derived. It is shown how ensembles of high-resolution images can be used to capture the a priori special character of different context classes. As a consequence, a priori information such as the translational invariance of edges along the edge direction, edge discontinuity, and the character of corners is captured and can be used to interpret image array data with greater spatial resolution than would be expected by the Nyquist limit. A Gibb-like artifact associated with this super-resolution is discussed. More realistic context dependent image quality models are needed and a suggestion is made for using a quality model which now is finding application in data compression.
Propagation phasor approach for holographic image reconstruction
Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan
2016-01-01
To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears. PMID:26964671
Constructing a Database from Multiple 2D Images for Camera Pose Estimation and Robot Localization
NASA Technical Reports Server (NTRS)
Wolf, Michael; Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.; Padgett, Curtis W.
2012-01-01
The LMDB (Landmark Database) Builder software identifies persistent image features (landmarks) in a scene viewed multiple times and precisely estimates the landmarks 3D world positions. The software receives as input multiple 2D images of approximately the same scene, along with an initial guess of the camera poses for each image, and a table of features matched pair-wise in each frame. LMDB Builder aggregates landmarks across an arbitrarily large collection of frames with matched features. Range data from stereo vision processing can also be passed to improve the initial guess of the 3D point estimates. The LMDB Builder aggregates feature lists across all frames, manages the process to promote selected features to landmarks, and iteratively calculates the 3D landmark positions using the current camera pose estimations (via an optimal ray projection method), and then improves the camera pose estimates using the 3D landmark positions. Finally, it extracts image patches for each landmark from auto-selected key frames and constructs the landmark database. The landmark database can then be used to estimate future camera poses (and therefore localize a robotic vehicle that may be carrying the cameras) by matching current imagery to landmark database image patches and using the known 3D landmark positions to estimate the current pose.
2-D Gaussian beam imaging of multicomponent seismic data in anisotropic media
NASA Astrophysics Data System (ADS)
Protasov, M. I.
2015-12-01
An approach for true-amplitude seismic beam imaging of multicomponent seismic data in 2-D anisotropic elastic media is presented and discussed. Here, the recovered true-amplitude function is a scattering potential. This approach is a migration procedure based on the weighted summation of pre-stack data. The true-amplitude weights are computed by applying Gaussian beams (GBs). We shoot a pair of properly chosen GBs with a fixed dip and opening angles from the current imaging point towards an acquisition system. This pair of beams is used to compute a true-amplitude selective image of a rapid velocity variation. The total true-amplitude image is constructed by superimposing selective images computed for a range of available dip angles. The global regularity of the GBs allows one to disregard whether a ray field is regular or irregular. P- and S-wave GBs can be used to handle raw multicomponent data without separating the waves. The use of anisotropic GBs allows one to take into account the anisotropy of the background model.
Three-dimensional image reconstruction for PET by multi-slice rebinning and axial image filtering.
Lewittt, R M; Muehllehner, G; Karpt, J S
1994-03-01
A fast method is described for reconstructing volume images from three-dimensional (3D) coincidence data in positron emission tomography (PET). The reconstruction method makes use of all coincidence data acquired by high-sensitivity PET systems that do not have inter-slice absorbers (septa) to restrict the axial acceptance angle. The reconstruction method requires only a small amount of storage and computation, making it well suited for dynamic and whole-body studies. The method consists of three steps: (i) rebinning of coincidence data into a stack of 2D sinograms; (ii) slice-by-slice reconstruction of the sinogram associated with each slice to produce a preliminary 3D image having strong blurring in the axial (z) direction, but with different blurring at different z positions; and (iii) spatially variant filtering of the 3D image in the axial direction (i.e. 1D filtering in z for each x-y column) to produce the final image. The first step involves a new form of the rebinning operation in which multiple sinograms are incremented for each oblique coincidence line (multi-slice rebinning). The axial filtering step is formulated and implemented using the singular value decomposition (SVD). The method has been applied successfully to simulated data and to measured data for different kinds of phantom (multiple point sources, multiple discs, a cylinder with cold spheres, and a 3D brain phantom). PMID:15551583
Performance-based assessment of reconstructed images
Hanson, Kenneth
2009-01-01
During the early 90s, I engaged in a productive and enjoyable collaboration with Robert Wagner and his colleague, Kyle Myers. We explored the ramifications of the principle that tbe quality of an image should be assessed on the basis of how well it facilitates the performance of appropriate visual tasks. We applied this principle to algorithms used to reconstruct scenes from incomplete and/or noisy projection data. For binary visual tasks, we used both the conventional disk detection and a new challenging task, inspired by the Rayleigh resolution criterion, of deciding whether an object was a blurred version of two dots or a bar. The results of human and machine observer tests were summarized with the detectability index based on the area under the ROC curve. We investigated a variety of reconstruction algorithms, including ART, with and without a nonnegativity constraint, and the MEMSYS3 algorithm. We concluded that the performance of the Raleigh task was optimized when the strength of the prior was near MEMSYS's default 'classic' value for both human and machine observers. A notable result was that the most-often-used metric of rms error in the reconstruction was not necessarily indicative of the value of a reconstructed image for the purpose of performing visual tasks.
Application of Compressed Sensing to 2-D Ultrasonic Propagation Imaging System data
Mascarenas, David D.; Farrar, Charles R.; Chong, See Yenn; Lee, J.R.; Park, Gyu Hae; Flynn, Eric B.
2012-06-29
The Ultrasonic Propagation Imaging (UPI) System is a unique, non-contact, laser-based ultrasonic excitation and measurement system developed for structural health monitoring applications. The UPI system imparts laser-induced ultrasonic excitations at user-defined locations on a structure of interest. The response of these excitations is then measured by piezoelectric transducers. By using appropriate data reconstruction techniques, a time-evolving image of the response can be generated. A representative measurement of a plate might contain 800x800 spatial data measurement locations and each measurement location might be sampled at 500 instances in time. The result is a total of 640,000 measurement locations and 320,000,000 unique measurements. This is clearly a very large set of data to collect, store in memory and process. The value of these ultrasonic response images for structural health monitoring applications makes tackling these challenges worthwhile. Recently compressed sensing has presented itself as a candidate solution for directly collecting relevant information from sparse, high-dimensional measurements. The main idea behind compressed sensing is that by directly collecting a relatively small number of coefficients it is possible to reconstruct the original measurement. The coefficients are obtained from linear combinations of (what would have been the original direct) measurements. Often compressed sensing research is simulated by generating compressed coefficients from conventionally collected measurements. The simulation approach is necessary because the direct collection of compressed coefficients often requires compressed sensing analog front-ends that are currently not commercially available. The ability of the UPI system to make measurements at user-defined locations presents a unique capability on which compressed measurement techniques may be directly applied. The application of compressed sensing techniques on this data holds the potential to
A survey among Brazilian thoracic surgeons about the use of preoperative 2D and 3D images
Cipriano, Federico Enrique Garcia; Arcêncio, Livia; Dessotte, Lycio Umeda; Rodrigues, Alfredo José; Vicente, Walter Villela de Andrade
2016-01-01
Background Describe the characteristics of how the thoracic surgeon uses the 2D/3D medical imaging to perform surgical planning, clinical practice and teaching in thoracic surgery and check the initial choice and the final choice of the Brazilian Thoracic surgeon as the 2D and 3D models pictures before and after acquiring theoretical knowledge on the generation, manipulation and interactive 3D views. Methods A descriptive research type Survey cross to data provided by the Brazilian Thoracic Surgeons (members of the Brazilian Society of Thoracic Surgery) who responded to the online questionnaire via the internet on their computers or personal devices. Results Of the 395 invitations visualized distributed by email, 107 surgeons completed the survey. There was no statically difference when comparing the 2D vs. 3D models pictures for the following purposes: diagnosis, assessment of the extent of disease, preoperative surgical planning, and communication among physicians, resident training, and undergraduate medical education. Regarding the type of tomographic image display routinely used in clinical practice (2D or 3D or 2D–3D model image) and the one preferred by the surgeon at the end of the questionnaire. Answers surgeons for exclusive use of 2D images: initial choice =50.47% and preferably end =14.02%. Responses surgeons to use 3D models in combination with 2D images: initial choice =48.60% and preferably end =85.05%. There was a significant change in the final selection of 3D models used together with the 2D images (P<0.0001). Conclusions There is a lack of knowledge of the 3D imaging, as well as the use and interactive manipulation in dedicated 3D applications, with consequent lack of uniformity in the surgical planning based on CT images. These findings certainly confirm in changing the preference of thoracic surgeons of 2D views of technologies for 3D images. PMID:27621874
NASA Astrophysics Data System (ADS)
Eckstein, Johannes; Lei, Wang; Becker, Jonathan; Jun, Gao; Ott, Peter
2006-04-01
In this paper a distance measurement sensor is introduced, equipped with two integrated optical systems, the first one for rotationally symmetric triangulation and the second one for imaging the object while using only one 2D detector for both purposes. Rotationally symmetric triangulation, introduced in [1], eliminates some disadvantages of classical triangulation sensors, especially at steps or strong curvatures of the object, wherefore the measurement result depends not any longer on the angular orientation of the sensor. This is achieved by imaging the scattered light from an illuminated object point to a centered and sharp ring on a low cost area detector. The diameter of the ring is proportional to the distance of the object. The optical system consists of two off axis aspheric reflecting surfaces. This system allows for integrating a second optical system in order to capture images of the object at the same 2D detector. A mock-up was realized for the first time which consists of the reflecting optics for triangulation manufactured by diamond turning. A commercially available appropriate small lens system for imaging was mechanically integrated in the reflecting optics. Alternatively, some designs of retrofocus lens system for larger field of views were investigated. The optical designs allow overlying the image of the object and the ring for distance measurement in the same plane. In this plane a CCD detector is mounted, centered to the optical axis for both channels. A fast algorithm for the evaluation of the ring is implemented. The characteristics, i.e. the ring diameter versus object distance shows very linear behavior. For illumination of the object point for distance measurement, the beam of a red laser diode system is reflected by a wavelength bandpath filter on the axis of the optical system in. Additionally, the surface of the object is illuminated by LED's in the green spectrum. The LED's are located on the outside rim of the reflecting optics. The
Hyperspectral image reconstruction for diffuse optical tomography
Larusson, Fridrik; Fantini, Sergio; Miller, Eric L.
2011-01-01
We explore the development and performance of algorithms for hyperspectral diffuse optical tomography (DOT) for which data from hundreds of wavelengths are collected and used to determine the concentration distribution of chromophores in the medium under investigation. An efficient method is detailed for forming the images using iterative algorithms applied to a linearized Born approximation model assuming the scattering coefficient is spatially constant and known. The L-surface framework is employed to select optimal regularization parameters for the inverse problem. We report image reconstructions using 126 wavelengths with estimation error in simulations as low as 0.05 and mean square error of experimental data of 0.18 and 0.29 for ink and dye concentrations, respectively, an improvement over reconstructions using fewer specifically chosen wavelengths. PMID:21483616
Embedded morphological dilation coding for 2D and 3D images
NASA Astrophysics Data System (ADS)
Lazzaroni, Fabio; Signoroni, Alberto; Leonardi, Riccardo
2002-01-01
Current wavelet-based image coders obtain high performance thanks to the identification and the exploitation of the statistical properties of natural images in the transformed domain. Zerotree-based algorithms, as Embedded Zerotree Wavelets (EZW) and Set Partitioning In Hierarchical Trees (SPIHT), offer high Rate-Distortion (RD) coding performance and low computational complexity by exploiting statistical dependencies among insignificant coefficients on hierarchical subband structures. Another possible approach tries to predict the clusters of significant coefficients by means of some form of morphological dilation. An example of a morphology-based coder is the Significance-Linked Connected Component Analysis (SLCCA) that has shown performance which are comparable to the zerotree-based coders but is not embedded. A new embedded bit-plane coder is proposed here based on morphological dilation of significant coefficients and context based arithmetic coding. The algorithm is able to exploit both intra-band and inter-band statistical dependencies among wavelet significant coefficients. Moreover, the same approach is used both for two and three-dimensional wavelet-based image compression. Finally we the algorithms are tested on some 2D images and on a medical volume, by comparing the RD results to those obtained with the state-of-the-art wavelet-based coders.
Clinical breast imaging using sound-speed reconstructions of ultrasound tomography data
NASA Astrophysics Data System (ADS)
Li, Cuiping; Duric, Neb; Huang, Lianjie
2008-03-01
To improve clinical breast imaging, a new ultrasound tomography imaging device (CURE) has been built at the Karmanos Cancer Institute. The ring array of the CURE device records ultrasound transmitted and reflected ultrasound signals simultaneously. We develop a bent-ray tomography algorithm for reconstructing the sound-speed distribution of the breast using time-of-flights of transmitted signals. We study the capability of the algorithm using a breast phantom dataset and over 190 patients' data. Examples are presented to demonstrate the sound-speed reconstructions for different breast types from fatty to dense on the BI-RADS categories 1-4. Our reconstructions show that the mean sound-speed value increases from fatty to dense breasts: 1440.8 m/ s (fatty), 1451.9 m/ s (scattered), 1473.2 m/ s(heterogeneous), and 1505.25 m/ s (dense). This is an important clinical implication of our reconstruction. The mean sound speed can be used for breast density analysis. In addition, the sound-speed reconstruction, in combination with attenuation and reflectivity images, has the potential to improve breast-cancer diagnostic imaging. The breast is not compressed and does not move during the ultrasound scan using the CURE device, stacking 2D slices of ultrasound sound-speed tomography images forms a 3D volumetric view of the whole breast. The 3D image can also be projected into a 2-D "ultrasound mammogram" to visually mimic X-ray mammogram without breast compression and ionizing radiation.
Gilbert, Robert P; Guyenne, Philippe; Li, Jing
2014-02-01
In this paper, we compare ultrasound interrogations of actual CT-scanned images of trabecular bone with artificial randomly constructed bone. Even though it is known that actual bone does not have randomly distributed trabeculae, we find that the ultrasound attenuations are close enough to cast doubt on any microstructural information, such as trabeculae width and distance between trabeculae, being gleaned from such experiments. More precisely, we perform numerical simulations of ultrasound interrogation on cancellous bone to investigate the phenomenon of ultrasound attenuation as a function of excitation frequency and bone porosity. The theoretical model is based on acoustic propagation equations for a composite fluid-solid material and is solved by a staggered-grid finite-difference scheme in the time domain. Numerical experiments are performed on two-dimensional bone samples reconstructed from CT-scanned images of real human calcaneus and from random distributions of fluid-solid particles generated via the turning bands method. A detailed comparison is performed on various parameters such as the attenuation rate and speed of sound through the bone samples as well as the normalized broadband ultrasound attenuation coefficient. Comparing results from these two types of bone samples allows us to assess the role of bone microstructure in ultrasound attenuation. It is found that the random model provides suitable bone samples for ultrasound interrogation in the transverse direction of the trabecular network. PMID:24480174
Registration of 2D to 3D joint images using phase-based mutual information
NASA Astrophysics Data System (ADS)
Dalvi, Rupin; Abugharbieh, Rafeef; Pickering, Mark; Scarvell, Jennie; Smith, Paul
2007-03-01
Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.
Bom, M. J. van der; Bartels, L. W.; Gounis, M. J.; Homan, R.; Timmer, J.; Viergever, M. A.; Pluim, J. P. W.
2010-04-15
Purpose: The image registration literature comprises many methods for 2D-3D registration for which accuracy has been established in a variety of applications. However, clinical application is limited by a small capture range. Initial offsets outside the capture range of a registration method will not converge to a successful registration. Previously reported capture ranges, defined as the 95% success range, are in the order of 4-11 mm mean target registration error. In this article, a relatively computationally inexpensive and robust estimation method is proposed with the objective to enlarge the capture range. Methods: The method uses the projection-slice theorem in combination with phase correlation in order to estimate the transform parameters, which provides an initialization of the subsequent registration procedure. Results: The feasibility of the method was evaluated by experiments using digitally reconstructed radiographs generated from in vivo 3D-RX data. With these experiments it was shown that the projection-slice theorem provides successful estimates of the rotational transform parameters for perspective projections and in case of translational offsets. The method was further tested on ex vivo ovine x-ray data. In 95% of the cases, the method yielded successful estimates for initial mean target registration errors up to 19.5 mm. Finally, the method was evaluated as an initialization method for an intensity-based 2D-3D registration method. The uninitialized and initialized registration experiments had success rates of 28.8% and 68.6%, respectively. Conclusions: The authors have shown that the initialization method based on the projection-slice theorem and phase correlation yields adequate initializations for existing registration methods, thereby substantially enlarging the capture range of these methods.
Xu, Qiaofeng; Sidky, Emil Y.; Pan, Xiaochuan; Stampanoni, Marco; Modregger, Peter; Anastasio, Mark A.
2012-01-01
Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen. PMID:22565698
Optical tomographic image reconstruction from ultrafast time-sliced transmission measurements.
Cai, W; Gayen, S K; Xu, M; Zevallos, M; Alrubaiee, M; Lax, M; Alfano, R R
1999-07-01
Optical imaging and localization of objects inside a highly scattering medium, such as a tumor in the breast, is a challenging problem with many practical applications. Conventional imaging methods generally provide only two-dimensional (2-D) images of limited spatial resolution with little diagnostic ability. Here we present an inversion algorithm that uses time-resolved transillumination measurements in the form of a sequence of picosecond-duration intensity patterns of transmitted ultrashort light pulses to reconstruct three-dimensional (3-D) images of an absorbing object located inside a slab of a highly scattering medium. The experimental arrangement used a 3-mm-diameter collimated beam of 800-nm, 150-fs, 1-kHz repetition rate light pulses from a Ti:sapphire laser and amplifier system to illuminate one side of the slab sample. An ultrafast gated intensified camera system that provides a minimum FWHM gate width of 80 ps recorded the 2-D intensity patterns of the light transmitted through the opposite side of the slab. The gate position was varied in steps of 100 ps over a 5-ns range to obtain a sequence of 2-D transmitted light intensity patterns of both less-scattered and multiple-scattered light for image reconstruction. The inversion algorithm is based on the diffusion approximation of the radiative transfer theory for photon transport in a turbid medium. It uses a Green s function perturbative approach under the Rytov approximation and combines a 2-D matrix inversion with a one-dimensional Fourier-transform inversion to achieve speedy 3-D image reconstruction. In addition to the lateral position, the method provides information about the axial position of the object as well, whereas the 2-D reconstruction methods yield only lateral position. PMID:18323906
3D Reconstruction of the Retinal Arterial Tree Using Subject-Specific Fundus Images
NASA Astrophysics Data System (ADS)
Liu, D.; Wood, N. B.; Xu, X. Y.; Witt, N.; Hughes, A. D.; Samcg, Thom
Systemic diseases, such as hypertension and diabetes, are associated with changes in the retinal microvasculature. Although a number of studies have been performed on the quantitative assessment of the geometrical patterns of the retinal vasculature, previous work has been confined to 2 dimensional (2D) analyses. In this paper, we present an approach to obtain a 3D reconstruction of the retinal arteries from a pair of 2D retinal images acquired in vivo. A simple essential matrix based self-calibration approach was employed for the "fundus camera-eye" system. Vessel segmentation was performed using a semi-automatic approach and correspondence between points from different images was calculated. The results of 3D reconstruction show the centreline of retinal vessels and their 3D curvature clearly. Three-dimensional reconstruction of the retinal vessels is feasible and may be useful in future studies of the retinal vasculature in disease.
2D photoacoustic scanning imaging with a single pulsed laser diode excitation
NASA Astrophysics Data System (ADS)
Chen, Xuegang; Li, Changwei; Zeng, Lvming; Liu, Guodong; Huang, Zhen; Ren, Zhong
2011-11-01
A portable near-infrared photoacoustic scanning imaging system has been developed with a single pulsed laser diode, which was integrated with an optical lens system to straightforward boost the laser energy density for photoacoustic generation. The 905 nm laser diode provides a maximum energy output of 14 μJ within 100 ns pulse duration, and the pulse repetition frequency rate is 0.8 KHz. As a possible alternative light source, the preliminary 2D photoacoustic results primely correspond with the test phantoms of umbonate extravasated gore and knotted blood vessel network. The photoacoustic SNR can reach 20.6+/-1.2 dB while signal averaging reduces to 128 pulses from thousands to tens of thousands times, and the signal acquisition time accelerates to less than 0.2 s in each A-scan, especially the volume of the total radiation source is only 10 × 3 × 3 cm3. It demonstrated that the pulsed semiconductor laser could be a candidate of photoacoustic equipment for daily clinical application.
2D photoacoustic scanning imaging with a single pulsed laser diode excitation
NASA Astrophysics Data System (ADS)
Chen, Xuegang; Li, Changwei; Zeng, Lvming; Liu, Guodong; Huang, Zhen; Ren, Zhong
2012-03-01
A portable near-infrared photoacoustic scanning imaging system has been developed with a single pulsed laser diode, which was integrated with an optical lens system to straightforward boost the laser energy density for photoacoustic generation. The 905 nm laser diode provides a maximum energy output of 14 μJ within 100 ns pulse duration, and the pulse repetition frequency rate is 0.8 KHz. As a possible alternative light source, the preliminary 2D photoacoustic results primely correspond with the test phantoms of umbonate extravasated gore and knotted blood vessel network. The photoacoustic SNR can reach 20.6+/-1.2 dB while signal averaging reduces to 128 pulses from thousands to tens of thousands times, and the signal acquisition time accelerates to less than 0.2 s in each A-scan, especially the volume of the total radiation source is only 10 × 3 × 3 cm3. It demonstrated that the pulsed semiconductor laser could be a candidate of photoacoustic equipment for daily clinical application.
NASA Astrophysics Data System (ADS)
Song, Qiyuan; Isobe, Keisuke; Hirosawa, Kenichi; Midorikawa, Katsumi; Kannari, Fumihiko
2015-03-01
Simultaneous spatial and temporal focusing (SSTF) multiphoton microscopy offers us widefield imaging with sectioning ability. As extending the idea to 2D SSTF, people can utilize a 2D spectral disperser. In this study, we use a 2D spectral disperser via a virtually-imaged phased-array (VIPA) and a diffraction grating to fulfill the back aperture of objective lens with a spectrum matrix. This offers us an axial resolution enhanced by a factor of ~1.7 compared with conventional SSTF microscopy. Furthermore, the small free spectral range (FSR) of VIPA will reduce the temporal self-imaging effect around out-of-focus region and thus will reduce the out-of-focus multiphoton excited fluorescence (MPEF) signal of 2D SSTF microscopy. We experimentally show that inside a sample with dense MPEF, the contrast of the sectioning image is increased in our 2D SSTF microscope compared with SSTF microscope. In our microscope, we use a 1 kHz chirped amplification laser, a piezo stage and a sCMOS camera integrated with 2D SSTF to realize high speed volume imaging at a speed of 50 volumes per second as well as improved sectioning ability. Volume imaging of Brownian motions of fluorescent beads as small as 1μm has been demonstrated. Not only the lateral motion but also the axial motion could be traced.
NASA Astrophysics Data System (ADS)
Esteghamatian, Mehdi; Pautler, Stephen E.; McKenzie, Charles A.; Peters, Terry M.
2011-03-01
Robotically assisted laparoscopic radical prostatectomy (RARP) is an effective approach to resect the diseased organ, with stereoscopic views of the targeted tissue improving the dexterity of the surgeons. However, since the laparoscopic view acquires only the surface image of the tissue, the underlying distribution of the cancer within the organ is not observed, making it difficult to make informed decisions on surgical margins and sparing of neurovascular bundles. One option to address this problem is to exploit registration to integrate the laparoscopic view with images of pre-operatively acquired dynamic contrast enhanced (DCE) MRI that can demonstrate the regions of malignant tissue within the prostate. Such a view potentially allows the surgeon to visualize the location of the malignancy with respect to the surrounding neurovascular structures, permitting a tissue-sparing strategy to be formulated directly based on the observed tumour distribution. If the tumour is close to the capsule, it may be determined that the adjacent neurovascular bundle (NVB) needs to be sacrificed within the surgical margin to ensure that any erupted tumour was resected. On the other hand, if the cancer is sufficiently far from the capsule, one or both NVBs may be spared. However, in order to realize such image integration, the pre-operative image needs to be fused with the laparoscopic view of the prostate. During the initial stages of the operation, the prostate must be tracked in real time so that the pre-operative MR image remains aligned with patient coordinate system. In this study, we propose and investigate a novel 2D to 3D ultrasound image registration algorithm to track the prostate motion with an accuracy of 2.68+/-1.31mm.
Deep Reconstruction Models for Image Set Classification.
Hayat, Munawar; Bennamoun, Mohammed; An, Senjian
2015-04-01
Image set classification finds its applications in a number of real-life scenarios such as classification from surveillance videos, multi-view camera networks and personal albums. Compared with single image based classification, it offers more promises and has therefore attracted significant research attention in recent years. Unlike many existing methods which assume images of a set to lie on a certain geometric surface, this paper introduces a deep learning framework which makes no such prior assumptions and can automatically discover the underlying geometric structure. Specifically, a Template Deep Reconstruction Model (TDRM) is defined whose parameters are initialized by performing unsupervised pre-training in a layer-wise fashion using Gaussian Restricted Boltzmann Machines (GRBMs). The initialized TDRM is then separately trained for images of each class and class-specific DRMs are learnt. Based on the minimum reconstruction errors from the learnt class-specific models, three different voting strategies are devised for classification. Extensive experiments are performed to demonstrate the efficacy of the proposed framework for the tasks of face and object recognition from image sets. Experimental results show that the proposed method consistently outperforms the existing state of the art methods. PMID:26353289
3D Reconstruction of Human Motion from Monocular Image Sequences.
Wandt, Bastian; Ackermann, Hanno; Rosenhahn, Bodo
2016-08-01
This article tackles the problem of estimating non-rigid human 3D shape and motion from image sequences taken by uncalibrated cameras. Similar to other state-of-the-art solutions we factorize 2D observations in camera parameters, base poses and mixing coefficients. Existing methods require sufficient camera motion during the sequence to achieve a correct 3D reconstruction. To obtain convincing 3D reconstructions from arbitrary camera motion, our method is based on a-priorly trained base poses. We show that strong periodic assumptions on the coefficients can be used to define an efficient and accurate algorithm for estimating periodic motion such as walking patterns. For the extension to non-periodic motion we propose a novel regularization term based on temporal bone length constancy. In contrast to other works, the proposed method does not use a predefined skeleton or anthropometric constraints and can handle arbitrary camera motion. We achieve convincing 3D reconstructions, even under the influence of noise and occlusions. Multiple experiments based on a 3D error metric demonstrate the stability of the proposed method. Compared to other state-of-the-art methods our algorithm shows a significant improvement. PMID:27093439
Nonrigid 2D registration of fluoroscopic coronary artery image sequence with layered motion
NASA Astrophysics Data System (ADS)
Park, Taewoo; Jung, Hoyup; Yun, Il Dong
2016-03-01
We present a new method for nonrigid registration of coronary artery models with layered motion information. 2D nonrigid registration method is proposed that brings layered motion information into correspondence with fluoroscopic angiograms. The registered model is overlaid on top of interventional angiograms to provide surgical assistance during image-guided chronic total occlusion procedures. The proposed methodology is divided into two parts: layered structures alignments and local nonrigid registration. In the first part, inpainting method is used to estimate a layered rigid transformation that aligns layered motion information. In the second part, a nonrigid registration method is implemented and used to compensate for any local shape discrepancy. Experimental evaluation conducted on a set of 7 fluoroscopic angiograms results in a reduced target registration error, which showed the effectiveness of the proposed method over single layered approach.
3D prostate boundary segmentation from ultrasound images using 2D active shape models.
Hodge, Adam C; Ladak, Hanif M
2006-01-01
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09+/-0.49 mm, the average percent absolute volume difference was 3.28+/-3.16%, and a 5x speed increase as compared manual planimetry was achieved. PMID:17946106
Tomographic image reconstruction using systolic array algorithms
Azevedo, S.G.; DeGroot, A.J.; Schneberk, D.J.; Brase, J.M.; Martz, H.E.; Jain, A.K.; Current, K.W.; Hurst, P.J.
1988-12-22
Image reconstruction for Computed Tomography (CT) is a time consuming operation on current uniprocessor computers and even on array processors. This is particularly true for three-dimensional data sets or for limited-data reconstructions requiring iterative procedures. In these cases, the projection operation (Radon transform) and its inverse (filtered back-projection) are major computational tasks that are performed many times. Multiprocessor computers, especially in systolic array configurations, can provide dramatic improvements in reconstruction times at reasonable costs. An in-house systolic processor, called SPRINT, has been programmed to demonstrate these improved speeds while achieving near 100% efficiency of all processor elements. We report on these results in this paper. In addition, two proposed hardware implementations of a new architecture are shown to have even greater speedup possibilities. One, using standard DSP chips, has been simulated to give a factor of three improvement over SPRINT, while the other, using custom VLSI that is now in the early stages of design, could potentially perform 512/sup 2/ reconstructions at video rates (100 times further speedup). These processors are also interconnected in a systolic array configuration. Experimental and projected results, with future plans, are also reported in this paper. 11 refs., 5 figs., 1 tab.
Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation
NASA Astrophysics Data System (ADS)
Lu, Kongkuo; Hall, Christopher S.
2014-03-01
Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.
Extending Ripley’s K-Function to Quantify Aggregation in 2-D Grayscale Images
Amgad, Mohamed; Itoh, Anri; Tsui, Marco Man Kin
2015-01-01
In this work, we describe the extension of Ripley’s K-function to allow for overlapping events at very high event densities. We show that problematic edge effects introduce significant bias to the function at very high densities and small radii, and propose a simple correction method that successfully restores the function’s centralization. Using simulations of homogeneous Poisson distributions of events, as well as simulations of event clustering under different conditions, we investigate various aspects of the function, including its shape-dependence and correspondence between true cluster radius and radius at which the K-function is maximized. Furthermore, we validate the utility of the function in quantifying clustering in 2-D grayscale images using three modalities: (i) Simulations of particle clustering; (ii) Experimental co-expression of soluble and diffuse protein at varying ratios; (iii) Quantifying chromatin clustering in the nuclei of wt and crwn1 crwn2 mutant Arabidopsis plant cells, using a previously-published image dataset. Overall, our work shows that Ripley’s K-function is a valid abstract statistical measure whose utility extends beyond the quantification of clustering of non-overlapping events. Potential benefits of this work include the quantification of protein and chromatin aggregation in fluorescent microscopic images. Furthermore, this function has the potential to become one of various abstract texture descriptors that are utilized in computer-assisted diagnostics in anatomic pathology and diagnostic radiology. PMID:26636680
Image inpainting on the basis of spectral structure from 2-D nonharmonic analysis.
Hasegawa, Masaya; Kako, Takahiro; Hirobayashi, Shigeki; Misawa, Tadanobu; Yoshizawa, Toshio; Inazumi, Yasuhiro
2013-08-01
The restoration of images by digital inpainting is an active field of research and such algorithms are, in fact, now widely used. Conventional methods generally apply textures that are most similar to the areas around the missing region or use a large image database. However, this produces discontinuous textures and thus unsatisfactory results. Here, we propose a new technique to overcome this limitation by using signal prediction based on the nonharmonic analysis (NHA) technique proposed by the authors. NHA can be used to extract accurate spectra, irrespective of the window function, and its frequency resolution is less than that of the discrete Fourier transform. The proposed method sequentially generates new textures on the basis of the spectrum obtained by NHA. Missing regions from the spectrum are repaired using an improved cost function for 2D NHA. The proposed method is evaluated using the standard images Lena, Barbara, Airplane, Pepper, and Mandrill. The results show an improvement in MSE of about 10-20 compared with the examplar-based method and good subjective quality. PMID:23549889
A sparse reconstruction algorithm for ultrasonic images in nondestructive testing.
Guarneri, Giovanni Alfredo; Pipa, Daniel Rodrigues; Neves Junior, Flávio; de Arruda, Lúcia Valéria Ramos; Zibetti, Marcelo Victor Wüst
2015-01-01
Ultrasound imaging systems (UIS) are essential tools in nondestructive testing (NDT). In general, the quality of images depends on two factors: system hardware features and image reconstruction algorithms. This paper presents a new image reconstruction algorithm for ultrasonic NDT. The algorithm reconstructs images from A-scan signals acquired by an ultrasonic imaging system with a monostatic transducer in pulse-echo configuration. It is based on regularized least squares using a l1 regularization norm. The method is tested to reconstruct an image of a point-like reflector, using both simulated and real data. The resolution of reconstructed image is compared with four traditional ultrasonic imaging reconstruction algorithms: B-scan, SAFT, ω-k SAFT and regularized least squares (RLS). The method demonstrates significant resolution improvement when compared with B-scan-about 91% using real data. The proposed scheme also outperforms traditional algorithms in terms of signal-to-noise ratio (SNR). PMID:25905700
A Sparse Reconstruction Algorithm for Ultrasonic Images in Nondestructive Testing
Guarneri, Giovanni Alfredo; Pipa, Daniel Rodrigues; Junior, Flávio Neves; de Arruda, Lúcia Valéria Ramos; Zibetti, Marcelo Victor Wüst
2015-01-01
Ultrasound imaging systems (UIS) are essential tools in nondestructive testing (NDT). In general, the quality of images depends on two factors: system hardware features and image reconstruction algorithms. This paper presents a new image reconstruction algorithm for ultrasonic NDT. The algorithm reconstructs images from A-scan signals acquired by an ultrasonic imaging system with a monostatic transducer in pulse-echo configuration. It is based on regularized least squares using a l1 regularization norm. The method is tested to reconstruct an image of a point-like reflector, using both simulated and real data. The resolution of reconstructed image is compared with four traditional ultrasonic imaging reconstruction algorithms: B-scan, SAFT, ω-k SAFT and regularized least squares (RLS). The method demonstrates significant resolution improvement when compared with B-scan—about 91% using real data. The proposed scheme also outperforms traditional algorithms in terms of signal-to-noise ratio (SNR). PMID:25905700
Visser, R; Godart, J; Wauben, D J L; Langendijk, J A; Van't Veld, A A; Korevaar, E W
2016-05-21
The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a detector model and an optimizer. Expected detector response was calculated using a radiotherapy treatment plan in combination with the fluence model and detector model. MLC leaf positions were reconstructed by minimizing differences between expected and measured detector response. The iterative reconstruction method was evaluated for an Elekta SLi with 10.0 mm MLC leafs in combination with the COMPASS system and the MatriXX Evolution (IBA Dosimetry) detector with a spacing of 7.62 mm. The detector was positioned in such a way that each leaf pair of the MLC was aligned with one row of ionization chambers. Known leaf displacements were introduced in various field geometries ranging from -10.0 mm to 10.0 mm. Error detection performance was tested for MLC leaf position dependency relative to the detector position, gantry angle dependency, monitor unit dependency, and for ten clinical intensity modulated radiotherapy (IMRT) treatment beams. For one clinical head and neck IMRT treatment beam, influence of the iterative reconstruction method on existing 3D dose reconstruction artifacts was evaluated. The described iterative reconstruction method was capable of individual MLC leaf position reconstruction with millimeter accuracy, independent of the relative detector position within the range of clinically applied MU's for IMRT. Dose reconstruction artifacts in a clinical IMRT treatment beam were considerably reduced as compared to the current dose verification procedure. The iterative reconstruction method allows high accuracy 3D dose verification by including actual MLC leaf positions reconstructed from low resolution 2D measurements. PMID:27100169
NASA Astrophysics Data System (ADS)
Visser, R.; Godart, J.; Wauben, D. J. L.; Langendijk, J. A.; van’t Veld, A. A.; Korevaar, E. W.
2016-05-01
The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a detector model and an optimizer. Expected detector response was calculated using a radiotherapy treatment plan in combination with the fluence model and detector model. MLC leaf positions were reconstructed by minimizing differences between expected and measured detector response. The iterative reconstruction method was evaluated for an Elekta SLi with 10.0 mm MLC leafs in combination with the COMPASS system and the MatriXX Evolution (IBA Dosimetry) detector with a spacing of 7.62 mm. The detector was positioned in such a way that each leaf pair of the MLC was aligned with one row of ionization chambers. Known leaf displacements were introduced in various field geometries ranging from ‑10.0 mm to 10.0 mm. Error detection performance was tested for MLC leaf position dependency relative to the detector position, gantry angle dependency, monitor unit dependency, and for ten clinical intensity modulated radiotherapy (IMRT) treatment beams. For one clinical head and neck IMRT treatment beam, influence of the iterative reconstruction method on existing 3D dose reconstruction artifacts was evaluated. The described iterative reconstruction method was capable of individual MLC leaf position reconstruction with millimeter accuracy, independent of the relative detector position within the range of clinically applied MU’s for IMRT. Dose reconstruction artifacts in a clinical IMRT treatment beam were considerably reduced as compared to the current dose verification procedure. The iterative reconstruction method allows high accuracy 3D dose verification by including actual MLC leaf positions reconstructed from low resolution 2D measurements.
Web-based interactive 2D/3D medical image processing and visualization software.
Mahmoudi, Seyyed Ehsan; Akhondi-Asl, Alireza; Rahmani, Roohollah; Faghih-Roohi, Shahrooz; Taimouri, Vahid; Sabouri, Ahmad; Soltanian-Zadeh, Hamid
2010-05-01
There are many medical image processing software tools available for research and diagnosis purposes. However, most of these tools are available only as local applications. This limits the accessibility of the software to a specific machine, and thus the data and processing power of that application are not available to other workstations. Further, there are operating system and processing power limitations which prevent such applications from running on every type of workstation. By developing web-based tools, it is possible for users to access the medical image processing functionalities wherever the internet is available. In this paper, we introduce a pure web-based, interactive, extendable, 2D and 3D medical image processing and visualization application that requires no client installation. Our software uses a four-layered design consisting of an algorithm layer, web-user-interface layer, server communication layer, and wrapper layer. To compete with extendibility of the current local medical image processing software, each layer is highly independent of other layers. A wide range of medical image preprocessing, registration, and segmentation methods are implemented using open source libraries. Desktop-like user interaction is provided by using AJAX technology in the web-user-interface. For the visualization functionality of the software, the VRML standard is used to provide 3D features over the web. Integration of these technologies has allowed implementation of our purely web-based software with high functionality without requiring powerful computational resources in the client side. The user-interface is designed such that the users can select appropriate parameters for practical research and clinical studies. PMID:20022133
Absorption and Scattering 2D Volcano Images from Numerically Calculated Space-weighting functions
NASA Astrophysics Data System (ADS)
Del Pezzo, Edoardo; Ibañez, Jesus; Prudencio, Janire; Bianco, Francesca; De Siena, Luca
2016-04-01
Short period small magnitude seismograms mainly comprise scattered waves in the form of coda waves (the tail part of the seismogram, starting after S-waves and ending when the noise prevails), spanning more than 70% of the whole seismogram duration. Corresponding coda envelopes provide important information about the earth inhomogeneity, which can be stochastically modeled in terms of distribution of scatterers in a random medium. In suitable experimental conditions (i.e. high earth heterogeneity) either the two parameters describing heterogeneity (scattering coefficient), intrinsic energy dissipation (coefficient of intrinsic attenuation) or a combination of them (extinction length and seismic albedo) can be used to image Earth structures. Once a set of such parameter couples has been measured in a given area and for a number of sources and receivers, imaging their space distribution with standard methods is straightforward. However, as for finite-frequency and full-waveform tomography, the essential problem for a correct imaging is the determination of the weighting function describing the spatial sensitivity of observable data to scattering and absorption anomalies. Due to the nature of coda waves, the measured parameter-couple can be seen as a weighted space average of the real parameters characterizing the rock volumes illuminated by the scattered waves. This paper uses the Monte Carlo numerical solution of the Energy Transport Equation to find approximate but realistic 2D space-weighting functions for coda waves. Separate images for scattering and absorption based on these sensitivity functions are then compared with those obtained with commonly-used sensitivity functions in an application to data from an active seismic experiment carried out at Deception Island (Antarctica). Results show the that these novel functions are based on a reliable and physically grounded method to image magnitude and shape of scattering and absorption anomalies. Their extension to
Absorption and scattering 2-D volcano images from numerically calculated space-weighting functions
NASA Astrophysics Data System (ADS)
Del Pezzo, Edoardo; Ibañez, Jesus; Prudencio, Janire; Bianco, Francesca; De Siena, Luca
2016-08-01
Short-period small magnitude seismograms mainly comprise scattered waves in the form of coda waves (the tail part of the seismogram, starting after S waves and ending when the noise prevails), spanning more than 70 per cent of the whole seismogram duration. Corresponding coda envelopes provide important information about the earth inhomogeneity, which can be stochastically modeled in terms of distribution of scatterers in a random medium. In suitable experimental conditions (i.e. high earth heterogeneity), either the two parameters describing heterogeneity (scattering coefficient), intrinsic energy dissipation (coefficient of intrinsic attenuation) or a combination of them (extinction length and seismic albedo) can be used to image Earth structures. Once a set of such parameter couples has been measured in a given area and for a number of sources and receivers, imaging their space distribution with standard methods is straightforward. However, as for finite-frequency and full-waveform tomography, the essential problem for a correct imaging is the determination of the weighting function describing the spatial sensitivity of observable data to scattering and absorption anomalies. Due to the nature of coda waves, the measured parameter couple can be seen as a weighted space average of the real parameters characterizing the rock volumes illuminated by the scattered waves. This paper uses the Monte Carlo numerical solution of the Energy Transport Equation to find approximate but realistic 2-D space-weighting functions for coda waves. Separate images for scattering and absorption based on these sensitivity functions are then compared with those obtained with commonly used sensitivity functions in an application to data from an active seismic experiment carried out at Deception Island (Antarctica). Results show that these novel functions are based on a reliable and physically grounded method to image magnitude and shape of scattering and absorption anomalies. Their
2-D traveltime and waveform inversion for improved seismic imaging: Naga Thrust and Fold Belt, India
NASA Astrophysics Data System (ADS)
Jaiswal, Priyank; Zelt, Colin A.; Bally, Albert W.; Dasgupta, Rahul
2008-05-01
Exploration along the Naga Thrust and Fold Belt in the Assam province of Northeast India encounters geological as well as logistic challenges. Drilling for hydrocarbons, traditionally guided by surface manifestations of the Naga thrust fault, faces additional challenges in the northeast where the thrust fault gradually deepens leaving subtle surface expressions. In such an area, multichannel 2-D seismic data were collected along a line perpendicular to the trend of the thrust belt. The data have a moderate signal-to-noise ratio and suffer from ground roll and other acquisition-related noise. In addition to data quality, the complex geology of the thrust belt limits the ability of conventional seismic processing to yield a reliable velocity model which in turn leads to poor subsurface image. In this paper, we demonstrate the application of traveltime and waveform inversion as supplements to conventional seismic imaging and interpretation processes. Both traveltime and waveform inversion utilize the first arrivals that are typically discarded during conventional seismic processing. As a first step, a smooth velocity model with long wavelength characteristics of the subsurface is estimated through inversion of the first-arrival traveltimes. This velocity model is then used to obtain a Kirchhoff pre-stack depth-migrated image which in turn is used for the interpretation of the fault. Waveform inversion is applied to the central part of the seismic line to a depth of ~1 km where the quality of the migrated image is poor. Waveform inversion is performed in the frequency domain over a series of iterations, proceeding from low to high frequency (11-19 Hz) using the velocity model from traveltime inversion as the starting model. In the end, the pre-stack depth-migrated image and the waveform inversion model are jointly interpreted. This study demonstrates that a combination of traveltime and waveform inversion with Kirchhoff pre-stack depth migration is a promising approach
Voxel-based 2-D/3-D registration of fluoroscopy images and CT scans for image-guided surgery.
Weese, J; Penney, G P; Desmedt, P; Buzug, T M; Hill, D L; Hawkes, D J
1997-12-01
Registration of intraoperative fluoroscopy images with preoperative three-dimensional (3-D) CT images can be used for several purposes in image-guided surgery. On the one hand, it can be used to display the position of surgical instruments, which are being tracked by a localizer, in the preoperative CT scan. On the other hand, the registration result can be used to project preoperative planning information or important anatomical structures visible in the CT image onto the fluoroscopy image. For this registration task, a novel voxel-based method in combination with a new similarity measure (pattern intensity) has been developed. The basic concept of the method is explained at the example of two-dimensional (2-D)/3-D registration of a vertebra in an X-ray fluoroscopy image with a 3-D CT image. The registration method is described, and the results for a spine phantom are presented and discussed. Registration has been carried out repeatedly with different starting estimates to study the capture range. Information about registration accuracy has been obtained by comparing the registration results with a highly accurate "ground-truth" registration, which has been derived from fiducial markers attached to the phantom prior to imaging. In addition, registration results for different vertebrae have been compared. The results show that the rotation parameters and the shifts parallel to the projection plane can accurately be determined from a single projection. Because of the projection geometry, the accuracy of the height above the projection plane is significantly lower. PMID:11020832
NASA Astrophysics Data System (ADS)
Okawa, Shinpei; Hirasawa, Takeshi; Kushibiki, Toshihiro; Ishihara, Miya
2015-03-01
Quantification of the optical properties of the tissues and blood by noninvasive photoacoustic (PA) imaging may provide useful information for screening and early diagnosis of diseases. Linearized 2D image reconstruction algorithm based on PA wave equation and the photon diffusion equation (PDE) can reconstruct the image with computational cost smaller than a method based on 3D radiative transfer equation. However, the reconstructed image is affected by the differences between the actual and assumed light propagations. A quantitative capability of a linearized 2D image reconstruction was investigated and discussed by the numerical simulations and the phantom experiment in this study. The numerical simulations with the 3D Monte Carlo (MC) simulation and the 2D finite element calculation of the PDE were carried out. The phantom experiment was also conducted. In the phantom experiment, the PA pressures were acquired by a probe which had an optical fiber for illumination and the ring shaped P(VDF-TrFE) ultrasound transducer. The measured object was made of Intralipid and Indocyanine green. In the numerical simulations, it was shown that the linearized image reconstruction method recovered the absorption coefficients with alleviating the dependency of the PA amplitude on the depth of the photon absorber. The linearized image reconstruction method worked effectively under the light propagation calculated by 3D MC simulation, although some errors occurred. The phantom experiments validated the result of the numerical simulations.
Schwerter, Michael; Lietzmann, Florian; Schad, Lothar R
2016-09-01
Minimally invasive interventions are frequently aided by 2D projective image guidance. To facilitate the navigation of medical tools within the patient, information from preoperative 3D images can supplement interventional data. This work describes a novel approach to perform a 3D CT data registration to a single interventional native fluoroscopic frame. The goal of this procedure is to recover and visualize a current 2D interventional tool position in its corresponding 3D dataset. A dedicated routine was developed and tested on a phantom. The 3D position of a guidewire inserted into the phantom could successfully be reconstructed for varying 2D image acquisition geometries. The scope of the routine includes projecting the CT data into the plane of the fluoroscopy. A subsequent registration of the real and virtual projections is performed with an accuracy within the range of 1.16±0.17mm for fixed landmarks. The interventional tool is extracted from the fluoroscopy and matched to the corresponding part of the projected and transformed arterial vasculature. A root mean square error of up to 0.56mm for matched point pairs is reached. The desired 3D view is provided by backprojecting the matched guidewire through the CT array. Due to its potential to reduce patient dose and treatment times, the proposed routine has the capability of reducing patient stress at lower overall treatment costs. PMID:27157275
Mu, Zhiping; Hong, Baoming; Li, Shimin; Liu, Yi-Hwa
2009-01-01
Coded aperture imaging for two-dimensional (2D) planar objects has been investigated extensively in the past, whereas little success has been achieved in imaging 3D objects using this technique. In this article, the authors present a novel method of 3D single photon emission computerized tomography (SPECT) reconstruction for near-field coded aperture imaging. Multiangular coded aperture projections are acquired and a stack of 2D images is reconstructed separately from each of the projections. Secondary projections are subsequently generated from the reconstructed image stacks based on the geometry of parallel-hole collimation and the variable magnification of near-field coded aperture imaging. Sinograms of cross-sectional slices of 3D objects are assembled from the secondary projections, and the ordered subset expectation and maximization algorithm is employed to reconstruct the cross-sectional image slices from the sinograms. Experiments were conducted using a customized capillary tube phantom and a micro hot rod phantom. Imaged at approximately 50 cm from the detector, hot rods in the phantom with diameters as small as 2.4 mm could be discerned in the reconstructed SPECT images. These results have demonstrated the feasibility of the authors’ 3D coded aperture image reconstruction algorithm for SPECT, representing an important step in their effort to develop a high sensitivity and high resolution SPECT imaging system. PMID:19544769
On the assimilation of flood extension images into 2D shallow-water models
NASA Astrophysics Data System (ADS)
Monnier, J.; Couderc, F.; Dartus, D.; Madec, R.; Vila, J.
2012-12-01
In river hydraulics, assimilation of water level measurements at gauging stations is well controlled, while assimilation of images (e.g. from satellite) is still delicate. In the present talk, we address the richness of satellite information to constraint a 2D shallow-water model, and present also related difficulties. A preliminary study done on Mosel river is presented in [LaMo] [HoLaMoPu]. On selected parts of the image, an 0th order model flow allows to obtain some reliable water levels with quantified uncertainties (C. Puech et al.). Next, variationnal sensitivities (based on a gradient computation and adjoint equations) reveal some difficulties that a model designer have to tackle (e.g. roughness parameters at open boundaries), and allow to better understand both the model and the flow. Next, a variational data assimilation algorithm (4D-var) shows that such data lead to a better calibration of the model (e.g. roughness coefficients) and potentially allows to identify the incoming and/or outgoing flow at open boundaries, [LaMo] [HoLaMoPu]. On the other side, the flood dynamic extension is difficult to represent accurately using a 2D SW model since the wet-dry front dynamics is difficult to compute. We compare some 2nd order finite volume solvers and obtain an accurate and stable scheme at wet-dry front. Then, we present some basic rules of compatibility between data and mesh resolution in order to be reliable enough to constraint the model with flood extension data, [CoMaMoViDa]. All the algorithms are implemented into DassFlow software (Fortran, MPI, adjoint) [Da]. [CoMaMoViDa] F. Couderc, R. Madec, J. Monnier, J.-P. Vila, D. Dartus. "Sensitivity analysis and variational data assimilation for geophysical shallow water flows". Submitted. [Da] DassFlow - Data Assimilation for Free Surface Flows. Open-source computational software http://www-gmm.insa-toulouse.fr/~monnier/DassFlow/ [HoLaMoPu] R. Hostache, X. Lai, J. Monnier, C. Puech. "Assimilation of spatial
Coronary arteries motion modeling on 2D x-ray images
NASA Astrophysics Data System (ADS)
Gao, Yang; Sundar, Hari
2012-02-01
During interventional procedures, 3D imaging modalities like CT and MRI are not commonly used due to interference with the surgery and radiation exposure concerns. Therefore, real-time information is usually limited and building models of cardiac motion are difficult. In such case, vessel motion modeling based on 2-D angiography images become indispensable. Due to issues with existing vessel segmentation algorithms and the lack of contrast in occluded vessels, manual segmentation of certain branches is usually necessary. In addition, such occluded branches are the most important vessels during coronary interventions and obtaining motion models for these can greatly help in reducing the procedure time and radiation exposure. Segmenting different cardiac phases independently does not guarantee temporal consistency and is not efficient for occluded branches required manual segmentation. In this paper, we propose a coronary motion modeling system which extracts the coronary tree for every cardiac phase, maintaining the segmentation by tracking the coronary tree during the cardiac cycle. It is able to map every frame to the specific cardiac phase, thereby inferring the shape information of the coronary arteries using the model corresponding to its phase. Our experiments show that our motion modeling system can achieve promising results with real-time performance.
2D metamaterials with hexagonal structure: spatial resonances and near field imaging.
Zhuromskyy, O; Shamonina, E; Solymar, L
2005-11-14
The current and field distribution in a 2D metamaterial consisting of resonant elements in a hexagonal arrangement are found assuming magnetic interaction between the elements. The dispersion equation of magnetoinductive (MI) waves is derived with the aid of the direct and reciprocal lattice familiar from solid state theory. A continuous model for the current variation in the elements is introduced leading to the familiar wave equation in the form of a second order differential equation. The current distributions are shown to exhibit a series of spatial resonances for rectangular, circular and hexagonal boundaries. The axial and radial components of the resulting magnetic field are compared with previously obtained experimental results on a Swiss Roll metamaterial with hexagonal boundaries. Experimental and theoretical results are also compared for the near field image of an object in the shape of the letter M followed by a more general discussion of imaging. It is concluded that a theoretical formulation based on the propagation of MI waves can correctly describe the experimental results. PMID:19503131
Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography
Yang, Xiaofeng; Torres, Mylin; Kirkpatrick, Stephanie; Curran, Walter J.; Liu, Tian
2015-01-01
In this paper, we present a new approach to calculate 2D strain through the registration of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid registration algorithm (INRA). Compared with the most commonly used cross-correlation (CC) method, our approach is not constrained to any particular set of directions, and can overcome displacement estimation errors introduced by incoherent motion and variations in the signal under high compression. This INRA method was tested using phantom and in vivo data. The robustness of our approach was demonstrated in the axial direction as well as the lateral direction where the standard CC method frequently fails. In addition, our approach copes well under large compression (over 6%). In the phantom study, we computed the strain image under various compressions and calculated the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. The SNR and CNS values of the INRA method were much higher than those calculated from the CC-based method. Furthermore, the clinical feasibility of our approach was demonstrated with the in vivo data from patients with arm lymphedema. PMID:25914492
Ultrasound 2D strain estimator based on image registration for ultrasound elastography
NASA Astrophysics Data System (ADS)
Yang, Xiaofeng; Torres, Mylin; Kirkpatrick, Stephanie; Curran, Walter J.; Liu, Tian
2014-03-01
In this paper, we present a new approach to calculate 2D strain through the registration of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid registration algorithm (INRA). Compared with the most commonly used cross-correlation (CC) method, our approach is not constrained to any particular set of directions, and can overcome displacement estimation errors introduced by incoherent motion and variations in the signal under high compression. This INRA method was tested using phantom and in vivo data. The robustness of our approach was demonstrated in the axial direction as well as the lateral direction where the standard CC method frequently fails. In addition, our approach copes well under large compression (over 6%). In the phantom study, we computed the strain image under various compressions and calculated the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. The SNR and CNS values of the INRA method were much higher than those calculated from the CC-based method. Furthermore, the clinical feasibility of our approach was demonstrated with the in vivo data from patients with arm lymphedema.
Analysis of 2-d ultrasound cardiac strain imaging using joint probability density functions.
Ma, Chi; Varghese, Tomy
2014-06-01
Ultrasound frame rates play a key role for accurate cardiac deformation tracking. Insufficient frame rates lead to an increase in signal de-correlation artifacts resulting in erroneous displacement and strain estimation. Joint probability density distributions generated from estimated axial strain and its associated signal-to-noise ratio provide a useful approach to assess the minimum frame rate requirements. Previous reports have demonstrated that bi-modal distributions in the joint probability density indicate inaccurate strain estimation over a cardiac cycle. In this study, we utilize similar analysis to evaluate a 2-D multi-level displacement tracking and strain estimation algorithm for cardiac strain imaging. The effect of different frame rates, final kernel dimensions and a comparison of radio frequency and envelope based processing are evaluated using echo signals derived from a 3-D finite element cardiac model and five healthy volunteers. Cardiac simulation model analysis demonstrates that the minimum frame rates required to obtain accurate joint probability distributions for the signal-to-noise ratio and strain, for a final kernel dimension of 1 λ by 3 A-lines, was around 42 Hz for radio frequency signals. On the other hand, even a frame rate of 250 Hz with envelope signals did not replicate the ideal joint probability distribution. For the volunteer study, clinical data was acquired only at a 34 Hz frame rate, which appears to be sufficient for radio frequency analysis. We also show that an increase in the final kernel dimensions significantly affect the strain probability distribution and joint probability density function generated, with a smaller effect on the variation in the accumulated mean strain estimated over a cardiac cycle. Our results demonstrate that radio frequency frame rates currently achievable on clinical cardiac ultrasound systems are sufficient for accurate analysis of the strain probability distribution, when a multi-level 2-D
Wan, Yong; Otsuna, Hideo; Chien, Chi-Bin; Hansen, Charles
2013-01-01
2D image space methods are processing methods applied after the volumetric data are projected and rendered into the 2D image space, such as 2D filtering, tone mapping and compositing. In the application domain of volume visualization, most 2D image space methods can be carried out more efficiently than their 3D counterparts. Most importantly, 2D image space methods can be used to enhance volume visualization quality when applied together with volume rendering methods. In this paper, we present and discuss the applications of a series of 2D image space methods as enhancements to confocal microscopy visualizations, including 2D tone mapping, 2D compositing, and 2D color mapping. These methods are easily integrated with our existing confocal visualization tool, FluoRender, and the outcome is a full-featured visualization system that meets neurobiologists’ demands for qualitative analysis of confocal microscopy data. PMID:23584131
Bayesian Image Reconstruction in Quantitative Photoacoustic Tomography.
Tarvainen, Tanja; Pulkkinen, Aki; Cox, Ben; Kaipio, Jari; Arridge, Simon
2013-08-30
Quantitative photoacoustic tomography is an emerging imaging technique aimed at estimating chromophore concentrations inside tissues from photoacoustic images, which are formed by combining optical information and ultrasonic propagation. This is a hybrid imaging problem in which the solution of one inverse problem acts as the data for another ill-posed inverse problem. In the optical reconstruction of quantitative photoacoustic tomography, the data is obtained as a solution of an acoustic inverse initial value problem. Thus, both the data and the noise are affected by the method applied to solve the acoustic inverse problem. In this paper, the noise of optical data is modelled as Gaussian distributed with mean and covariance approximated by solving several acoustic inverse initial value problems using acoustic noise samples as data. Furthermore, Bayesian approximation error modelling is applied to compensate for the modelling errors in the optical data caused by the acoustic solver. The results show that modelling of the noise statistics and the approximation errors can improve the optical reconstructions. PMID:24001987
Wavelet-based stereo images reconstruction using depth images
NASA Astrophysics Data System (ADS)
Jovanov, Ljubomir; Pižurica, Aleksandra; Philips, Wilfried
2007-09-01
It is believed by many that three-dimensional (3D) television will be the next logical development toward a more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a single stream of monoscopic images and a second stream of associated images usually termed depth images or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that contains information about distance from camera to a certain point of the object as a function of the image coordinates. By using this depth information and the original image it is possible to reconstruct a virtual image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space and finding their position in the desired view plane. One of the most significant advantages of the DIBR is that depth maps can be coded more efficiently than two streams corresponding to left and right view of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse existing transmission channels for the transmission of 3D TV. This technique can also be applied for other 3D technologies such as multimedia systems. In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic images, which solves some of the shortcommings of the existing methods discussed above. We perform the wavelet transform of both the luminance and depth images in order to obtain significant geometric features, which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach uses Markov random field smoothness prior for regularization of the estimated motion field. The evaluation of the proposed reconstruction method is done on two video sequences which are typically used for comparison of stereo reconstruction algorithms. The results demonstrate
Near-infrared optical imaging of human brain based on the semi-3D reconstruction algorithm
NASA Astrophysics Data System (ADS)
Liu, Ming; Meng, Wei; Qin, Zhuanping; Zhou, Xiaoqing; Zhao, Huijuan; Gao, Feng
2013-03-01
In the non-invasive brain imaging with near-infrared light, precise head model is of great significance to the forward model and the image reconstruction. To deal with the individual difference of human head tissues and the problem of the irregular curvature, in this paper, we extracted head structure with Mimics software from the MRI image of a volunteer. This scheme makes it possible to assign the optical parameters to every layer of the head tissues reasonably and solve the diffusion equation with the finite-element analysis. During the solution of the inverse problem, a semi-3D reconstruction algorithm is adopted to trade off the computation cost and accuracy between the full 3-D and the 2-D reconstructions. In this scheme, the changes in the optical properties of the inclusions are assumed either axially invariable or confined to the imaging plane, while the 3-D nature of the photon migration is still retained. This therefore leads to a 2-D inverse issue with the matched 3-D forward model. Simulation results show that comparing to the 3-D reconstruction algorithm, the Semi-3D reconstruction algorithm cut 27% the calculation time consumption.
Multiscale likelihood analysis and image reconstruction
NASA Astrophysics Data System (ADS)
Willett, Rebecca M.; Nowak, Robert D.
2003-11-01
The nonparametric multiscale polynomial and platelet methods presented here are powerful new tools for signal and image denoising and reconstruction. Unlike traditional wavelet-based multiscale methods, these methods are both well suited to processing Poisson or multinomial data and capable of preserving image edges. At the heart of these new methods lie multiscale signal decompositions based on polynomials in one dimension and multiscale image decompositions based on what the authors call platelets in two dimensions. Platelets are localized functions at various positions, scales and orientations that can produce highly accurate, piecewise linear approximations to images consisting of smooth regions separated by smooth boundaries. Polynomial and platelet-based maximum penalized likelihood methods for signal and image analysis are both tractable and computationally efficient. Polynomial methods offer near minimax convergence rates for broad classes of functions including Besov spaces. Upper bounds on the estimation error are derived using an information-theoretic risk bound based on squared Hellinger loss. Simulations establish the practical effectiveness of these methods in applications such as density estimation, medical imaging, and astronomy.
Pulsed holography for combustion diagnostics. [image reconstruction
NASA Technical Reports Server (NTRS)
Klein, N.; Dewilde, M. A.
1980-01-01
Image reconstruction and data extraction techniques were considered with respect to their application to combustion diagnostics. A system was designed and constructed that possesses sufficient stability and resolution to make quantitative data extraction possible. Example data were manually processed using the system to demonstrate its feasibility for the purpose intended. The system was interfaced with the PDP-11-04 computer for maximum design capability. It was concluded that the use of specialized digital hardware controlled by a relatively small computer provides the best combination of accuracy, speed, and versatility for this particular problem area.
Reproducing 2D breast mammography images with 3D printed phantoms
NASA Astrophysics Data System (ADS)
Clark, Matthew; Ghammraoui, Bahaa; Badal, Andreu
2016-03-01
Mammography is currently the standard imaging modality used to screen women for breast abnormalities and, as a result, it is a tool of great importance for the early detection of breast cancer. Physical phantoms are commonly used as surrogates of breast tissue to evaluate some aspects of the performance of mammography systems. However, most phantoms do not reproduce the anatomic heterogeneity of real breasts. New fabrication technologies, such as 3D printing, have created the opportunity to build more complex, anatomically realistic breast phantoms that could potentially assist in the evaluation of mammography systems. The primary objective of this work is to present a simple, easily reproducible methodology to design and print 3D objects that replicate the attenuation profile observed in real 2D mammograms. The secondary objective is to evaluate the capabilities and limitations of the competing 3D printing technologies, and characterize the x-ray properties of the different materials they use. Printable phantoms can be created using the open-source code introduced in this work, which processes a raw mammography image to estimate the amount of x-ray attenuation at each pixel, and outputs a triangle mesh object that encodes the observed attenuation map. The conversion from the observed pixel gray value to a column of printed material with equivalent attenuation requires certain assumptions and knowledge of multiple imaging system parameters, such as x-ray energy spectrum, source-to-object distance, compressed breast thickness, and average breast material attenuation. A detailed description of the new software, a characterization of the printed materials using x-ray spectroscopy, and an evaluation of the realism of the sample printed phantoms are presented.
Regularized image reconstruction for continuously self-imaging gratings.
Horisaki, Ryoichi; Piponnier, Martin; Druart, Guillaume; Guérineau, Nicolas; Primot, Jérôme; Goudail, François; Taboury, Jean; Tanida, Jun
2013-06-01
In this paper, we demonstrate two image reconstruction schemes for continuously self-imaging gratings (CSIGs). CSIGs are diffractive optical elements that generate a depth-invariant propagation pattern and sample objects with a sparse spatial frequency spectrum. To compensate for the sparse sampling, we apply two methods with different regularizations for CSIG imaging. The first method employs continuity of the spatial frequency spectrum, and the second one uses sparsity of the intensity pattern. The two methods are demonstrated with simulations and experiments. PMID:23736336
NASA Astrophysics Data System (ADS)
Ouadah, S.; Stayman, J. W.; Gang, G.; Uneri, A.; Ehtiati, T.; Siewerdsen, J. H.
2015-03-01
Purpose: Robotic C-arm systems are capable of general noncircular orbits whose trajectories can be driven by the particular imaging task. However obtaining accurate calibrations for reconstruction in such geometries can be a challenging problem. This work proposes a method to perform a unique geometric calibration of an arbitrary C-arm orbit by registering 2D projections to a previously acquired 3D image to determine the transformation parameters representing the system geometry. Methods: Experiments involved a cone-beam CT (CBCT) bench system, a robotic C-arm, and three phantoms. A robust 3D-2D registration process was used to compute the 9 degree of freedom (DOF) transformation between each projection and an existing 3D image by maximizing normalized gradient information with a digitally reconstructed radiograph (DRR) of the 3D volume. The quality of the resulting "self-calibration" was evaluated in terms of the agreement with an established calibration method using a BB phantom as well as image quality in the resulting CBCT reconstruction. Results: The self-calibration yielded CBCT images without significant difference in spatial resolution from the standard ("true") calibration methods (p-value >0.05 for all three phantoms), and the differences between CBCT images reconstructed using the "self" and "true" calibration methods were on the order of 10-3 mm-1. Maximum error in magnification was 3.2%, and back-projection ray placement was within 0.5 mm. Conclusion: The proposed geometric "self" calibration provides a means for 3D imaging on general noncircular orbits in CBCT systems for which a geometric calibration is either not available or not reproducible. The method forms the basis of advanced "task-based" 3D imaging methods now in development for robotic C-arms.
Prior image constrained image reconstruction in emerging computed tomography applications
NASA Astrophysics Data System (ADS)
Brunner, Stephen T.
Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation
Venters, Ronald A; Coggins, Brian E; Kojetin, Doug; Cavanagh, John; Zhou, Pei
2005-06-22
Projection-reconstruction NMR experiments have been shown to significantly reduce the acquisition time required to obtain protein backbone assignment data. To date, this concept has only been applied to smaller (15)N/(13)C-labeled proteins. Here, we show that projection-reconstruction NMR techniques can be extended to larger protonated and perdeuterated proteins. We present a suite of (4,2)D triple-resonance experiments for protein backbone assignment and a Hybrid Backprojection/Lower-Value algorithm for reconstructing data with relatively weak signal-to-noise ratios. In addition, we propose a sampling theorem and discuss its implication on the choice of projection angles. We demonstrate the efficacy of this approach using the 29 kDa protein, human carbonic anhydrase II and the 30 kDa protein, calbindin D(28K). PMID:15954785
Nagayama, T.; Mancini, R. C.; Mayes, D.; Tommasini, R.; Florido, R.
2015-11-15
Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ∼6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ∼10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application.
Nagayama, T; Mancini, R C; Mayes, D; Tommasini, R; Florido, R
2015-11-01
Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ∼6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ∼10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application. PMID:26628133
NASA Astrophysics Data System (ADS)
Nagayama, T.; Mancini, R. C.; Mayes, D.; Tommasini, R.; Florido, R.
2015-11-01
Temperature and density asymmetry diagnosis is critical to advance inertial confinement fusion (ICF) science. A multi-monochromatic x-ray imager (MMI) is an attractive diagnostic for this purpose. The MMI records the spectral signature from an ICF implosion core with time resolution, 2-D space resolution, and spectral resolution. While narrow-band images and 2-D space-resolved spectra from the MMI data constrain temperature and density spatial structure of the core, the accuracy of the images and spectra depends not only on the quality of the MMI data but also on the reliability of the post-processing tools. Here, we synthetically quantify the accuracy of images and spectra reconstructed from MMI data. Errors in the reconstructed images are less than a few percent when the space-resolution effect is applied to the modeled images. The errors in the reconstructed 2-D space-resolved spectra are also less than a few percent except those for the peripheral regions. Spectra reconstructed for the peripheral regions have slightly but systematically lower intensities by ˜6% due to the instrumental spatial-resolution effects. However, this does not alter the relative line ratios and widths and thus does not affect the temperature and density diagnostics. We also investigate the impact of the pinhole size variation on the extracted images and spectra. A 10% pinhole size variation could introduce spatial bias to the images and spectra of ˜10%. A correction algorithm is developed, and it successfully reduces the errors to a few percent. It is desirable to perform similar synthetic investigations to fully understand the reliability and limitations of each MMI application.
Moriguchi, H; Wendt, M; Duerk, J L
2000-11-01
Various kinds of nonrectilinear Cartesian k-space trajectories have been studied, such as spiral, circular, and rosette trajectories. Although the nonrectilinear Cartesian sampling techniques generally have the advantage of fast data acquisition, the gridding process prior to 2D-FFT image reconstruction usually requires a number of additional calculations, thus necessitating an increase in the computation time. Further, the reconstructed image often exhibits artifacts resulting from both the k-space sampling pattern and the gridding procedure. To date, it has been demonstrated in only a few studies that the special geometric sampling patterns of certain specific trajectories facilitate fast image reconstruction. In other words, the inherent link among the trajectory, the sampling scheme, and the associated complexity of the regridding/reconstruction process has been investigated to only a limited extent. In this study, it is demonstrated that a Lissajous trajectory has the special geometric characteristics necessary for rapid reconstruction of nonrectilinear Cartesian k-space trajectories with constant sampling time intervals. Because of the applicability of a uniform resampling (URS) algorithm, a high-quality reconstructed image is obtained in a short reconstruction time when compared to other gridding algorithms. PMID:11064412
Optimized Quasi-Interpolators for Image Reconstruction.
Sacht, Leonardo; Nehab, Diego
2015-12-01
We propose new quasi-interpolators for the continuous reconstruction of sampled images, combining a narrowly supported piecewise-polynomial kernel and an efficient digital filter. In other words, our quasi-interpolators fit within the generalized sampling framework and are straightforward to use. We go against standard practice and optimize for approximation quality over the entire Nyquist range, rather than focusing exclusively on the asymptotic behavior as the sample spacing goes to zero. In contrast to previous work, we jointly optimize with respect to all degrees of freedom available in both the kernel and the digital filter. We consider linear, quadratic, and cubic schemes, offering different tradeoffs between quality and computational cost. Experiments with compounded rotations and translations over a range of input images confirm that, due to the additional degrees of freedom and the more realistic objective function, our new quasi-interpolators perform better than the state of the art, at a similar computational cost. PMID:26390452
Determining ice water content from 2D crystal images in convective cloud systems
NASA Astrophysics Data System (ADS)
Leroy, Delphine; Coutris, Pierre; Fontaine, Emmanuel; Schwarzenboeck, Alfons; Strapp, J. Walter
2016-04-01
Cloud microphysical in-situ instrumentation measures bulk parameters like total water content (TWC) and/or derives particle size distributions (PSD) (utilizing optical spectrometers and optical array probes (OAP)). The goal of this work is to introduce a comprehensive methodology to compute TWC from OAP measurements, based on the dataset collected during recent HAIC (High Altitude Ice Crystals)/HIWC (High Ice Water Content) field campaigns. Indeed, the HAIC/HIWC field campaigns in Darwin (2014) and Cayenne (2015) provide a unique opportunity to explore the complex relationship between cloud particle mass and size in ice crystal environments. Numerous mesoscale convective systems (MCSs) were sampled with the French Falcon 20 research aircraft at different temperature levels from -10°C up to 50°C. The aircraft instrumentation included an IKP-2 (isokinetic probe) to get reliable measurements of TWC and the optical array probes 2D-S and PIP recording images over the entire ice crystal size range. Based on the known principle relating crystal mass and size with a power law (m=α•Dβ), Fontaine et al. (2014) performed extended 3D crystal simulations and thereby demonstrated that it is possible to estimate the value of the exponent β from OAP data, by analyzing the surface-size relationship for the 2D images as a function of time. Leroy et al. (2015) proposed an extended version of this method that produces estimates of β from the analysis of both the surface-size and perimeter-size relationships. Knowing the value of β, α then is deduced from the simultaneous IKP-2 TWC measurements for the entire HAIC/HIWC dataset. The statistical analysis of α and β values for the HAIC/HIWC dataset firstly shows that α is closely linked to β and that this link changes with temperature. From these trends, a generalized parameterization for α is proposed. Finally, the comparison with the initial IKP-2 measurements demonstrates that the method is able to predict TWC values
NASA Astrophysics Data System (ADS)
Muller, David
2014-03-01
Even though glasses are almost ubiquitous--in our windows, on our iPhones, even on our faces--they are also mysterious. Because glasses are notoriously difficult to study, basic questions like: ``How are the atoms arranged? Where and how do glasses break?'' are still under contention. We use aberration corrected transmission electron microscopy (TEM) to image the atoms in a new two-dimensional phase of silica glass - freestanding it becomes the world's thinnest pane of glass at only 3-atoms thick, and take a unique look into these questions. Using atom-by-atom imaging and spectroscopy, we are able to reconstruct the full structure and bonding of this 2D glass and identify it as a bi-tetrahedral layer of SiO2. Our images also strikingly resemble Zachariasen's original cartoon models of glasses, drawn in 1932. As such, our work realizes an 80-year-old vision for easily understandable glassy systems and introduces promising methods to test theoretical predictions against experimental data. We image atoms in the disordered solid and track their motions in response to local strain. We directly obtain ring statistics and pair distribution functions that span short-, medium-, and long-range order, and test these against long-standing theoretical predictions of glass structure and dynamics. We use the electron beam to excite atomic rearrangements, producing surprisingly rich and beautiful videos of how a glass bends and breaks, as well as the exchange of atoms at a solid/liquid interface. Detailed analyses of these videos reveal a complex dance of elastic and plastic deformations, phase transitions, and their interplay. These examples illustrate the wide-ranging and fundamental materials physics that can now be studied at atomic-resolution via transmission electron microscopy of two-dimensional glasses. Work in collaboration with: S. Kurasch, U. Kaiser, R. Hovden, Q. Mao, J. Kotakoski, J. S. Alden, A. Shekhawat, A. A. Alemi, J. P. Sethna, P. L. McEuen, A.V. Krasheninnikov
NASA Astrophysics Data System (ADS)
Shah, Jainil P.; Mann, Steve D.; McKinley, Randolph L.; Tornai, Martin P.
2014-03-01
The 2D scatter-to-primary (SPR) ratios and 3D voxelized difference volumes were characterized for a cone beam breast CT scanner capable of arbitrary (non-traditional) 3D trajectories. The CT system uses a 30x30cm2 flat panel imager with 197 micron pixellation and a rotating tungsten anode x-ray source with 0.3mm focal spot, with an SID of 70cm. Data were acquired for two cylindrical phantoms (12.5cm and 15cm diameter) filled with three different combinations of water and methanol yielding a range of uniform densities. Projections were acquired with two acquisition trajectories: 1) simple-circular azimuthal orbit with fixed tilt; and 2) saddle orbit following a +/-15° sinusoidal trajectory around the object. Projection data were acquired in 2x2 binned mode. Projections were scatter corrected using a beam stop array method, and the 2D SPR was measured on the projections. The scatter corrected and uncorrected data were then reconstructed individually using an iterative ordered subsets convex algorithm, and the 3D difference volumes were calculated as the absolute difference between the two. Results indicate that the 2D SPR is ~7-15% higher on projections with greatest tilt for the saddle orbit, due to the longer x-ray path length through the volume, compared to the 0° tilt projections. Additionally, the 2D SPR increases with object diameter as well as density. The 3D voxelized difference volumes are an estimate of the scatter contribution to the reconstructed attenuation coefficients on a voxel level. They help visualize minor deficiencies and artifacts in the volumes due to correction methods.
Modulus reconstruction from prostate ultrasound images using finite element modeling
NASA Astrophysics Data System (ADS)
Yan, Zhennan; Zhang, Shaoting; Alam, S. Kaisar; Metaxas, Dimitris N.; Garra, Brian S.; Feleppa, Ernest J.
2012-03-01
In medical diagnosis, use of elastography is becoming increasingly more useful. However, treatments usually assume a planar compression applied to tissue surfaces and measure the deformation. The stress distribution is relatively uniform close to the surface when using a large, flat compressor but it diverges gradually along tissue depth. Generally in prostate elastography, the transrectal probes used for scanning and compression are cylindrical side-fire or rounded end-fire probes, and the force is applied through the rectal wall. These make it very difficult to detect cancer in prostate, since the rounded contact surfaces exaggerate the non-uniformity of the applied stress, especially for the distal, anterior prostate. We have developed a preliminary 2D Finite Element Model (FEM) to simulate prostate deformation in elastography. The model includes a homogeneous prostate with a stiffer tumor in the proximal, posterior region of the gland. A force is applied to the rectal wall to deform the prostate, strain and stress distributions can be computed from the resultant displacements. Then, we assume the displacements as boundary condition and reconstruct the modulus distribution (inverse problem) using linear perturbation method. FEM simulation shows that strain and strain contrast (of the lesion) decrease very rapidly with increasing depth and lateral distance. Therefore, lesions would not be clearly visible if located far away from the probe. However, the reconstructed modulus image can better depict relatively stiff lesion wherever the lesion is located.
Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET
NASA Astrophysics Data System (ADS)
Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E.; Nuyts, Johan
2016-02-01
Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov’s momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.
Image reconstruction of IRAS survey scans
NASA Technical Reports Server (NTRS)
Bontekoe, Tj. Romke
1990-01-01
The IRAS survey data can be used successfully to produce images of extended objects. The major difficulties, viz. non-uniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, were resolved. The results of three different image construction techniques are compared: co-addition, constrained least squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arc seconds is presented, using 60 micron survey data. This exceeds the telescope diffraction limit of 1 minute of arc, at this wavelength. Data fusion is a proposed method for combining data from different instruments, with different spacial resolutions, at different wavelengths. Data estimates of the physical parameters, temperature, density and composition, can be made from the data without prior image (re-)construction. An increase in the accuracy of these parameters is expected as the result of this more systematic approach.
NASA Astrophysics Data System (ADS)
Cumbrera, Ramiro; Millán, Humberto; Martín-Sotoca, Juan Jose; Pérez Soto, Luis; Sanchez, Maria Elena; Tarquis, Ana Maria
2016-04-01
methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Cumbrera, R., Ana M. Tarquis, Gabriel Gascó, Humberto Millán (2012) Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images. Journal of Hydrology (452-453), 205-212. Martin Sotoca; J.J. Antonio Saa-Requejo, Juan Grau and Ana M. Tarquis (2016). Segmentation of singularity maps in the context of soil porosity. Geophysical Research Abstracts, 18, EGU2016-11402. Millán, H., Cumbrera, R. and Ana M. Tarquis (2016) Multifractal and Levy-stable statistics of soil surface moisture distribution derived from 2D image analysis. Applied Mathematical Modelling, 40(3), 2384-2395.
Application of 2D and 3D Digital Image Correlation on CO2-like altered carbonate
NASA Astrophysics Data System (ADS)
zinsmeister, Louis; Dautriat, Jérémie; Dimanov, Alexandre; Raphanel, Jean; Bornert, Michel
2013-04-01
In order to provide mechanical constitutive laws for reservoir monitoring during CO2 long term storage, we studied the mechanical properties of Lavoux limestone before and after a homogeneous alteration following the protocol of acid treatments defined by Egermann et al, (2006). The mechanical data have been analysed at the light of systematic microstructural investigations. Firstly, the alteration impact on the evolution of flow properties related to microstructural changes was studied at successive levels of alteration by classical petrophysical measurements of porosity and permeability (including NMR, mercury porosimetry and laser diffraction) and by observations of microstructures on thin sections and by SEM. Secondly, the mechanical properties of the samples were investigated by classical (macroscopic) triaxial and uniaxial tests and are discussed in terms of the structural modifications. The macroscopic tests indicate that the alteration weakens the material, according to the observed decrease of elastic moduli and Uniaxial Compressive Strengths, from 29MPa to 19MPa after 6 cycles of acid treatments. The study is further complemented by 2D full (mechanical) field measurements, thanks to Digital Image Correlation (DIC) performed on images acquired during the uniaxial tests. This technique allows for continuous quantitative micro-mechanical monitoring in terms of deformation history and localisation processes during compression. This technique was applied on both intact and altered materials and at different scales of observation: (i) cm-sized samples were compressed in a classical load frame and optically imaged, (ii) mm-sized samples were loaded with a miniaturized compression rig implemented within a Scanning Electron Microscope. At last, 3D full field measurements were performed by 3D-DIC on mm-sized samples, which were compressed "in-situ" an X-ray microtomograph thanks to a miniaturized triaxial cell allowing for confining pressures of up to 15 MPa. At
NASA Astrophysics Data System (ADS)
Gao, MingLiang; He, XiaoHai; Teng, QiZhi; Zuo, Chen; Chen, DongDong
2015-01-01
A random three-dimensional (3D) porous medium can be reconstructed from a two-dimensional (2D) image by reconstructing an image from the original 2D image, and then repeatedly using the result to reconstruct the next 2D image. The reconstructed images are then stacked together to generate the entire reconstructed 3D porous medium. To perform this successfully, a very important issue must be addressed, i.e., controlling the continuity and variability among adjacent layers. Continuity and variability, which are consistent with the statistics characteristic of the training image (TI), ensure that the reconstructed result matches the TI. By selecting the number and location of the sampling points in the sampling process, the continuity and variability can be controlled directly, and thus the characteristics of the reconstructed image can be controlled indirectly. In this paper, we propose and develop an original sampling method called three-step sampling. In our sampling method, sampling points are extracted successively from the center of 5 ×5 and 3 ×3 sampling templates and the edge area based on a two-point correlation function. The continuity and variability of adjacent layers were considered during the three steps of the sampling process. Our method was tested on a Berea sandstone sample, and the reconstructed result was compared with the original sample, using tests involving porosity distribution, the lineal path function, the autocorrelation function, the pore and throat size distributions, and two-phase flow relative permeabilities. The comparison indicates that many statistical characteristics of the reconstructed result match with the TI and the reference 3D medium perfectly.
Gao, MingLiang; He, XiaoHai; Teng, QiZhi; Zuo, Chen; Chen, DongDong
2015-01-01
A random three-dimensional (3D) porous medium can be reconstructed from a two-dimensional (2D) image by reconstructing an image from the original 2D image, and then repeatedly using the result to reconstruct the next 2D image. The reconstructed images are then stacked together to generate the entire reconstructed 3D porous medium. To perform this successfully, a very important issue must be addressed, i.e., controlling the continuity and variability among adjacent layers. Continuity and variability, which are consistent with the statistics characteristic of the training image (TI), ensure that the reconstructed result matches the TI. By selecting the number and location of the sampling points in the sampling process, the continuity and variability can be controlled directly, and thus the characteristics of the reconstructed image can be controlled indirectly. In this paper, we propose and develop an original sampling method called three-step sampling. In our sampling method, sampling points are extracted successively from the center of 5×5 and 3×3 sampling templates and the edge area based on a two-point correlation function. The continuity and variability of adjacent layers were considered during the three steps of the sampling process. Our method was tested on a Berea sandstone sample, and the reconstructed result was compared with the original sample, using tests involving porosity distribution, the lineal path function, the autocorrelation function, the pore and throat size distributions, and two-phase flow relative permeabilities. The comparison indicates that many statistical characteristics of the reconstructed result match with the TI and the reference 3D medium perfectly. PMID:25679740
Ukwatta, Eranga; Arevalo, Hermenegild; Rajchl, Martin; White, James; Pashakhanloo, Farhad; Prakosa, Adityo; Herzka, Daniel A.; McVeigh, Elliot; Lardo, Albert C.; Trayanova, Natalia A.; Vadakkumpadan, Fijoy
2015-01-01
Purpose: Accurate three-dimensional (3D) reconstruction of myocardial infarct geometry is crucial to patient-specific modeling of the heart aimed at providing therapeutic guidance in ischemic cardiomyopathy. However, myocardial infarct imaging is clinically performed using two-dimensional (2D) late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) techniques, and a method to build accurate 3D infarct reconstructions from the 2D LGE-CMR images has been lacking. The purpose of this study was to address this need. Methods: The authors developed a novel methodology to reconstruct 3D infarct geometry from segmented low-resolution (Lo-res) clinical LGE-CMR images. Their methodology employed the so-called logarithm of odds (LogOdds) function to implicitly represent the shape of the infarct in segmented image slices as LogOdds maps. These 2D maps were then interpolated into a 3D image, and the result transformed via the inverse of LogOdds to a binary image representing the 3D infarct geometry. To assess the efficacy of this method, the authors utilized 39 high-resolution (Hi-res) LGE-CMR images, including 36 in vivo acquisitions of human subjects with prior myocardial infarction and 3 ex vivo scans of canine hearts following coronary ligation to induce infarction. The infarct was manually segmented by trained experts in each slice of the Hi-res images, and the segmented data were downsampled to typical clinical resolution. The proposed method was then used to reconstruct 3D infarct geometry from the downsampled images, and the resulting reconstructions were compared with the manually segmented data. The method was extensively evaluated using metrics based on geometry as well as results of electrophysiological simulations of cardiac sinus rhythm and ventricular tachycardia in individual hearts. Several alternative reconstruction techniques were also implemented and compared with the proposed method. Results: The accuracy of the LogOdds method in reconstructing 3D
NASA Astrophysics Data System (ADS)
Otake, Y.; Schafer, S.; Stayman, J. W.; Zbijewski, W.; Kleinszig, G.; Graumann, R.; Khanna, A. J.; Siewerdsen, J. H.
2012-02-01
Localization of target vertebrae is an essential step in minimally invasive spine surgery, with conventional methods relying on "level counting" - i.e., manual counting of vertebrae under fluoroscopy starting from readily identifiable anatomy (e.g., the sacrum). The approach requires an undesirable level of radiation, time, and is prone to counting errors due to the similar appearance of vertebrae in projection images; wrong-level surgery occurs in 1 of every ~3000 cases. This paper proposes a method to automatically localize target vertebrae in x-ray projections using 3D-2D registration between preoperative CT (in which vertebrae are preoperatively labeled) and intraoperative fluoroscopy. The registration uses an intensity-based approach with a gradient-based similarity metric and the CMA-ES algorithm for optimization. Digitally reconstructed radiographs (DRRs) and a robust similarity metric are computed on GPU to accelerate the process. Evaluation in clinical CT data included 5,000 PA and LAT projections randomly perturbed to simulate human variability in setup of mobile intraoperative C-arm. The method demonstrated 100% success for PA view (projection error: 0.42mm) and 99.8% success for LAT view (projection error: 0.37mm). Initial implementation on GPU provided automatic target localization within about 3 sec, with further improvement underway via multi-GPU. The ability to automatically label vertebrae in fluoroscopy promises to streamline surgical workflow, improve patient safety, and reduce wrong-site surgeries, especially in large patients for whom manual methods are time consuming and error prone.
Register cardiac fiber orientations from 3D DTI volume to 2D ultrasound image of rat hearts
NASA Astrophysics Data System (ADS)
Qin, Xulei; Wang, Silun; Shen, Ming; Zhang, Xiaodong; Lerakis, Stamatios; Wagner, Mary B.; Fei, Baowei
2015-03-01
Two-dimensional (2D) ultrasound or echocardiography is one of the most widely used examinations for the diagnosis of cardiac diseases. However, it only supplies the geometric and structural information of the myocardium. In order to supply more detailed microstructure information of the myocardium, this paper proposes a registration method to map cardiac fiber orientations from three-dimensional (3D) magnetic resonance diffusion tensor imaging (MR-DTI) volume to the 2D ultrasound image. It utilizes a 2D/3D intensity based registration procedure including rigid, log-demons, and affine transformations to search the best similar slice from the template volume. After registration, the cardiac fiber orientations are mapped to the 2D ultrasound image via fiber relocations and reorientations. This method was validated by six images of rat hearts ex vivo. The evaluation results indicated that the final Dice similarity coefficient (DSC) achieved more than 90% after geometric registrations; and the inclination angle errors (IAE) between the mapped fiber orientations and the gold standards were less than 15 degree. This method may provide a practical tool for cardiologists to examine cardiac fiber orientations on ultrasound images and have the potential to supply additional information for diagnosis of cardiac diseases.
Kaaouana, Takoua; de Rochefort, Ludovic; Samaille, Thomas; Thiery, Nathalie; Dufouil, Carole; Delmaire, Christine; Dormont, Didier; Chupin, Marie
2015-01-01
Cerebral microbleeds (CMBs) have emerged as a new imaging marker of small vessel disease. Composed of hemosiderin, CMBs are paramagnetic and can be detected with MRI sequences sensitive to magnetic susceptibility (typically, gradient recalled echo T2* weighted images). Nevertheless, their identification remains challenging on T2* magnitude images because of confounding structures and lesions. In this context, T2* phase image may play a key role in better characterizing CMBs because of its direct relationship with local magnetic field variations due to magnetic susceptibility difference. To address this issue, susceptibility-based imaging techniques were proposed, such as Susceptibility Weighted Imaging (SWI) and Quantitative Susceptibility Mapping (QSM). But these techniques have not yet been validated for 2D clinical data in multicenter settings. Here, we introduce 2DHF, a fast 2D phase processing technique embedding both unwrapping and harmonic filtering designed for data acquired in 2D, even with slice-to-slice inconsistencies. This method results in internal field maps which reveal local field details due to magnetic inhomogeneity within the region of interest only. This technique is based on the physical properties of the induced magnetic field and should yield consistent results. A synthetic phantom was created for numerical simulations. It simulates paramagnetic and diamagnetic lesions within a 'brain-like' tissue, within a background. The method was evaluated on both this synthetic phantom and multicenter 2D datasets acquired in standardized clinical setting, and compared with two state-of-the-art methods. It proved to yield consistent results on synthetic images and to be applicable and robust on patient data. As a proof-of-concept, we finally illustrate that it is possible to find a magnetic signature of CMBs and CMCs on internal field maps generated with 2DHF on 2D clinical datasets that give consistent results with CT-scans in a subsample of 10 subjects
Dubousset, Jean; Charpak, Georges; Dorion, Irène; Skalli, Wafa; Lavaste, François; Deguise, Jacques; Kalifa, Gabriel; Ferey, Solène
2005-02-01
Close collaboration between multidisciplinary specialists (physicists, biomecanical engineers, medical radiologists and pediatric orthopedic surgeons) has led to the development of a new low-dose radiation device named EOS. EOS has three main advantages: The use of a gaseous X-ray detector, invented by Georges Charpak (Nobel Prizewinner 1992), the dose necessary to obtain a 2D image of the skeletal system has been reduced by 8 to 10 times, while that required to obtain a 3D reconstruction from CT slices has fallen by a factor of 800 to 1000. The accuracy of the 3D reconstruction obtained with EOS is as good as that obtained with CT. The patient is examined in the standing (or seated) position, and is scanned simultaneously from head to feet, both frontally and laterally. This is a major advantage over conventional CT which requires the patient to be placed horizontally. -The 3D reconstructions of each element of the osteo-articular system are as precise as those obtained by conventional CT. EOS is also rapid, taking only 15 to 30 minutes to image the entire spine. PMID:16114859
NASA Astrophysics Data System (ADS)
Peters, C. A.; Crandell, L. E.; Um, W.; Jones, K. W.; Lindquist, W. B.
2011-12-01
Geochemical reactions in the subsurface can alter the porosity and permeability of a porous medium through mineral precipitation and dissolution. While effects on porosity are relatively well understood, changes in permeability are more difficult to estimate. In this work, pore-network modeling is used to estimate the permeability of a porous medium using pore and throat size distributions. These distributions can be determined from 2D Scanning Electron Microscopy (SEM) images of thin sections or from 3D X-ray Computed Tomography (CT) images of small cores. Each method has unique advantages as well as unique sources of error. 3D CT imaging has the advantage of reconstructing a 3D pore network without the inherent geometry-based biases of 2D images but is limited by resolutions around 1 μm. 2D SEM imaging has the advantage of higher resolution, and the ability to examine sub-grain scale variations in porosity and mineralogy, but is limited by the small size of the sample of pores that are quantified. A pore network model was created to estimate flow permeability in a sand-packed experimental column investigating reaction of sediments with caustic radioactive tank wastes in the context of the Hanford, WA site. Before, periodically during, and after reaction, 3D images of the porous medium in the column were produced using the X2B beam line facility at the National Synchrotron Light Source (NSLS) at Brookhaven National Lab. These images were interpreted using 3DMA-Rock to characterize the pore and throat size distributions. After completion of the experiment, the column was sectioned and imaged using 2D SEM in backscattered electron mode. The 2D images were interpreted using erosion-dilation to estimate the pore and throat size distributions. A bias correction was determined by comparison with the 3D image data. A special image processing method was developed to infer the pore space before reaction by digitally removing the precipitate. The different sets of pore
Image-based reconstruction of 3D myocardial infarct geometry for patient specific applications
NASA Astrophysics Data System (ADS)
Ukwatta, Eranga; Rajchl, Martin; White, James; Pashakhanloo, Farhad; Herzka, Daniel A.; McVeigh, Elliot; Lardo, Albert C.; Trayanova, Natalia; Vadakkumpadan, Fijoy
2015-03-01
Accurate reconstruction of the three-dimensional (3D) geometry of a myocardial infarct from two-dimensional (2D) multi-slice image sequences has important applications in the clinical evaluation and treatment of patients with ischemic cardiomyopathy. However, this reconstruction is challenging because the resolution of common clinical scans used to acquire infarct structure, such as short-axis, late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) images, is low, especially in the out-of-plane direction. In this study, we propose a novel technique to reconstruct the 3D infarct geometry from low resolution clinical images. Our methodology is based on a function called logarithm of odds (LogOdds), which allows the broader class of linear combinations in the LogOdds vector space as opposed to being limited to only a convex combination in the binary label space. To assess the efficacy of the method, we used high-resolution LGE-CMR images of 36 human hearts in vivo, and 3 canine hearts ex vivo. The infarct was manually segmented in each slice of the acquired images, and the manually segmented data were downsampled to clinical resolution. The developed method was then applied to the downsampled image slices, and the resulting reconstructions were compared with the manually segmented data. Several existing reconstruction techniques were also implemented, and compared with the proposed method. The results show that the LogOdds method significantly outperforms all the other tested methods in terms of region overlap.
Ren, X; Domier, C W; Kramer, G; Luhmann, N C; Muscatello, C M; Shi, L; Tobias, B J; Valeo, E
2014-11-01
A synthetic microwave imaging reflectometer (MIR) diagnostic employing the full-wave reflectometer code (FWR2D) has been developed and is currently being used to guide the design of real systems, such as the one recently installed on DIII-D. The FWR2D code utilizes real plasma profiles as input, and it is combined with optical simulation tools for synthetic diagnostic signal generation. A detailed discussion of FWR2D and the process to generate the synthetic signal are presented in this paper. The synthetic signal is also compared to a prescribed density fluctuation spectrum to quantify the imaging quality. An example is presented with H-mode-like plasma profiles derived from a DIII-D discharge, where the MIR focal is located in the pedestal region. It is shown that MIR is suitable for diagnosing fluctuations with poloidal wavenumber up to 2.0 cm(-1) and fluctuation amplitudes less than 5%. PMID:25430276
Imaging, Reconstruction, And Display Of Corneal Topography
NASA Astrophysics Data System (ADS)
Klyce, Stephen D.; Wilson, Steven E.
1989-12-01
The cornea is the major refractive element in the eye; even minor surface distortions can produce a significant reduction in visual acuity. Standard clinical methods used to evaluate corneal shape include keratometry, which assumes the cornea is ellipsoidal in shape, and photokeratoscopy, which images a series of concentric light rings on the corneal surface. These methods fail to document many of the corneal distortions that can degrade visual acuity. Algorithms have been developed to reconstruct the three dimensional shape of the cornea from keratoscope images, and to present these data in the clinically useful display of color-coded contour maps of corneal surface power. This approach has been implemented on a new generation video keratoscope system (Computed Anatomy, Inc.) with rapid automatic digitization of the image rings by a rule-based approach. The system has found clinical use in the early diagnosis of corneal shape anomalies such as keratoconus and contact lens-induced corneal warpage, in the evaluation of cataract and corneal transplant procedures, and in the assessment of corneal refractive surgical procedures. Currently, ray tracing techniques are being used to correlate corneal surface topography with potential visual acuity in an effort to more fully understand the tolerances of corneal shape consistent with good vision and to help determine the site of dysfunction in the visually impaired.
Photogrammetric 3D reconstruction using mobile imaging
NASA Astrophysics Data System (ADS)
Fritsch, Dieter; Syll, Miguel
2015-03-01
In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.
Possum-A Framework for Three-Dimensional Reconstruction of Brain Images from Serial Sections.
Majka, Piotr; Wójcik, Daniel K
2016-07-01
Techniques based on imaging serial sections of brain tissue provide insight into brain structure and function. However, to compare or combine them with results from three dimensional imaging methods, reconstruction into a volumetric form is required. Currently, there are no tools for performing such a task in a streamlined way. Here we propose the Possum volumetric reconstruction framework which provides a selection of 2D to 3D image reconstruction routines allowing one to build workflows tailored to one's specific requirements. The main components include routines for reconstruction with or without using external reference and solutions for typical issues encountered during the reconstruction process, such as propagation of the registration errors due to distorted sections. We validate the implementation using synthetic datasets and actual experimental imaging data derived from publicly available resources. We also evaluate efficiency of a subset of the algorithms implemented. The Possum framework is distributed under MIT license and it provides researchers with a possibility of building reconstruction workflows from existing components, without the need for low-level implementation. As a consequence, it also facilitates sharing and data exchange between researchers and laboratories. PMID:26687079
Registration of 2D x-ray images to 3D MRI by generating pseudo-CT data
NASA Astrophysics Data System (ADS)
van der Bom, M. J.; Pluim, J. P. W.; Gounis, M. J.; van de Kraats, E. B.; Sprinkhuizen, S. M.; Timmer, J.; Homan, R.; Bartels, L. W.
2011-02-01
Spatial and soft tissue information provided by magnetic resonance imaging can be very valuable during image-guided procedures, where usually only real-time two-dimensional (2D) x-ray images are available. Registration of 2D x-ray images to three-dimensional (3D) magnetic resonance imaging (MRI) data, acquired prior to the procedure, can provide optimal information to guide the procedure. However, registering x-ray images to MRI data is not a trivial task because of their fundamental difference in tissue contrast. This paper presents a technique that generates pseudo-computed tomography (CT) data from multi-spectral MRI acquisitions which is sufficiently similar to real CT data to enable registration of x-ray to MRI with comparable accuracy as registration of x-ray to CT. The method is based on a k-nearest-neighbors (kNN)-regression strategy which labels voxels of MRI data with CT Hounsfield Units. The regression method uses multi-spectral MRI intensities and intensity gradients as features to discriminate between various tissue types. The efficacy of using pseudo-CT data for registration of x-ray to MRI was tested on ex vivo animal data. 2D-3D registration experiments using CT and pseudo-CT data of multiple subjects were performed with a commonly used 2D-3D registration algorithm. On average, the median target registration error for registration of two x-ray images to MRI data was approximately 1 mm larger than for x-ray to CT registration. The authors have shown that pseudo-CT data generated from multi-spectral MRI facilitate registration of MRI to x-ray images. From the experiments it could be concluded that the accuracy achieved was comparable to that of registering x-ray images to CT data.
Head pose estimation from a 2D face image using 3D face morphing with depth parameters.
Kong, Seong G; Mbouna, Ralph Oyini
2015-06-01
This paper presents estimation of head pose angles from a single 2D face image using a 3D face model morphed from a reference face model. A reference model refers to a 3D face of a person of the same ethnicity and gender as the query subject. The proposed scheme minimizes the disparity between the two sets of prominent facial features on the query face image and the corresponding points on the 3D face model to estimate the head pose angles. The 3D face model used is morphed from a reference model to be more specific to the query face in terms of the depth error at the feature points. The morphing process produces a 3D face model more specific to the query image when multiple 2D face images of the query subject are available for training. The proposed morphing process is computationally efficient since the depth of a 3D face model is adjusted by a scalar depth parameter at feature points. Optimal depth parameters are found by minimizing the disparity between the 2D features of the query face image and the corresponding features on the morphed 3D model projected onto 2D space. The proposed head pose estimation technique was evaluated on two benchmarking databases: 1) the USF Human-ID database for depth estimation and 2) the Pointing'04 database for head pose estimation. Experiment results demonstrate that head pose estimation errors in nodding and shaking angles are as low as 7.93° and 4.65° on average for a single 2D input face image. PMID:25706638
Total variation minimization-based multimodality medical image reconstruction
NASA Astrophysics Data System (ADS)
Cui, Xuelin; Yu, Hengyong; Wang, Ge; Mili, Lamine
2014-09-01
Since its recent inception, simultaneous image reconstruction for multimodality fusion has received a great deal of attention due to its superior imaging performance. On the other hand, the compressed sensing (CS)-based image reconstruction methods have undergone a rapid development because of their ability to significantly reduce the amount of raw data. In this work, we combine computed tomography (CT) and magnetic resonance imaging (MRI) into a single CS-based reconstruction framework. From a theoretical viewpoint, the CS-based reconstruction methods require prior sparsity knowledge to perform reconstruction. In addition to the conventional data fidelity term, the multimodality imaging information is utilized to improve the reconstruction quality. Prior information in this context is that most of the medical images can be approximated as piecewise constant model, and the discrete gradient transform (DGT), whose norm is the total variation (TV), can serve as a sparse representation. More importantly, the multimodality images from the same object must share structural similarity, which can be captured by DGT. The prior information on similar distributions from the sparse DGTs is employed to improve the CT and MRI image quality synergistically for a CT-MRI scanner platform. Numerical simulation with undersampled CT and MRI datasets is conducted to demonstrate the merits of the proposed hybrid image reconstruction approach. Our preliminary results confirm that the proposed method outperforms the conventional CT and MRI reconstructions when they are applied separately.
Li, Feng; Seillier-Moiseiwitsch, Françoise
2011-01-01
Image analysis of two-dimensional gel electrophoresis is a key step in proteomic workflow for identifying proteins that change under different experimental conditions. Since there are usually large amount of proteins and variations shown in the gel images, the use of software for analysis of 2D gel images is inevitable. We developed open-source software with graphical user interface for differential analysis of 2D gel images. The user-friendly software, RegStatGel, contains fully automated as well as interactive procedures. It was developed and has been tested under Matlab 7.01. Availability The database is available for free at http://www.mediafire.com/FengLi/2DGelsoftware PMID:21904427
Block-based reconstructions for compressive spectral imaging
NASA Astrophysics Data System (ADS)
Correa, Claudia V.; Arguello, Henry; Arce, Gonzalo R.
2013-05-01
Coded Aperture Snapshot Spectral Imaging system (CASSI) captures spectral information of a scene using a reduced amount of focal plane array (FPA) projections. These projections are highly structured and localized such that each measurement contains information of a small portion of the data cube. Compressed sensing reconstruction algorithms are then used to recover the underlying 3-dimensional (3D) scene. The computational burden to recover a hyperspectral scene in CASSI is overwhelming for some applications such that reconstructions can take hours in desktop architectures. This paper presents a new method to reconstruct a hyperspectral signal from its compressive measurements using several overlapped block reconstructions. This approach exploits the structure of the CASSI sensing matrix to separately reconstruct overlapped regions of the 3D scene. The resultant reconstructions are then assembled to obtain the full recovered data cube. Typically, block-processing causes undesired artifacts in the recovered signal. Vertical and horizontal overlaps between adjacent blocks are then used to avoid these artifacts and increase the quality of reconstructed images. The reconstruction time and the quality of the reconstructed images are calculated as a function of the block-size and the amount of overlapped regions. Simulations show that the quality of the reconstructions is increased up to 6 dB and the reconstruction time is reduced up to 4 times when using block-based reconstruction instead of full data cube recovery at once. The proposed method is suitable for multi-processor architectures in which each core recovers one block at a time.
Tree STEM Reconstruction Using Vertical Fisheye Images: a Preliminary Study
NASA Astrophysics Data System (ADS)
Berveglieri, A.; Tommaselli, A. M. G.
2016-06-01
A preliminary study was conducted to assess a tree stem reconstruction technique with panoramic images taken with fisheye lenses. The concept is similar to the Structure from Motion (SfM) technique, but the acquisition and data preparation rely on fisheye cameras to generate a vertical image sequence with height variations of the camera station. Each vertical image is rectified to four vertical planes, producing horizontal lateral views. The stems in the lateral view are rectified to the same scale in the image sequence to facilitate image matching. Using bundle adjustment, the stems are reconstructed, enabling later measurement and extraction of several attributes. The 3D reconstruction was performed with the proposed technique and compared with SfM. The preliminary results showed that the stems were correctly reconstructed by using the lateral virtual images generated from the vertical fisheye images and with the advantage of using fewer images and taken from one single station.
NASA Astrophysics Data System (ADS)
Salvetti, Ovidio; Marraccini, Paolo; Braccini, Giovanni; Bragagni, Paolo; Levorato, Dianora; L'Abbate, Antonio; Marzilli, Mario
1994-05-01
The aim of this study was to develop a diagnostic and evaluation system for analyzing 3D spaces defined by digitized cross-sectional US images of coronaries to quantify the vasomotion in relation to the morphology of arterial wall. Sequences of echographic images were obtained to have ordered stacks of 2D frames recorded on a VHS videotape. For each image, an automatic lumen edge segmentation is performed, then 3D reconstruction is obtained to evaluate time-dependent lumen and vessel wall modifications. Directly on 3D volumes, dynamic phenomena can be evidenced and quantitative analysis can be performed (e.g., area/hemidiameter variations, projections, sections, `carving', etc.).
NASA Astrophysics Data System (ADS)
Jol, Harry M.; Lawton, Don C.; Smith, Derald G.
2003-07-01
The ability to effectively interpret and reconstruct geomorphic environments has been significantly aided by the subsurface imaging capabilities of ground penetrating radar (GPR). The GPR method, which is based on the propagation and reflection of pulsed high frequency electromagnetic energy, provides high resolution (cm to m scale) and shallow subsurface (0-60 m), near continuous profiles of many coarser-grained deposits (sediments of low electrical conductivity). This paper presents 2-D and 3-D GPR results from an experiment on a regressive modern barrier spit at Willapa Bay, WA, USA. The medium-grained sand spit is 38 km long, up to 2-3.5 km wide, and is influenced by a 3.7-m tidal range (spring) as well as high energy longshore transport and high wave energy depositional processes. The spit has a freshwater aquifer recharged by rainfall. The GPR acquisition system used for the test was a portable, digital pulseEKKO™ system with antennae frequency ranging from 25 to 200 MHz and transmitter voltages ranging from 400 to 1000 V. Step sizes and antennae separation varied depending on the test requirements. In addition, 100-MHz antennae were used for conducting antennae orientation tests and collecting a detailed grid of data (50×50 m sampled every meter). The 2-D digital profiles were processed and plotted using pulseEKKO™ software. The 3-D datasets, after initial processing, were entered into a LANDMARK™ workstation that allowed for unique 3-D perspectives of the subsurface. To provide depth, near-surface velocity measurements were calculated from common midpoint (CMP) surveys. Results from the present study demonstrate higher resolution from the 200-MHz antennae for the top 5-6 m, whereas the 25- and 50-MHz antennae show deeper penetration to >10 m. For the study site, 100-MHz antennae provided acceptable resolution, continuity of reflections, and penetration. The dip profiles show a shingle-like accretionary depositional pattern, whereas strike profiles
Hara, Daisuke; Nakashima, Yasuharu; Hamai, Satoshi; Higaki, Hidehiko; Ikebe, Satoru; Shimoto, Takeshi; Hirata, Masanobu; Kanazawa, Masayuki; Kohno, Yusuke; Iwamoto, Yukihide
2014-01-01
Dynamic hip kinematics during weight-bearing activities were analyzed for six healthy subjects. Continuous X-ray images of gait, chair-rising, squatting, and twisting were taken using a flat panel X-ray detector. Digitally reconstructed radiographic images were used for 3D-to-2D model-to-image registration technique. The root-mean-square errors associated with tracking the pelvis and femur were less than 0.3 mm and 0.3° for translations and rotations. For gait, chair-rising, and squatting, the maximum hip flexion angles averaged 29.6°, 81.3°, and 102.4°, respectively. The pelvis was tilted anteriorly around 4.4° on average during full gait cycle. For chair-rising and squatting, the maximum absolute value of anterior/posterior pelvic tilt averaged 12.4°/11.7° and 10.7°/10.8°, respectively. Hip flexion peaked on the way of movement due to further anterior pelvic tilt during both chair-rising and squatting. For twisting, the maximum absolute value of hip internal/external rotation averaged 29.2°/30.7°. This study revealed activity dependent kinematics of healthy hip joints with coordinated pelvic and femoral dynamic movements. Kinematics' data during activities of daily living may provide important insight as to the evaluating kinematics of pathological and reconstructed hips. PMID:25506056
Yi, Faliu; Lee, Jieun; Moon, Inkyu
2014-05-01
The reconstruction of multiple depth images with a ray back-propagation algorithm in three-dimensional (3D) computational integral imaging is computationally burdensome. Further, a reconstructed depth image consists of a focus and an off-focus area. Focus areas are 3D points on the surface of an object that are located at the reconstructed depth, while off-focus areas include 3D points in free-space that do not belong to any object surface in 3D space. Generally, without being removed, the presence of an off-focus area would adversely affect the high-level analysis of a 3D object, including its classification, recognition, and tracking. Here, we use a graphics processing unit (GPU) that supports parallel processing with multiple processors to simultaneously reconstruct multiple depth images using a lookup table containing the shifted values along the x and y directions for each elemental image in a given depth range. Moreover, each 3D point on a depth image can be measured by analyzing its statistical variance with its corresponding samples, which are captured by the two-dimensional (2D) elemental images. These statistical variances can be used to classify depth image pixels as either focus or off-focus points. At this stage, the measurement of focus and off-focus points in multiple depth images is also implemented in parallel on a GPU. Our proposed method is conducted based on the assumption that there is no occlusion of the 3D object during the capture stage of the integral imaging process. Experimental results have demonstrated that this method is capable of removing off-focus points in the reconstructed depth image. The results also showed that using a GPU to remove the off-focus points could greatly improve the overall computational speed compared with using a CPU. PMID:24921860
Mikhaylova, E.; Kolstein, M.; De Lorenzo, G.; Chmeissani, M.
2014-01-01
A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project [1]. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head [2]. With unprecedented high channel density (450 channels/cm3) image reconstruction is a challenge. Therefore optimization is needed to find the best algorithm in order to exploit correctly the promising detector potential. The following reconstruction algorithms are evaluated: 2-D Filtered Backprojection (FBP), Ordered Subset Expectation Maximization (OSEM), List-Mode OSEM (LM-OSEM), and the Origin Ensemble (OE) algorithm. The evaluation is based on the comparison of a true image phantom with a set of reconstructed images obtained by each algorithm. This is achieved by calculation of image quality merit parameters such as the bias, the variance and the mean square error (MSE). A systematic optimization of each algorithm is performed by varying the reconstruction parameters, such as the cutoff frequency of the noise filters and the number of iterations. The region of interest (ROI) analysis of the reconstructed phantom is also performed for each algorithm and the results are compared. Additionally, the performance of the image reconstruction methods is compared by calculating the modulation transfer function (MTF). The reconstruction time is also taken into account to choose the optimal algorithm. The analysis is based on GAMOS [3] simulation including the expected CdTe and electronic specifics. PMID:25018777
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. PMID:25018777
Mid-IR hyperspectral imaging of laminar flames for 2-D scalar values.
Rhoby, Michael R; Blunck, David L; Gross, Kevin C
2014-09-01
This work presents a new emission-based measurement which permits quantification of two-dimensional scalar distributions in laminar flames. A Michelson-based Fourier-transform spectrometer coupled to a mid-infrared camera (1.5 μm to 5.5 μm) obtained 256 × 128pixel hyperspectral flame images at high spectral (δν̃ = 0.75cm(−1)) and spatial (0.52 mm) resolutions. The measurements revealed line and band emission from H2O, CO2, and CO. Measurements were collected from a well-characterized partially-premixed ethylene (C2H4) flame produced on a Hencken burner at equivalence ratios, Φ, of 0.8, 0.9, 1.1, and 1.3. After describing the instrument and novel calibration methodology, analysis of the flames is presented. A single-layer, line-by-line radiative transfer model is used to retrieve path-averaged temperature, H2O, CO2 and CO column densities from emission spectra between 2.3 μm to 5.1 μm. The radiative transfer model uses line intensities from the latest HITEMP and CDSD-4000 spectroscopic databases. For the Φ = 1.1 flame, the spectrally estimated temperature for a single pixel 10 mm above burner center was T = (2318 ± 19)K, and agrees favorably with recently reported laser absorption measurements, T = (2348 ± 115)K, and a NASA CEA equilibrium calculation, T = 2389K. Near the base of the flame, absolute concentrations can be estimated, and H2O, CO2, and CO concentrations of (12.5 ± 1.7) %, (10.1 ± 1.0) %, and (3.8 ± 0.3) %, respectively, compared favorably with the corresponding CEA values of 12.8%, 9.9% and 4.1%. Spectrally-estimated temperatures and concentrations at the other equivalence ratios were in similar agreement with measurements and equilibrium calculations. 2-D temperature and species column density maps underscore the Φ-dependent chemical composition of the flames. The reported uncertainties are 95% confidence intervals and include both statistical fit errors and the propagation of systematic calibration errors using a Monte Carlo
Parallel computation of optimized arrays for 2-D electrical imaging surveys
NASA Astrophysics Data System (ADS)
Loke, M. H.; Wilkinson, P. B.; Chambers, J. E.
2010-12-01
Modern automatic multi-electrode survey instruments have made it possible to use non-traditional arrays to maximize the subsurface resolution from electrical imaging surveys. Previous studies have shown that one of the best methods for generating optimized arrays is to select the set of array configurations that maximizes the model resolution for a homogeneous earth model. The Sherman-Morrison Rank-1 update is used to calculate the change in the model resolution when a new array is added to a selected set of array configurations. This method had the disadvantage that it required several hours of computer time even for short 2-D survey lines. The algorithm was modified to calculate the change in the model resolution rather than the entire resolution matrix. This reduces the computer time and memory required as well as the computational round-off errors. The matrix-vector multiplications for a single add-on array were replaced with matrix-matrix multiplications for 28 add-on arrays to further reduce the computer time. The temporary variables were stored in the double-precision Single Instruction Multiple Data (SIMD) registers within the CPU to minimize computer memory access. A further reduction in the computer time is achieved by using the computer graphics card Graphics Processor Unit (GPU) as a highly parallel mathematical coprocessor. This makes it possible to carry out the calculations for 512 add-on arrays in parallel using the GPU. The changes reduce the computer time by more than two orders of magnitude. The algorithm used to generate an optimized data set adds a specified number of new array configurations after each iteration to the existing set. The resolution of the optimized data set can be increased by adding a smaller number of new array configurations after each iteration. Although this increases the computer time required to generate an optimized data set with the same number of data points, the new fast numerical routines has made this practical on
NASA Astrophysics Data System (ADS)
Kiflu, H. G.; Kruse, S. E.; Harro, D.; Loke, M. H.; Wilkinson, P. B.
2013-12-01
Electrical resistivity tomography is commonly used to identify geologic features associated with sinkhole formation. In covered karst terrain, however, it can be difficult to resolve the depth to top of limestone with this method. This is due to the fact that array lengths, and hence depth of resolution, are often limited by residential or commercial lot dimensions in urban environments. Furthermore, the sediments mantling the limestone are often clay-rich and highly conductive. The resistivity method has limited sensitivity to resistive zones beneath conductive zones. This sensitivity can be improved significantly with electrodes implanted at depth in the cover sediments near the top of limestone. An array of deep electrodes is installed with direct push technology in the karst cover. When combined with a surface array in which each surface electrode is underlain by a deep electrode, the array geometry is similar to a borehole array turned on its side. This method, called the Multi-Electrode Resistivity Implant Technique (MERIT), offers the promise of significantly improved resolution of epikarst and cover collapse development zones in the overlying sediment, the limestone or at the sediment-bedrock interface in heterogeneous karst environments. With a non-traditional array design, the question of optimal array geometries arises. Optimizing array geometries is complicated by the fact that many plausible 4-electrode readings will produce negative apparent resistivity values, even in homogeneous terrain. Negative apparent resistivities cannot be used in inversions based on the logarithm of the apparent resistivity. New algorithms for seeking optimal array geometries have been developed by modifying the 'Compare R' method of Wilkinson and Loke. The optimized arrays show significantly improved resolution over basic arrays adapted from traditional 2D surface geometries. Several MERIT case study surveys have been conducted in covered karst in west-central Florida, with
Concurrent image and dose reconstruction for image guided radiation therapy
NASA Astrophysics Data System (ADS)
Sheng, Ke
The importance of knowing the patient actual position is essential for intensity modulated radiation therapy (IMRT). This procedure uses tightened margin and escalated tumor dose. In order to eliminate the uncertainty of the geometry in IMRT, daily imaging is prefered. The imaging dose, limited field of view and the imaging concurrency of the MVCT (mega-voltage computerized tomography) are investigated in this work. By applying partial volume imaging (PVI), imaging dose can be reduced for a region of interest (ROI) imaging. The imaging dose and the image quality are quantitatively balanced with inverse imaging dose planning. With PVI, 72% average imaging dose reduction was observed on a typical prostate patient case. The algebraic reconstruction technique (ART) based projection onto convex sets (POCS) shows higher robustness than filtered back projection when available imaging data is not complete and continuous. However, when the projection is continuous as in the actual delivery, a non-iterative wavelet based multiresolution local tomography (WMLT) is able to achieve 1% accuracy within the ROI. The reduction of imaging dose is dependent on the size of ROI. The improvement of concurrency is also discussed based on the combination of PVI and WMLT. Useful target images were acquired with treatment beams and the temporal resolution can be increased to 20 seconds in tomotherapy. The data truncation problem with the portal imager was also studied. Results show that the image quality is not adversely affected by truncation when WMLT is employed. When the online imaging is available, a perturbation dose calculation (PDC) that estimates the actual delivered dose is proposed. Corrected from the Fano's theorem, PDC counts the first order term in the density variation to calculate the internal and external anatomy change. Although change in the dose distribution that is caused by the internal organ motion is less than 1% for 6 MV beams, the external anatomy change has
NASA Astrophysics Data System (ADS)
Elangovan, Premkumar; Warren, Lucy M.; Mackenzie, Alistair; Rashidnasab, Alaleh; Diaz, Oliver; Dance, David R.; Young, Kenneth C.; Bosmans, Hilde; Strudley, Celia J.; Wells, Kevin
2014-08-01
Planar 2D x-ray mammography is generally accepted as the preferred screening technique used for breast cancer detection. Recently, digital breast tomosynthesis (DBT) has been introduced to overcome some of the inherent limitations of conventional planar imaging, and future technological enhancements are expected to result in the introduction of further innovative modalities. However, it is crucial to understand the impact of any new imaging technology or methodology on cancer detection rates and patient recall. Any such assessment conventionally requires large scale clinical trials demanding significant investment in time and resources. The concept of virtual clinical trials and virtual performance assessment may offer a viable alternative to this approach. However, virtual approaches require a collection of specialized modelling tools which can be used to emulate the image acquisition process and simulate images of a quality indistinguishable from their real clinical counterparts. In this paper, we present two image simulation chains constructed using modelling tools that can be used for the evaluation of 2D-mammography and DBT systems. We validate both approaches by comparing simulated images with real images acquired using the system being simulated. A comparison of the contrast-to-noise ratios and image blurring for real and simulated images of test objects shows good agreement ( < 9% error). This suggests that our simulation approach is a promising alternative to conventional physical performance assessment followed by large scale clinical trials.
Field, J E; Rygg, J R; Barrios, M A; Benedetti, L R; Döppner, T; Izumi, N; Jones, O; Khan, S F; Ma, T; Nagel, S R; Pak, A; Tommasini, R; Bradley, D K; Town, R P J
2014-11-01
Two-dimensional radiographs of imploding fusion capsules are obtained at the National Ignition Facility by projection through a pinhole array onto a time-gated framing camera. Parallax among images in the image array makes it possible to distinguish contributions from the capsule and from the backlighter, permitting correction of backlighter non-uniformities within the capsule radiograph. Furthermore, precise determination of the imaging system geometry and implosion velocity enables combination of multiple images to reduce signal-to-noise and discover new capsule features. PMID:25430345
Field, J. E. Rygg, J. R.; Barrios, M. A.; Benedetti, L. R.; Döppner, T.; Izumi, N.; Jones, O.; Khan, S. F.; Ma, T.; Nagel, S. R.; Pak, A.; Tommasini, R.; Bradley, D. K.; Town, R. P. J.
2014-11-15
Two-dimensional radiographs of imploding fusion capsules are obtained at the National Ignition Facility by projection through a pinhole array onto a time-gated framing camera. Parallax among images in the image array makes it possible to distinguish contributions from the capsule and from the backlighter, permitting correction of backlighter non-uniformities within the capsule radiograph. Furthermore, precise determination of the imaging system geometry and implosion velocity enables combination of multiple images to reduce signal-to-noise and discover new capsule features.
Electrophysiology Catheter Detection and Reconstruction From Two Views in Fluoroscopic Images.
Hoffmann, Matthias; Brost, Alexander; Koch, Martin; Bourier, Felix; Maier, Andreas; Kurzidim, Klaus; Strobel, Norbert; Hornegger, Joachim
2016-02-01
Electrophysiology (EP) studies and catheter ablation have become important treatment options for several types of cardiac arrhythmias. We present a novel image-based approach for automatic detection and 3-D reconstruction of EP catheters where the physician marks the catheter to be reconstructed by a single click in each image. The result can be used to provide 3-D information for enhanced navigation throughout EP procedures. Our approach involves two X-ray projections acquired from different angles, and it is based on two steps: First, we detect the catheter in each view after manual initialization using a graph-search method. Then, the detection results are used to reconstruct a full 3-D model of the catheter based on automatically determined point pairs for triangulation. An evaluation on 176 different clinical fluoroscopic images yielded a detection rate of 83.4%. For measuring the error, we used the coupling distance which is a more accurate quality measure than the average point-wise distance to a reference. For successful outcomes, the 2-D detection error was 1.7 mm ±1.2 mm. Using successfully detected catheters for reconstruction, we obtained a reconstruction error of 1.8 mm ±1.1 mm on phantom data. On clinical data, our method yielded a reconstruction error of 2.2 mm ±2.2 mm. PMID:26441411
Automatic Texture Reconstruction of 3d City Model from Oblique Images
NASA Astrophysics Data System (ADS)
Kang, Junhua; Deng, Fei; Li, Xinwei; Wan, Fang
2016-06-01
In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.
3D structural measurements of the proximal femur from 2D DXA images using a statistical atlas
NASA Astrophysics Data System (ADS)
Ahmad, Omar M.; Ramamurthi, Krishna; Wilson, Kevin E.; Engelke, Klaus; Bouxsein, Mary; Taylor, Russell H.
2009-02-01
A method to obtain 3D structural measurements of the proximal femur from 2D DXA images and a statistical atlas is presented. A statistical atlas of a proximal femur was created consisting of both 3D shape and volumetric density information and then deformably registered to 2D fan-beam DXA images. After the registration process, a series of 3D structural measurements were taken on QCT-estimates generated by transforming the registered statistical atlas into a voxel volume. These measurements were compared to the equivalent measurements taken on the actual QCT (ground truth) associated with the DXA images for each of 20 human cadaveric femora. The methodology and results are presented to address the potential clinical feasibility of obtaining 3D structural measurements from limited angle DXA scans and a statistical atlas of the proximal femur in-vivo.
Hansen, Hendrik H G; Richards, Michael S; Doyley, Marvin M; de Korte, Chris L
2013-01-01
Atherosclerotic plaque rupture can initiate stroke or myocardial infarction. Lipid-rich plaques with thin fibrous caps have a higher risk to rupture than fibrotic plaques. Elastic moduli differ for lipid-rich and fibrous tissue and can be reconstructed using tissue displacements estimated from intravascular ultrasound radiofrequency (RF) data acquisitions. This study investigated if modulus reconstruction is possible for noninvasive RF acquisitions of vessels in transverse imaging planes using an iterative 2D cross-correlation based displacement estimation algorithm. Furthermore, since it is known that displacements can be improved by compounding of displacements estimated at various beam steering angles, we compared the performance of the modulus reconstruction with and without compounding. For the comparison, simulated and experimental RF data were generated of various vessel-mimicking phantoms. Reconstruction errors were less than 10%, which seems adequate for distinguishing lipid-rich from fibrous tissue. Compounding outperformed single-angle reconstruction: the interquartile range of the reconstructed moduli for the various homogeneous phantom layers was approximately two times smaller. Additionally, the estimated lateral displacements were a factor of 2-3 better matched to the displacements corresponding to the reconstructed modulus distribution. Thus, noninvasive elastic modulus reconstruction is possible for transverse vessel cross sections using this cross-correlation method and is more accurate with compounding. PMID:23478602
Hansen, Hendrik H.G.; Richards, Michael S.; Doyley, Marvin M.; de Korte, Chris L.
2013-01-01
Atherosclerotic plaque rupture can initiate stroke or myocardial infarction. Lipid-rich plaques with thin fibrous caps have a higher risk to rupture than fibrotic plaques. Elastic moduli differ for lipid-rich and fibrous tissue and can be reconstructed using tissue displacements estimated from intravascular ultrasound radiofrequency (RF) data acquisitions. This study investigated if modulus reconstruction is possible for noninvasive RF acquisitions of vessels in transverse imaging planes using an iterative 2D cross-correlation based displacement estimation algorithm. Furthermore, since it is known that displacements can be improved by compounding of displacements estimated at various beam steering angles, we compared the performance of the modulus reconstruction with and without compounding. For the comparison, simulated and experimental RF data were generated of various vessel-mimicking phantoms. Reconstruction errors were less than 10%, which seems adequate for distinguishing lipid-rich from fibrous tissue. Compounding outperformed single-angle reconstruction: the interquartile range of the reconstructed moduli for the various homogeneous phantom layers was approximately two times smaller. Additionally, the estimated lateral displacements were a factor of 2–3 better matched to the displacements corresponding to the reconstructed modulus distribution. Thus, noninvasive elastic modulus reconstruction is possible for transverse vessel cross sections using this cross-correlation method and is more accurate with compounding. PMID:23478602
NASA Astrophysics Data System (ADS)
Rabbani, Arash; Ayatollahi, Shahab; Kharrat, Riyaz; Dashti, Nader
2016-08-01
In this study, we have utilized 3-D micro-tomography images of real and synthetic rocks to introduce two mathematical correlations which estimate the distribution parameters of 3-D coordination number using a single 2-D cross-sectional image. By applying a watershed segmentation algorithm, it is found that the distribution of 3-D coordination number is acceptably predictable by statistical analysis of the network extracted from 2-D images. In this study, we have utilized 25 volumetric images of rocks in order to propose two mathematical formulas. These formulas aim to approximate the average and standard deviation of coordination number in 3-D pore networks. Then, the formulas are applied for five independent test samples to evaluate the reliability. Finally, pore network flow modeling is used to find the error of absolute permeability prediction using estimated and measured coordination numbers. Results show that the 2-D images are considerably informative about the 3-D network of the rocks and can be utilized to approximate the 3-D connectivity of the porous spaces with determination coefficient of about 0.85 that seems to be acceptable considering the variety of the studied samples.
An enhanced CCRTM (E-CCRTM) damage imaging technique using a 2D areal scan for composite plates
NASA Astrophysics Data System (ADS)
He, Jiaze; Yuan, Fuh-Gwo
2016-04-01
A two-dimensional (2-D) non-contact areal scan system was developed to image and quantify impact damage in a composite plate using an enhanced zero-lag cross-correlation reverse-time migration (E-CCRTM) technique. The system comprises a single piezoelectric actuator mounted on the composite plate and a laser Doppler vibrometer (LDV) for scanning a region to capture the scattered wavefield in the vicinity of the PZT. The proposed damage imaging technique takes into account the amplitude, phase, geometric spreading, and all of the frequency content of the Lamb waves propagating in the plate; thus, the reflectivity coefficients of the delamination can be calculated and potentially related to damage severity. Comparisons are made in terms of damage imaging quality between 2-D areal scans and linear scans as well as between the proposed and existing imaging conditions. The experimental results show that the 2-D E-CCRTM performs robustly when imaging and quantifying impact damage in large-scale composites using a single PZT actuator with a nearby areal scan using LDV.
Synergistic image reconstruction for hybrid ultrasound and photoacoustic computed tomography
NASA Astrophysics Data System (ADS)
Matthews, Thomas P.; Wang, Kun; Wang, Lihong V.; Anastasio, Mark A.
2015-03-01
Conventional photoacoustic computed tomography (PACT) image reconstruction methods assume that the object and surrounding medium are described by a constant speed-of-sound (SOS) value. In order to accurately recover fine structures, SOS heterogeneities should be quantified and compensated for during PACT reconstruction. To address this problem, several groups have proposed hybrid systems that combine PACT with ultrasound computed tomography (USCT). In such systems, a SOS map is reconstructed first via USCT. Consequently, this SOS map is employed to inform the PACT reconstruction method. Additionally, the SOS map can provide structural information regarding tissue, which is complementary to the functional information from the PACT image. We propose a paradigm shift in the way that images are reconstructed in hybrid PACT-USCT imaging. Inspired by our observation that information about the SOS distribution is encoded in PACT measurements, we propose to jointly reconstruct the absorbed optical energy density and SOS distributions from a combined set of USCT and PACT measurements, thereby reducing the two reconstruction problems into one. This innovative approach has several advantages over conventional approaches in which PACT and USCT images are reconstructed independently: (1) Variations in the SOS will automatically be accounted for, optimizing PACT image quality; (2) The reconstructed PACT and USCT images will possess minimal systematic artifacts because errors in the imaging models will be optimally balanced during the joint reconstruction; (3) Due to the exploitation of information regarding the SOS distribution in the full-view PACT data, our approach will permit high-resolution reconstruction of the SOS distribution from sparse array data.
Oliveira-Santos, Thiago; Baumberger, Christian; Constantinescu, Mihai; Olariu, Radu; Nolte, Lutz-Peter; Alaraibi, Salman; Reyes, Mauricio
2013-05-01
The human face is a vital component of our identity and many people undergo medical aesthetics procedures in order to achieve an ideal or desired look. However, communication between physician and patient is fundamental to understand the patient's wishes and to achieve the desired results. To date, most plastic surgeons rely on either "free hand" 2D drawings on picture printouts or computerized picture morphing. Alternatively, hardware dependent solutions allow facial shapes to be created and planned in 3D, but they are usually expensive or complex to handle. To offer a simple and hardware independent solution, we propose a web-based application that uses 3 standard 2D pictures to create a 3D representation of the patient's face on which facial aesthetic procedures such as filling, skin clearing or rejuvenation, and rhinoplasty are planned in 3D. The proposed application couples a set of well-established methods together in a novel manner to optimize 3D reconstructions for clinical use. Face reconstructions performed with the application were evaluated by two plastic surgeons and also compared to ground truth data. Results showed the application can provide accurate 3D face representations to be used in clinics (within an average of 2 mm error) in less than 5 min. PMID:23319167
Active catheter tracking using parallel MRI and real-time image reconstruction.
Bock, Michael; Müller, Sven; Zuehlsdorff, Sven; Speier, Peter; Fink, Christian; Hallscheidt, Peter; Umathum, Reiner; Semmler, Wolfhard
2006-06-01
In this work active MR catheter tracking with automatic slice alignment was combined with an autocalibrated parallel imaging technique. Using an optimized generalized autocalibrating partially parallel acquisitions (GRAPPA) algorithm with an acceleration factor of 2, we were able to reduce the acquisition time per image by 34%. To accelerate real-time GRAPPA image reconstruction, the coil sensitivities were updated only after slice reorientation. For a 2D trueFISP acquisition (160 x 256 matrix, 80% phase matrix, half Fourier acquisition, TR = 3.7 ms, GRAPPA factor = 2) real-time image reconstruction was achieved with up to six imaging coils. In a single animal experiment the method was used to steer a catheter from the vena cava through the beating heart into the pulmonary vasculature at an image update rate of about five images per second. Under all slice orientations, parallel image reconstruction was accomplished with only minor image artifacts, and the increased temporal resolution provided a sharp delineation of intracardial structures, such as the papillary muscle. PMID:16683261
Initial Images of the Synthetic Aperture Radiometer 2D-STAR
Technology Transfer Automated Retrieval System (TEKTRAN)
Initial results obtained using a new synthetic aperture radiometer, 2D-STAR, a dual polarized, L-band radiometer that employs aperture synthesis in two dimensions are presented and analyzed. This airborne instrument is the natural evolution of a previous design that employed employs aperture synthes...
Numerical modelling and image reconstruction in diffuse optical tomography
Dehghani, Hamid; Srinivasan, Subhadra; Pogue, Brian W.; Gibson, Adam
2009-01-01
The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue. The application of model-based image reconstruction is reviewed in this paper, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data. A comprehensive review and details of the basis for using spatial and structural prior information are also discussed, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution. PMID:19581256
Reconstruction of biofilm images: combining local and global structural parameters.
Resat, Haluk; Renslow, Ryan S; Beyenal, Haluk
2014-10-01
Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parameters into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process. PMID:25377487
Undersampled MR Image Reconstruction with Data-Driven Tight Frame
Liu, Jianbo; Wang, Shanshan; Peng, Xi; Liang, Dong
2015-01-01
Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI. PMID:26199641
Research on THz CT system and image reconstruction algorithm
NASA Astrophysics Data System (ADS)
Li, Ming-liang; Wang, Cong; Cheng, Hong
2009-07-01
Terahertz Computed Tomography takes the advantages of not only high resolution in space and density without image overlap but also the capability of being directly used in digital processing and spectral analysis, which determine it to be a good choice in parameter detection for process control. But Diffraction and scattering of THz wave will obfuscate or distort the reconstructed image. In order to find the most effective reconstruction method to build THz CT model. Because of the expensive cost, a fan-shaped THz CT industrial detection system scanning model, which consists of 8 emitters and 32 receivers, is established based on studying infrared CT technology. The model contains control and interface, data collecting and image reconstruction sub-system. It analyzes all the sub-function modules then reconstructs images with algebraic reconstruction algorithm. The experimental result proves it to be an effective, efficient algorithm with high resolution and even better than back-projection method.
Reconstruction of biofilm images: combining local and global structural parameters
Resat, Haluk; Renslow, Ryan S.; Beyenal, Haluk
2014-11-07
Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parameters into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process.
Evaluation of back projection methods for breast tomosynthesis image reconstruction.
Zhou, Weihua; Lu, Jianping; Zhou, Otto; Chen, Ying
2015-06-01
Breast cancer is the most common cancer among women in the USA. Compared to mammography, digital breast tomosynthesis is a new imaging technique that may improve the diagnostic accuracy by removing the ambiguities of overlapped tissues and providing 3D information of the breast. Tomosynthesis reconstruction algorithms generate 3D reconstructed slices from a few limited angle projection images. Among different reconstruction algorithms, back projection (BP) is considered an important foundation of quite a few reconstruction techniques with deblurring algorithms such as filtered back projection. In this paper, two BP variants, including α-trimmed BP and principal component analysis-based BP, were proposed to improve the image quality against that of traditional BP. Computer simulations and phantom studies demonstrated that the α-trimmed BP may improve signal response performance and suppress noise in breast tomosynthesis image reconstruction. PMID:25384538
Calibration and Image Reconstruction for the Hurricane Imaging Radiometer (HIRAD)
NASA Technical Reports Server (NTRS)
Ruf, Christopher; Roberts, J. Brent; Biswas, Sayak; James, Mark W.; Miller, Timothy
2012-01-01
The Hurricane Imaging Radiometer (HIRAD) is a new airborne passive microwave synthetic aperture radiometer designed to provide wide swath images of ocean surface wind speed under heavy precipitation and, in particular, in tropical cyclones. It operates at 4, 5, 6 and 6.6 GHz and uses interferometric signal processing to synthesize a pushbroom imager in software from a low profile planar antenna with no mechanical scanning. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during Fall 2010 as its first science field campaign. HIRAD produced images of upwelling brightness temperature over a aprox 70 km swath width with approx 3 km spatial resolution. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The calibration and image reconstruction algorithms that were used to verify HIRAD functional performance during and immediately after GRIP were only preliminary and used a number of simplifying assumptions and approximations about the instrument design and performance. The development and performance of a more detailed and complete set of algorithms are reported here.
2D grating simulation for X-ray phase-contrast and dark-field imaging with a Talbot interferometer
NASA Astrophysics Data System (ADS)
Zanette, Irene; David, Christian; Rutishauser, Simon; Weitkamp, Timm
2010-04-01
Talbot interferometry is a recently developed and an extremely powerful X-ray phase-contrast imaging technique. Besides giving access to ultra-high sensitivity differential phase contrast images, it also provides the dark field image, which is a map of the scattering power of the sample. In this paper we investigate the potentialities of an improved version of the interferometer, in which two dimensional gratings are used instead of standard line grids. This approach allows to overcome the difficulties that might be encountered in the images produced by a one dimensional interferometer. Among these limitations there are the phase wrapping and quantitative phase retrieval problems and the directionality of the differential phase and dark-field signals. The feasibility of the 2D Talbot interferometer has been studied with a numerical simulation on the performances of its optical components under different circumstances. The gratings can be obtained either by an ad hoc fabrication of the 2D structures or by a superposition of two perpendicular linear grids. Through this simulation it has been possible to find the best parameters for a practical implementation of the 2D Talbot interferometer.
Towards real-time 2D/3D registration for organ motion monitoring in image-guided radiation therapy
NASA Astrophysics Data System (ADS)
Gendrin, C.; Spoerk, J.; Bloch, C.; Pawiro, S. A.; Weber, C.; Figl, M.; Markelj, P.; Pernus, F.; Georg, D.; Bergmann, H.; Birkfellner, W.
2010-02-01
Nowadays, radiation therapy systems incorporate kV imaging units which allow for the real-time acquisition of intra-fractional X-ray images of the patient with high details and contrast. An application of this technology is tumor motion monitoring during irradiation. For tumor tracking, implanted markers or position sensors are used which requires an intervention. 2D/3D intensity based registration is an alternative, non-invasive method but the procedure must be accelerate to the update rate of the device, which lies in the range of 5 Hz. In this paper we investigate fast CT to a single kV X-ray 2D/3D image registration using a new porcine reference phantom with seven implanted fiducial markers. Several parameters influencing the speed and accuracy of the registrations are investigated. First, four intensity based merit functions, namely Cross-Correlation, Rank Correlation, Mutual Information and Correlation Ratio, are compared. Secondly, wobbled splatting and ray casting rendering techniques are implemented on the GPU and the influence of each algorithm on the performance of 2D/3D registration is evaluated. Rendering times for a single DRR of 20 ms were achieved. Different thresholds of the CT volume were also examined for rendering to find the setting that achieves the best possible correspondence with the X-ray images. Fast registrations below 4 s became possible with an inplane accuracy down to 0.8 mm.
Li, Shu; Chan, Cheong; Stockmann, Jason P.; Tagare, Hemant; Adluru, Ganesh; Tam, Leo K.; Galiana, Gigi; Constable, R. Todd; Kozerke, Sebastian; Peters, Dana C.
2014-01-01
Purpose To investigate algebraic reconstruction technique (ART) for parallel imaging reconstruction of radial data, applied to accelerated cardiac cine. Methods A GPU-accelerated ART reconstruction was implemented and applied to simulations, point spread functions (PSF) and in twelve subjects imaged with radial cardiac cine acquisitions. Cine images were reconstructed with radial ART at multiple undersampling levels (192 Nr x Np = 96 to 16). Images were qualitatively and quantitatively analyzed for sharpness and artifacts, and compared to filtered back-projection (FBP), and conjugate gradient SENSE (CG SENSE). Results Radial ART provided reduced artifacts and mainly preserved spatial resolution, for both simulations and in vivo data. Artifacts were qualitatively and quantitatively less with ART than FBP using 48, 32, and 24 Np, although FBP provided quantitatively sharper images at undersampling levels of 48-24 Np (all p<0.05). Use of undersampled radial data for generating auto-calibrated coil-sensitivity profiles resulted in slightly reduced quality. ART was comparable to CG SENSE. GPU-acceleration increased ART reconstruction speed 15-fold, with little impact on the images. Conclusion GPU-accelerated ART is an alternative approach to image reconstruction for parallel radial MR imaging, providing reduced artifacts while mainly maintaining sharpness compared to FBP, as shown by its first application in cardiac studies. PMID:24753213
NASA Astrophysics Data System (ADS)
Feygelman, V.; Nelms, B.
2013-06-01
As IMRT technology continues to evolve, so do the dosimetric QA methods. A historical review of those is presented, starting with longstanding techniques such as film and ion chamber in a phantom and progressing towards 3D and 4D dose reconstruction in the patient. Regarding patient-specific QA, we envision that the currently prevalent limited comparison of dose distributions in the phantom by γ-analysis will be eventually replaced by clinically meaningful patient dose analyses with improved sensitivity and specificity. In a larger sense, we envision a future of QA built upon lessons from the rich history of "quality" as a science and philosophy. This future will aim to improve quality (and ultimately reduce cost) via advanced commissioning processes that succeed in detecting and rooting out systematic errors upstream of patient treatment, thus reducing our reliance on, and the resource burden associated with, per-beam/per-plan inspection.
Chord-based image reconstruction from clinical projection data
NASA Astrophysics Data System (ADS)
King, Martin; Xia, Dan; Pan, Xiaochuan; Vannier, Michael; Köhler, Thomas; La Riviére, Patrick; Sidky, Emil; Giger, Maryellen
2008-03-01
Chord-based algorithms can eliminate cone-beam artifacts in images reconstructed from a clinical computed tomography (CT) scanner. The feasibility of using chord-based reconstruction algorithms was evaluated with three clinical CT projection data sets. The first projection data set was acquired using a clinical 64-channel CT scanner (Philips Brilliance 64) that consisted of an axial scan from a quality assurance phantom. Images were reconstructed using (1) a full-scan FDK algorithm, (2) a short-scan FDK algorithm, and (3) the chord-based backprojection filtration algorithm (BPF) using full-scan data. The BPF algorithm was capable of reproducing the morphology of the phantom quite well, but exhibited significantly less noise than the two FDK reconstructions as well as the reconstruction obtained from the clinical scanner. The second and third data sets were obtained from scans of a head phantom and a patient's thorax. For both of these data sets, the BPF reconstructions were comparable to the short-scan FDK reconstructions in terms of image quality, although sharper features were indistinct in the BPF reconstructions. This research demonstrates the feasibility of chord-based algorithms for reconstructing images from clinical CT projection data sets and provides a framework for implementing and testing algorithmic innovations.
Super-Resolution Image Reconstruction Using Diffuse Source Models
Ellis, Michael A.; Viola, Francesco; Walker, William F.
2010-01-01
Image reconstruction is central to many scientific fields, from medical ultrasound and sonar to computed tomography and computer vision. While lenses play a critical reconstruction role in these fields, digital sensors enable more sophisticated computational approaches. A variety of computational methods have thus been developed, with the common goal of increasing contrast and resolution to extract the greatest possible information from raw data. This paper describes a new image reconstruction method named the Diffuse Time-domain Optimized Near-field Estimator (dTONE). dTONE represents each hypothetical target in the system model as a diffuse region of targets rather than a single discrete target, which more accurately represents the experimental data that arise from signal sources in continuous space, with no additional computational requirements at the time of image reconstruction. Simulation and experimental ultrasound images of animal tissues show that dTONE achieves image resolution and contrast far superior to those of conventional image reconstruction methods. We also demonstrate the increased robustness of the diffuse target model to major sources of image degradation, through the addition of electronic noise, phase aberration, and magnitude aberration to ultrasound simulations. Using experimental ultrasound data from a tissue-mimicking phantom containing a 3 mm diameter anechoic cyst, the conventionally reconstructed image has a cystic contrast of −6.3 dB whereas the dTONE image has a cystic contrast of −14.4 dB. PMID:20447760
Super-resolution image reconstruction using diffuse source models.
Ellis, Michael A; Viola, Francesco; Walker, William F
2010-06-01
Image reconstruction is central to many scientific fields, from medical ultrasound and sonar to computed tomography and computer vision. Although lenses play a critical reconstruction role in these fields, digital sensors enable more sophisticated computational approaches. A variety of computational methods have thus been developed, with the common goal of increasing contrast and resolution to extract the greatest possible information from raw data. This paper describes a new image reconstruction method named the Diffuse Time-domain Optimized Near-field Estimator (dTONE). dTONE represents each hypothetical target in the system model as a diffuse region of targets rather than a single discrete target, which more accurately represents the experimental data that arise from signal sources in continuous space, with no additional computational requirements at the time of image reconstruction. Simulation and experimental ultrasound images of animal tissues show that dTONE achieves image resolution and contrast far superior to those of conventional image reconstruction methods. We also demonstrate the increased robustness of the diffuse target model to major sources of image degradation through the addition of electronic noise, phase aberration and magnitude aberration to ultrasound simulations. Using experimental ultrasound data from a tissue-mimicking phantom containing a 3-mm-diameter anechoic cyst, the conventionally reconstructed image has a cystic contrast of -6.3 dB, whereas the dTONE image has a cystic contrast of -14.4 dB. PMID:20447760
On multigrid methods for image reconstruction from projections
Henson, V.E.; Robinson, B.T.; Limber, M.
1994-12-31
The sampled Radon transform of a 2D function can be represented as a continuous linear map R : L{sup 1} {yields} R{sup N}. The image reconstruction problem is: given a vector b {element_of} R{sup N}, find an image (or density function) u(x, y) such that Ru = b. Since in general there are infinitely many solutions, the authors pick the solution with minimal 2-norm. Numerous proposals have been made regarding how best to discretize this problem. One can, for example, select a set of functions {phi}{sub j} that span a particular subspace {Omega} {contained_in} L{sup 1}, and model R : {Omega} {yields} R{sup N}. The subspace {Omega} may be chosen as a member of a sequence of subspaces whose limit is dense in L{sup 1}. One approach to the choice of {Omega} gives rise to a natural pixel discretization of the image space. Two possible choices of the set {phi}{sub j} are the set of characteristic functions of finite-width `strips` representing energy transmission paths and the set of intersections of such strips. The authors have studied the eigenstructure of the matrices B resulting from these choices and the effect of applying a Gauss-Seidel iteration to the problem Bw = b. There exists a near null space into which the error vectors migrate with iteration, after which Gauss-Seidel iteration stalls. The authors attempt to accelerate convergence via a multilevel scheme, based on the principles of McCormick`s Multilevel Projection Method (PML). Coarsening is achieved by thickening the rays which results in a much smaller discretization of an optimal grid, and a halving of the number of variables. This approach satisfies all the requirements of the PML scheme. They have observed that a multilevel approach based on this idea accelerates convergence at least to the point where noise in the data dominates.
High-resolution image reconstruction for PET using estimated detector response functions
NASA Astrophysics Data System (ADS)
Tohme, Michel S.; Qi, Jinyi
2007-02-01
The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed PET images. For efficient computation in reconstruction, the system model in PET can be factored into a product of geometric projection matrix and detector blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. In this work, we propose a method to estimate the 2D detector blurring matrix from experimental measurements. Point source data were acquired with high-count statistics in the microPET II scanner using a computer-controlled 2-D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner with the modeling of the detector block structure. Since the resulting blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo simulation. Reconstructed images of a line source phantom show improved resolution with the new detector blurring matrix compared to the original one from the Monte Carlo simulation. This method can be applied to other small-animal and clinical scanners.
2-D/3-D ECE imaging data for validation of turbulence simulations
NASA Astrophysics Data System (ADS)
Choi, Minjun; Lee, Jaehyun; Yun, Gunsu; Lee, Woochang; Park, Hyeon K.; Park, Young-Seok; Sabbagh, Steve A.; Wang, Weixing; Luhmann, Neville C., Jr.
2015-11-01
The 2-D/3-D KSTAR ECEI diagnostic can provide a local 2-D/3-D measurement of ECE intensity. Application of spectral analysis techniques to the ECEI data allows local estimation of frequency spectra S (f) , wavenumber spectra S (k) , wavernumber and frequency spectra S (k , f) , and bispectra b (f1 ,f2) of ECE intensity over the 2-D/3-D space, which can be used to validate turbulence simulations. However, the minimum detectable fluctuation amplitude and the maximum detectable wavenumber are limited by the temporal and spatial resolutions of the diagnostic system, respectively. Also, the finite measurement area of the diagnostic channel could introduce uncertainty in the spectra estimation. The limitations and accuracy of the ECEI estimated spectra have been tested by a synthetic ECEI diagnostic with the model and/or fluctuations calculated by GTS. Supported by the NRF of Korea under Contract No. NRF-2014M1A7A1A03029881 and NRF-2014M1A7A1A03029865 and by U.S. DOE grant DE-FG02-99ER54524.
Quantitative image quality evaluation for cardiac CT reconstructions
NASA Astrophysics Data System (ADS)
Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.; Balhorn, William; Okerlund, Darin R.
2016-03-01
Maintaining image quality in the presence of motion is always desirable and challenging in clinical Cardiac CT imaging. Different image-reconstruction algorithms are available on current commercial CT systems that attempt to achieve this goal. It is widely accepted that image-quality assessment should be task-based and involve specific tasks, observers, and associated figures of merits. In this work, we developed an observer model that performed the task of estimating the percentage of plaque in a vessel from CT images. We compared task performance of Cardiac CT image data reconstructed using a conventional FBP reconstruction algorithm and the SnapShot Freeze (SSF) algorithm, each at default and optimal reconstruction cardiac phases. The purpose of this work is to design an approach for quantitative image-quality evaluation of temporal resolution for Cardiac CT systems. To simulate heart motion, a moving coronary type phantom synchronized with an ECG signal was used. Three different percentage plaques embedded in a 3 mm vessel phantom were imaged multiple times under motion free, 60 bpm, and 80 bpm heart rates. Static (motion free) images of this phantom were taken as reference images for image template generation. Independent ROIs from the 60 bpm and 80 bpm images were generated by vessel tracking. The observer performed estimation tasks using these ROIs. Ensemble mean square error (EMSE) was used as the figure of merit. Results suggest that the quality of SSF images is superior to the quality of FBP images in higher heart-rate scans.
Iterative image reconstruction techniques: cardiothoracic computed tomography applications.
Cho, Young Jun; Schoepf, U Joseph; Silverman, Justin R; Krazinski, Aleksander W; Canstein, Christian; Deak, Zsuzsanna; Grimm, Jochen; Geyer, Lucas L
2014-07-01
Iterative image reconstruction algorithms provide significant improvements over traditional filtered back projection in computed tomography (CT). Clinically available through recent advances in modern CT technology, iterative reconstruction enhances image quality through cyclical image calculation, suppressing image noise and artifacts, particularly blooming artifacts. The advantages of iterative reconstruction are apparent in traditionally challenging cases-for example, in obese patients, those with significant artery calcification, or those with coronary artery stents. In addition, as clinical use of CT has grown, so have concerns over ionizing radiation associated with CT examinations. Through noise reduction, iterative reconstruction has been shown to permit radiation dose reduction while preserving diagnostic image quality. This approach is becoming increasingly attractive as the routine use of CT for pediatric and repeated follow-up evaluation grows ever more common. Cardiovascular CT in particular, with its focus on detailed structural and functional analyses, stands to benefit greatly from the promising iterative solutions that are readily available. PMID:24662334
Adaptive clutter filter in 2-D color flow imaging based on in vivo I/Q signal.
Zhou, Xiaoming; Zhang, Congyao; Liu, Dong C
2014-01-01
Color flow imaging has been well applied in clinical diagnosis. For the high quality color flow images, clutter filter is important to separate the Doppler signals from blood and tissue. Traditional clutter filters, such as finite impulse response, infinite impulse response and regression filters, were applied, which are based on the hypothesis that the clutter signal is stationary or tissue moves slowly. However, in realistic clinic color flow imaging, the signals are non-stationary signals because of accelerated moving tissue. For most related papers, simulated RF signals are widely used without in vivo I/Q signal. Hence, in this paper, adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, was proposed based on in vivo carotid I/Q signal in realistic color flow imaging. To get the best performance, the optimal polynomial order of polynomial regression filter and the optimal polynomial order for estimation of instantaneous clutter frequency respectively were confirmed. Finally, compared with the mean blood velocity and quality of 2-D color flow image, the experiment results show that adaptive polynomial regression filter, which is down mixing with instantaneous clutter frequency, can significantly enhance the mean blood velocity and get high quality 2-D color flow image. PMID:24211911
Subramanian, K R; Thubrikar, M J; Fowler, B; Mostafavi, M T; Funk, M W
2000-01-01
We present a technique that accurately reconstructs complex three dimensional blood vessel geometry from 2D intravascular ultrasound (IVUS) images. Biplane x-ray fluoroscopy is used to image the ultrasound catheter tip at a few key points along its path as the catheter is pulled through the blood vessel. An interpolating spline describes the continuous catheter path. The IVUS images are located orthogonal to the path, resulting in a non-uniform structured scalar volume of echo densities. Isocontour surfaces are used to view the vessel geometry, while transparency and clipping enable interactive exploration of interior structures. The two geometries studied are a bovine artery vascular graft having U-shape and a constriction, and a canine carotid artery having multiple branches and a constriction. Accuracy of the reconstructions is established by comparing the reconstructions to (1) silicone moulds of the vessel interior, (2) biplane x-ray images, and (3) the original echo images. Excellent shape and geometry correspondence was observed in both geometries. Quantitative measurements made at key locations of the 3D reconstructions also were in good agreement with those made in silicone moulds. The proposed technique is easily adoptable in clinical practice, since it uses x-rays with minimal exposure and existing IVUS technology. PMID:11105284
NASA Astrophysics Data System (ADS)
Aizenberg, Evgeni; Bigio, Irving J.; Rodriguez-Diaz, Eladio
2012-03-01
The Fourier descriptors paradigm is a well-established approach for affine-invariant characterization of shape contours. In the work presented here, we extend this method to images, and obtain a 2D Fourier representation that is invariant to image rotation. The proposed technique retains phase uniqueness, and therefore structural image information is not lost. Rotation-invariant phase coefficients were used to train a single multi-valued neuron (MVN) to recognize satellite and human face images rotated by a wide range of angles. Experiments yielded 100% and 96.43% classification rate for each data set, respectively. Recognition performance was additionally evaluated under effects of lossy JPEG compression and additive Gaussian noise. Preliminary results show that the derived rotation-invariant features combined with the MVN provide a promising scheme for efficient recognition of rotated images.
Takata, Tadanori; Ichikawa, Katsuhiro; Hayashi, Hiroyuki; Mitsui, Wataru; Sakuta, Keita; Koshida, Haruka; Yokoi, Tomohiro; Matsubara, Kousuke; Horii, Jyunsei; Iida, Hiroji
2012-01-01
The purpose of this study was to evaluate the image quality of an iterative reconstruction method, the iterative reconstruction in image space (IRIS), which was implemented in a 128-slices multi-detector computed tomography system (MDCT), Siemens Somatom Definition Flash (Definition). We evaluated image noise by standard deviation (SD) as many researchers did before, and in addition, we measured modulation transfer function (MTF), noise power spectrum (NPS), and perceptual low-contrast detectability using a water phantom including a low-contrast object with a 10 Hounsfield unit (HU) contrast, to evaluate whether the noise reduction of IRIS was effective. The SD and NPS were measured from the images of a water phantom. The MTF was measured from images of a thin metal wire and a bar pattern phantom with the bar contrast of 125 HU. The NPS of IRIS was lower than that of filtered back projection (FBP) at middle and high frequency regions. The SD values were reduced by 21%. The MTF of IRIS and FBP measured by the wire phantom coincided precisely. However, for the bar pattern phantom, the MTF values of IRIS at 0.625 and 0.833 cycle/mm were lower than those of FBP. Despite the reduction of the SD and the NPS, the low-contrast detectability study indicated no significant difference between IRIS and FBP. From these results, it was demonstrated that IRIS had the noise reduction performance with exact preservation for high contrast resolution and slight degradation of middle contrast resolution, and could slightly improve the low contrast detectability but with no significance. PMID:22516592
NASA Astrophysics Data System (ADS)
Gao, Mingliang; Teng, Qizhi; He, Xiaohai; Zuo, Chen; Li, ZhengJi
2016-01-01
Three-dimensional (3D) structures are useful for studying the spatial structures and physical properties of porous media. A 3D structure can be reconstructed from a single two-dimensional (2D) training image (TI) by using mathematical modeling methods. Among many reconstruction algorithms, an optimal-based algorithm was developed and has strong stability. However, this type of algorithm generally uses an autocorrelation function (which is unable to accurately describe the morphological features of porous media) as its objective function. This has negatively affected further research on porous media. To accurately reconstruct 3D porous media, a pattern density function is proposed in this paper, which is based on a random variable employed to characterize image patterns. In addition, the paper proposes an original optimal-based algorithm called the pattern density function simulation; this algorithm uses a pattern density function as its objective function, and adopts a multiple-grid system. Meanwhile, to address the key point of algorithm reconstruction speed, we propose the use of neighborhood statistics, the adjacent grid and reversed phase method, and a simplified temperature-controlled mechanism. The pattern density function is a high-order statistical function; thus, when all grids in the reconstruction results converge in the objective functions, the morphological features and statistical properties of the reconstruction results will be consistent with those of the TI. The experiments include 2D reconstruction using one artificial structure, and 3D reconstruction using battery materials and cores. Hierarchical simulated annealing and single normal equation simulation are employed as the comparison algorithms. The autocorrelation function, linear path function, and pore network model are used as the quantitative measures. Comprehensive tests show that 3D porous media can be reconstructed accurately from a single 2D training image by using the method proposed
SART-Type Image Reconstruction from Overlapped Projections
Yu, Hengyong; Ji, Changguo; Wang, Ge
2011-01-01
To maximize the time-integrated X-ray flux from multiple X-ray sources and shorten the data acquisition process, a promising way is to allow overlapped projections from multiple sources being simultaneously on without involving the source multiplexing technology. The most challenging task in this configuration is to perform image reconstruction effectively and efficiently from overlapped projections. Inspired by the single-source simultaneous algebraic reconstruction technique (SART), we hereby develop a multisource SART-type reconstruction algorithm regularized by a sparsity-oriented constraint in the soft-threshold filtering framework to reconstruct images from overlapped projections. Our numerical simulation results verify the correctness of the proposed algorithm and demonstrate the advantage of image reconstruction from overlapped projections. PMID:20871854
Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image
Guo, Jingyu; Qi, Hongliang; Xu, Yuan; Chen, Zijia; Li, Shulong; Zhou, Linghong
2016-01-01
Limited-angle computed tomography (CT) has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction performance but has not been studied deeply yet. In this work, we proposed to generate optimized initial image followed by total variation (TV) based iterative reconstruction considering the feature of image symmetry. The simulated data and real data reconstruction results indicate that the proposed method effectively removes the artifacts nearby edges. PMID:27066107
Calibration model of a dual gain flat panel detector for 2D and 3D x-ray imaging
Schmidgunst, C.; Ritter, D.; Lang, E.
2007-09-15
The continuing research and further development in flat panel detector technology have led to its integration into more and more medical x-ray systems for two-dimensional (2D) and three-dimensional (3D) imaging, such as fixed or mobile C arms. Besides the obvious advantages of flat panel detectors, like the slim design and the resulting optimum accessibility to the patient, their success is primarily a product of the image quality that can be achieved. The benefits in the physical and performance-related features as opposed to conventional image intensifier systems (e.g., distortion-free reproduction of imaging information or almost linear signal response over a large dynamic range) can be fully exploited, however, only if the raw detector images are correctly calibrated and postprocessed. Previous procedures for processing raw data contain idealizations that, in the real world, lead to artifacts or losses in image quality. Thus, for example, temperature dependencies or changes in beam geometry, as can occur with mobile C arm systems, have not been taken into account up to this time. Additionally, adverse characteristics such as image lag or aging effects have to be compensated to attain the best possible image quality. In this article a procedure is presented that takes into account the important dependencies of the individual pixel sensitivity of flat panel detectors used in 2D or 3D imaging and simultaneously minimizes the work required for an extensive recalibration. It is suitable for conventional detectors with only one gain mode as well as for the detectors specially developed for 3D imaging with dual gain read-out technology.
Sparsity-constrained PET image reconstruction with learned dictionaries.
Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie
2016-09-01
PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging. PMID:27494441
MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods
Schmidt, Johannes F. M.; Santelli, Claudio; Kozerke, Sebastian
2016-01-01
An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675
MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods.
Schmidt, Johannes F M; Santelli, Claudio; Kozerke, Sebastian
2016-01-01
An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675
Sparsity-constrained PET image reconstruction with learned dictionaries
NASA Astrophysics Data System (ADS)
Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie
2016-09-01
PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging.
Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis
Dehghan, Ehsan; Moradi, Mehdi; Wen, Xu; French, Danny; Lobo, Julio; Morris, W. James; Salcudean, Septimiu E.; Fichtinger, Gabor
2011-10-15
Purpose: Accurate localization of prostate implants from several C-arm images is necessary for ultrasound-fluoroscopy fusion and intraoperative dosimetry. The authors propose a computational motion compensation method for tomosynthesis-based reconstruction that enables 3D localization of prostate implants from C-arm images despite C-arm oscillation and sagging. Methods: Five C-arm images are captured by rotating the C-arm around its primary axis, while measuring its rotation angle using a protractor or the C-arm joint encoder. The C-arm images are processed to obtain binary seed-only images from which a volume of interest is reconstructed. The motion compensation algorithm, iteratively, compensates for 2D translational motion of the C-arm by maximizing the number of voxels that project on a seed projection in all of the images. This obviates the need for C-arm full pose tracking traditionally implemented using radio-opaque fiducials or external trackers. The proposed reconstruction method is tested in simulations, in a phantom study and on ten patient data sets. Results: In a phantom implanted with 136 dummy seeds, the seed detection rate was 100% with a localization error of 0.86 {+-} 0.44 mm (Mean {+-} STD) compared to CT. For patient data sets, a detection rate of 99.5% was achieved in approximately 1 min per patient. The reconstruction results for patient data sets were compared against an available matching-based reconstruction method and showed relative localization difference of 0.5 {+-} 0.4 mm. Conclusions: The motion compensation method can successfully compensate for large C-arm motion without using radio-opaque fiducial or external trackers. Considering the efficacy of the algorithm, its successful reconstruction rate and low computational burden, the algorithm is feasible for clinical use.
Infrared Astronomical Satellite (IRAS) image reconstruction and restoration
NASA Technical Reports Server (NTRS)
Gonsalves, R. A.; Lyons, T. D.; Price, S. D.; Levan, P. D.; Aumann, H. H.
1987-01-01
IRAS sky mapping data is being reconstructed as images, and an entropy-based restoration algorithm is being applied in an attempt to improve spatial resolution in extended sources. Reconstruction requires interpolation of non-uniformly sampled data. Restoration is accomplished with an iterative algorithm which begins with an inverse filter solution and iterates on it with a weighted entropy-based spectral subtraction.
Fast reconstruction of digital tomosynthesis using on-board images
Yan Hui; Godfrey, Devon J.; Yin Fangfang
2008-05-15
Digital tomosynthesis (DTS) is a method to reconstruct pseudo three-dimensional (3D) volume images from two-dimensional x-ray projections acquired over limited scan angles. Compared with cone-beam computed tomography, which is frequently used for 3D image guided radiation therapy, DTS requires less imaging time and dose. Successful implementation of DTS for fast target localization requires the reconstruction process to be accomplished within tight clinical time constraints (usually within 2 min). To achieve this goal, substantial improvement of reconstruction efficiency is necessary. In this study, a reconstruction process based upon the algorithm proposed by Feldkamp, Davis, and Kress was implemented on graphics hardware for the purpose of acceleration. The performance of the novel reconstruction implementation was tested for phantom and real patient cases. The efficiency of DTS reconstruction was improved by a factor of 13 on average, without compromising image quality. With acceleration of the reconstruction algorithm, the whole DTS generation process including data preprocessing, reconstruction, and DICOM conversion is accomplished within 1.5 min, which ultimately meets clinical requirement for on-line target localization.
Microphysical Analysis using Airborne 2-D Cloud and Precipitation Imaging Probe Data
NASA Astrophysics Data System (ADS)
Guy, N.; Jorgensen, D.; Witte, M.; Chuang, P. Y.; Black, R. A.
2013-12-01
The NOAA P-3 instrumented aircraft provided in-situ cloud and precipitation microphysical observations during the DYNAMO (Dynamics of the Madden-Julian Oscillation) field experiment. The Particle Measuring System 2D cloud (2D-C) and precipitation (2D-P) probes collected data for particles between 12.5 μm - 1.55 mm (25 μm resolution) and 100 μm - 6.2 mm (100 μm resolution), respectively. Spectra from each instrument were combined to provide a broad distribution of precipitation particle sizes. The 'method of moments' technique was used to analyze drop size distribution (DSD) spectra, which were modeled by fitting a three-parameter (slope, shape, and intercept) gamma distribution to the spectra. The characteristic shape of the mean spectrum compares to previous maritime measurements. DSD variability will be presented with respect to the temporal evolution of cloud populations during a Madden-Julian Oscillation (MJO) event, as well as in-situ aircraft vertical wind velocity measurements. Using the third and sixth moments, rainfall rate (R) and equivalent radar reflectivity factor (Z), respectively, were computed for each DSD. Linear regression was applied to establish a Z-R relationship for the data for the estimation of precipitation. The study indicated unique characteristics of microphysical processes for this region. These results are important to continue to define the cloud population characteristics in the climatological MJO region. Improved representation of the cloud characteristics on the microphysical scale will serve as a check to model parameterizations, helping to improve numerical simulations.
Curve-based 2D-3D registration of coronary vessels for image guided procedure
NASA Astrophysics Data System (ADS)
Duong, Luc; Liao, Rui; Sundar, Hari; Tailhades, Benoit; Meyer, Andreas; Xu, Chenyang
2009-02-01
3D roadmap provided by pre-operative volumetric data that is aligned with fluoroscopy helps visualization and navigation in Interventional Cardiology (IC), especially when contrast agent-injection used to highlight coronary vessels cannot be systematically used during the whole procedure, or when there is low visibility in fluoroscopy for partially or totally occluded vessels. The main contribution of this work is to register pre-operative volumetric data with intraoperative fluoroscopy for specific vessel(s) occurring during the procedure, even without contrast agent injection, to provide a useful 3D roadmap. In addition, this study incorporates automatic ECG gating for cardiac motion. Respiratory motion is identified by rigid body registration of the vessels. The coronary vessels are first segmented from a multislice computed tomography (MSCT) volume and correspondent vessel segments are identified on a single gated 2D fluoroscopic frame. Registration can be explicitly constrained using one or multiple branches of a contrast-enhanced vessel tree or the outline of guide wire used to navigate during the procedure. Finally, the alignment problem is solved by Iterative Closest Point (ICP) algorithm. To be computationally efficient, a distance transform is computed from the 2D identification of each vessel such that distance is zero on the centerline of the vessel and increases away from the centerline. Quantitative results were obtained by comparing the registration of random poses and a ground truth alignment for 5 datasets. We conclude that the proposed method is promising for accurate 2D-3D registration, even for difficult cases of occluded vessel without injection of contrast agent.
NASA Astrophysics Data System (ADS)
Saxena, Nishank; Mavko, Gary
2016-03-01
Estimation of elastic rock moduli using 2D plane strain computations from thin sections has several numerical and analytical advantages over using 3D rock images, including faster computation, smaller memory requirements, and the availability of cheap thin sections. These advantages, however, must be weighed against the estimation accuracy of 3D rock properties from thin sections. We present a new method for predicting elastic properties of natural rocks using thin sections. Our method is based on a simple power-law transform that correlates computed 2D thin section moduli and the corresponding 3D rock moduli. The validity of this transform is established using a dataset comprised of FEM-computed elastic moduli of rock samples from various geologic formations, including Fontainebleau sandstone, Berea sandstone, Bituminous sand, and Grossmont carbonate. We note that using the power-law transform with a power-law coefficient between 0.4-0.6 contains 2D moduli to 3D moduli transformations for all rocks that are considered in this study. We also find that reliable estimates of P-wave (Vp) and S-wave velocity (Vs) trends can be obtained using 2D thin sections.
NASA Astrophysics Data System (ADS)
Prior, Phillip; Roth, Bradley J.
2009-05-01
Optical mapping is a commonly used technique to visualize the electrical activity in the heart. Recently, several groups have attempted to use the signals acquired in optical mapping to image the transmembrane potential in the heart, which would be particularly advantageous when studying the effects of defibrillation-type shocks throughout the wall of the heart. Our work presents an alternative imaging method that makes use of data obtained using multiple wavelengths and therefore multiple optical decay constants. A modified form of the diffusion equation Green's function for a semi-infinite slab of tissue is derived and used to relate the detected optical signals to the source of emission photons. Images using the optical signals are reconstructed using Gaussian quadrature and matrix inversion. Our results show that images can be obtained for source terms located below the tissue surface. Furthermore, we demonstrate that our reconstruction method's susceptibility to noise can be alleviated using sophisticated matrix inverse techniques, such as singular value decomposition. Sources that rapidly decay with depth or are highly localized in the image plane require more sophisticated techniques (e.g., regularization methods) to image the electrical activity in the heart. The work presented here demonstrates the feasibility of a new imaging technique of cardiac electrical activity using optical mapping.
Reconstructing liver shape and position from MR image slices using an active shape model
NASA Astrophysics Data System (ADS)
Fenchel, Matthias; Thesen, Stefan; Schilling, Andreas
2008-03-01
We present an algorithm for fully automatic reconstruction of 3D position, orientation and shape of the human liver from a sparsely covering set of n 2D MR slice images. Reconstructing the shape of an organ from slice images can be used for scan planning, for surgical planning or other purposes where 3D anatomical knowledge has to be inferred from sparse slices. The algorithm is based on adapting an active shape model of the liver surface to a given set of slice images. The active shape model is created from a training set of liver segmentations from a group of volunteers. The training set is set up with semi-manual segmentations of T1-weighted volumetric MR images. Searching for the optimal shape model that best fits to the image data is done by maximizing a similarity measure based on local appearance at the surface. Two different algorithms for the active shape model search are proposed and compared: both algorithms seek to maximize the a-posteriori probability of the grey level appearance around the surface while constraining the surface to the space of valid shapes. The first algorithm works by using grey value profile statistics in normal direction. The second algorithm uses average and variance images to calculate the local surface appearance on the fly. Both algorithms are validated by fitting the active shape model to abdominal 2D slice images and comparing the shapes, which have been reconstructed, to the manual segmentations and to the results of active shape model searches from 3D image data. The results turn out to be promising and competitive to active shape model segmentations from 3D data.
NASA Astrophysics Data System (ADS)
Maeda, Takuto; Nishida, Kiwamu; Takagi, Ryota; Obara, Kazushige
2016-04-01
The high-sensitive seismograph network (Hi-net) operated by National Research Institute for Earth Science and Disaster Prevention (NIED) has about 800 stations with average separation of 20 km all over the Japanese archipelago. Although it is equipped with short-period seismometers, we also can observe long-period seismic wave up to 100 s in periods for significantly large earthquakes. In this case, we may treat long-period seismic waves as a 2D wavefield with station separations shorter than wavelength rather than individual traces at stations. In this study, we attempt to reconstruct 2D wavefield and obtain its propagation properties from seismic gradiometry (SG) method. The SG estimates the wave amplitude and its spatial derivative coefficients from discrete station record by the Taylor series approximation with an inverse problem. By using spatial derivatives in horizontal directions, we can obtain properties of propagating wave packet such as the arrival direction, slowness, geometrical spreading and radiation pattern. In addition, by using spatial derivatives together with free-surface boundary condition, we may decompose the vector elastic 2D wavefield estimated by the SG into divergence and rotation components. First, we applied the seismic gradiometry to a synthetic long-period (20-50 s) seismogram dataset computed by numerical simulation in realistic 3D medium at the Hi-net station layout as a feasibility test. We confirmed that the wave amplitude and its spatial derivatives are very well reproduced with average correlation coefficients higher than 0.99 in this period range. Applications to a real large earthquakes show that the amplitude and phase of the wavefield are well reconstructed with additional information of arrival direction and its slowness. The reconstructed wavefield contained a clear contrast in slowness between body and surface waves, regional non-great-circle-path wave propagation which may be attributed to scattering. Slowness
Image reconstruction in transcranial photoacoustic computed tomography of the brain
NASA Astrophysics Data System (ADS)
Mitsuhashi, Kenji; Wang, Lihong V.; Anastasio, Mark A.
2015-03-01
Photoacoustic computed tomography (PACT) holds great promise for transcranial brain imaging. However, the strong reflection, scattering, attenuation, and mode-conversion of photoacoustic waves in the skull pose serious challenges to establishing the method. The lack of an appropriate model of solid media in conventional PACT imaging models, which are based on the canonical scalar wave equation, causes a significant model mismatch in the presence of the skull and thus results in deteriorated reconstructed images. The goal of this study was to develop an image reconstruction algorithm that accurately models the skull and thereby ameliorates the quality of reconstructed images. The propagation of photoacoustic waves through the skull was modeled by a viscoelastic stress tensor wave equation, which was subsequently discretized by use of a staggered grid fourth-order finite-difference time-domain (FDTD) method. The matched adjoint of the FDTD-based wave propagation operator was derived for implementing a back-projection operator. Systematic computer simulations were conducted to demonstrate the effectiveness of the back-projection operator for reconstructing images in a realistic three-dimensional PACT brain imaging system. The results suggest that the proposed algorithm can successfully reconstruct images from transcranially-measured pressure data and readily be translated to clinical PACT brain imaging applications.
Compressed sensing sparse reconstruction for coherent field imaging
NASA Astrophysics Data System (ADS)
Bei, Cao; Xiu-Juan, Luo; Yu, Zhang; Hui, Liu; Ming-Lai, Chen
2016-04-01
Return signal processing and reconstruction plays a pivotal role in coherent field imaging, having a significant influence on the quality of the reconstructed image. To reduce the required samples and accelerate the sampling process, we propose a genuine sparse reconstruction scheme based on compressed sensing theory. By analyzing the sparsity of the received signal in the Fourier spectrum domain, we accomplish an effective random projection and then reconstruct the return signal from as little as 10% of traditional samples, finally acquiring the target image precisely. The results of the numerical simulations and practical experiments verify the correctness of the proposed method, providing an efficient processing approach for imaging fast-moving targets in the future. Project supported by the National Natural Science Foundation of China (Grant No. 61505248) and the Fund from Chinese Academy of Sciences, the Light of “Western” Talent Cultivation Plan “Dr. Western Fund Project” (Grant No. Y429621213).
Compressed Sensing Inspired Image Reconstruction from Overlapped Projections
Yang, Lin; Lu, Yang; Wang, Ge
2010-01-01
The key idea discussed in this paper is to reconstruct an image from overlapped projections so that the data acquisition process can be shortened while the image quality remains essentially uncompromised. To perform image reconstruction from overlapped projections, the conventional reconstruction approach (e.g., filtered backprojection (FBP) algorithms) cannot be directly used because of two problems. First, overlapped projections represent an imaging system in terms of summed exponentials, which cannot be transformed into a linear form. Second, the overlapped measurement carries less information than the traditional line integrals. To meet these challenges, we propose a compressive sensing-(CS-) based iterative algorithm for reconstruction from overlapped data. This algorithm starts with a good initial guess, relies on adaptive linearization, and minimizes the total variation (TV). Then, we demonstrated the feasibility of this algorithm in numerical tests. PMID:20689701
Online reconstruction of 3D magnetic particle imaging data
NASA Astrophysics Data System (ADS)
Knopp, T.; Hofmann, M.
2016-06-01
Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s‑1. However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time.
Online reconstruction of 3D magnetic particle imaging data.
Knopp, T; Hofmann, M
2016-06-01
Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s(-1). However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time. PMID:27182668
Exponential filtering of singular values improves photoacoustic image reconstruction.
Bhatt, Manish; Gutta, Sreedevi; Yalavarthy, Phaneendra K
2016-09-01
Model-based image reconstruction techniques yield better quantitative accuracy in photoacoustic image reconstruction. In this work, an exponential filtering of singular values was proposed for carrying out the image reconstruction in photoacoustic tomography. The results were compared with widely popular Tikhonov regularization, time reversal, and the state of the art least-squares QR-based reconstruction algorithms for three digital phantom cases with varying signal-to-noise ratios of data. It was shown that exponential filtering provides superior photoacoustic images of better quantitative accuracy. Moreover, the proposed filtering approach was observed to be less biased toward the regularization parameter and did not come with any additional computational burden as it was implemented within the Tikhonov filtering framework. It was also shown that the standard Tikhonov filtering becomes an approximation to the proposed exponential filtering. PMID:27607501
Munbodh, Reshma; Tagare, Hemant D.; Chen Zhe; Jaffray, David A.; Moseley, Douglas J.; Knisely, Jonathan P. S.; Duncan, James S.
2009-10-15
Purpose: In external beam radiation therapy of pelvic sites, patient setup errors can be quantified by registering 2D projection radiographs acquired during treatment to a 3D planning computed tomograph (CT). We present a 2D-3D registration framework based on a statistical model of the intensity values in the two imaging modalities. Methods: The model assumes that intensity values in projection radiographs are independently but not identically distributed due to the nonstationary nature of photon counting noise. Two probability distributions are considered for the intensity values: Poisson and Gaussian. Using maximum likelihood estimation, two similarity measures, maximum likelihood with a Poisson (MLP) and maximum likelihood with Gaussian (MLG), distribution are derived. Further, we investigate the merit of the model-based registration approach for data obtained with current imaging equipment and doses by comparing the performance of the similarity measures derived to that of the Pearson correlation coefficient (ICC) on accurately collected data of an anthropomorphic phantom of the pelvis and on patient data. Results: Registration accuracy was similar for all three similarity measures and surpassed current clinical requirements of 3 mm for pelvic sites. For pose determination experiments with a kilovoltage (kV) cone-beam CT (CBCT) and kV projection radiographs of the phantom in the anterior-posterior (AP) view, registration accuracies were 0.42 mm (MLP), 0.29 mm (MLG), and 0.29 mm (ICC). For kV CBCT and megavoltage (MV) AP portal images of the same phantom, registration accuracies were 1.15 mm (MLP), 0.90 mm (MLG), and 0.69 mm (ICC). Registration of a kV CT and MV AP portal images of a patient was successful in all instances. Conclusions: The results indicate that high registration accuracy is achievable with multiple methods including methods that are based on a statistical model of a 3D CT and 2D projection images.
Infrared imaging of 2-D temperature distribution during cryogen spray cooling.
Choi, Bernard; Welch, Ashley J
2002-12-01
Cryogen spray cooling (CSC) is used in conjunction with pulsed laser irradiation for treatment of dermatologic indications. The main goal of this study was to determine the radial temperature distribution created by CSC and evaluate the importance of radial temperature gradients upon the subsequent analysis of tissue cooling throughout the skin. Since direct measurement of surface temperatures during CSC are hindered by the formation of a liquid cryogen layer, temperature distributions were estimated using a thin, black aluminum sheet. An infrared focal plane array camera was used to determine the 2-D backside temperature distribution during a cryogen spurt, which preliminary measurements have shown is a good indicator of the front-side temperature distribution. The measured temperature distribution was approximately gaussian in shape. Next, the transient temperature distributions in skin were calculated for two cases: 1) the standard 1-D solution which assumes a uniform cooling temperature distribution, and 2) a 2-D solution using a nonuniform surface cooling temperature distribution based upon the back-side infrared temperature measurements. At the end of a 100-ms cryogen spurt, calculations showed that, for the two cases, large discrepancies in temperatures at the surface and at a 60-micron depth were found at radii greater than 2.5 mm. These results suggest that it is necessary to consider radial temperature gradients during cryogen spray cooling of tissue. PMID:12596634
Iterative Stable Alignment and Clustering of 2D Transmission Electron Microscope Images
Yang, Zhengfan; Fang, Jia; Chittuluru, Johnathan; Asturias, Francisco J.; Penczek, Pawel A.
2012-01-01
SUMMARY Identification of homogeneous subsets of images in a macromolecular electron microscopy (EM) image data set is a critical step in single-particle analysis. The task is handled by iterative algorithms, whose performance is compromised by the compounded limitations of image alignment and K-means clustering. Here we describe an approach, iterative stable alignment and clustering (ISAC) that, relying on a new clustering method and on the concepts of stability and reproducibility, can extract validated, homogeneous subsets of images. ISAC requires only a small number of simple parameters and, with minimal human intervention, can eliminate bias from two-dimensional image clustering and maximize the quality of group averages that can be used for ab initio three-dimensional structural determination and analysis of macromolecular conformational variability. Repeated testing of the stability and reproducibility of a solution within ISAC eliminates heterogeneous or incorrect classes and introduces critical validation to the process of EM image clustering. PMID:22325773
ISAKOS classification of meniscal tears-illustration on 2D and 3D isotropic spin echo MR imaging.
Wadhwa, Vibhor; Omar, Hythem; Coyner, Katherine; Khazzam, Michael; Robertson, William; Chhabra, Avneesh
2016-01-01
Magnetic Resonance Imaging is modality of choice for the non-invasive evaluation of meniscal tears. Accurate and uniform documentation of meniscal pathology is necessary for optimal multi-disciplinary communication, to guide treatment options and for validation of patient outcomes studies. The increasingly used ISAKOS arthroscopic meniscus tear classification system has been shown to provide sufficient interobserver reliability among the surgeons. However, the terminology is not in common use in the radiology world. In this article, the authors discuss the MR imaging appearances of meniscal tears based on ISAKOS classification on 2D and multiplanar 3D isotropic spin echo imaging techniques and illustrate the correlations of various meniscal pathologies with relevant arthroscopic images. PMID:26724644
Reconstruction algorithms for optoacoustic imaging based on fiber optic detectors
NASA Astrophysics Data System (ADS)
Lamela, Horacio; Díaz-Tendero, Gonzalo; Gutiérrez, Rebeca; Gallego, Daniel
2011-06-01
Optoacoustic Imaging (OAI), a novel hybrid imaging technology, offers high contrast, molecular specificity and excellent resolution to overcome limitations of the current clinical modalities for detection of solid tumors. The exact time-domain reconstruction formula produces images with excellent resolution but poor contrast. Some approximate time-domain filtered back-projection reconstruction algorithms have also been reported to solve this problem. A wavelet transform implementation filtering can be used to sharpen object boundaries while simultaneously preserving high contrast of the reconstructed objects. In this paper, several algorithms, based on Back Projection (BP) techniques, have been suggested to process OA images in conjunction with signal filtering for ultrasonic point detectors and integral detectors. We apply these techniques first directly to a numerical generated sample image and then to the laserdigitalized image of a tissue phantom, obtaining in both cases the best results in resolution and contrast for a waveletbased filter.
Three-dimensional surface reconstruction from multistatic SAR images.
Rigling, Brian D; Moses, Randolph L
2005-08-01
This paper discusses reconstruction of three-dimensional surfaces from multiple bistatic synthetic aperture radar (SAR) images. Techniques for surface reconstruction from multiple monostatic SAR images already exist, including interferometric processing and stereo SAR. We generalize these methods to obtain algorithms for bistatic interferometric SAR and bistatic stereo SAR. We also propose a framework for predicting the performance of our multistatic stereo SAR algorithm, and, from this framework, we suggest a metric for use in planning strategic deployment of multistatic assets. PMID:16121463
Beyond maximum entropy: Fractal Pixon-based image reconstruction
NASA Technical Reports Server (NTRS)
Puetter, Richard C.; Pina, R. K.
1994-01-01
We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other competing methods, including Goodness-of-Fit methods such as Least-Squares fitting and Lucy-Richardson reconstruction, as well as Maximum Entropy (ME) methods such as those embodied in the MEMSYS algorithms. Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME. Our past work has shown how uniform information content pixons can be used to develop a 'Super-ME' method in which entropy is maximized exactly. Recently, however, we have developed a superior pixon basis for the image, the Fractal Pixon Basis (FPB). Unlike the Uniform Pixon Basis (UPB) of our 'Super-ME' method, the FPB basis is selected by employing fractal dimensional concepts to assess the inherent structure in the image. The Fractal Pixon Basis results in the best image reconstructions to date, superior to both UPB and the best ME reconstructions. In this paper, we review the theory of the UPB and FPB pixon and apply our methodology to the reconstruction of far-infrared imaging of the galaxy M51. The results of our reconstruction are compared to published reconstructions of the same data using the Lucy-Richardson algorithm, the Maximum Correlation Method developed at IPAC, and the MEMSYS ME algorithms. The results show that our reconstructed image has a spatial resolution a factor of two better than best previous methods (and a factor of 20 finer than the width of the point response function), and detects sources two orders of magnitude fainter than other methods.
Sarkar, Soham; Das, Swagatam
2013-12-01
Multilevel thresholding amounts to segmenting a gray-level image into several distinct regions. This paper presents a 2D histogram based multilevel thresholding approach to improve the separation between objects. Recent studies indicate that the results obtained with 2D histogram oriented approaches are superior to those obtained with 1D histogram based techniques in the context of bi-level thresholding. Here, a method to incorporate 2D histogram related information for generalized multilevel thresholding is proposed using the maximum Tsallis entropy. Differential evolution (DE), a simple yet efficient evolutionary algorithm of current interest, is employed to improve the computational efficiency of the proposed method. The performance of DE is investigated extensively through comparison with other well-known nature inspired global optimization techniques such as genetic algorithm, particle swarm optimization, artificial bee colony, and simulated annealing. In addition, the outcome of the proposed method is evaluated using a well known benchmark--the Berkley segmentation data set (BSDS300) with 300 distinct images. PMID:23955760
The speckle image reconstruction of the solar small scale features
NASA Astrophysics Data System (ADS)
Zhong, Libo; Tian, Yu; Rao, Changhui
2014-11-01
The resolution of the astronomical object observed by the earth-based telescope is limited due to the atmospheric turbulence. Speckle image reconstruction method provides access to detect small-scale solar features near the diffraction limit of the telescope. This paper describes the implementation of the reconstruction of images obtained by the 1-m new vacuum solar telescope at Full-Shine solar observatory. Speckle masking method is used to reconstruct the Fourier phases for its better dynamic range and resolution capabilities. Except of the phase reconstruction process, several problems encounter in the solar image reconstruction are discussed. The details of the implement including the flat-field, image segmentation, Fried parameter estimation and noise filter estimating are described particularly. It is demonstrated that the speckle image reconstruction is effective to restore the wide field of view images. The qualities of the restorations are evaluated by the contrast ratio. When the Fried parameter is 10cm, the contrast ratio of the sunspot and granulation can be improved from 0.3916 to 0.6845 and from 0.0248 to 0.0756 respectively.
Implementation of a new multiple monochromatic x-ray 2D imager at NIF
NASA Astrophysics Data System (ADS)
Kyrala, G. A.; Martinson, D.; Polk, P. J.; Gravlin, T.; Schmitt, M. J.; Johnson, R.; Murphy, T. J.; Lopez, F. E.; Oertel, J. A.; House, A.; Wood, R.; Lee, J.; Haugh, M.
2013-09-01
We will describe the installation and wavelength calibration of a multiple monochromatic imager [MMI]1 to be used on mix experiments at National Ignition Facility [NIF]2. The imager works between 8 and 13 keV, has a spatial resolution of 16 micrometers and generates many images each with an energy bandwidth of ~80 eV. The images are recorded either on image plates or on gated x-ray detectors. We will describe: how we aligned the instrument on the bench using visible light, how we checked the alignment and determined the energy range using a k-alpha x-ray source, and how we installed and aligned the instrument to the NIF target chamber.
Enhanced 2D-image upconversion using solid-state lasers.
Pedersen, Christian; Karamehmedović, Emir; Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter
2009-11-01
Based on enhanced upconversion, we demonstrate a highly efficient method for converting a full image from one part of the electromagnetic spectrum into a new desired wavelength region. By illuminating a metal transmission mask with a 765 nm Gaussian beam to create an image and subsequently focusing the image inside a nonlinear PPKTP crystal located in the high intra-cavity field of a 1342 nm solid-state Nd:YVO(4) laser, an upconverted image at 488 nm is generated. We have experimentally achieved an upconversion efficiency of 40% under CW conditions. The proposed technique can be further adapted for high efficiency mid-infrared image upconversion where direct and fast detection is difficult or impossible to perform with existing detector technologies. PMID:19997325
Experimental validation of 2D uncertainty quantification for digital image correlation.
Reu, Phillip L.
2010-03-01
Because digital image correlation (DIC) has become such an important and standard tool in the toolbox of experimental mechanicists, a complete uncertainty quantification of the method is needed. It should be remembered that each DIC setup and series of images will have a unique uncertainty based on the calibration quality and the image and speckle quality of the analyzed images. Any pretest work done with a calibrated DIC stereo-rig to quantify the errors using known shapes and translations, while useful, do not necessarily reveal the uncertainty of a later test. This is particularly true with high-speed applications where actual test images are often less than ideal. Work has previously been completed on the mathematical underpinnings of DIC uncertainty quantification and is already published, this paper will present corresponding experimental work used to check the validity of the uncertainty equations.
Munbodh, Reshma; Chen Zhe; Jaffray, David A.; Moseley, Douglas J.; Knisely, Jonathan P. S.; Duncan, James S.
2007-07-15
In many radiotherapy clinics, geometric uncertainties in the delivery of 3D conformal radiation therapy and intensity modulated radiation therapy of the prostate are reduced by aligning the patient's bony anatomy in the planning 3D CT to corresponding bony anatomy in 2D portal images acquired before every treatment fraction. In this paper, we seek to determine if there is a frequency band within the portal images and the digitally reconstructed radiographs (DRRs) of the planning CT in which bony anatomy predominates over non-bony anatomy such that portal images and DRRs can be suitably filtered to achieve high registration accuracy in an automated 2D-3D single portal intensity-based registration framework. Two similarity measures, mutual information and the Pearson correlation coefficient were tested on carefully collected gold-standard data consisting of a kilovoltage cone-beam CT (CBCT) and megavoltage portal images in the anterior-posterior (AP) view of an anthropomorphic phantom acquired under clinical conditions at known poses, and on patient data. It was found that filtering the portal images and DRRs during the registration considerably improved registration performance. Without filtering, the registration did not always converge while with filtering it always converged to an accurate solution. For the pose-determination experiments conducted on the anthropomorphic phantom with the correlation coefficient, the mean (and standard deviation) of the absolute errors in recovering each of the six transformation parameters were {theta}{sub x}:0.18(0.19) deg., {theta}{sub y}:0.04(0.04) deg., {theta}{sub z}:0.04(0.02) deg., t{sub x}:0.14(0.15) mm, t{sub y}:0.09(0.05) mm, and t{sub z}:0.49(0.40) mm. The mutual information-based registration with filtered images also resulted in similarly small errors. For the patient data, visual inspection of the superimposed registered images showed that they were correctly aligned in all instances. The results presented in this
Reconstruction Techniques for Sparse Multistatic Linear Array Microwave Imaging
Sheen, David M.; Hall, Thomas E.
2014-06-09
Sequentially-switched linear arrays are an enabling technology for a number of near-field microwave imaging applications. Electronically sequencing along the array axis followed by mechanical scanning along an orthogonal axis allows dense sampling of a two-dimensional aperture in near real-time. In this paper, a sparse multi-static array technique will be described along with associated Fourier-Transform-based and back-projection-based image reconstruction algorithms. Simulated and measured imaging results are presented that show the effectiveness of the sparse array technique along with the merits and weaknesses of each image reconstruction approach.
Method for image reconstruction of moving radionuclide source distribution
Stolin, Alexander V.; McKisson, John E.; Lee, Seung Joon; Smith, Mark Frederick
2012-12-18
A method for image reconstruction of moving radionuclide distributions. Its particular embodiment is for single photon emission computed tomography (SPECT) imaging of awake animals, though its techniques are general enough to be applied to other moving radionuclide distributions as well. The invention eliminates motion and blurring artifacts for image reconstructions of moving source distributions. This opens new avenues in the area of small animal brain imaging with radiotracers, which can now be performed without the perturbing influences of anesthesia or physical restraint on the biological system.
NASA Astrophysics Data System (ADS)
Uneri, A.; Stayman, J. W.; De Silva, T.; Wang, A. S.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Wolinsky, J.-P.; Gokaslan, Z. L.; Siewerdsen, J. H.
2015-03-01
Purpose. To extend the functionality of radiographic / fluoroscopic imaging systems already within standard spine surgery workflow to: 1) provide guidance of surgical device analogous to an external tracking system; and 2) provide intraoperative quality assurance (QA) of the surgical product. Methods. Using fast, robust 3D-2D registration in combination with 3D models of known components (surgical devices), the 3D pose determination was solved to relate known components to 2D projection images and 3D preoperative CT in near-real-time. Exact and parametric models of the components were used as input to the algorithm to evaluate the effects of model fidelity. The proposed algorithm employs the covariance matrix adaptation evolution strategy (CMA-ES) to maximize gradient correlation (GC) between measured projections and simulated forward projections of components. Geometric accuracy was evaluated in a spine phantom in terms of target registration error at the tool tip (TREx), and angular deviation (TREΦ) from planned trajectory. Results. Transpedicle surgical devices (probe tool and spine screws) were successfully guided with TREx<2 mm and TREΦ <0.5° given projection views separated by at least >30° (easily accommodated on a mobile C-arm). QA of the surgical product based on 3D-2D registration demonstrated the detection of pedicle screw breach with TREx<1 mm, demonstrating a trend of improved accuracy correlated to the fidelity of the component model employed. Conclusions. 3D-2D registration combined with 3D models of known surgical components provides a novel method for near-real-time guidance and quality assurance using a mobile C-arm without external trackers or fiducial markers. Ongoing work includes determination of optimal views based on component shape and trajectory, improved robustness to anatomical deformation, and expanded preclinical testing in spine and intracranial surgeries.
Ertas, Metin; Yildirim, Isa; Kamasak, Mustafa; Akan, Aydin
2016-02-01
In this work, algebraic reconstruction technique (ART) is extended by using non-local means (NLM) and total variation (TV) for reduction of artifacts that are due to insufficient projection data. TV and NLM algorithms use different image models and their application in tandem becomes a powerful denoising method that reduces erroneous variations in the image while preserving edges and details. Simulations were performed on a widely used 2D Shepp-Logan phantom to demonstrate performance of the introduced method (ART + TV) NLM and compare it to TV based ART (ART + TV) and ART. The results indicate that (ART + TV) NLM achieves better reconstructions compared to (ART + TV) and ART. PMID:26890898
Padhi, Shantanu K.; Howard, John
2013-01-01
Nonlinear microwave imaging heavily relies on an accurate numerical electromagnetic model of the antenna system. The model is used to simulate scattering data that is compared to its measured counterpart in order to reconstruct the image. In this paper an antenna system immersed in water is used to image different canonical objects in order to investigate the implication of modeling errors on the final reconstruction using a time domain-based iterative inverse reconstruction algorithm and three-dimensional FDTD modeling. With the test objects immersed in a background of air and tap water, respectively, we have studied the impact of antenna modeling errors, errors in the modeling of the background media, and made a comparison with a two-dimensional version of the algorithm. In conclusion even small modeling errors in the antennas can significantly alter the reconstructed image. Since the image reconstruction procedure is highly nonlinear general conclusions are very difficult to make. In our case it means that with the antenna system immersed in water and using our present FDTD-based electromagnetic model the imaging results are improved if refraining from modeling the water-wall-air interface and instead just use a homogeneous background of water in the model. PMID:23606825
Rashwan, Shaheera; Sarhan, Amany; Faheem, Muhamed Talaat; Youssef, Bayumy A
2015-01-01
Detection and quantification of protein spots is an important issue in the analysis of two-dimensional electrophoresis images. However, there is a main challenge in the segmentation of 2DGE images which is to separate overlapping protein spots correctly and to find the weak protein spots. In this paper, we describe a new robust technique to segment and model the different spots present in the gels. The watershed segmentation algorithm is modified to handle the problem of over-segmentation by initially partitioning the image to mosaic regions using the composition of fuzzy relations. The experimental results showed the effectiveness of the proposed algorithm to overcome the over segmentation problem associated with the available algorithm. We also use a wavelet denoising function to enhance the quality of the segmented image. The results of using a denoising function before the proposed fuzzy watershed segmentation algorithm is promising as they are better than those without denoising. PMID:26510287
Fuzzy-rule-based image reconstruction for positron emission tomography
NASA Astrophysics Data System (ADS)
Mondal, Partha P.; Rajan, K.
2005-09-01
Positron emission tomography (PET) and single-photon emission computed tomography have revolutionized the field of medicine and biology. Penalized iterative algorithms based on maximum a posteriori (MAP) estimation eliminate noisy artifacts by utilizing available prior information in the reconstruction process but often result in a blurring effect. MAP-based algorithms fail to determine the density class in the reconstructed image and hence penalize the pixels irrespective of the density class. Reconstruction with better edge information is often difficult because prior knowledge is not taken into account. The recently introduced median-root-prior (MRP)-based algorithm preserves the edges, but a steplike streaking effect is observed in the reconstructed image, which is undesirable. A fuzzy approach is proposed for modeling the nature of interpixel interaction in order to build an artifact-free edge-preserving reconstruction. The proposed algorithm consists of two elementary steps: (1) edge detection, in which fuzzy-rule-based derivatives are used for the detection of edges in the nearest neighborhood window (which is equivalent to recognizing nearby density classes), and (2) fuzzy smoothing, in which penalization is performed only for those pixels for which no edge is detected in the nearest neighborhood. Both of these operations are carried out iteratively until the image converges. Analysis shows that the proposed fuzzy-rule-based reconstruction algorithm is capable of producing qualitatively better reconstructed images than those reconstructed by MAP and MRP algorithms. The reconstructed images are sharper, with small features being better resolved owing to the nature of the fuzzy potential function.
A novel method to acquire 3D data from serial 2D images of a dental cast
NASA Astrophysics Data System (ADS)
Yi, Yaxing; Li, Zhongke; Chen, Qi; Shao, Jun; Li, Xinshe; Liu, Zhiqin
2007-05-01
This paper introduced a newly developed method to acquire three-dimensional data from serial two-dimensional images of a dental cast. The system consists of a computer and a set of data acquiring device. The data acquiring device is used to take serial pictures of the a dental cast; an artificial neural network works to translate two-dimensional pictures to three-dimensional data; then three-dimensional image can reconstruct by the computer. The three-dimensional data acquiring of dental casts is the foundation of computer-aided diagnosis and treatment planning in orthodontics.
Sparse-Coding-Based Computed Tomography Image Reconstruction
Yoon, Gang-Joon
2013-01-01
Computed tomography (CT) is a popular type of medical imaging that generates images of the internal structure of an object based on projection scans of the object from several angles. There are numerous methods to reconstruct the original shape of the target object from scans, but they are still dependent on the number of angles and iterations. To overcome the drawbacks of iterative reconstruction approaches like the algebraic reconstruction technique (ART), while the recovery is slightly impacted from a random noise (small amount of ℓ2 norm error) and projection scans (small amount of ℓ1 norm error) as well, we propose a medical image reconstruction methodology using the properties of sparse coding. It is a very powerful matrix factorization method which each pixel point is represented as a linear combination of a small number of basis vectors. PMID:23576898
Matrix-based image reconstruction methods for tomography
Llacer, J.; Meng, J.D.
1984-10-01
Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures.
Digital holographic method for tomography-image reconstruction
NASA Astrophysics Data System (ADS)
Liu, Cheng; Yan, Changchun; Gao, Shumei
2004-02-01
A digital holographic method for three-dimensional reconstruction of tomography images is demonstrated theoretically and experimentally. In this proposed method, a numerical hologram is first computed by calculating the total diffraction field of all transect images of a detected organ. Then, the numerical hologram is transferred to the usual recording medium to generate a physical hologram. Last, all the transect images are reconstructed in their original position by illuminating the physical hologram with a laser, thereby forming a three-dimensional transparent image of the organ detected. Due to its true third dimension, the reconstructed image using this method is much more vivid and accurate than that of other methods. Potentially, it may have great prospects for application in medical engineering.
Compensation for air voids in photoacoustic computed tomography image reconstruction
NASA Astrophysics Data System (ADS)
Matthews, Thomas P.; Li, Lei; Wang, Lihong V.; Anastasio, Mark A.
2016-03-01
Most image reconstruction methods in photoacoustic computed tomography (PACT) assume that the acoustic properties of the object and the surrounding medium are homogeneous. This can lead to strong artifacts in the reconstructed images when there are significant variations in sound speed or density. Air voids represent a particular challenge due to the severity of the differences between the acoustic properties of air and water. In whole-body small animal imaging, the presence of air voids in the lungs, stomach, and gastrointestinal system can limit image quality over large regions of the object. Iterative reconstruction methods based on the photoacoustic wave equation can account for these acoustic variations, leading to improved resolution, improved contrast, and a reduction in the number of imaging artifacts. However, the strong acoustic heterogeneities can lead to instability or errors in the numerical wave solver. Here, the impact of air voids on PACT image reconstruction is investigated, and procedures for their compensation are proposed. The contributions of sound speed and density variations to the numerical stability of the wave solver are considered, and a novel approach for mitigating the impact of air voids while reducing the computational burden of image reconstruction is identified. These results are verified by application to an experimental phantom.
NASA Astrophysics Data System (ADS)
Seidel, Anne; Wagner, Steven; Dreizler, Andreas; Ebert, Volker
2013-04-01
.9 ppmv?m??Hz. For absorption path lengths of up to 2 m and time resolution of 0.2 sec, we attained detection limits of 1 ppmv. Furthermore we realized a wide dynamic range covering concentrations between 200 ppmv and 12300 ppmv. The static spectrometer will now be extended to a spatially scanning TDL sensor using rapidly rotating polygon mirrors. In combination with tomographic reconstruction methods, spatially resolved 2D-fields will be measured and retrieved. The aim is to capture concentration fields with at least 1 m2 spatial coverage with concentration detection faster than 1 Hz rate. We simulated various measurements from typical concentration distributions ("phantoms") and used Algebraic Reconstruction Techniques (ART) to compute the according 2D-fields. The reconstructions look very promising and demonstrate the potential of the measurement method. In the presentation we will describe and discuss the optical setup of the stationary instrument and explain the concept of extending this instrument to a spatially scanning tomographic TDL instrument for soil studies. Further we present first results evaluating the capabilities of the selected ART reconstruction on tomographic phantoms. [1] E. Schuur, J. G. Vogel, K. G. Crummer, H. Lee, J. O. Sickman, and T. E. Osterkamp, "The effect of permafrost thaw on old carbon release and net carbon exchange from tundra.," Nature, vol. 459, no. 7246, pp. 556-9, May 2009. [2] A. Seidel, S. Wagner, and V. Ebert, "TDLAS-based open-path laser hygrometer using simple reflective foils as scattering targets," Applied Physics B, vol. 109, no. 3, pp. 497-504, Oct. 2012.
Information Propagation in Prior-Image-Based Reconstruction
Stayman, J. Webster; Prince, Jerry L.; Siewerdsen, Jeffrey H.
2016-01-01
Advanced reconstruction methods for computed tomography include sophisticated forward models of the imaging system that capture the pertinent physical processes affecting the signal and noise in projection measurements. However, most do little to integrate prior knowledge of the subject – often relying only on very general notions of local smoothness or edges. In many cases, as in longitudinal surveillance or interventional imaging, a patient has undergone a sequence of studies prior to the current image acquisition that hold a wealth of prior information on patient-specific anatomy. While traditional techniques tend to treat each data acquisition as an isolated event and disregard such valuable patient-specific prior information, some reconstruction methods, such as PICCS[1] and PIR-PLE[2], can incorporate prior images into a reconstruction objective function. Inclusion of such information allows for dramatic reduction in the data fidelity requirements and more robustly accommodate substantial undersampling and exposure reduction with consequent benefits to imaging speed and reduced radiation dose. While such prior-image-based methods offer tremendous promise, the introduction of prior information in the reconstruction raises significant concern regarding the accurate representation of features in the image and whether those features arise from the current data acquisition or from the prior images. In this work we propose a novel framework to analyze the propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by the current data acquisition and by the prior image. This decomposition quantifies the contributions from prior and current data as a spatial map and can trace specific features in the image to their source. Such “information source maps” can potentially be used as a check on confidence that a given image feature arises from the current data or from the prior and to more
Tracking contrast agents using real-time 2D photoacoustic imaging system for cardiac applications
NASA Astrophysics Data System (ADS)
Olafsson, Ragnar; Montilla, Leonardo; Ingram, Pier; Witte, Russell S.
2009-02-01
Photoacoustic (PA) imaging is a rapidly developing imaging modality that can detect optical contrast agents with high sensitivity. While detectors in PA imaging have traditionally been single element ultrasound transducers, use of array systems is desirable because they potentially provide high frame rates to capture dynamic events, such as injection and distribution of contrast in clinical applications. We present preliminary data consisting of 40 second sequences of coregistered pulse-echo (PE) and PA images acquired simultaneously in real time using a clinical ultrasonic machine. Using a 7 MHz linear array, the scanner allowed simultaneous acquisition of inphase-quadrature (IQ) data on 64 elements at a rate limited by the illumination source (Q-switched laser at 20 Hz) with spatial resolution determined to be 0.6 mm (axial) and 0.4 mm (lateral). PA images had a signal-to-noise ratio of approximately 35 dB without averaging. The sequences captured the injection and distribution of an infrared-absorbing contrast agent into a cadaver rat heart. From these data, a perfusion time constant of 0.23 s-1 was estimated. After further refinement, the system will be tested in live animals. Ultimately, an integrated system in the clinic could facilitate inexpensive molecular screening for coronary artery disease.
Hodge, Adam C; Fenster, Aaron; Downey, Dónal B; Ladak, Hanif M
2006-12-01
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm based on two-dimensional (2D) active shape models (ASM) for semi-automatic segmentation of the prostate boundary from ultrasound images. Optimisation of the 2D ASM for prostatic ultrasound was done first by examining ASM construction and image search parameters. Extension of the algorithm to three-dimensional (3D) segmentation was then done using rotational-based slicing. Evaluation of the 3D segmentation algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. Minimum description length landmark placement for ASM construction, and specific values for constraints and image search were found to be optimal. Evaluation of the algorithm versus gold standard boundaries found an average mean absolute distance of 1.09+/-0.49 mm, an average percent absolute volume difference of 3.28+/-3.16%, and a 5x speed increase versus manual segmentation. PMID:16930764
NASA Astrophysics Data System (ADS)
Straatsma, Menno; Huthoff, Fredrik
2011-01-01
In The Netherlands, 2D-hydrodynamic simulations are used to evaluate the effect of potential safety measures against river floods. In the investigated scenarios, the floodplains are completely inundated, thus requiring realistic representations of hydraulic roughness of floodplain vegetation. The current study aims at providing better insight into the uncertainty of flood water levels due to uncertain floodplain roughness parameterization. The study focuses on three key elements in the uncertainty of floodplain roughness: (1) classification error of the landcover map, (2), within class variation of vegetation structural characteristics, and (3) mapping scale. To assess the effect of the first error source, new realizations of ecotope maps were made based on the current floodplain ecotope map and an error matrix of the classification. For the second error source, field measurements of vegetation structure were used to obtain uncertainty ranges for each vegetation structural type. The scale error was investigated by reassigning roughness codes on a smaller spatial scale. It is shown that classification accuracy of 69% leads to an uncertainty range of predicted water levels in the order of decimeters. The other error sources are less relevant. The quantification of the uncertainty in water levels can help to make better decisions on suitable flood protection measures. Moreover, the relation between uncertain floodplain roughness and the error bands in water levels may serve as a guideline for the desired accuracy of floodplain characteristics in hydrodynamic models.
NASA Astrophysics Data System (ADS)
Ali, Nisa'; Saad, Rosli; Muztaza, Nordiana M.; Ismail, Noer E. H.
2013-05-01
The purpose of this study was to locate the geological contact using 2D resistivity method for Light Rail Transit (LRT) track alignment. The resistivity method was conducted on eight survey lines with the length of line 1 was 600m. The length of line 2, 3, 4, 5, 6, and 7 were 200m each while line 8 is 115m. All the survey used minimum electrode spacing of 5m and using Pole-dipole array with minimum current is 2mA and maximum was 20mA. The result obtained from the pseudosection showed that the area generally divided into three main zones, fill materials/residual soil with a resistivity value of <500 Ωm, saturated zone with a resistivity value of 30-100 Ωm and bedrock with a resistivity value of >2000 Ωm. Three fractured zones were detected along line L1 and a lot of boulders were detected at L1, L3, L4, L5 and L6. The geological contact was between the residual soil and granite bedrock.
Accurate Angle Estimator for High-Frame-Rate 2-D Vector Flow Imaging.
Villagomez Hoyos, Carlos Armando; Stuart, Matthias Bo; Hansen, Kristoffer Lindskov; Nielsen, Michael Bachmann; Jensen, Jorgen Arendt
2016-06-01
This paper presents a novel approach for estimating 2-D flow angles using a high-frame-rate ultrasound method. The angle estimator features high accuracy and low standard deviation (SD) over the full 360° range. The method is validated on Field II simulations and phantom measurements using the experimental ultrasound scanner SARUS and a flow rig before being tested in vivo. An 8-MHz linear array transducer is used with defocused beam emissions. In the simulations of a spinning disk phantom, a 360° uniform behavior on the angle estimation is observed with a median angle bias of 1.01° and a median angle SD of 1.8°. Similar results are obtained on a straight vessel for both simulations and measurements, where the obtained angle biases are below 1.5° with SDs around 1°. Estimated velocity magnitudes are also kept under 10% bias and 5% relative SD in both simulations and measurements. An in vivo measurement is performed on a carotid bifurcation of a healthy individual. A 3-s acquisition during three heart cycles is captured. A consistent and repetitive vortex is observed in the carotid bulb during systoles. PMID:27093598
Machine Learning of Hierarchical Clustering to Segment 2D and 3D Images
Nunez-Iglesias, Juan; Kennedy, Ryan; Parag, Toufiq; Shi, Jianbo; Chklovskii, Dmitri B.
2013-01-01
We aim to improve segmentation through the use of machine learning tools during region agglomeration. We propose an active learning approach for performing hierarchical agglomerative segmentation from superpixels. Our method combines multiple features at all scales of the agglomerative process, works for data with an arbitrary number of dimensions, and scales to very large datasets. We advocate the use of variation of information to measure segmentation accuracy, particularly in 3D electron microscopy (EM) images of neural tissue, and using this metric demonstrate an improvement over competing algorithms in EM and natural images. PMID:23977123
Chen, C.T.; Metz, C.E.
1984-01-01
Positron emission tomographic systems capable of time-of-flight measurements open new avenues for image reconstruction. Three algorithms have been proposed previously: the most-likely position method (MLP), the confidence weighting method (CW) and the estimated posterior-density weighting method (EPDW). While MLP suffers from poorer noise properties, both CW and EPDW require substantially more computer processing time. Mathematically, the TOFPET image data at any projection angle represents a 2D image blurred by different TOF and detector spatial resolutions in two perpendicular directions. The integration of TOFPET images over all angles produces a preprocessed 2D image which is the convolution of the true image and a rotationally symmetric point spread function (PSF). Hence the tomographic reconstruction problem for TOFPET can be viewed as nothing more than a 2D image processing task to compensate for a known PSF. A new algorithm based on a generalized iterative deconvolution method and its equivalent filters (''Metz filters'') developed earlier for conventional nuclear medicine image processing is proposed for this purpose. The algorithm can be carried out in a single step by an equivalent filter in the frequency domain; therefore, much of the computation time necessary for CW and EPDW is avoided. Results from computer simulation studies show that this new approach provides excellent resolution enhancement at low frequencies, good noise suppression at high frequencies, a reduction of Gibbs' phenomenon due to sharp filter cutoff, and better quantitative measurements than other methods.
Compressed Sensing MR Image Reconstruction Exploiting TGV and Wavelet Sparsity
Du, Huiqian; Han, Yu; Mei, Wenbo
2014-01-01
Compressed sensing (CS) based methods make it possible to reconstruct magnetic resonance (MR) images from undersampled measurements, which is known as CS-MRI. The reference-driven CS-MRI reconstruction schemes can further decrease the sampling ratio by exploiting the sparsity of the difference image between the target and the reference MR images in pixel domain. Unfortunately existing methods do not work well given that contrast changes are incorrectly estimated or motion compensation is inaccurate. In this paper, we propose to reconstruct MR images by utilizing the sparsity of the difference image between the target and the motion-compensated reference images in wavelet transform and gradient domains. The idea is attractive because it requires neither the estimation of the contrast changes nor multiple times motion compensations. In addition, we apply total generalized variation (TGV) regularization to eliminate the staircasing artifacts caused by conventional total variation (TV). Fast composite splitting algorithm (FCSA) is used to solve the proposed reconstruction problem in order to improve computational efficiency. Experimental results demonstrate that the proposed method can not only reduce the computational cost but also decrease sampling ratio or improve the reconstruction quality alternatively. PMID:25371704
Influence of Iterative Reconstruction Algorithms on PET Image Resolution
NASA Astrophysics Data System (ADS)
Karpetas, G. E.; Michail, C. M.; Fountos, G. P.; Valais, I. G.; Nikolopoulos, D.; Kandarakis, I. S.; Panayiotakis, G. S.
2015-09-01
The aim of the present study was to assess image quality of PET scanners through a thin layer chromatography (TLC) plane source. The source was simulated using a previously validated Monte Carlo model. The model was developed by using the GATE MC package and reconstructed images obtained with the STIR software for tomographic image reconstruction. The simulated PET scanner was the GE DiscoveryST. A plane source consisted of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrates, immersed in 18F-FDG bath solution (1MBq). Image quality was assessed in terms of the modulation transfer function (MTF). MTF curves were estimated from transverse reconstructed images of the plane source. Images were reconstructed by the maximum likelihood estimation (MLE)-OSMAPOSL, the ordered subsets separable paraboloidal surrogate (OSSPS), the median root prior (MRP) and OSMAPOSL with quadratic prior, algorithms. OSMAPOSL reconstruction was assessed by using fixed subsets and various iterations, as well as by using various beta (hyper) parameter values. MTF values were found to increase with increasing iterations. MTF also improves by using lower beta values. The simulated PET evaluation method, based on the TLC plane source, can be useful in the resolution assessment of PET scanners.
Constrained TV-minimization image reconstruction for industrial CT system
NASA Astrophysics Data System (ADS)
Chen, Buxin; Yang, Min; Zhang, Zheng; Bian, Junguo; Han, Xiao; Sidky, Emil; Pan, Xiaochuan
2014-02-01
In this work, we investigate the applicability of the constrained total-variation (TV)-minimization reconstruction method to industrial CT system. In general, industrial CT systems have the same principles of imaging process with clinical CT systems, but different imaging objectives and evaluation metrics. Optimization-based image reconstruction methods have been actively developed to meet practical challenges and extensively tested for clinical CT systems. However, the utility of optimization-based reconstruction methods is task-specific and not necessarily transferrable among different tasks. In this work, we adopt constrained TV-minimization programs together with adaptive-steepest-descent-projection-ontoconvex-sets (ASD-POCS) algorithm for reconstructing images from data of a concrete sample collected using a laboratory industrial CT system developed for non-destructive evaluation. Our results, compared to those reconstructed from FBPbased algorithm, suggest that the constrained TV-minimization program combined with ASD-POCS algorithm can yield images with comparable or improved visual quality and achieve equivalent or better imaging objectives over the currently used FBP-based algorithm under dense sampling data condition.
Compressed sensing MR image reconstruction exploiting TGV and wavelet sparsity.
Zhao, Di; Du, Huiqian; Han, Yu; Mei, Wenbo
2014-01-01
Compressed sensing (CS) based methods make it possible to reconstruct magnetic resonance (MR) images from undersampled measurements, which is known as CS-MRI. The reference-driven CS-MRI reconstruction schemes can further decrease the sampling ratio by exploiting the sparsity of the difference image between the target and the reference MR images in pixel domain. Unfortunately existing methods do not work well given that contrast changes are incorrectly estimated or motion compensation is inaccurate. In this paper, we propose to reconstruct MR images by utilizing the sparsity of the difference image between the target and the motion-compensated reference images in wavelet transform and gradient domains. The idea is attractive because it requires neither the estimation of the contrast changes nor multiple times motion compensations. In addition, we apply total generalized variation (TGV) regularization to eliminate the staircasing artifacts caused by conventional total variation (TV). Fast composite splitting algorithm (FCSA) is used to solve the proposed reconstruction problem in order to improve computational efficiency. Experimental results demonstrate that the proposed method can not only reduce the computational cost but also decrease sampling ratio or improve the reconstruction quality alternatively. PMID:25371704
Learning-based roof style classification in 2D satellite images
NASA Astrophysics Data System (ADS)
Zang, Andi; Zhang, Xi; Chen, Xin; Agam, Gady
2015-05-01
Accurately recognizing building roof style leads to a much more realistic 3D building modeling and rendering. In this paper, we propose a novel system for image based roof style classification using machine learning technique. Our system is capable of accurately recognizing four individual roof styles and a complex roof which is composed of multiple parts. We make several novel contributions in this paper. First, we propose an algorithm that segments a complex roof to parts which enable our system to recognize the entire roof based on recognition of each part. Second, to better characterize a roof image, we design a new feature extracted from a roof edge image. We demonstrate that this feature has much better performance compared to recognition results generated by Histogram of Oriented Gradient (HOG), Scale-invariant Feature Transform (SIFT) and Local Binary Patterns (LBP). Finally, to generate a classifier, we propose a learning scheme that trains the classifier using both synthetic and real roof images. Experiment results show that our classifier performs well on several test collections.
Single-snapshot 2D color measurement by plenoptic imaging system
NASA Astrophysics Data System (ADS)
Masuda, Kensuke; Yamanaka, Yuji; Maruyama, Go; Nagai, Sho; Hirai, Hideaki; Meng, Lingfei; Tosic, Ivana
2014-03-01
Plenoptic cameras enable capture of directional light ray information, thus allowing applications such as digital refocusing, depth estimation, or multiband imaging. One of the most common plenoptic camera architectures contains a microlens array at the conventional image plane and a sensor at the back focal plane of the microlens array. We leverage the multiband imaging (MBI) function of this camera and develop a single-snapshot, single-sensor high color fidelity camera. Our camera is based on a plenoptic system with XYZ filters inserted in the pupil plane of the main lens. To achieve high color measurement precision of this system, we perform an end-to-end optimization of the system model that includes light source information, object information, optical system information, plenoptic image processing and color estimation processing. Optimized system characteristics are exploited to build an XYZ plenoptic colorimetric camera prototype that achieves high color measurement precision. We describe an application of our colorimetric camera to color shading evaluation of display and show that it achieves color accuracy of ΔE<0.01.
Lin, Yu; Liao, Ning-fang; Luo, Yong-dao; Cui, De-qi; Tan, Bo-neng; Wu, Wen-min
2010-08-01
In the present paper, the authors will introduce our research on spectral reconstruction of Fourier transform computed tomography imaging spectrometer by means of the algebraic reconstruction technology. A simulation experiment was carried out to demonstrate the algorithm. The spatial similarities and spectral similarities were evaluated using the normalized correlation coefficient. The performance of ART was evaluated when the quantity of projection is 45. In that case, filter back projection can't work well. Actual spectral slices were reconstructed by using ART in the last part of this paper. PMID:20939312
Digital Three-dimensional Reconstruction Based On Integral Imaging
Li, Chao; Chen, Qian; Hua, Hong; Mao, Chen; Shao, Ajun
2015-01-01
This paper presents a digital three dimensional reconstruction method based on a set of small-baseline elemental images captured with a micro-lens array and a CCD sensor. In this paper, we adopt the ASIFT (Affine Scale-invariant feature transform) operator as the image registration method. Among the set of captured elemental images, the elemental image located in the middle of the overall image field is used as the reference and corresponding matching points in each elemental image around the reference elemental are calculated, which enables to accurately compute the depth value of object points relatively to the reference image frame. Using optimization algorithm with redundant matching points can achieve 3D reconstruction finally. Our experimental results are presented to demonstrate excellent performance in accuracy and speed of the proposed algorithm. PMID:26236151
NASA Astrophysics Data System (ADS)
Hoefer, Christoph; Santner, Jakob; Borisov, Sergey; Kreuzeder, Andreas; Wenzel, Walter; Puschenreiter, Markus
2015-04-01
Two dimensional chemical imaging of root processes refers to novel in situ methods to investigate and map solutes at a high spatial resolution (sub-mm). The visualization of these solutes reveals new insights in soil biogeochemistry and root processes. We derive chemical images by using data from DGT-LA-ICP-MS (Diffusive Gradients in Thin Films and Laser Ablation Inductively Coupled Plasma Mass Spectrometry) and POS (Planar Optode Sensors). Both technologies have shown promising results when applied in aqueous environment but need to be refined and improved for imaging at the soil-plant interface. Co-localized mapping using combined DGT and POS technologies and the development of new gel combinations are in our focus. DGTs are smart and thin (<0.4 mm) hydrogels; containing a binding resin for the targeted analytes (e.g. trace metals, phosphate, sulphide or radionuclides). The measurement principle is passive and diffusion based. The present analytes are diffusing into the gel and are bound by the resin. Thereby, the resin acts as zero sink. After application, DGTs are retrieved, dried, and analysed using LA-ICP-MS. The data is then normalized by an internal standard (e.g. 13C), calibrated using in-house standards and chemical images of the target area are plotted using imaging software. POS are, similar to DGT, thin sensor foils containing a fluorophore coating depending on the target analyte. The measurement principle is based on excitation of the flourophore by a specific wavelength and emission of the fluorophore depending on the presence of the analyte. The emitted signal is captured using optical filters and a DSLR camera. While DGT analysis is destructive, POS measurements can be performed continuously during the application. Both semi-quantitative techniques allow an in situ application to visualize chemical processes directly at the soil-plant interface. Here, we present a summary of results from rhizotron experiments with different plants in metal
A GPU Simulation Tool for Training and Optimisation in 2D Digital X-Ray Imaging
Gallio, Elena; Rampado, Osvaldo; Gianaria, Elena; Bianchi, Silvio Diego; Ropolo, Roberto
2015-01-01
Conventional radiology is performed by means of digital detectors, with various types of technology and different performance in terms of efficiency and image quality. Following the arrival of a new digital detector in a radiology department, all the staff involved should adapt the procedure parameters to the properties of the detector, in order to achieve an optimal result in terms of correct diagnostic information and minimum radiation risks for the patient. The aim of this study was to develop and validate a software capable of simulating a digital X-ray imaging system, using graphics processing unit computing. All radiological image components were implemented in this application: an X-ray tube with primary beam, a virtual patient, noise, scatter radiation, a grid and a digital detector. Three different digital detectors (two digital radiography and a computed radiography systems) were implemented. In order to validate the software, we carried out a quantitative comparison of geometrical and anthropomorphic phantom simulated images with those acquired. In terms of average pixel values, the maximum differences were below 15%, while the noise values were in agreement with a maximum difference of 20%. The relative trends of contrast to noise ratio versus beam energy and intensity were well simulated. Total calculation times were below 3 seconds for clinical images with pixel size of actual dimensions less than 0.2 mm. The application proved to be efficient and realistic. Short calculation times and the accuracy of the results obtained make this software a useful tool for training operators and dose optimisation studies. PMID:26545097
A GPU Simulation Tool for Training and Optimisation in 2D Digital X-Ray Imaging.
Gallio, Elena; Rampado, Osvaldo; Gianaria, Elena; Bianchi, Silvio Diego; Ropolo, Roberto
2015-01-01
Conventional radiology is performed by means of digital detectors, with various types of technology and different performance in terms of efficiency and image quality. Following the arrival of a new digital detector in a radiology department, all the staff involved should adapt the procedure parameters to the properties of the detector, in order to achieve an optimal result in terms of correct diagnostic information and minimum radiation risks for the patient. The aim of this study was to develop and validate a software capable of simulating a digital X-ray imaging system, using graphics processing unit computing. All radiological image components were implemented in this application: an X-ray tube with primary beam, a virtual patient, noise, scatter radiation, a grid and a digital detector. Three different digital detectors (two digital radiography and a computed radiography systems) were implemented. In order to validate the software, we carried out a quantitative comparison of geometrical and anthropomorphic phantom simulated images with those acquired. In terms of average pixel values, the maximum differences were below 15%, while the noise values were in agreement with a maximum difference of 20%. The relative trends of contrast to noise ratio versus beam energy and intensity were well simulated. Total calculation times were below 3 seconds for clinical images with pixel size of actual dimensions less than 0.2 mm. The application proved to be efficient and realistic. Short calculation times and the accuracy of the results obtained make this software a useful tool for training operators and dose optimisation studies. PMID:26545097
Fast dictionary-based reconstruction for diffusion spectrum imaging.
Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F; Yendiki, Anastasia; Wald, Lawrence L; Adalsteinsson, Elfar
2013-11-01
Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm. PMID:23846466
Probe and object function reconstruction in incoherent stem imaging
Nellist, P.D.; Pennycook, S.J.
1996-09-01
Using the phase-object approximation it is shown how an annular dark- field (ADF) detector in a scanning transmission electron microscope (STEM) leads to an image which can be described by an incoherent model. The point spread function is found to be simply the illuminating probe intensity. An important consequence of this is that there is no phase problem in the imaging process, which allows various image processing methods to be applied directly to the image intensity data. Using an image of a GaAs<110>, the probe intensity profile is reconstructed, confirming the existence of a 1.3 {Angstrom} probe in a 300kV STEM. It is shown that simply deconvolving this reconstructed probe from the image data does not improve its interpretability because the dominant effects of the imaging process arise simply from the restricted resolution of the microscope. However, use of the reconstructed probe in a maximum entropy reconstruction is demonstrated, which allows information beyond the resolution limit to be restored and does allow improved image interpretation.
Fast fully 3-D image reconstruction in PET using planograms.
Brasse, D; Kinahan, P E; Clackdoyle, R; Defrise, M; Comtat, C; Townsend, D W
2004-04-01
We present a method of performing fast and accurate three-dimensional (3-D) backprojection using only Fourier transform operations for line-integral data acquired by planar detector arrays in positron emission tomography. This approach is a 3-D extension of the two-dimensional (2-D) linogram technique of Edholm. By using a special choice of parameters to index a line of response (LOR) for a pair of planar detectors, rather than the conventional parameters used to index a LOR for a circular tomograph, all the LORs passing through a point in the field of view (FOV) lie on a 2-D plane in the four-dimensional (4-D) data space. Thus, backprojection of all the LORs passing through a point in the FOV corresponds to integration of a 2-D plane through the 4-D "planogram." The key step is that the integration along a set of parallel 2-D planes through the planogram, that is, backprojection of a plane of points, can be replaced by a 2-D section through the origin of the 4-D Fourier transform of the data. Backprojection can be performed as a sequence of Fourier transform operations, for faster implementation. In addition, we derive the central-section theorem for planogram format data, and also derive a reconstruction filter for both backprojection-filtering and filtered-backprojection reconstruction algorithms. With software-based Fourier transform calculations we provide preliminary comparisons of planogram backprojection to standard 3-D backprojection and demonstrate a reduction in computation time by a factor of approximately 15. PMID:15084067
Cervigram image segmentation based on reconstructive sparse representations
NASA Astrophysics Data System (ADS)
Zhang, Shaoting; Huang, Junzhou; Wang, Wei; Huang, Xiaolei; Metaxas, Dimitris
2010-03-01
We proposed an approach based on reconstructive sparse representations to segment tissues in optical images of the uterine cervix. Because of large variations in image appearance caused by the changing of the illumination and specular reflection, the color and texture features in optical images often overlap with each other and are not linearly separable. By leveraging sparse representations the data can be transformed to higher dimensions with sparse constraints and become more separated. K-SVD algorithm is employed to find sparse representations and corresponding dictionaries. The data can be reconstructed from its sparse representations and positive and/or negative dictionaries. Classification can be achieved based on comparing the reconstructive errors. In the experiments we applied our method to automatically segment the biomarker AcetoWhite (AW) regions in an archive of 60,000 images of the uterine cervix. Compared with other general methods, our approach showed lower space and time complexity and higher sensitivity.
Reconstruction of indoor scene from a single image
NASA Astrophysics Data System (ADS)
Wu, Di; Li, Hongyu; Zhang, Lin
2015-03-01
Given a single image of an indoor scene without any prior knowledge, is it possible for a computer to automatically reconstruct the structure of the scene? This letter proposes a reconstruction method, called RISSIM, to recover the 3D modelling of an indoor scene from a single image. The proposed method is composed of three steps: the estimation of vanishing points, the detection and classification of lines, and the plane mapping. To find vanishing points, a new feature descriptor, named "OCR", is defined to describe the texture orientation. With Phrase Congruency and Harris Detector, the line segments can be detected exactly, which is a prerequisite. Perspective transform is a defined as a reliable method whereby the points on the image can be represented on a 3D model. Experimental results show that the 3D structure of an indoor scene can be well reconstructed from a single image although the available depth information is limited.
Security of Color Image Data Designed by Public-Key Cryptosystem Associated with 2D-DWT
NASA Astrophysics Data System (ADS)
Mishra, D. C.; Sharma, R. K.; Kumar, Manish; Kumar, Kuldeep
2014-08-01
In present times the security of image data is a major issue. So, we have proposed a novel technique for security of color image data by public-key cryptosystem or asymmetric cryptosystem. In this technique, we have developed security of color image data using RSA (Rivest-Shamir-Adleman) cryptosystem with two-dimensional discrete wavelet transform (2D-DWT). Earlier proposed schemes for security of color images designed on the basis of keys, but this approach provides security of color images with the help of keys and correct arrangement of RSA parameters. If the attacker knows about exact keys, but has no information of exact arrangement of RSA parameters, then the original information cannot be recovered from the encrypted data. Computer simulation based on standard example is critically examining the behavior of the proposed technique. Security analysis and a detailed comparison between earlier developed schemes for security of color images and proposed technique are also mentioned for the robustness of the cryptosystem.
NASA Astrophysics Data System (ADS)
Debenham, Helen
2014-06-01
In the Browse Basin, as in many areas of the world, complex seafloor topography can cause problems with seismic imaging. This is related to complex ray paths, and sharp lateral changes in velocity. This paper compares ways in which 2D Kirchhoff imaging can be improved below seafloor canyons, using both time and depth domain processing. In the time domain, to improve on standard pre-stack time migration (PSTM) we apply removable seafloor static time shifts in order to reduce the push down effect under seafloor canyons before migration. This allows for better event continuity in the seismic imaging. However this approach does not fully solve the problem, still giving sub-optimal imaging, leaving amplitude shadows and structural distortion. Only depth domain processing with a migration algorithm that honours the paths of the seismic energy as well as a detailed velocity model can provide improved imaging under these seafloor canyons, and give confidence in the structural components of the exploration targets in this area. We therefore performed depth velocity model building followed by pre-stack depth migration (PSDM), the result of which provided a step change improvement in the imaging, and provided new insights into the area.
Heterogeneity of Particle Deposition by Pixel Analysis of 2D Gamma Scintigraphy Images
Xie, Miao; Zeman, Kirby; Hurd, Harry; Donaldson, Scott
2015-01-01
Abstract Background: Heterogeneity of inhaled particle deposition in airways disease may be a sensitive indicator of physiologic changes in the lungs. Using planar gamma scintigraphy, we developed new methods to locate and quantify regions of high (hot) and low (cold) particle deposition in the lungs. Methods: Initial deposition and 24 hour retention images were obtained from healthy (n=31) adult subjects and patients with mild cystic fibrosis lung disease (CF) (n=14) following inhalation of radiolabeled particles (Tc99m-sulfur colloid, 5.4 μm MMAD) under controlled breathing conditions. The initial deposition image of the right lung was normalized to (i.e., same median pixel value), and then divided by, a transmission (Tc99m) image in the same individual to obtain a pixel-by-pixel ratio image. Hot spots were defined where pixel values in the deposition image were greater than 2X those of the transmission, and cold spots as pixels where the deposition image was less than 0.5X of the transmission. The number ratio (NR) of the hot and cold pixels to total lung pixels, and the sum ratio (SR) of total counts in hot pixels to total lung counts were compared between healthy and CF subjects. Other traditional measures of regional particle deposition, nC/P and skew of the pixel count histogram distribution, were also compared. Results: The NR of cold spots was greater in mild CF, 0.221±0.047(CF) vs. 0.186±0.038 (healthy) (p<0.005) and was significantly correlated with FEV1 %pred in the patients (R=−0.70). nC/P (central to peripheral count ratio), skew of the count histogram, and hot NR or SR were not different between the healthy and mild CF patients. Conclusions: These methods may provide more sensitive measures of airway function and localization of deposition that might be useful for assessing treatment efficacy in these patients. PMID:25393109
Label free biochemical 2D and 3D imaging using secondary ion mass spectrometry
Fletcher, John S.; Vickerman, John C.; Winograd, Nicholas
2011-01-01
Time-of-flight Secondary ion mass spectrometry (ToF-SIMS) provides a method for the detection of native and exogenous compounds in biological samples on a cellular scale. Through the development of novel ion beams the amount of molecular signal available from the sample surface has been increased. Through the introduction of polyatomic ion beams, particularly C60, ToF-SIMS can now be used to monitor molecular signals as a function of depth as the sample is eroded thus proving the ability to generate 3D molecular images. Here we describe how this new capability has led to the development of novel instrumentation for 3D molecular imaging while also highlighting the importance of sample preparation and discuss the challenges that still need to be overcome to maximise the impact of the technique. PMID:21664172
Distributed Computing Architecture for Image-Based Wavefront Sensing and 2 D FFTs
NASA Technical Reports Server (NTRS)
Smith, Jeffrey S.; Dean, Bruce H.; Haghani, Shadan
2006-01-01
Image-based wavefront sensing (WFS) provides significant advantages over interferometric-based wavefi-ont sensors such as optical design simplicity and stability. However, the image-based approach is computational intensive, and therefore, specialized high-performance computing architectures are required in applications utilizing the image-based approach. The development and testing of these high-performance computing architectures are essential to such missions as James Webb Space Telescope (JWST), Terrestial Planet Finder-Coronagraph (TPF-C and CorSpec), and Spherical Primary Optical Telescope (SPOT). The development of these specialized computing architectures require numerous two-dimensional Fourier Transforms, which necessitate an all-to-all communication when applied on a distributed computational architecture. Several solutions for distributed computing are presented with an emphasis on a 64 Node cluster of DSPs, multiple DSP FPGAs, and an application of low-diameter graph theory. Timing results and performance analysis will be presented. The solutions offered could be applied to other all-to-all communication and scientifically computationally complex problems.
Reconstruction of 3D ultrasound images based on Cyclic Regularized Savitzk